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Journal articles on the topic 'Fault Library'

Author: Grafiati

Published: 3 June 2025

Last updated: 1 August 2025

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1

Cheng, Huan Xin, Fei Yi, and Li Cheng. "Fault Detection and Diagnosis and Fault Tolerance Compensation for Electric Actuator." Applied Mechanics and Materials 328 (June 2013): 144–48. http://dx.doi.org/10.4028/www.scientific.net/amm.328.144.

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In the paperhe faults of loops for the process control system, electric actuators (valves) faults for example,established a historical fault library to diagnose the type of faults.Through system modeling method, a mathematical model analyzed the residuals robustness, which proposed a weighted moving average residuals and adaptive threshold envelope trajectory-based fault detection methods.Finally, the faults were adjusted by the active fault tolerant compensation module reasonably.

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Sun, Min, Huaxing Zhao, Bo Chen, Wei Zeng, and Zaineng Yang. "Fault Diagnosis Strategy for Solar Cells Based on Reverse Derivation of I-V Curve." Journal of Physics: Conference Series 2564, no. 1 (2023): 012018. http://dx.doi.org/10.1088/1742-6596/2564/1/012018.

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Abstract This paper proposes a fault diagnosis strategy for solar cells based on the reverse derivation of the I-V curve. This strategy does not require real-time monitoring of the surface irradiance and average temperature of the solar cell during operation. It only needs to calculate(establish) the I-V curve library under different irradiance and solar cell temperature in advance, then measure the open circuit voltage and short circuit current of the photovoltaic module during operation. And the measured voltage and current at the maximum power point can determine whether the solar cell is f

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Wang, Jie, and Jiwei Liu. "Fault-Tolerant Strategy for Real-Time System Based on Evolvable Hardware." Journal of Circuits, Systems and Computers 26, no. 07 (2017): 1750111. http://dx.doi.org/10.1142/s0218126617501110.

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The evolvable hardware (EHW) is widely used in the design of fault-tolerant system. Fault-tolerant system is really a real-time system, and the recovery time is necessary in fault detection and recovery. However, when applying EHW, real-time characteristic is usually ignored. In this paper, a fault-tolerant strategy based on EHW is proposed. The recovery time, predicted by the fault tree analysis (FTA), is considered as a constraint condition. A configuration library is set up in the design phase to accelerate the repair process of the anticipated faults. An evolvable algorithm (EA) based on s

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Sudhakar, Ambarapu, Gaddi Nagasai, Modala Prudhvi Sagar, Maya Vamshi, Vasala Nikhil, and Bodapati Venkata Rajanna. "Transmission line fault analysis using actuating relays and Atmega 328P controller." International Journal of Applied Power Engineering (IJAPE) 12, no. 2 (2023): 190. http://dx.doi.org/10.11591/ijape.v12.i2.pp190-195.

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<span lang="EN-US">Since transmission lines account for 80–86% of power system problems, protecting transmission lines is a critical concern. This research proposes a method to identify and categorize various short circuit defects on transmission lines. Various operational and fault circumstances on the transmission of high voltage lines, including L-L fault, single phase to earth fault, and double line fault, double line Three fault scenarios triple line fault, triple line to ground fault, and triple line are simulated using MATLAB software. These flaws damage the linked devices to the

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Sudhakar, Ambarapu, Gaddi Nagasai, Modala Prudhvi Sagar, Maya Vamshi, Vasala Nikhil, and Bodapati Venkata Rajanna. "Transmission line fault analysis using actuating relays and Atmega 328P controller." International Journal of Applied Power Engineering (IJAPE) 12, no. 2 (2023): 190–95. https://doi.org/10.11591/ijape.v12.i2.pp190-195.

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Since transmission lines account for 80–86% of power system problems, protecting transmission lines is a critical concern. This research proposes a method to identify and categorize various short circuit defects on transmission lines. Various operational and fault circumstances on the transmission of high voltage lines, including L-L fault, single phase to earth fault, and double line fault, double line Three fault scenarios triple line fault, triple line to ground fault, and triple line are simulated using MATLAB software. These flaws damage the linked devices to the power grid. The mai

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Cheng, Zhenglin, Kan Liu, Xueming Li, Shaolong Xu, Zhiwen Chen, and Fengbing Jiang. "Real-Time Evaluation of Ground Insulation Degradation and Fault Warning Method Under Multiple Operating Conditions for Train Traction Drive System." Sensors 25, no. 5 (2025): 1296. https://doi.org/10.3390/s25051296.

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Aiming at the problem that the main circuit grounding fault in the traction drive system of locomotives and high-speed trains can only be diagnosed under a single operating condition and cannot be warned about early, a mechanism and data-driven real-time evaluation and full operating condition fault warning method for ground insulation degradation is proposed. Firstly, based on the mechanism of grounding faults, the circuit characteristics of the main circuit of the traction transmission system under different grounding fault conditions are analyzed, and mathematical models are established for

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Ling, Jie, Qiu Ping Zhang, and Wan Min Huang. "Research and Implementation of Network Fault Location System Based on Event Correlation." Advanced Materials Research 756-759 (September 2013): 2410–15. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.2410.

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Network fault location is the premise of fault repair. Event correlation technique is an important fault location strategy which has its own advantages, but this technique also has some defects. Automatic fault location has not been realized and it worthy further study. This paper proposes a fault location method based on event correlation and realizes a network fault location system, which uses the relationship of topological structure of network node to generate fault correlation graph and the adjacency matrix, and through the fault correlation algorithm to locate the sources of faults. At t

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Peng, Qian, Xiao Hu Yan, Fan Liu, Yong Xing Cao, and Hai Long Zhang. "Transformer Fault Diagnosis Study Based on Bayesian Case Library." Applied Mechanics and Materials 433-435 (October 2013): 1826–31. http://dx.doi.org/10.4028/www.scientific.net/amm.433-435.1826.

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The transformer fault diagnostic method based on Bayesian case library is proposed in the paper. Firstly, a transformer fault case library is established by collecting standard guideline and expert experience. Secondly, by standardizing the states and fault modes in the case library, the method takes the states as inputs and the fault modes as outputs, which are used to train a naive Bayesian network classifier. When it is necessary for a fault diagnosis, the user is expected to input the fault states in order to finalize the correct fault mode with the help of the well-trained classifier. On

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Chen, Yimin, Guanjing Lin, Eliot Crowe, and Jessica Granderson. "Development of a Unified Taxonomy for HVAC System Faults." Energies 14, no. 17 (2021): 5581. http://dx.doi.org/10.3390/en14175581.

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Detecting and diagnosing HVAC faults is critical for maintaining building operation performance, reducing energy waste, and ensuring indoor comfort. An increasing deployment of commercial fault detection and diagnostics (FDD) software tools in commercial buildings in the past decade has significantly increased buildings’ operational reliability and reduced energy consumption. A massive amount of data has been generated by the FDD software tools. However, efficiently utilizing FDD data for ‘big data’ analytics, algorithm improvement, and other data-driven applications is challenging because the

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Patil, Harshal Vilas. "Three-Phase Fault Analysis on Transmission Line in Matlab Simulink." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (2021): 5386–91. http://dx.doi.org/10.22214/ijraset.2021.36027.

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Now-a-days the demand of electricity or power areincreases day by day this results to transmits more power byIncreasing the transmission line capacity from one place to theother place. But during the transmission some faults areoccurred in the system, such as L-L fault (line to line), 1L-Gfault (single line to ground) and 2L-G fault (double line toground). These faults affect the power system equipmentswhich are connected to it. The main aim of this paper is tostudy or analysis of faults and also identifies the effect of thefault in transmission line along with bus system which isconnected to

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Michalak, Michał P., Christian Gerhards, and Peter Menzel. "SubsurfaceBreaks v. 1.0: a supervised detection of fault-related structures on triangulated models of subsurface homoclinal interfaces." Geoscientific Model Development 18, no. 14 (2025): 4469–81. https://doi.org/10.5194/gmd-18-4469-2025.

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Abstract. The study presents a novel approach for fault detection on subsurface geological homoclinal interfaces (slopes) using a supervised learning algorithm and careful input variable (feature) selection. Synthetic faulted slopes are generated using Delaunay triangulation via the Computational Geometry Algorithms Library (CGAL), allowing for adjustments of parameters. We introduce 24 features, including local geometric features and neighborhood analysis, for classification. Support Vector Machine (SVM) is employed as the classification algorithm, achieving high precision and recall rates fo

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Kysarin, M. K. "BEARING FAULT DETECTION BY USING AUTOENCODER CONVOLUTIONAL NEURAL NETWORK." Radio Electronics, Computer Science, Control, no. 2 (June 29, 2025): 116–25. https://doi.org/10.15588/1607-3274-2025-2-10.

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Context. Bearings are an important part for the functioning of various means of transportation. They have the property of wear and failure, which requires high-quality and timely detection of faults. Failures are not always easy to detect, so the use of traditional detection methods may not be effective enough. The use of machine learning methods well-suited to the task can effectively solve the problem of detecting bearing faults. The object of study is the process of non-destructive diagnosis of bearings. The subject of study is methods of selecting hyperparameters and other optimization for

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Ahmed, Ibrahim, Marcos Quiñones-Grueiro, and Gautam Biswas. "Complementary Meta-Reinforcement Learning for Fault-Adaptive Control." Annual Conference of the PHM Society 12, no. 1 (2020): 8. http://dx.doi.org/10.36001/phmconf.2020.v12i1.1289.

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Faults are endemic to all systems. Adaptive fault-tolerant control accepts degraded performance under faults in exchange for continued operation. In systems with abrupt faults and strict time constraints, it is imperative for control to adapt fast to system changes. We present a meta-reinforcement learning approach that quickly adapts control policy. The approach builds upon model-agnostic meta learning (MAML). The controller maintains a complement of prior policies learned under system faults. This ``library" is evaluated on a system after a new fault to initialize the new policy. This contra

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14

Li, Jinjie, Yu Guo, Yajie Dou, JiKai Wang, Biaobiao Qiu, and Xi Liu. "An approach to bearing fault diagnosis based on ensemble learning and case-based reasoning." Journal of Physics: Conference Series 2787, no. 1 (2024): 012042. http://dx.doi.org/10.1088/1742-6596/2787/1/012042.

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Abstract In response to the challenge of multiple fault types and complex diagnostic criteria in bearing fault diagnosis, a case reasoning method based on ensemble learning is proposed. The approach utilizes Case-Based Reasoning (CBR) to construct a case library for vibration-based features of rolling bearings and perform fault diagnosis. Moreover, addressing the issue of determining optimal feature weight ratios when retrieving similar cases in traditional case reasoning methods, a Random Forest algorithm combined with Bayesian Optimization is introduced. This integration allows for adaptive

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Junqiang Ma, Junqiang Ma, Weihao Yan Junqiang Ma, Xiaotian Zhang Weihao Yan, Min Huang Xiaotian Zhang, and Jingyang Wang Min Huang. "PyRS: Cross-platform Data Fault-tolerant Storage Library Based on RS Erasure Code." 網際網路技術學刊 23, no. 7 (2022): 1597–611. http://dx.doi.org/10.53106/160792642022122307014.

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<p>Erasure code has been used by more and more researchers to solve the problem of efficient, reliable, and fault-tolerant data storage. However, the existing libraries based on erase code can only run on the Linux platform, and some of them need GPU support. This paper implements a cross-platform data fault-tolerant storage library based on RS erasure code, PyRS, which is running on CPU without GPU support and developed in Python. PyRS uses Vandermonde matrix as the coding matrix and Numba and NumPy libraries to speed up and optimize the program. This paper compares PyRS with Jerasure o

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Yanna, Pampapathi, Dr Nithin M, and Jeetpal Singh Chhabra. "Improving Quality of Manufacturing Test using Cell-Aware ATPG." Journal of University of Shanghai for Science and Technology 23, no. 06 (2021): 1055–60. http://dx.doi.org/10.51201/jusst/21/05308.

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The existing fault models like stuck-at, small delay defect, transition, and bridge fault models and their associated patterns are becoming less efficient, as the technology moves to increasingly smaller geometries. It is because traditional defect models target the faults only on IC gate boundaries, and the interconnects between the cells, but a significant population of defects (perhaps up to 50%) occurs within the cells or gates which are not specifically targeted by existing ATPG fault models. In this paper, a new ATPG methodology known as the Cell-aware test is implemented explicitly to t

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17

Bryan, Michael J., Srinivas Devadas, and Kurt Keutzer. "Analysis and Design of Regular Structures for Robust Dynamic Fault Testability." VLSI Design 1, no. 1 (1993): 45–60. http://dx.doi.org/10.1155/1993/38536.

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Recent methods of synthesizing logic that is fully and robustly testable for dynamic faults, namely path delay, transistor stuck-open and gate delay faults, rely almost exclusively on flattening given logic expressions into sum-of-products form, minimizing the cover to obtain a fully dynamic-fault testable two-level representation of the functions, and performing structural transformations to resynthesize the circuit into a multilevel network, while also maintaining full dynamic-fault testability. While this technique will work well for random or control logic, it is not practical for many reg

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18

Ni, Huiting, Liqun Lu, Meng Sun, Xin Bai, and Yongfang Yin. "Research on Fault Diagnosis of PST Electro-Hydraulic Control System of Heavy Tractor Based on Support Vector Machine." Processes 10, no. 4 (2022): 791. http://dx.doi.org/10.3390/pr10040791.

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Due to the harsh working environment of the tractor, the transmission can often be faulty. In order to ensure the reliability of its operation, it must be monitored and the fault discovered. In this paper, the support vector machine (SVM) method is used. The eigenvector conversion of the original data uses the following eigenvectors: Three fault modes (leakage fault of shift clutch hydraulic cylinder, blockage fault of oil passage, and blockage fault of proportional valve spool) are identified in matrix and laboratory (MATLAB) with the help of the library for support vector machines (LibSVM) t

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19

Ren, Hongtao, and Ying Zhang. "Study on fault waveform library of PT high voltage side fuse in hydropower station." Journal of Physics: Conference Series 2488, no. 1 (2023): 012018. http://dx.doi.org/10.1088/1742-6596/2488/1/012018.

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Abstract In the arc-suppression coil grounding system of a medium voltage distribution network, high voltage side voltage transformer insurance fusing faults frequently occur, including fusing during startup and grid connection, fusing during operation, fusing during the shutdown, etc., which will directly affect the accuracy of measurement, metering, protection, and other secondary equipment. In this paper, we used the calculation of electromagnetic transient EMTP-ATP software, theoretical analysis of the typical hydropower station wiring and parameters of the medium voltage system, set up th

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Morales, Giovanni, and Sebastian Reyes Angarita. "DETECTION OF OPERATIONAL FAILURES WITH ARTIFICIAL NEURAL NETWORKS: APPLICATION TO THE TENNESSEE EASTMAN PROCESS." Revista Ingenierías Universidad de Medellín 23, no. 44 (2024): 1–19. https://doi.org/10.22395/rium.v23n44a1.

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The purpose of this article is to compare results of fault detection for the Tennessee Eastman (TE) process with the application of artificial neural networks (ANN). The Neuralnet library of the open-source program R, as well as the Keras library of the open-source program Python were used for the training of ANN. The TE process simulation data were down loaded from Harvard University’s server, and subsequently analyzed, defining the trends in the operational variables during the appearance of failures. With the database, the training and validation of different ANN structures were developed,

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Lai, Weijian, Jingguang Li, Weihong Chen, Jiahui Chen, and Shuan Liu. "Algorithm for extracting spectral features of substation high-voltage isolation switch card shibboleth faults." Journal of Physics: Conference Series 2803, no. 1 (2024): 012035. http://dx.doi.org/10.1088/1742-6596/2803/1/012035.

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Abstract Disconnectors are susceptible to equipment defects and hidden dangers due to the harsh natural environment, the impact of load fluctuations in the power grid, and manufacturers’ manufacturing processes. The current production of commonly used fault diagnosis technology is limited, and the number of features extracted from on-site data cannot timely and accurately reflect the equipment failure conditions. Therefore, this paper uses the substation high-voltage isolation switch jamming fault spectrum feature extraction algorithm, the use of high-frequency acquisition technology to establ

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Shahzad, Faisal, Moritz Kreutzer, Thomas Zeiser, et al. "Building and utilizing fault tolerance support tools for the GASPI applications." International Journal of High Performance Computing Applications 32, no. 5 (2016): 613–26. http://dx.doi.org/10.1177/1094342016677085.

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Today’s high performance computing systems are made possible by multiple increases in hardware parallelity. This results in the decrease of mean time to failures of the systems with each newer generation, which is an alarming trend. Therefore, it is not surprising that a lot of research is going on in the area of fault tolerance and fault mitigation. Applications should survive a failure and/or be able to recover with minimal cost. We have used Global Address Space Programming Interface (GASPI), which is a relatively new communication library based on the PGAS model. It fulfills the basic requ

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Lambture, Rahul. "Printed Circuit Board (PCB) Fault Detection." International Journal for Research in Applied Science and Engineering Technology 12, no. 6 (2024): 542–48. http://dx.doi.org/10.22214/ijraset.2024.63142.

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Abstract: Nowadays many industries heavily depend on devices, those, with printed circuit boards (PCBs) to function properly. However issues like connections, damaged components or short circuits can cause malfunctions that result in downtime and financial losses. It is crucial to identify and resolve thesePCB faults to maintain the operation of electronic systems. On average businesses experience a 23% decrease in productivity due to PCB faults. One of the contributors to this problem is the lack of detection and resolution. To tackle this issue we propose an approach using machine learning t

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MacLeod, J. D., V. Taylor, and J. C. G. Laflamme. "Implanted Component Faults and Their Effects on Gas Turbine Engine Performance." Journal of Engineering for Gas Turbines and Power 114, no. 2 (1992): 174–79. http://dx.doi.org/10.1115/1.2906567.

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Under the sponsorship of the Canadian Department of National Defence, the Engine Laboratory of the National Research Council of Canada (NRCC) has established a program for the evaluation of component deterioration on gas turbine engine performance. The effect is aimed at investigating the effects of typical in-service faults on the performance characteristics of each individual engine component. The objective of the program is the development of a generalized fault library, which will be used with fault identification techniques in the field, to reduce unscheduled maintenance. To evaluate the

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Gou, Linfeng, Ruiqian Sun, and Xiaobao Han. "FDIA System for Sensors of the Aero-Engine Control System Based on the Immune Fusion Kalman Filter." Mathematical Problems in Engineering 2021 (March 18, 2021): 1–17. http://dx.doi.org/10.1155/2021/6662425.

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The Kalman filter plays an important role in the field of aero-engine control system fault diagnosis. However, the design of the Kalman filter bank is complex, the structure is fixed, and the parameter estimation accuracy in the non-Gaussian environment is low. In this study, a new filtering method, immune fusion Kalman filter, was proposed based on the artificial immune system (AIS) theory and the Kalman filter algorithm. The proposed method was used to establish the fault diagnosis, isolation, and accommodation (FDIA) system for sensors of the aero-engine control system. Through a filtering

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Bailey, Margaret B., and Jan F. Kreider. "Creating an automated chiller fault detection and diagnostics tool using a data fault library." ISA Transactions 42, no. 3 (2003): 485–95. http://dx.doi.org/10.1016/s0019-0578(07)60149-9.

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Fang, Jin, Xudong Deng, Yuancan Xia, et al. "Research on Identification Method of Transformer Windings’ Loose Vibration Spectrum Considering a Multi-Load Current Condition." Applied Sciences 15, no. 12 (2025): 6949. https://doi.org/10.3390/app15126949.

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During transformer operation, long-term vibration causes the winding to loosen axially. When hit by a short-circuit, the winding deforms to different extents. Thus, identifying early looseness faults in transformer windings is vital for power systems’ stability. To address issues including scarce vibration data across multiple load conditions for transformer winding looseness faults, inadequate extraction of two-dimensional spectrogram features, and the inability to boost recognition accuracy caused by overfitting during fault recognition model training, this study constructed a 10 kV power tr

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DE ALMEIDA, MAURICIO A., HAKIM LOUNIS, and WALCELIO L. MELO. "AN INVESTIGATION ON THE USE OF MACHINE LEARNED MODELS FOR ESTIMATING SOFTWARE CORRECTABILITY." International Journal of Software Engineering and Knowledge Engineering 09, no. 05 (1999): 565–93. http://dx.doi.org/10.1142/s0218194099000310.

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In this paper we present the results of an empirical study in which we have investigated Machine Learning (ML) algorithms with regard to their capabilities to accurately assess the correctability of faulty software components. Three different families algorithms have been analyzed: divide and conquer (top down induction decision tree), covering, and inductive logic programming (ILP). We have used (1) fault data collected on corrective maintenance activities for the Generalized Support Software reuse asset library located at the Flight Dynamics Division of NASA's GSFC and (2) product measures e

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Al-Asaad, H. "New Global Fault Collapsing Techniques for Combinational Library Modules." International Journal of Modelling and Simulation 30, no. 1 (2010): 30–37. http://dx.doi.org/10.1080/02286203.2010.11442555.

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Yuan, Jing, Chenjun Wei, Bo Zou, et al. "A Comparative Study on Multiwavelet Construction Methods and Customized Multiwavelet Library for Mechanical Fault Detection." Shock and Vibration 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/963528.

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Inner product transform principle reveals that the basis functions most relevant or similar to the fault features are pivotal to the meaningful fault detection. Customized multiwavelet methods and practices have continued to improve over the recent years, focused on two-scale similarity transform (TST), lifting transform (LT), and lifting scheme (LS). Due to the respective advantages and disadvantages, a comparative study on the multiwavelet construction methods by TST, symmetric and dissymmetric LT, and LS is discussed in the paper, covering the differences of construction theories, the synth

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Lee, Kyung-Min, and Chul-Won Park. "Ground Fault Detection Using Hybrid Method in IT System LVDC Microgrid." Energies 13, no. 10 (2020): 2606. http://dx.doi.org/10.3390/en13102606.

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Low voltage direct current (LVDC) microgrid systems have many advantages over low voltage alternating current (LVAC) systems. Furthermore, LVDC microgrids are growing in use because they are easy to link to distributed energy resources (DER) and energy storage systems (ESS), etc. Currently, IT system LVDC microgrids are widely used in direct current (DC) railways, hospitals, photovoltaic (PV) systems, and so on. When a ground fault occurs in an IT system LVDC microgrid, the ground fault may not be detected because the fault current is very small and there is no current path. In this paper, gro

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Zeng, Wen Feng, Yu Min Tian, Bao Hui Zhu, and Dong Li. "The Design of a Maintenance Simulation System for Lasers." Advanced Materials Research 926-930 (May 2014): 1440–43. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.1440.

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The MCU system is used to simulate laser signals and the signals received by avalanche transistors so as to conduct signal detection of actual circuit boards.With establishing a library of fault cases through the computer serial port, the MCU and the fault setting module can be based on to realize the fault simulation of actual circuit boards and conduct the training in fault detection and removal. The designed fault setting software and assessment software can be combined to assess the training effects of fault analysis, detection and removal. The developed prototype passes the test of traini

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Ledesma, Pablo, Peyman Jafary, Sami Repo, et al. "Event-Based Simulation of a Decentralized Protection System Based on Secured GOOSE Messages." Energies 13, no. 12 (2020): 3250. http://dx.doi.org/10.3390/en13123250.

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A new simulation library is developed on OMNeT++ to model faults in distribution systems. The proposed library makes it possible to calculate the status of lines and busbars from the point of view of a protection system, enabling the modeling of overcurrents, power outages and fault passage indicators. The library is applied to model a decentralized protection system based on the exchange of IEC 61850 Generic Object Oriented Substation Events (GOOSE) messages between intelligent electronic devices responsible for the operation of circuit breakers and disconnectors. The time needed to secure an

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Mauck, Benjamin M., Vishnumohan Ravichandran, and Usman Azeez Mughal. "On-Die Parametric Analysis of SRAM." EDFA Technical Articles 7, no. 3 (2005): 22–28. http://dx.doi.org/10.31399/asm.edfa.2005-3.p022.

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Abstract Parametric analysis of SRAM cells is widely used to locate faults and analyze device failures, but the pico-probing and bit-line multiplexing required for data acquisition is becoming increasingly difficult. This article explains how the addition of an on-die low-yield analysis circuit eliminates the problem. The simplicity of the measurement circuit and the potential to use a known library of curves, makes low-yield analysis one of the most versatile DFT techniques for cache fault isolation.

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Piesciorovsky, Emilio C., and Marissa E. Morales Rodriguez. "Assessment of the Phase-to-Ground Fault Apparent Admittance Method with Phase/Ground Boundaries to Detect Types of Electrical Faults for Protective Relays Using Signature Library and Simulated Events." International Transactions on Electrical Energy Systems 2022 (September 26, 2022): 1–20. http://dx.doi.org/10.1155/2022/1951836.

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Protective relays in electric power grids recognize the types of electrical faults in a few seconds. The most common detection method to detect the types of electrical faults is based on measuring the angle between the zero and negative sequence currents. However, it is not completely accurate because the phase-to-phase-ground and phase-to-ground electrical faults could have the same detection conditions. Therefore, engineers need to plot the events after an electrical fault to observe the nature of the incidents in detail. In this study, the phase-to-ground fault apparent (PGFA) admittance me

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Atkinson, R. M., M. R. Montakhab, K. D. A. Pillay, et al. "Automated Fault Analysis for Hydraulic Systems: Part 1: Fundamentals." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 206, no. 4 (1992): 207–14. http://dx.doi.org/10.1243/pime_proc_1992_206_336_02.

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Early expert systems for fault analysis tended to be based on shallow, heuristic knowledge. For success in engineering applications, it is argued that the complementary knowledge of the underlying principles (deep knowledge) should also be modelled. An object-oriented software library representing models of components of hydraulic circuits is being built using deep knowledge alone. The software modules within this library are reusable for the construction of model-based expert systems for the performance of failure mode and effects analysis and fault tree analysis on any arbitrary hydraulic ci

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Sun, Pei Feng, and Yong Ni. "Study on CBR-Based Automobile Engine Intelligent Fault Diagnosis Technique." Key Engineering Materials 460-461 (January 2011): 637–41. http://dx.doi.org/10.4028/www.scientific.net/kem.460-461.637.

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It is difficult to do the fault diagnosis on the modern car engines which have high technology and complex structures. In this study, a case-based-reasoning (CBR) based automobile engine intelligent fault diagnosis system was proposed against this problem. The system’s structure and its mechanism of fault diagnosis were introduced. The key techniques to implement the system were analyzed, including the case establishment, the case search, the case learning and the maintenance of case library. The proposed system gave a new way to establish an efficient automobile engine fault diagnosis system.

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Zhao, Yang, Yun Xiong, Xin Qing Wang, Hong Wei Li, and Hui Jie Zhu. "Fault Reasoning and Diagnosis Technology Based on ACO & CBR." Advanced Materials Research 655-657 (January 2013): 1722–29. http://dx.doi.org/10.4028/www.scientific.net/amr.655-657.1722.

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Due to the inaccuracy of reasoning conclusion because of the discrepancy among the cases ontology in the process of case reuse or revision, a new reasoning method for fault diagnosis based on ACO and CBR is proposed by this paper. This method uses CBR to reason new cases firstly, if it can match successfully brings to the corresponding results, else use ACO to reason the cases which have not matching in the case-library. As a result, the accuracy and efficiency of fault diagnosis are improved greatly and use the characteristic of the strong memory in CBR to repair the shortcoming of ACO reason

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Palacin, Luis G., Fernando Tadeo, Hamza Elfil, Cesar de Prada, and Johanna Salazar. "New dynamic library of reverse osmosis plants with fault simulation." Desalination and Water Treatment 25, no. 1-3 (2011): 127–32. http://dx.doi.org/10.5004/dwt.2011.1434.

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Nam, Soon-Ryul, Woong-Hie Ko, Sopheap Key, Sang-Hee Kang, and Nam-Ho Lee. "IEC 61850-Based Centralized Protection against Single Line-To-Ground Faults in Ungrounded Distribution Systems." Energies 14, no. 3 (2021): 722. http://dx.doi.org/10.3390/en14030722.

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We developed an International Electrotechnical Commission (IEC) 61850-based centralized protection scheme to prevent single line-to-ground (SLG) faults in the feeders and busbars of ungrounded distribution systems. Each feeder intelligent electronic device (IED) measures its zero-sequence current and voltage signals and periodically transmits zero-sequence phasors to a central IED via a Generic Oriented Object Substation Event message. Using the zero-sequence phasors, the central IED detects SLG faults in feeders and busbars. To achieve centralized protection, angle differences between the zer

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Liu, Zhen Wu, Zhi Wu Shang, Ya Feng Li, and Tai Yong Wang. "A Fault Diagnosis System Based on Bistable Stochastic Resonance and Dynamic Time Warping." Key Engineering Materials 693 (May 2016): 1294–99. http://dx.doi.org/10.4028/www.scientific.net/kem.693.1294.

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Stator current signal of driving motor can be easily measured. Using it in the gearbox fault diagnosis system is inexpensive and suitable for remote monitoring. According to the application of the Motor Current Signal Analysis in machinery fault detection, we present a new gearbox fault diagnosis system. In modern signal processing technology, Stochastic Resonance theory is widely used to improve SNR (signal to noise ratio). Dynamic time warping algorithm is a simple and efficient way of the pattern identified. Combine the Stochastic Resonance theory and dynamic time warping algorithm as the b

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Yan, Zichen, Jianzhong Sun, Yang Yi, Caiqiong Yang, and Jingbo Sun. "Data-Driven Anomaly Detection Framework for Complex Degradation Monitoring of Aero-Engine." International Journal of Turbomachinery, Propulsion and Power 8, no. 1 (2023): 3. http://dx.doi.org/10.3390/ijtpp8010003.

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Data analysis is an important part of aero engine health management. In order to complete accurate condition monitoring, it is necessary to establish more effective analysis tools. Therefore, an integrated algorithm library dedicated for engine anomaly detection is established, which is PyPEFD (Python Package for Engine Fault Detection). Different algorithms for baseline modeling, anomaly detection and trend analysis are presented and compared. In this paper, the simulation data are used to verify the function of the anomaly detection algorithms, successfully completing the detection of multip

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Wang, Xiaowei, Yanfang Wei, Zhihui Zeng, Yaxiao Hou, Jie Gao, and Xiangxiang Wei. "Fault Line Selection Method of Small Current to Ground System Based on Atomic Sparse Decomposition and Extreme Learning Machine." Journal of Sensors 2015 (2015): 1–19. http://dx.doi.org/10.1155/2015/678120.

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This paper proposed a fault line voting selection method based on atomic sparse decomposition (ASD) and extreme learning machine (ELM). Firstly, it adopted ASD algorithm to decompose zero sequence current of every feeder line at first two cycles and selected the first four atoms to construct main component atom library, fundamental atom library, and transient characteristic atom libraries 1 and 2, respectively. And it used information entropy theory to calculate the atom libraries; the measure values of information entropy are got. It constructed four ELM networks to train and test atom sample

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Zheng, Rong Shu, Xin Min Dong, Wang Sheng Hao, Yan Li, and Rui Xin Wang. "Application of Hidden Markov Models in Ball Mill Gearbox for Fault Diagnosis." Advanced Materials Research 842 (November 2013): 401–4. http://dx.doi.org/10.4028/www.scientific.net/amr.842.401.

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In this paper, a ball mill gear reducer was regarded as the research object. Based on the HMM pattern recognition theory, DHMM methods that were used in fault diagnosis had been researched. The vibration signal was required a series transformations which are feature extraction, normalization, scalarization and quantization to get the sequence collections. Then the quantified sequence collections were trained to get the DHMM parameter, or the Viterbi Algorithm which was used for the quantified sequence collections to calculate the maximum probability, thereby the DHMM fault models library was e

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Ma, Jiming, and Jianbin Guo. "Hierarchical Fault Diagnosis for a Hybrid System Based on a Multidomain Model." Mathematical Problems in Engineering 2015 (2015): 1–16. http://dx.doi.org/10.1155/2015/361631.

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The diagnosis procedure is performed by integrating three steps: multidomain modeling, event identification, and failure event classification. Multidomain model can describe the normal and fault behaviors of hybrid systems efficiently and can meet the diagnosis requirements of hybrid systems. Then the multidomain model is used to simulate and obtain responses under different failure events; the responses are further utilized as a priori information when training the event identification library. Finally, a brushless DC motor is selected as the study case. The experimental result indicates that

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Shahid, Muhammad Asim, Muhammad Mansoor Alam, and Mazliham Mohd Su’ud. "Achieving Reliability in Cloud Computing by a Novel Hybrid Approach." Sensors 23, no. 4 (2023): 1965. http://dx.doi.org/10.3390/s23041965.

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Cloud computing (CC) benefits and opportunities are among the fastest growing technologies in the computer industry. Cloud computing’s challenges include resource allocation, security, quality of service, availability, privacy, data management, performance compatibility, and fault tolerance. Fault tolerance (FT) refers to a system’s ability to continue performing its intended task in the presence of defects. Fault-tolerance challenges include heterogeneity and a lack of standards, the need for automation, cloud downtime reliability, consideration for recovery point objects, recovery time objec

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Wang, Gang, Robert Youngs, Maurice Power, and Zhihua Li. "Design Ground Motion Library: An Interactive Tool for Selecting Earthquake Ground Motions." Earthquake Spectra 31, no. 2 (2015): 617–35. http://dx.doi.org/10.1193/090612eqs283m.

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The Design Ground Motion Library (DGML) is an interactive tool for selecting earthquake ground motion time histories based on contemporary knowledge and engineering practice. It was created from a ground motion database that consists of 3,182 records from shallow crustal earthquakes in active tectonic regions rotated to fault-normal and fault-parallel directions. The DGML enables users to construct design response spectra based on Next-Generation Attenuation (NGA) relationships, including conditional mean spectra, code spectra, and user-specified spectra. It has the broad capability of searchi

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Combs, Sinclair R., and Annalise E. Maughan. "PyFaults: a Python tool for stacking fault screening." Journal of Applied Crystallography 57, no. 6 (2024): 1996–2009. http://dx.doi.org/10.1107/s1600576724009956.

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PyFaults is an open-source Python library designed to model stacking fault disorder in crystalline materials and qualitatively assess the characteristic selective broadening effects in powder X-ray diffraction (PXRD). Here, the main capabilities of PyFaults are presented, including unit cell and supercell model construction, PXRD pattern calculation, assessment against experimental PXRD, and methods for rapid screening of candidate models within a set of possible stacking vectors and fault occurrence probabilities. This program aims to serve as a computationally inexpensive tool for identifyin

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Behravan, Ali, Bahareh Kiamanesh, and Roman Obermaisser. "Fault Diagnosis of DCV and Heating Systems Based on Causal Relation in Fuzzy Bayesian Belief Networks Using Relation Direction Probabilities." Energies 14, no. 20 (2021): 6607. http://dx.doi.org/10.3390/en14206607.

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The state-of-the-art provides data-driven and knowledge-driven diagnostic methods. Each category has its strengths and shortcomings. The knowledge-driven methods rely mainly on expert knowledge and resemble the diagnostic thinking of domain experts with a high capacity in the reasoning of uncertainties, diagnostics of different fault severities, and understandability. However, these methods involve higher and more time-consuming effort; they require a deep understanding of the causal relationships between faults and symptoms; and there is still a lack of automatic approaches to improving the e

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Lu, Jiantao, Weiwei Qian, Shunming Li, and Rongqing Cui. "Enhanced K-Nearest Neighbor for Intelligent Fault Diagnosis of Rotating Machinery." Applied Sciences 11, no. 3 (2021): 919. http://dx.doi.org/10.3390/app11030919.

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Case-based intelligent fault diagnosis methods of rotating machinery can deal with new faults effectively by adding them into the case library. However, case-based methods scarcely refer to automatic feature extraction, and k-nearest neighbor (KNN) commonly required by case-based methods is unable to determine the nearest neighbors for different testing samples adaptively. To solve these problems, a new intelligent fault diagnosis method of rotating machinery is proposed based on enhanced KNN (EKNN), which can take advantage of both parameter-based and case-based methods. First, EKNN is embedd

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