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1
Jia, Mingxing, Zhiheng Pan, Guanghai Li, Chunhua Chen und Chen Wang. „A Fast Diagnosis Method of Escalator Reversal Faults Based on Dynamic Information and Multiattribute Decision-Making“. Journal of Mathematics 2021 (20.12.2021): 1–10. http://dx.doi.org/10.1155/2021/6294869.
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There are many reasons for escalator reversal failure, and the reasons are distributed in different locations. It is difficult to locate the specific location of the fault in the actual fault troubleshooting. At the same time, the information related to the failure is not used in the troubleshooting, so there is a problem of inefficient troubleshooting. To this end, this paper proposes a multiattribute decision-making method that integrates dynamic information and gives the optimal troubleshooting order to improve the efficiency of the troubleshooting. First of all, according to the structure of the escalator components, the escalator reversal fault tree is established. Secondly, a static decision matrix is established by comprehensively considering the failure probability, search cost, and influence degree of the bottom event of the fault tree. Finally, the influence matrix of information on each attribute is given by the dynamic information obtained in troubleshooting, the static decision fusion influence matrix determines the dynamic decision matrix, the dynamic decision matrix is weighted and normalized, and the Technique for Order Preference by Similarity to Ideal Solution is used to determine the optimal troubleshooting order. Taking the reversal failure of a certain type of escalators as an example, the method of multiattribute decision-making of fusion dynamic information is used to shorten the troubleshooting time, improve the efficiency of troubleshooting, and verify the effectiveness of this method.
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Ariff, Idzham Fauzi Mohd, und Mardhiyah Bakir. „Dynamic Simulation of Petrochemical Wastewater Treatment Using Wastewater Plant Simulation Software“. MATEC Web of Conferences 203 (2018): 03005. http://dx.doi.org/10.1051/matecconf/201820303005.
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A dynamic simulation model was developed, calibrated and validated for a petrochemical plant in Terengganu, Malaysia. Calibration and validation of the model was conducted based on plant monitoring data spanning 3 years resulting in a model accuracy (RMSD) for effluent chemical oxygen demand (COD), ammoniacal nitrogen (NH3-N) and total suspended solids (TSS) of ±11.7 mg/L, ±0.52 mg/L and ± 3.27 mg/L respectively. The simulation model has since been used for troubleshooting during plant upsets, planning of plant turnarounds and developing upgrade options. A case study is presented where the simulation model was used to assist in troubleshooting and rectification of a plant upset where ingress of a surfactant compound resulted in high effluent TSS and COD. The model was successfully used in the incident troubleshooting activities and provided critical insights that assisted the plant operators to quickly respond and bring back the system to normal, stable condition.
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Fath, J. L., C. M. Mitchell und T. Govindaraj. „An ICAI architecture for troubleshooting in complex, dynamic systems“. IEEE Transactions on Systems, Man, and Cybernetics 20, Nr. 3 (1990): 537–58. http://dx.doi.org/10.1109/21.57268.
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4
Jesse Huang, H. „An Adaptive Troubleshooting Model for Complex and Dynamic System“. IFAC Proceedings Volumes 28, Nr. 15 (Juni 1995): 571–74. http://dx.doi.org/10.1016/s1474-6670(17)45293-1.
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5
Mobki, Hamed, Morteza Homayoun Sedighi, Aydin Azizi und Mir Mohammad Eskandari. „DESIGNING AN EFFICIENT OBSERVER FOR THE NON-LINEAR LIPSCHITZ SYSTEM TO TROUBLESHOOT AND DETECT SECONDARY FAULTS CONSIDERING LINEARIZING THE DYNAMIC ERROR“. Facta Universitatis, Series: Mechanical Engineering 20, Nr. 3 (30.11.2022): 677. http://dx.doi.org/10.22190/fume220528043m.
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The presence of faults in a system leads to a lower value for efficiency, accuracy and speed, and, in some cases, even a complete breakdown. Thus, early fault detection is a major factor in efficiency and productivity of the procedure. In recent decades, many research studies have been conducted on troubleshooting and secondary fault detection. The current work presents an efficient and novel observer design capable of stabilizing the residue and dynamic error for the nonlinear Lipschitz systems with faults as well as a troubleshooting analysis and determining the formation of secondary faults in defective systems. The observer is designed based on linearizing dynamic error considering uncertainty, disturbance, and defects by employing non-linear gain factors instead of using state transformation. The dynamic error and residue stabilization of a non-linear faulty system have been discussed as well as the likelihood of secondary fault generation. The results indicate that the observer is able to determine fault-emergence, fault-disappearance and secondary fault formation well and quite fast.
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Niu, Dapeng, Chenshu Qi, Guanghai Li, Hongru Li und Hali Pang. „Rapid Fault Diagnosis Method of Elevator System Based on Multiattribute Decision Making“. Shock and Vibration 2021 (08.10.2021): 1–9. http://dx.doi.org/10.1155/2021/9939493.
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Fault tree analysis is often used in elevator fault diagnosis because of its simplicity and reliability. However, the traditional fault tree method has the problems of low efficiency due to ignoring location change of bottom events during troubleshooting. This paper proposes a rapid diagnosis method based on multiattribute decision making to solve the problem. The fault tree of the elevator system is constructed based on expert knowledge and multisource data, and the location-related matrix is constructed according to the complex vertical structure of the elevator. Then, the attributes of bottom events such as the failure probability, search cost, location time cost, and location-related attributes are comprehensively analyzed in this paper. Finally, the TOPSIS method for dynamic attributes is used based on the work above to achieve the optimal troubleshooting sequence of elevator vibration fault. The results show that the proposed method is more efficient when compared to the optimal troubleshooting sequence obtained by the traditional method.
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Wu, Song Lin, Shi Chao Li und Jun Zhao. „The Principle of Dynamic Diagnosis Based on Integrated Maintenance Information and its Application“. Applied Mechanics and Materials 385-386 (August 2013): 1785–89. http://dx.doi.org/10.4028/www.scientific.net/amm.385-386.1785.
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Based on the concept of an integrated maintenance information system and related information environment, this paper discusses the process of troubleshooting in modern maintenance in detail, and gives a model of dynamic faults diagnosis, in which a reasoning program is designed through taking advantage of information fusion and time analysis. In the end, the authors present the logic process of dynamic diagnosis through a typical example, and propose a dynamic diagnostic system based on information fusion.
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Qin, S. Joe, Yingxiang Liu und Yining Dong. „Plant-wide troubleshooting and diagnosis using dynamic embedded latent feature analysis“. Computers & Chemical Engineering 152 (September 2021): 107392. http://dx.doi.org/10.1016/j.compchemeng.2021.107392.
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Roldán-Pérez, Javier, Aurelio García-Cerrada, Juan Luis Zamora-Macho, Pedro Roncero-Sánchez und Enrique Acha. „Troubleshooting a digital repetitive controller for a versatile dynamic voltage restorer“. International Journal of Electrical Power & Energy Systems 57 (Mai 2014): 105–15. http://dx.doi.org/10.1016/j.ijepes.2013.11.054.
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Mircea, Alina, und Karl Popp. „Troubleshooting in Studying the Behavior of Ballast Stones using Molecular Dynamic Simulation“. PAMM 5, Nr. 1 (Dezember 2005): 209–10. http://dx.doi.org/10.1002/pamm.200510082.
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Bury, S. J., C. K. Groot, C. Huth und N. Hardt. „Dynamic simulation of chemical industry wastewater treatment plants“. Water Science and Technology 45, Nr. 4-5 (01.02.2002): 355–63. http://dx.doi.org/10.2166/wst.2002.0623.
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High variability, stringent effluent permits, and often extreme operating conditions define the practice of wastewater treatment in the chemical industry. This paper reviews the benefits and challenges of applying dynamic simulation to chemical-industry wastewater treatment plants by describing case studies at full-scale wastewater treatment plants (WWTP). The applications range from process troubleshooting to optimization and control. The applications have been valuable and useful in developing a deeper understanding of the plants as integrated systems. However there still remains substantial work to implement the dynamic simulations for daily real-time use by plant engineers and operators. This opportunity to improve plant operations is still largely untapped and will remain so until dynamic state estimation and data reconciliation are incorporated into simulation packages for use in developing the on-line simulations.
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Lu, Shibao, June Wei, Haijun Bao, Yangang Xue und Weiwei Ye. „The dynamic hydropower troubleshooting information based on EMD multi-scale feature entropy extraction“. International Journal of Mobile Communications 15, Nr. 6 (2017): 677. http://dx.doi.org/10.1504/ijmc.2017.086882.
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Ye, Weiwei, June Wei, Haijun Bao, Yangang Xue und Shibao Lu. „The dynamic hydropower troubleshooting information based on EMD multi-scale feature entropy extraction“. International Journal of Mobile Communications 15, Nr. 6 (2017): 677. http://dx.doi.org/10.1504/ijmc.2017.10005657.
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HAJEK, J. „Computational fluid dynamic simulations in thermal waste treatment technology—Design, optimisation and troubleshooting“. Energy 33, Nr. 6 (Juni 2008): 930–41. http://dx.doi.org/10.1016/j.energy.2007.11.010.
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Zheng, Hai Yan, Rui Li Zhang und Wan Chun Gao. „Research and Application of SVG in the Feeder Data Analysis System Based on Ajax“. Advanced Materials Research 1044-1045 (Oktober 2014): 1441–45. http://dx.doi.org/10.4028/www.scientific.net/amr.1044-1045.1441.
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It researched key technology based on ajax of svg in feeder data analysis system, for the requirement of complicated circuit quick analysis and high efficiency in aviation arming ensure domain, combined with S1000D specification for interactive electronic technical manuals and data requirements of creative thinking, proposed feeder S1000D data modules and svg technology dynamic publishing model,and the application of research results, case study results show that: The design can be automatically and quickly analyze circuit through the auxiliary equipment, leads the list of inter-path, achieve troubleshooting.
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Liu, Jie, und Wei Wang. „Influence of different testing positions of sensors on the dynamic response of load sensing hydraulic systems“. Journal of Physics: Conference Series 2457, Nr. 1 (01.03.2023): 012016. http://dx.doi.org/10.1088/1742-6596/2457/1/012016.
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Abstract This paper first introduced the load sensing hydraulic system and elaborated on its load feedback, pressure cut-off, and constant power control principles. Moreover, based on the response hysteresis of the load sensing hydraulic system in the actual commissioning of the project, this paper proposed the possible influence of the sensor on the response of the hydraulic system through troubleshooting analysis. Third, experiments were conducted to obtain the system dynamic response curves given different sensor positions and to prove the hypothesis. Meanwhile, the influence mechanism and improvement measures were analyzed. Finally, the optimal installation positions of the sensor based on different operating conditions were discussed.
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Borba Evangelista, Gustavo, Guilherme Conceição Rocha und Wlamir Olivares Loesch Vianna. „Aircraft Troubleshooting Optimization Using Case-based Reasoning and Decision Analysis“. Annual Conference of the PHM Society 12, Nr. 1 (03.11.2020): 8. http://dx.doi.org/10.36001/phmconf.2020.v12i1.1170.
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The Fault Isolation Manual (FIM) can be seen as a specialist system that carries the expectations and expertise of engineers and technical team concerning the aircraft components and systems operation. It is basically a manual that supports the maintainers regarding the actions to perform in determined situations to properly isolate a fault. Although the FIM is the most common tool that assists maintainer on the troubleshooting process today, it does not adequately consider field experience and it does not explore situations where the maintenance operator has limited resources, such as a lack of tools and equipment. These drawbacks are essentially caused by the lack of flexibility or adaptability of this method since it is a static manual. There are several dynamic methods studied in the field of system troubleshooting and aircraft maintenance such as Artificial Neural Networks, Support Vector Machine, K Nearest Neighbor and many other machine learning algorithms. These techniques are considered very powerful and useful; however, the training process of the data-driven strategies requires a large amount of data to provide a reliable result.
In this context, the present work proposes a combination of data-driven with legacy knowledge-based approaches. The following techniques are employed to integrate the concepts mentioned: decision trees that explore the legacy knowledge with its topology based on the FIM, truth tables and decision analysis that explores Bayes’ rule to assist the decision- making process and case-based reasoning, technique that enables the learning from the field experience.
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DAVE, RAKESH, SUBHASHINI GANAPATHY, MARY FENDLEY und S. NARAYANAN. „A KNOWLEDGE-BASED SYSTEM TO MODEL HUMAN SUPERVISORY CONTROL IN DYNAMIC PLANNING“. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 12, supp02 (Oktober 2004): 1–14. http://dx.doi.org/10.1142/s0218488504003004.
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With the increases in the levels of automation and computerization, supervisory control systems are becoming increasingly common in commercial and military applications. A supervisory control system consists of one or more human operators interacting with highly automated components such as those seen in satellite ground control, flexible manufacturing systems, or nuclear power plants. Humans typically perform cognitively intense tasks such as monitoring, planning, real-time control, and troubleshooting, and are ultimately responsible for the safe and efficient operation of the overall system. Although developments on supervisory control have led to useful applications in interface design and automation, there is a scarcity of research that empirically evaluates human decision making in supervisory control through emulation of task performance using knowledge-based systems. In the context of dynamic planning involving simulated search and rescue missions using ground based autonomous robots and uninhabited aerial vehicles, we developed a knowledge-based system that mimics supervisory control performance. This paper describes the application domain, the details of the simulation model, and the implementation and assessment of a knowledge-based system that mimics human supervisory control performance.
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Majeed, Saqib. „Energy Aware Drone Enabled Base Stations Deployment in Flying Adhoc Networks“. Quaid-e-Awam University Research Journal of Engineering, Science & Technology 20, Nr. 2 (28.12.2022): 39–47. http://dx.doi.org/10.52584/qrj.2002.06.
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The demand for Wireless Networks has increased rapidly for downloading and uploading all types of data, which is due to the inefficiency and high cost of infrastructure based cellular Networks. Unmanned Aerial Vehicle (UAVs) is the reliable solution for improving efficiency, latency redundancy, business, and troubleshooting problems on a high scale. Although, the deployment of UAVs to meet user demand in any environment or region is quite thought-provoking. This deployment not merely provides the only the coverage area, but also provides the capacity balancing and accommodation of extremely populated areas. In this research, the suggested solutions show significant achievements in terms of energy proficiency related to the fixed and dynamic drone base station system. We propose FSO (free space optical) communication system and evaluate three feasible algorithms for separate dynamic repositioning of drone base stations in terms of communicational energy. In MATLAB, the simulation result shows 20 percent of communicational energy consumption improvement can be obtained deprived of adversely affecting any other factor of the drone.
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Wu, Fayong, Jie Hong, Xueqi Chen und Yanhong Ma. „Analysis of High-Speed Rotor Vibration Failure Due to Sudden Angular Deformation of Bolt Joints“. Symmetry 15, Nr. 10 (19.10.2023): 1937. http://dx.doi.org/10.3390/sym15101937.
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As the efficiency of advanced aero engines improves, the operational speed of their rotors increases. This heightened operational speed makes the rotor dynamics highly sensitive to changes in the rotor’s mass asymmetry state, or unbalance state. During the use of a dual-spool turbofan engine, when its supercritical high-pressure rotor (HPR) exceeds a certain operational speed, the rotor’s vibration spikes and continues to increase with the operational speed until it drops sharply near the maximum operational speed. Analysis of the bolt joints in the faulty rotor reveals various phenomena such as joint interface damage, changes in bolt loosening torque distribution, and alterations in rotor initial unbalance. This paper proposes that at high operational speeds, the bolt joint of the HPR undergoes sudden angular deformation, resulting in the slanting of the principal axis of inertia of the turbine disk. This slant leads to changes in the unbalanced state of the HPR. The additional unbalance causes a sudden rotational inertia load excitation, triggering the rotor vibration failure. Subsequently, a rotor dynamic model that incorporates the angular deformation of the joints is established to simulate how this joint deformation influences the dynamic response of the rotor. The simulation results align well with the observed failure phenomenon and validate the proposed failure mechanism. Finally, troubleshooting measures are proposed and implemented in the faulty engine, effectively mitigating the vibration fault.
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Wagner, J., und R. Shoureshi. „A Failure Isolation Strategy for Thermofluid System Diagnostics“. Journal of Engineering for Industry 115, Nr. 4 (01.11.1993): 459–65. http://dx.doi.org/10.1115/1.2901790.
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The application of microprocessor-based diagnostic strategies to industrial processes provides improved system reliability while reducing maintenance costs. The prompt detection and classification of system anomalies enables reduced troubleshooting by technicians and minimizes the misclassification of system degradations. In this paper, an experimental-based multiple hypothesis failure isolation scheme for small-scale thermofluid systems is presented. The proposed classification strategy combines dynamic modeling, control theory, multivariate statistics, and pattern recognition to develop a methodology that may be tailored for a variety of applications. The primary goal of this study is the reduction of modeling activities associated with the set of hypothesized failure modes. The overall performance of the isolation scheme is investigated for a series of experimentally simulated heat pump failures.
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Eberhardt, M., M. Lehner, A. Ascher, M. Allwang und E. M. Biebl. „An active UHF RFID localization system for fawn saving“. Advances in Radio Science 13 (03.11.2015): 87–94. http://dx.doi.org/10.5194/ars-13-87-2015.
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Abstract. We present a localization concept for active UHF RFID transponders which enables mowing machine drivers to detect and localize marked fawns. The whole system design and experimental results with transponders located near the ground in random orientations in a meadow area are shown. The communication flow between reader and transponders is realized as a dynamic master-slave concept. Multiple marked fawns will be localized by processing detected transponders sequentially. With an eight-channel-receiver with integrated calibration method one can estimate the direction-of-arrival by measuring the phases of the transponder signals up to a range of 50 m in all directions. For further troubleshooting array manifolds have been measured. An additional hand-held receiver with a two-channel receiver allows a guided approaching search without endangering the fawn by the mowing machine.
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Nouby M. Ghazaly, Mahrousa M. Abdeltwab,. „A Review on Engine Fault Diagnosis through Vibration Analysis“. International Journal on Recent Technologies in Mechanical and Electrical Engineering 9, Nr. 2 (28.02.2022): 01–06. http://dx.doi.org/10.17762/ijrmee.v9i2.364.
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Vehicles engine failure is disapproved problem for drivers, and repair of that needs experience to identify fault and troubleshooting. The fault diagnosis in a machine is significant for fending off dangerous damage. The vibration signals of a machine always carry the dynamic information of the machine. These vibration signals of internal combustion engines are extremely helpful for the feature extraction and detect the fault diagnosis. The former sensing of defects by supervising can keep farther harm to the internal combustion engine and deflect further causalities. The faults lead to reducing the engine performance and increasing the harmful pollution. In this paper, present techniques of a denoising method for vibration signal analysis that had been proposed such as fast Fourier transform (STFT), higher-order statistics (HOS), Wigner–Ville distribution (WVD), and wavelet transform (WT) and adaptive order-tracking.
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Yin, Chengfeng, Qiang Zheng und Xiaoqing Shen. „Design of Real Network Hardware In-Loop Simulation Test Platform for Internet of Vehicles Testing“. Wireless Communications and Mobile Computing 2023 (05.01.2023): 1–12. http://dx.doi.org/10.1155/2023/1895496.
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Based on the function and performance testing requirements of Internet of Vehicles, a design scheme for automatic simulation test and verification platform for the Internet of Vehicles based on cellular networks and real network in-loop is proposed. First, the overall structure of the simulation test platform and the specific function of each component are presented. The main and functional components of the real cellular network simulation subsystem are then discussed. Finally, two typical application test scenarios are designed and presented; namely, vehicle remote-startup delay test based on a cloud platform and Internet of Vehicles local performance test of different frequency cell switching in a dynamic scenario. Experimental results verify that the simulation test platform can meet the test verification, performance evaluation, and troubleshooting requirements of the Internet of Vehicles function. It is important to improve the application experience of intelligent connected vehicles and the Internet of Vehicles.
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Gębura, Andrzej. „Investigation Of Tribologic Processes in Bearing Nodes with the Use of the Fam-C And Fdm-A Methods – The Model With Elevated Passive Resistance“. Research Works of Air Force Institute of Technology 35, Nr. 1 (01.12.2014): 115–25. http://dx.doi.org/10.1515/afit-2015-0008.
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Abstract The paper discloses selected results of application of the FAM-C (a.c. generator) and FDM-A (d.c. generator) methods for comprehensive troubleshooting of bearing nodes in single-spool turbojet engines. A.c. generators provide information about slow-changing processes and, consequently, that information makes it possible to monitor radial and axial clearance of bearings as well as misalignment of shafts. On the other hand, the information transmitted by d.c. generators refers to fast-changing processes and is suitable to monitor dynamic properties of antifriction bearings: variations in the Q factor of bearings, slip factor of mating antifriction surfaces, rates of bearing cage rotation against its journal, etc. Nearly ten years of observations and data collection from a numerous set of engines during their operation have made it possible to classify processes associated with wear of bearings and categorize them into four phenomenological models. This paper is devoted to the model of elevated passive resistance
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Liu, Kun, Xiping Song und Xiangyu Li. „Fault Reason and Diagnosis of Electronic Control Automatic Transmission of Modern“. Frontiers of Mechatronical Engineering 1, Nr. 1 (07.02.2018): 32. http://dx.doi.org/10.18282/fme.v1i1.599.
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<p>The mechanical transmission of automobile is very efficient, reliable and structurally simple, but is easy to wear the parts prematurely because of its dynamic load. In the case of complex external conditions, the frequent operation of the clutch, shift lever and throttle, increasing the burden on the driver is not conducive to safe driving. In recent decades, automatic transmission has been an unprecedented development; electronic control automatic transmission has become the development direction of modern car transmission. But the electronic control automatic transmission structure complex production cost is high; its repair and troubleshooting put forward the harsh requirements of the maintenance personnel, maintenance technology. Understanding the degree also constitutes a certain degree of difficulty. The modern car electronic control automatic transmission development history, composition and function of the failure of the file are not up to speed to make a major study. The cause and diagnosis of the exclusion of the automatic control of automotive electronic control and maintenance are of great significance.</p>
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Mbodila, Munienge. „Towards Fault Tolerance Management Systems in SDN“. International Conference on Intelligent and Innovative Computing Applications 2022 (31.12.2022): 302–14. http://dx.doi.org/10.59200/iconic.2022.033.
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The issue of network operation, monitoring, and availability in traditional network environments has been one of the major challenges to addressing network administrators' struggles to deal with. The capacity for the network to comprehend the status and the performance of every node has been one of the priorities amongst others for network administrators to protect during troubleshooting in their network. However, the growing use of software-defined networks (SDN) technologies, as well as virtualization, pave the way to the solution of network operation, monitoring, and availability of hardware and services in a network environment. SDN has emerged with a novel paradigm of network abstractions that is dynamic, able to monitor network performance and fault management automatically, using its programmable capability. This paper presents a design of a fault tolerance management system for SDN controller framework for small to medium sized networks capable of detecting controller faults and nodes/links faultsin case entire network access is unavailable. The fault management system applies various approaches for fault detection and recovery to ensure the reliability and availability of the network resources.
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Tang, Ruipeng. „Improved Dynamic PPI Network Construction and Application of Data Mining in Computer Artificial Intelligence Systems“. Scientific Programming 2022 (28.02.2022): 1–9. http://dx.doi.org/10.1155/2022/2729401.
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The protein interaction network is a network composed of the interactions between all proteins in living organisms. The use of computational methods to prove the functional modules in the PPI network is an important research topic in bioinformatics. With the development of technologies for detecting protein interactions, the available data on interactions has become more and more extensive, and the PPI networks created have become more and more extensive. At the same time, with the deepening of research, people have found that the real PPI network is constantly changing with time and conditions and this change is closely related to the creation and development of life activities. Therefore, it is also very important and necessary to understand and study the functional modules of the PPI dynamic network. At the same time, it focuses on analyzing the basic attributes of artificial intelligence and computer technology and analyzing the goals that can be achieved by using artificial intelligence in computer technology. The effects and directions that can be further explored can be extracted from a large amount of unrealistic, incomplete, fuzzy, and random actual data. These data are hidden from people who do not know them before , but this is a potentially useful process for obtaining information and knowledge. Applying data mining technology to diagnose computer network problems can improve reliability, stability, flexibility, troubleshooting speed, and proper network management, automatically diagnose, predict, and maintain network failures, and ensure that the network has high-quality services and reliability. Drive AI applications in computer science.
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Sabati, Asghar, Ramazan Bayindir, Sanjeevikumar Padmanaban, Eklas Hossain und Mehmet Rida Tur. „Small Signal Stability with the Householder Method in Power Systems“. Energies 12, Nr. 18 (04.09.2019): 3412. http://dx.doi.org/10.3390/en12183412.
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Voltage collapse in power systems is still considered the greatest threat, especially for the transmission system. This is directly related to the quality of the power, which is characterized by the loss of a stable operating point and the deterioration of voltage levels in the electrical center of the region exposed to voltage collapse. Numerous solution methods have been investigated for this undesirable degradation. This paper focuses on the steady state/dynamic stability subcategory and techniques that can be used to analyze and control the dynamic stability of a power system, especially following a minor disturbance. In particular, the failure of one generator among the network with a large number of synchronous generators will affect other synchronous generators. This will become a major problem and it will be difficult to find or resolve the fault in the network due to there being too many variables, consequently affecting the stability of the entire system. Since the solution of large matrices can be completed more easily in this complex system using the Householder method, which is a small signal stability analysis method that is suggested in the thesis, the detection of error and troubleshooting can be performed in a shorter period of time. In this paper, examples of different rotor angle deviations of synchronous generators were made by simulating rotor angle stability deviations up to five degrees, allowing the system to operate stably, and concluding that the system remains constant.
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Boice, Emily N., Sofia I. Hernandez Torres, Zechariah J. Knowlton, David Berard, Jose M. Gonzalez, Guy Avital und Eric J. Snider. „Training Ultrasound Image Classification Deep-Learning Algorithms for Pneumothorax Detection Using a Synthetic Tissue Phantom Apparatus“. Journal of Imaging 8, Nr. 9 (11.09.2022): 249. http://dx.doi.org/10.3390/jimaging8090249.
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Ultrasound (US) imaging is a critical tool in emergency and military medicine because of its portability and immediate nature. However, proper image interpretation requires skill, limiting its utility in remote applications for conditions such as pneumothorax (PTX) which requires rapid intervention. Artificial intelligence has the potential to automate ultrasound image analysis for various pathophysiological conditions. Training models require large data sets and a means of troubleshooting in real-time for ultrasound integration deployment, and they also require large animal models or clinical testing. Here, we detail the development of a dynamic synthetic tissue phantom model for PTX and its use in training image classification algorithms. The model comprises a synthetic gelatin phantom cast in a custom 3D-printed rib mold and a lung mimicking phantom. When compared to PTX images acquired in swine, images from the phantom were similar in both PTX negative and positive mimicking scenarios. We then used a deep learning image classification algorithm, which we previously developed for shrapnel detection, to accurately predict the presence of PTX in swine images by only training on phantom image sets, highlighting the utility for a tissue phantom for AI applications.
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Deenadhayalan, Pratiba, Ramakanth Kumar Pattar und Vijay Chiranjith Reddy. „Functional segments and software defined trends in enterprise networks“. Indonesian Journal of Electrical Engineering and Computer Science 31, Nr. 2 (01.08.2023): 957. http://dx.doi.org/10.11591/ijeecs.v31.i2.pp957-967.
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In the current scenarios most of the business growth comes from the user experience, while using the business applications. Any enterprise network performance depends on the fundamental process of securely serving the user with applications. The network usage patterns have completely changed from just data transfer, voice, and video transmissions to serving entire applications over the networks. With all the modern applications served over the private and public clouds the network resources utilization must be optimized and take full advantage of them which is not possible with current network architectures. The enterprises are currently shifting towards software defined implementation due to many reasons like consistent policy application across the network, run time analytics for troubleshooting the problems and making the network cloud computing ready. Software defined approaches provide centralized security monitoring and control, user data and identity-based segmentation over the network, dynamic recovery from network infrastructure failure and finally virtualization of almost everything. This paper is an overview of the functioning of enterprises in the networking perspective along with current software defined approaches being used in enterprise networking which will soon take over the traditional networks by solving the challenges present in the software defined networking.
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Chen, Junfu, Xiaodong Zhao und Dechang Pi. „A deep auto-encoder satellite anomaly advance warning framework“. Aircraft Engineering and Aerospace Technology 93, Nr. 6 (16.07.2021): 1085–96. http://dx.doi.org/10.1108/aeat-09-2019-0185.
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Purpose The purpose of this paper is to ensure the stable operation of satellites in orbit and to assist ground personnel in continuously monitoring the satellite telemetry data and finding anomalies in advance, which can improve the reliability of satellite operation and prevent catastrophic losses. Design/methodology/approach This paper proposes a deep auto-encoder (DAE) satellite anomaly advance warning framework for satellite telemetry data. Firstly, this study performs grey correlation analysis, extracts important feature attributes to construct feature vectors and builds the variational auto-encoder with bidirectional long short-term memory generative adversarial network discriminator (VAE/BLGAN). Then, the Mahalanobis distance is used to measure the reconstruction score of input and output. According to the periodic characteristic of satellite operation, a dynamic threshold method based on periodic time window is proposed. Satellite health monitoring and advance warning are achieved using reconstruction scores and dynamic thresholds. Findings Experiment results indicate DAE methods can probe that satellite telemetry data appear abnormal, trigger a warning before the anomaly occurring and thus allow enough time for troubleshooting. This paper further verifies that the proposed VAE/BLGAN model has stronger data learning ability than other two auto-encoder models and is sensitive to satellite monitoring data. Originality/value This paper provides a DAE framework to apply in the field of satellite health monitoring and anomaly advance warning. To the best of the authors’ knowledge, this is the first paper to combine DAE methods with satellite anomaly detection, which can promote the application of artificial intelligence in spacecraft health monitoring.
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Zhang, Heng, Zhiping Cai, Qiang Liu, Qingjun Xiao, Yangyang Li und Chak Fone Cheang. „A Survey on Security-Aware Measurement in SDN“. Security and Communication Networks 2018 (2018): 1–14. http://dx.doi.org/10.1155/2018/2459154.
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Software-defined networking (SDN) is one of the most prevailing networking paradigms in current and next-generation networks. Basically, the highly featured separation of control and data planes makes SDN a proper solution towards many practical problems that challenge legacy networks, for example, energy efficiency, dynamic network configuration, agile network measurement, and flexible network deployment. Although the SDN and its applications have been extensively studied for several years, the research of SDN security is still in its infancy. Typically, the SDN suffers from architecture defect and OpenFlow protocol loopholes such as single controller problem, deficiency of communication verification, and network resources constraint. Hence, network measurement is a fundamental technique of protecting SDN against the above security threats. Specifically, network measurement aims to understand and quantify a variety of network behaviors to facilitate network management and monitoring, anomaly detection, network troubleshooting, and the establishment of security mechanisms. In this paper, we present a systematic survey on security-aware measurement technology in SDN. In particular, we first review the basic architecture of SDN and corresponding security challenges. Then, we investigate two performance measurement techniques in SDN, namely, link latency and available bandwidth measurements. After that, we further provide a general overview of topology measurement in SDN including intradomain and interdomain topology discovering techniques. Finally, we list three interesting future directions of security-aware measurement in SDN followed by giving conclusion remarks.
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Sreedevi, Merlin, Dipu T. S., Preetha Prasanna, Fabia Edathadathil, Elizabeth Thomas, Hima Joy, Aswathy S., Vijayakumar K., Sreelakshmi Mohandas und Beena K. V. „A tertiary care system response to COVID-19 in a resource limited setting: a 6-month experience“. International Journal Of Community Medicine And Public Health 8, Nr. 2 (27.01.2021): 986. http://dx.doi.org/10.18203/2394-6040.ijcmph20210254.
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Kerala recorded the initial cases of COVID/SARS-CoV-2 in India and managed to successfully contain it initially through its public health system. As the number of cases increased, the private sector also needed to be prepared. Here, we describe the preparedness and response of a tertiary care system in the nonpublic sector. The Health system response and preparedness consisted of establishment of leadership and infrastructural modification; screening-fever clinic, inpatient admission pathway, dynamic screening strategy training; developing protocols for emergencies and review visits of patients requiring dialysis and chemotherapy. Other priorities included maintaining supply chain of PPE, other essentials such as antivirals and establishing tele consultation. A strong leadership spearheaded infrastructural developments, meetings and troubleshooting every day to adapt to the changing epidemiological and clinical scenario. The Fever clinic was the designated area for consultation of patients with positive symptoms complex and epidemiological risk factors. In early March the screening strategy focused on the presence of a combination of epidemiological and clinical risk factors. As the number of contact cases rose, the focus shifted to identifying any of the defined epidemiological risk factors among persons reaching the hospital. The challenges included redesigning a patient movement pathway, deployment of human resources from their regular work to the screening activities, training of the repurposed human resource, procurement of good quality PPE, coordinating among the specialties, ensuring psychological support etc. The implementation of a timely COVID screening strategy aided our tertiary care centre to provide health care to all patients during the pandemic seamlessly.
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Ramon Fontes, Allan Martins, Vicente Sousa, Kaio Dantas, Lucas Medeiros, Pedro Alves, Marcelo Fernandes et al. „Open-source emulation-based test environment to settle O-RAN-compliant trials“. ITU Journal on Future and Evolving Technologies 4, Nr. 2 (23.06.2023): 305–63. http://dx.doi.org/10.52953/vmbq6087.
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Experimental tools are a key factor in both academic and industrial research communities to create design evaluations of new networking technologies that involve troubleshooting or changing the planning of deployed networks. Physical Software-Defined Radio (SDR) experimental platforms enable a design solution for the quick prototyping of wireless communication systems. However, SDR-based experimental platforms incur high costs, which leads to scalability limitations in the experimental settings. Having said this, network simulators, emulators, and new testbeds have attracted increasing attention. Emulation-based research prototyping can be distinguished from real communication networks and SDR-based platforms by allowing a tradeoff between cost and flexibility. This paper examines the Mininet-RAN emulation tool, which, as well as Radio Access Network (RAN) modeling, provides a way to test Open RAN Intelligent Controller (RIC) services without the need to deploy an entire RAN infrastructure. The Mininet-RAN creates virtual network elements, such as hosts, L2/L3 devices, controllers, and links, by combining some of the best emulator features, hardware testbeds, and simulators. By running the current code of standard practice Unix/Linux network applications and network stack, the Mininet-RAN enables real-world network data traffic patterns to be delivered to the RIC, regarding the most significant aspect of the dynamic generation of wireless system's KPIs. We provide the basic code of Mininet-RAN for the first two O-RAN Alliance-defined use cases involving V2X and UAV. The xApps are being implemented in O-RAN SC near-RT RIC, with Mininet-RAN which provides a closed-loop validation environment.
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Ryzhov, Yevhen, Lev Sakovych, Sergey Glukhov und Yuriy Nastishin. „Assessment of the influence of diagnostic support on reliability of radio electronic systems“. Military Technical Collection, Nr. 24 (20.05.2021): 3–8. http://dx.doi.org/10.33577/2312-4458.24.2021.3-8.
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Currently, there is a trend of digital information processing in electronic weapons systems and military equipment. Software-controlled means of communication are being implemented. This requires new approaches in diagnosing them during maintenance, which are significantly different from the process of finding defects in analog tools. Particular attention is paid to the introduction of modern advances in technical diagnostics and metrology. The possibility of using special methods for assessing the technical condition of digital devices (energy-static, energy-dynamic, electromagnetic), both separately and in combination. This slightly increases the average recovery time, but significantly affects the achievement of the required value of a comprehensive indicator of product reliability - its readiness factor. For the first time, the possibility of classifying electronic systems as "absolutely reliable" due to the peculiarities of metrological and diagnostic software is considered. The influence of controlled variables on the value of the product readiness factor is investigated. Depending on the operating conditions of the repair body, the permissible values for the qualification of specialists (average time of inspection and troubleshooting), as well as for the metrological reliability of measuring equipment are justified. According to the results of research, an algorithm for providing the necessary values of reliability indicators of products, both during their design and during operation and recovery in military conditions. It is shown that the greatest influence on the value of the reliability of products has the training of specialists of the repair body, their ability to fully use the capabilities of modern measuring equipment. The article considers the possibility of using methods for diagnosing digital electronic systems and provides an assessment of the quality of diagnostic software for the reliability of systems as a whole.
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Sarwar, Sajid, Muhammad Yaqoob Javed, Mujtaba Hussain Jaffery, Muhammad Saqib Ashraf, Muhammad Talha Naveed und Muhammad Annas Hafeez. „Modular Level Power Electronics (MLPE) Based Distributed PV System for Partial Shaded Conditions“. Energies 15, Nr. 13 (30.06.2022): 4797. http://dx.doi.org/10.3390/en15134797.
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Photovoltaic (PV) solar energy is a very promising renewable energy technology, as solar PV systems are less efficient because of climate conditions, temperature, and irradiance change. So, to resolve this problem, two PV topologies are used, i.e., centralized and distributed PV systems. The centralized technique is quicker than the distributed technique in terms of convergence speed and a faster power tracking approach. In the event of uniform irradiance, the centralized system also has the benefit of supplying superior energy, but in PS scenarios, a huge amount of energy is lost. However, the distributed approach requires current and voltage measurements at each panel, resulting in a massive data set. Nevertheless, in the event of shading circumstances, the distributed technique is highly effective because a modular level power electronics (MLPE) converter is used. While in a centralized PV system, there is only a single DC-DC converter for the whole PV system. In this research work, a DFO-based DC-DC converter is designed for modular level, with an ability to perform a rapid shutdown of the module under fire hazard conditions, troubleshooting, and monitoring of a module in a very efficient way. The robustness of the proposed MPPT DFO algorithm is tested with different techniques such as Cuckoo Search (CS), Fruit Fly Optimization (FFO), Particle swarm optimization (PSO), Incremental conductance (InC), and Perturb and observe(P&O) techniques. The proposed technique shows better results in terms of MPPT efficiency, dynamic responsiveness, and harmonics. Furthermore, the result of MLPE and the centralized system is verified by using the Helioscope with different inverter companies like SMA, Tigo, Enphase, Solar edge, and Huawei. The results prove that MLPE is a better option in the case of shading region for attaining the maximum power point.
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Landes, N., G. Boksiner und R. Stencel. „Troubleshooting Problematic Chlorine Mixing Dynamics with CFD Analysis“. Proceedings of the Water Environment Federation 2015, Nr. 17 (01.01.2015): 3149–59. http://dx.doi.org/10.2175/193864715819539461.
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Johnson, Engr Nnadikwe, Ikputu Woyengikuro Hilary, Okiki Esther E und Ibe Raymond Obinna. „Design and CFD Application Value Series from Raw Natural Gas Processing to Automated Utilization Need“. International Journal for Research in Applied Science and Engineering Technology 10, Nr. 3 (31.03.2022): 2150–56. http://dx.doi.org/10.22214/ijraset.2022.41029.
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Abstract: Fluid flow systems are common in the energy value chain and are typically complex. To assure the system's performance, understanding and control are essential. Computational fluid dynamics (CFD) is a one-of-a-kind tool that predicts fluid flow events using numerical methods. It allows you to study fluid flow patterns and access non-measurable variables. Because of the rapid advancement of computer science, CFD can currently be used to handle the bulk of industrial operations that require fluid flows. The application's scope is extensive, and the problems it can solve are diverse, spanning from process design validation and optimization to operating condition management and troubleshooting. A few experiments done by Imo State University Petroleum and Gas Lab on upstream natural gas treatment systems to downstream industrial end-use for combined heat and power plants and petrochemical furnaces will demonstrate the application of CFD in troubleshooting. Keywords: CFD, Utilization, Automated, Natural Gas
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Yelgaonkar, Vivek, Gaurav Agrahari, Dhakar Vikrant, Rao Prasanna und B. K. Pathak. „Flow dynamics study of catalyst powder in catalytic cracking unit for troubleshooting“. Nukleonika 62, Nr. 4 (01.12.2017): 277–83. http://dx.doi.org/10.1515/nuka-2017-0040.
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Abstract Gamma scanning and radiotracer applications are very effective and inexpensive tools to understand and optimize the process as well as troubleshoot the various types of problems in many chemical, petrochemical industries and refineries. These techniques are non-invasive; hence, the problems can be pinpointed online, which leads to reduce the downtime, schedule the shutdown and maintenance of the plant equipment, rendering huge economic benefits. In a leading refinery of India, the catalytic cracking unit (CCU) was malfunctioning. It was suspected by the refinery engineers that the catalyst powder was being carried over to the fractionator, which could have led to erosion of the fractionator column internals resulting in their rupture, and consequentially, to the fire hazard. To understand the flow behaviour of the catalyst powder and to ensure the mechanical integrity, catalyst accumulation and choking, both radiotracer study and gamma scanning of the CCU reactor was carried out. The reactor consists of a riser, three primary cyclones and three secondary cyclones. Gamma scanning of the reactor was carried out with the help of an automatic gamma scanner using 1.8 GBq of Co-60 sealed source. Results showed that the catalyst powder was accumulated in one of the secondary cyclones and uneven density distribution was observed in another secondary cyclone. The radiotracer study was carried out using the irradiated catalyst powder as a radiotracer, which contains 0.9 GBq of Na-24. The radiotracer was injected in the reactor through the specially fabricated injection system. Radiation measurement was done using the thermally insulated and collimated NaI(Tl) scintillation detectors located at various strategic locations coupled to a multi-detector data acquisition system. The data were mathematically analysed. It was confirmed that the catalyst powder was accumulated in one of the secondary cyclones with no flow downwards. This resulted in excess powder available to travel along with hydrocarbon towards fractionator. Since the quantity of powder released through the hydrocarbon outlet of CCU was higher than the designed value, the catalyst powder was observed in various zones of the fractionator. Mathematical modelling of the radiotracer data obtained at various locations corroborated the scanning results; also, the flow pattern was obtained. Partially blocked secondary cyclone showed plug flow with recirculation; normal working cyclone had plug flow behaviour and the vortex breaker showed parallel flow.
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He, Ai, Qinghua Zeng, You Zhang, Pengfu Xie, Jianping Li und Ming Gao. „A Fault Diagnosis Analysis of Afterburner Failure of Aeroengine Based on Fault Tree“. Processes 11, Nr. 7 (13.07.2023): 2086. http://dx.doi.org/10.3390/pr11072086.
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The afterburner is essential for military aeroengines, providing rapid thrust increase during critical maneuvers. However, complex failure mechanisms pose challenges for fault diagnosis and troubleshooting. This study investigates a specific aviation engine’s afterburner engagement principle and typical faults, using fault tree analysis and computational fluid dynamics (CFD). We propose a hybrid diagnostic fault architecture combining traditional observer fault diagnosis with fault trees for online fault diagnosis of critical faults. Simulations and test bench verification confirm the feasibility and effectiveness of our approach, offering valuable insights and guidance for addressing afterburner engagement issues in aviation engines.
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Dalmacija, Milena, Bozo Dalmacija, Dejan Krcmar, Miljana Prica, Ljiljana Rajic, Srdjan Roncevic und Olivera Gavrilovic. „Solidification/stabilization of metal polluted sediment of Krivaja river“. Chemical Industry 66, Nr. 4 (2012): 469–78. http://dx.doi.org/10.2298/hemind111031110d.
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The Krivaja River is the longest natural water body (109 km) that flows completely within the borders of Serbian province of Vojvodina. In the absence of national legislation, the sediment quality was assessed in accordance with the Dutch classification methodology. It was found that the river sediment is highly contaminated with copper and zinc (192 mg kg-1 and 1218 mg kg-1 respectively), and as such is an extreme risk to the environment and human health. The solidification/stabilization (S/S) treatment with local clay, that has high capacity of cation exchange 70.2 meq/100 g and specific surface area of 630 m2 g-1, was employed for remediation of the contaminated sediment. The sequential extraction procedure showed that the copper and zinc have medium risk for the environment, with the percentage in the carbonate fraction of 18 and 22% respectively. The results of sequential extraction are not in full agreement with the results of pseudo-total metal concentration in the sediment, which only confirms that the total metal concentration is not sufficient to define the real danger to the environment. Based on the pseudo-total metals concentration, the sediment is of Class 4 (Dutch standards). However, judging from the results of sequential extraction, the metals show medium risk. Obviously, these results have to be taken into account in the assessment of the sediment quality, remediation procedures and sediment disposal in general. After the treatment, the proportion of these two metals in the first fraction is significantly reduced (Cu less than 2%, Zn 10%) in most of samples. In order to determine the long-term behavior of S/S mixtures, leaching tests were conducted in accordance with semi-dynamic ANS diffusion test for 90 days. The results indicated that clay can effectively immobilize Cu and Zn: the cumulative leached fraction of copper in mixtures with clay was in the range from 0.001% (mixture with 80% clay) to 0.15% (mixture with 10% clay), and the cumulative leached fraction of zinc in the range of 0.06% (mixture with 80% clay) to 0.10% (mixture with 10% clay). The diffusion coefficients, ranging from 1.5?10-12 cm2s-1 to 3.7?10-14 cm2s-1, showed an effective immobilization of both metals which suggests that these metals are practically immobilized in S/S mixtures even if the level of clay is low. From the point of LX values, all S/S mixtures can be used for the controlled utilization, because the leaching indices ranged from 11.8 to 13.4 for both metals. In all clay and sediment mixtures the dominant leaching mechanism is diffusion (slope values of 0.35 to 0.60), which once again confirms the effectiveness of the applied treatment and can be expected that only a very small amount of contaminants would leach into the environment over time. Future research is heading in the direction of troubleshooting the accumulation of used natural adsorbent after treatment, the possibility of permanent disposal, its regeneration or the possibility of its application as construction material.
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Ta, C. T., und J. Hague. „A Two-Phase Computational Fluid Dynamics Model for Ozone Tank Design and Troubleshooting in Water Treatment“. Ozone: Science & Engineering 26, Nr. 4 (August 2004): 403–11. http://dx.doi.org/10.1080/01919510490482313.
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Laurent, J., R. W. Samstag, J. M. Ducoste, A. Griborio, I. Nopens, D. J. Batstone, J. D. Wicks, S. Saunders und O. Potier. „A protocol for the use of computational fluid dynamics as a supportive tool for wastewater treatment plant modelling“. Water Science and Technology 70, Nr. 10 (24.10.2014): 1575–84. http://dx.doi.org/10.2166/wst.2014.425.
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To date, computational fluid dynamics (CFD) models have been primarily used for evaluation of hydraulic problems at wastewater treatment plants (WWTPs). A potentially more powerful use, however, is to simulate integrated physical, chemical and/or biological processes involved in WWTP unit processes on a spatial scale and to use the gathered knowledge to accelerate improvement in plant models for everyday use, that is, design and optimized operation. Evolving improvements in computer speed and memory and improved software for implementing CFD, as well as for integrated processes, has allowed for broader usage of this tool for understanding, troubleshooting, and optimal design of WWTP unit processes. This paper proposes a protocol for an alternative use of CFD in process modelling, as a way to gain insight into complex systems leading to improved modelling approaches used in combination with the IWA activated sludge models and other kinetic models.
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Kaium, Sk Abdul, Sayed Abul Hossain und Jafar Sadak Ali. „Modal parameter extraction from measured signal by frequency domain decomposition (FDD) technique“. International Journal of Structural Integrity 11, Nr. 2 (07.11.2019): 324–37. http://dx.doi.org/10.1108/ijsi-06-2019-0062.
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Purpose The purpose of this paper is to highlight that the need for improved system identification methods within the domain of modal analysis increases under the impulse of the broadening field of applications, e.g., damage detection and vibro-acoustics, and the increased complexity of today’s structures. Although significant research efforts during the last two decades have resulted in an extensive number of parametric identification algorithms, most of them are certainly not directly applicable for modal parameter extraction. So, based on this, the aim of the present work is to develop a technique for modal parameter extraction from the measured signal. Design/methodology/approach A survey and classification of the different modal analysis methods are made; however, the focus of this thesis is placed on modal parameter extraction from measured time signal. Some of the methods are examined in detail, including both single-degree-of-freedom and multi-degree-of-freedom approaches using single and global frequency-response analysis concepts. The theory behind each of these various analysis methods is presented in depth, together with the development of computer programs, theoretical and experimental examples and discussion, in order to evaluate the capabilities of those methods. The problem of identifying properties of structures that possess close modes is treated in particular detail, as this is a difficult situation to handle and yet a very common one in many structures. It is essential to obtain a good model for the behavior of the structure in order to pursue various applications of experimental modal analysis (EMA), namely: updating of finite element models, structural modification, subsystem-coupling and calculation of real modes from complex modes, to name a few. This last topic is particularly important for the validation of finite element models, and for this reason, a number of different methods to calculate real modes from complex modes are presented and discussed in this paper. Findings In this paper, Modal parameters like mode shapes and natural frequencies are extracted using an FFT analyzer and with the help of ARTeMiS, and subsequently, an algorithm has been developed based on frequency domain decomposition (FDD) technique to check the accuracy of the results as obtained from ARTeMiS. It is observed that the frequency domain-based algorithm shows good agreement with the extracted results. Hence the following conclusion may be drawn: among several frequency domain-based algorithms for modal parameter extraction, the FDD technique is more reliable and it shows a very good agreement with the experimental results. Research limitations/implications In the case of extraction techniques using measured data in the frequency domain, it is reported that the model using derivatives of modal parameters performed better in many situations. Lack of accurate and repeatable dynamic response measurements on complex structures in a real-life situation is a challenging problem to analyze exact modal parameters. Practical implications During the last two decades, there has been a growing interest in the domain of modal analysis. Evolved from a simple technique for troubleshooting, modal analysis has become an established technique to analyze the dynamical behavior of complex mechanical structures. Important examples are found in the automotive (cars, trucks, motorcycles), railway, maritime, aerospace (aircrafts, satellites, space shuttle), civil (bridges, buildings, offshore platforms) and heavy equipment industry. Social implications Presently structural health monitoring has become a significantly important issue in the area of structural engineering particularly in the context of safety and future usefulness of a structure. A lot of research is being carried out in this area incorporating the modern sophisticated instrumentations and efficient numerical techniques. The dynamic approach is mostly employed to detect structural damage, due to its inherent advantage of having global and location-independent responses. EMA has been attempted by many researchers in a controlled laboratory environment. However, measuring input excitation force(s) seems to be very expensive and difficult for the health assessment of an existing real-life structure. So Ambient Vibration Analysis is a good alternative to overcome those difficulties associated with the measurement of input excitation force. Originality/value Three single bay two storey frame structure has been chosen for the experiment. The frame has been divided into six small elements. An algorithm has been developed to determine the natural frequency of those frame structures of which one is undamaged and the rest two damages in single element and double element, respectively. The experimental results from ARTeMIS and from developed algorithm have been compared to verify the effectiveness of the developed algorithm. Modal parameters like mode shapes and natural frequencies are extracted using an FFT analyzer and with the help of ARTeMiS, and subsequently, an algorithm has been programmed in MATLAB based on the FDD technique to check the accuracy of the results as obtained from ARTeMiS. Using singular value decomposition, the power Spectral density function matrix is decomposed using the MATLAB program. It is observed that the frequency domain-based algorithm shows good consistency with the extracted results.
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Zulkarnaen, Iskandar, Jumadil Saputra, Fauzi Abdurrahman und Ella Suzanna. „A Study of Economic and Ecological Strategies for Sustainable Development in Aceh, Indonesia“. International Journal of Engineering & Technology 7, Nr. 4.34 (13.12.2018): 431. http://dx.doi.org/10.14419/ijet.v7i4.34.26905.
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The sustainable development becomes an inevitable paradigm today. It does not only concentrate on economic growth, but also pay attention to other issues on environmental sustainability such as justice, welfare, as well as the maintenance of social and cultural systems. The sustainable development has some indicators and should also proceed with a series of stages namely economic, ecological, political and social culture. Using qualitative data analysis, this study is written to identify whether or not the economic and ecological development in Aceh post-tsunami has met standards of sustainable development. Troubleshooting analysis is performed with statistical studies of a variety of documents compared to some facts and the evolving dynamics in the community that were recorded by media. Based on the central of statistics bureau, Aceh is one of the regions with the highest GDP in Indonesia and there are approximately 6 million hectares of forest and also rich in nature and marine resources. The result of this study shows Acehnese people actually trapped in poverty. It is very ironic because the majority of people are living in the location of natural resources such as forests and coastal areas, as well as natural gas industrial areas. Therefore, the Aceh Government should ensure the welfare of Acehnese people through an optimizing the utilization of the natural resources i.e. forest and coastal and also gas industry.
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Schuler, A. J. „Distributed microbial state effects on competitionin enhanced biological phosphorus removal systems“. Water Science and Technology 54, Nr. 1 (01.07.2006): 199–207. http://dx.doi.org/10.2166/wst.2006.388.
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Computer simulation of activated sludge population dynamics is a useful tool in process design, operation, and troubleshooting, but currently available programs rely on the assumption of “lumped,” or average, system characteristics in each reactor, such as microbial storage product contents. In reality, the states of individual bacteria are likely to vary due to variable residence times in reactors with completely mixed hydraulics. Earlier work by the present author introduced the MATLAB-based distributed state simulation program, Dissimulator 1.0, and demonstrated that distributed states may be particularly important in enhanced biological phosphorus removal (EBPR) systems, which rely on the cycling of bacteria through anaerobic and aerobic reactors to select for a population accumulating multiple microbial storage products. This paper explores the relationships between distributed state profiles, variable anaerobic and aerobic SRTs, and the process rates predicted by lumped and distributed approaches. Consistent with previous results, the lumped approach consistently predicted better EBPR performance than did the distributed approach. The primary reason for this was the presence of large fractions of polyphosphate accumulating organisms (PAOs) with depleted microbial storage product contents, which led to overestimation of process rates by the lumped approach. Distributed and lumped predictions were therefore most similar when microbial storage product depletion was minimal. The effects of variable anaerobic and aerobic SRTs on distributed profile characteristics and process rates are presented. This work demonstrated that lumped assumptions may overestimate EBPR performance, and the degree of this error is a function of the distributed state profile characteristics such as the degree to which fractions of the biomass contain depleted microbial storage product contents.
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Medvedeva, Oksana N., und Aleksander Yu Chilikin. „Determining the probability of accidents on gas distribution and gas consumption pipelines“. Vestnik MGSU, Nr. 10 (Oktober 2021): 1363–77. http://dx.doi.org/10.22227/1997-0935.2021.10.1363-1377.
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Introduction. The aim of this study is to analyze the current state of the Russian Federation gas distribution system, based on statistical material on accidents on gas distribution and gas consumption networks. The problem of ensuring reliable operation and safe operation of systems becomes most urgent in large cities and settlements with multi-stage and branched gas distribution networks, since every year the number of gas pipelines, equipment and fittings that have exhausted their design life increases. The objective of the study is to determine the causes and dynamics of accidents, identify the determining factors, develop an algorithm for quantitative assessment of the risk of emergencies and accidents at the facilities of the gas distribution system.
Materials and methods. In the work, proven research methods were used, including analysis and generalization of theory and experience in the field of reliability of gas distribution pipelines, a systematic approach and mathematical modeling were used.
Results. The materials on gasification of the territory of the Russian Federation using the methods of system analysis are generalized and systematized. Mechanisms of development of failures in gas distribution and gas consumption networks are considered, data on accidents are analyzed. The review of existing methods of troubleshooting and methods of assessing the state of gas pipelines, gas fittings and gas-using equipment is carried out. Methods for improving the efficiency, reliability and safety of gas distribution systems are proposed. The main results of the study are to summarize and systematize the materials of gas distribution organizations for the gasification of the territory of the Russian Federation using systems analysis methods.
Conclusions. The results obtained during the analysis on the state of the accident rate of the structural elements of the gas distribution system can be used to monitor the technical condition of the system, including taking preventive measures to prevent accident incidents.
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Hevener, W., B. Beine, J. Woodruff, D. Munafo, C. Fernandez, S. Rusk, Y. Nygate et al. „0636 Using AI To Predict Future CPAP Adherence and the Impact of Behavioral and Technical Interventions“. Sleep 43, Supplement_1 (April 2020): A243. http://dx.doi.org/10.1093/sleep/zsaa056.632.
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Abstract Introduction Clinical management of CPAP adherence remains an ongoing challenge. Behavioral and technical interventions such as patient outreach, coaching, troubleshooting, and resupply may be deployed to positively impact adherence. Previous authors have described adherence phenotypes that retrospectively categorize patients by discrete usage patterns. We design an AI model that predictively categorizes patients into previously studied adherence phenotypes and analyzes the statistical significance and effect size of several types of interventions on subsequent CPAP adherence. Methods We collected a cross-sectional cohort of subjects (N = 13,917) with 455 days of daily CPAP usage data acquired. Patient outreach notes and resupply data were temporally synchronized with daily CPAP usage. Each 30-days of usage was categorized into one of four adherence phenotypes as defined by Aloia et al. (2008) including Good Users, Variable Users, Occasional Attempters, and Non-Users. Cross-validation was used to train and evaluate a Recurrent Neural Network model for predicting future adherence phenotypes based on the dynamics of prior usage patterns. Two-sided 95% bootstrap confidence intervals and Cohen’s d statistic were used to analyze the significance and effect size of changes in usage behavior 30-days before and after administration of several resupply interventions. Results The AI model predicted the next 30-day adherence phenotype with an average of 90% sensitivity, 96% specificity, 95% accuracy, and 0.83 Cohen’s Kappa. The AI model predicted the number of days of CPAP non-use, use under 4-hours, and use over 4-hours for the next 30-days with OLS Regression R-squared values of 0.94, 0.88, and 0.95 compared to ground truth. Ten resupply interventions were associated with statistically significant increases in adherence, and ranked by adherence effect size using Cohen’s d. The most impactful were new cushions or masks, with a mean post-intervention CPAP adherence increase of 7-14% observed in Variable User, Occasional Attempter, and Non-User groups. Conclusion The AI model applied past CPAP usage data to predict future adherence phenotypes and usage with high sensitivity and specificity. We identified resupply interventions that were associated with significant increases in adherence for struggling patients. This work demonstrates a novel application for AI to aid clinicians in maintaining CPAP adherence. Support
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„Intellectualization of vehicle diagnosis process based on machine learning“. Truck, August 2022, 38–43. http://dx.doi.org/10.36652/1684-1298-2022-8-38-43.
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We proposed technique on the basis of associative rules — one of the machine learning methods, which makes it possible to significantly simplify the troubleshooting process. To facilitate its application during service process in a service enterprise, a web service was developed. With its help, the employee receives a list of parts that, with a high degree of probability, will turn out to be faulty at the same time as the already identified defective one. The developed methodology makes it possible to evaluate the effectiveness of design, technical, technological and other changes made to individual components of vehicle models based on the dynamic analysis of the structure of the association rules themselves. Keywords: machine learning, association rules, troubleshooting, web service, decision making