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Journal articles on the topic 'Automatic Test Generation and Fault Diagnosis'

Author: Grafiati

Published: 4 June 2021

Last updated: 6 February 2022

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1

RRadheesha, Mrs. "Fault diagnosis using automatic test packet generation." International Journal on Recent and Innovation Trends in Computing and Communication 3, no. 3 (2015): 919–22. http://dx.doi.org/10.17762/ijritcc2321-8169.150304.

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2

Savir, Jacob. "BIST-Based Fault Diagnosis in the Presence of Embedded Memories." VLSI Design 12, no. 4 (January 1, 2001): 487–500. http://dx.doi.org/10.1155/2001/32515.

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An efficient method is described for using fault simulation as a solution to the diagnostic problem created by the presence of embedded memories in BIST designs. The simulation is event-table-driven. Special techniques are described to cope with the faults in the Prelogic, Postlogic, and the logic embedding the memory control or address inputs. It is presumed that the memory itself has been previously tested, using automatic test pattern generation (ATPG) techniques via the correspondence inputs, and has been found to be fault-free.

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3

Deng, Da Wei, and Bao An Li. "Large Unmanned Aerial Vehicle Ground Testing System." Applied Mechanics and Materials 719-720 (January 2015): 1244–47. http://dx.doi.org/10.4028/www.scientific.net/amm.719-720.1244.

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The traditional high altitude long endurance UAV ground testing system (referred to as: testing system) not only lacks of universality and scalability, also incapable of handling faculties during flying procedure. In the paper, by using the new generation of automatic test system (New ATS), the flight simulation method, embedded technology and fault diagnosis technology, we are able to expand the testing system from ground to the sky, improving the generality of the system and UAV’s testing ability, also ensure the safety and reliability of the UAV flight at the same time.Keywords: Unmanned aerial vehicle; Automatic test system;Fault diagnosis; Embedded bus

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4

Gao, Zhan, Min-Chun Hu, Santosh Malagi, Joe Swenton, Jos Huisken, Kees Goossens, and Erik Jan Marinissen. "Reducing Library Characterization Time for Cell-aware Test while Maintaining Test Quality." Journal of Electronic Testing 37, no. 2 (April 2021): 161–89. http://dx.doi.org/10.1007/s10836-021-05943-3.

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AbstractCell-aware test (CAT) explicitly targets faults caused by defects inside library cells to improve test quality, compared with conventional automatic test pattern generation (ATPG) approaches, which target faults only at the boundaries of library cells. The CAT methodology consists of two stages. Stage 1, based on dedicated analog simulation, library characterization per cell identifies which cell-level test pattern detects which cell-internal defect; this detection information is encoded in a defect detection matrix (DDM). In Stage 2, with the DDMs as inputs, cell-aware ATPG generates chip-level test patterns per circuit design that is build up of interconnected instances of library cells. This paper focuses on Stage 1, library characterization, as both test quality and cost are determined by the set of cell-internal defects identified and simulated in the CAT tool flow. With the aim to achieve the best test quality, we first propose an approach to identify a comprehensive set, referred to as full set, of potential open- and short-defect locations based on cell layout. However, the full set of defects can be large even for a single cell, making the time cost of the defect simulation in Stage 1 unaffordable. Subsequently, to reduce the simulation time, we collapse the full set to a compact set of defects which serves as input of the defect simulation. The full set is stored for the diagnosis and failure analysis. With inspecting the simulation results, we propose a method to verify the test quality based on the compact set of defects and, if necessary, to compensate the test quality to the same level as that based on the full set of defects. For 351 combinational library cells in Cadence’s GPDK045 45nm library, we simulate only 5.4% defects from the full set to achieve the same test quality based on the full set of defects. In total, the simulation time, via linear extrapolation per cell, would be reduced by 96.4% compared with the time based on the full set of defects.

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5

Agrawal, Nishant. "Automatic Test Pattern Generation using Grover’s Algorithm." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 14, 2021): 2373–79. http://dx.doi.org/10.22214/ijraset.2021.34837.

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Quantum computing is an exciting new field in the intersection of computer science, physics and mathematics. It refines the central concepts from Quantum mechanics into its least difficult structures, peeling away the complications from the physical world. Any combinational circuit that has only one stuck at fault can be tested by applying a set of inputs that drive the circuit to verify the output response. The outputs of that circuit will be different from the one desired if the faults exist. This project describes a method of generating test patterns using the Boolean satisfaction method. First, the Boolean formula is constructed to express the Boolean difference between a fault-free circuit and a faulty circuit. Second, the Boolean satisfaction algorithm is applied to the formula in the previous step. The Grover algorithm is used to solve the Boolean satisfaction problem. The Boolean Satisfiability problem for Automatic Test Pattern Generation(ATPG) is implemented on IBM Quantum Experience. The Python program initially generates the boolean expression from the file and converts it into Conjunctive Normal Form(CNF) which is passed on to Grover Oracle and runs on IBM simulator and produces excellent results on combinational circuits for test pattern generation with a quadratic speedup. Grover’s Algorithm on this problem has a run time of O(√N).

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6

Cox, H., and J. Rajski. "A method of fault analysis for test generation and fault diagnosis." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 7, no. 7 (July 1988): 813–33. http://dx.doi.org/10.1109/43.3952.

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7

Nam, Dong Soo, Yong Jin Choe, Yeo Hong Yoon, and En Sup Yoon. "Automatic generation of the symptom tree model for process fault diagnosis." Korean Journal of Chemical Engineering 10, no. 1 (January 1993): 28–35. http://dx.doi.org/10.1007/bf02697374.

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8

Hu, Wei, Yi Bing Deng, Hong Qi Feng, Qing E. Wu, Bin Tang, and Jian Hua Zou. "A Framework Design of Automatic Fault Diagnosis System." Applied Mechanics and Materials 330 (June 2013): 635–38. http://dx.doi.org/10.4028/www.scientific.net/amm.330.635.

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To resolve a lasting suitable cabin environment for the astronauts, this paper proposes an effective framework design for automatic fault diagnosis system. This framework can implement a real-time online diagnosis and decision support for fault, and carry out an early diagnosis for weak fault. Finally, this paper achieves an online automatic fault diagnosis system by using neural networks self-learning characteristics and expert knowledge. In two-men-two-days simulated manned space flight test, the software of diagnosis system framework worked well, which has been assessed and verified comprehensively.

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9

Mokhtarnia, Hossein, Shahram Etemadi Borujeni, and Mohammad Saeed Ehsani. "Automatic Test Pattern Generation Through Boolean Satisfiability for Testing Bridging Faults." Journal of Circuits, Systems and Computers 28, no. 14 (February 20, 2019): 1950240. http://dx.doi.org/10.1142/s0218126619502402.

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Automatic test pattern generation (ATPG) is one of the important issues in testing digital circuits. Due to considerable advances made in the past two decades, the ATPG algorithms that are based on Boolean satisfiability have become an integral part of the digital circuits. In this paper, a new method for ATPG for testing bridging faults is introduced. First of all, the application of Boolean satisfiability to circuit modeling is explained. Afterwards, a new method of testing the nonfeedback bridging faults in the combinational circuits is proposed based on Boolean satisfiability. In the proposed method, the faulty circuit is obtained by injecting the faulty gate into the main circuit. Afterwards, the final differential circuit is prepared by using the fault-free and the faulty circuits. Finally, using the resulting differential circuit, the testability of the fault is assessed and the input pattern for detecting the fault in the main circuit is derived. The experimental results presented at the end of this paper indicate the effectiveness and usefulness of this method for testing the bridging faults.

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10

Li, He Jia, Xue Wang, Hai Feng Xu, Cheng Yao, Wen Ju Gao, and Hui Wang. "Design of Automatic Test Platform for the Gyroscope Group Based on Pertinence Matrix." Applied Mechanics and Materials 556-562 (May 2014): 2567–70. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.2567.

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Aiming the problem of the armored vehicle's gun control system that there are many kinds of internal devices, complex fault reasons ,but no all-around and online fault diagnosis and state inspection mean, The automatic test platform for the gyroscope group with performance test and fault diagnosis for component and circuit is designed .The platform based on dependency matrix and optimal criterion of the maximum failure feature information entropy optimize test points ,choose optimal test points design. Performance test module is created and provides test result information for fault dictionary in fault diagnosis module. Automatic test platform is able to locate the circuit component failure.The platform is tested by actual vehicle experiment, and the results prove the reliability and validity of the platform.

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11

Lin, Yung-Chieh, Feng Lu, and Kwang-Ting Cheng. "Multiple-Fault Diagnosis Based On Adaptive Diagnostic Test Pattern Generation." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 26, no. 5 (May 2007): 932–42. http://dx.doi.org/10.1109/tcad.2006.884486.

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12

Lin, Yung-Chieh, Feng Lu, and Kwang-Ting Cheng. "Multiple-fault diagnosis based on adaptive diagnostic test pattern generation." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 26, no. 5 (May 2007): 932–42. http://dx.doi.org/10.1109/tcad.2007.8361586.

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13

Zhao, Wen Jun. "Fault Diagnosis Method Research of Avionics Systems Based on Testing." Applied Mechanics and Materials 519-520 (February 2014): 1149–54. http://dx.doi.org/10.4028/www.scientific.net/amm.519-520.1149.

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As for this problem that the equipment/devices maintenance and troubleshooting of new avionics systems is very difficult, the fault Diagnosis Method based on testing is proposed. This method is used to build fault diagnosis model and generate diagnostic testing strategy by establishing the relationship between the fault and test, and then the automatic test equipment is used to test for fault under the reasoning of the diagnosis inference, finally, fault conclusions are drawn. Application shows that this method is feasible, fault location accuracy is high and application prospect is broad.

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14

Janusz, Margaret E., and Venkat Venkatasubramanian. "Automatic generation of qualitative descriptions of process trends for fault detection and diagnosis." Engineering Applications of Artificial Intelligence 4, no. 5 (January 1991): 329–39. http://dx.doi.org/10.1016/0952-1976(91)90001-m.

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15

Jaffari, Aman, Cheol-Jung Yoo, and Jihyun Lee. "Automatic Test Data Generation Using the Activity Diagram and Search-Based Technique." Applied Sciences 10, no. 10 (May 14, 2020): 3397. http://dx.doi.org/10.3390/app10103397.

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In software testing, generating test data is quite expensive and time-consuming. The manual generation of an appropriately large set of test data to satisfy a specified coverage criterion carries a high cost and requires significant human effort. Currently, test automation has come at the cost of low quality. In this paper, we are motivated to propose a model-based approach utilizing the activity diagram of the system under test as a test base, focusing on its data flow aspect. The technique is incorporated with a search-based optimization heuristic to fully automate the test data generation process and deliver test cases with more improved quality. Our experimental investigation used three open-source software systems to assess and compare the proposed technique with two alternative approaches. The experimental results indicate the improved fault-detection performance of the proposed technique, which was 11.1% better than DFAAD and 38.4% better than EvoSuite, although the techniques did not differ significantly in terms of statement and branch coverage. The proposed technique was able to detect more computation-related faults and tends to have better fault detection capability as the system complexity increases.

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16

Xu, Bo, Li Wei Guo, and Jin Song Yu. "Software Platform for General Purpose Test and Diagnosis." Applied Mechanics and Materials 241-244 (December 2012): 284–87. http://dx.doi.org/10.4028/www.scientific.net/amm.241-244.284.

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This paper centers on the software reuses of Automatic Test Systems (ATS) and the integration of test and diagnosis to reduce maintenance costs. Based on the research into the basic framework, data services, packages and definition of interfaces, we present an integrated software platform for test and diagnosis system. The platform achieves the separation between the user interface and test logic, the combination of fault modeling and diagnostic reasoning, and the integration of test and diagnosis.

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17

Wang, Zhi Song, Li Wei Tang, Wen Wen Yu, and Jin Hua Cao. "Antiaircraft Gun Automatic Fusion Diagnosis Based on D-S Evidence Theory." Applied Mechanics and Materials 241-244 (December 2012): 288–92. http://dx.doi.org/10.4028/www.scientific.net/amm.241-244.288.

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Antiaircraft gun automatic is irrotational machine, its motion presents characteristic of stage, so we proposed a fault diagnosis fusion model based on Dempster-Shafer (D-S) evidence theory. At first, feature parameters are extracted from test data of multi-sensor, then, we propose a revised Minkowski distance to create evidences. Finally, we fuse basic belief assignments according to Dempster combination rule, and the analysis result verifies the effectiveness and feasibility of proposed fault diagnosis method.

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18

Wu, Dengyun, Jianwen Wang, Hong Wang, Hongxing Liu, Lin Lai, Tian He, and Tao Xie. "An Automatic Bearing Fault Diagnosis Method Based on Characteristics Frequency Ratio." Sensors 20, no. 5 (March 10, 2020): 1519. http://dx.doi.org/10.3390/s20051519.

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Bearing is a key component of satellite inertia actuators such as moment wheel assemblies (MWAs) and control moment gyros (CMGs), and its operating state is directly related to the performance and service life of satellites. However, because of the complexity of the vibration frequency components of satellite bearing assemblies and the small loading, normal running bearings normally present similar fault characteristics in long-term ground life experiments, which makes it difficult to judge the bearing fault status. This paper proposes an automatic fault diagnosis method for bearings based on a presented indicator called the characteristic frequency ratio. First, the vibration signals of various MWAs were picked up by the bearing vibration test. Then, the improved ensemble empirical mode decomposition (EEMD) method was introduced to demodulate the envelope of the bearing signals, and the fault characteristic frequencies of the vibration signals were acquired. Based on this, the characteristic frequency ratio for fault identification was defined, and a method for determining the threshold of fault judgment was further proposed. Finally, an automatic diagnosis process was proposed and verified by using different bearing fault data. The results show that the presented method is feasible and effective for automatic monitoring and diagnosis of bearing faults.

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19

Grasso, Francesco, Antonio Luchetta, Stefano Manetti, and Maria Cristina Piccirilli. "A Method for the Automatic Selection of Test Frequencies in Analog Fault Diagnosis." IEEE Transactions on Instrumentation and Measurement 56, no. 6 (December 2007): 2322–29. http://dx.doi.org/10.1109/tim.2007.907947.

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20

Ungermann, Michael, Jan Lunze, and Dieter Schwarzmann. "Test signal generation for service diagnosis based on local structural properties." International Journal of Applied Mathematics and Computer Science 22, no. 1 (March 1, 2012): 55–65. http://dx.doi.org/10.2478/v10006-012-0004-y.

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Test signal generation for service diagnosis based on local structural propertiesThe paper presents a new approach to the generation of test signals used in service diagnosis. The tests make it possible to isolate faults, which are isolable only if the system is brought into specific operating points. The basis for the test signal selection is a structure graph that represents the couplings among the external and internal signals of the system and the fault signals. Graph-theoretic methods are used to identify edges that disappear under certain operating conditions and prevent a fault from changing the system behavior at this operating point. These operating conditions are identified by validuals, which are indicators obtained during the graph-theoretic analysis. The test generation method is illustrated by a process engineering example.

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21

Hwang, G. H., and W. Z. Shen. "Fault analysis and automatic test pattern generation for break faults in programmable logic arrays." IEE Proceedings - Circuits, Devices and Systems 143, no. 3 (1996): 157. http://dx.doi.org/10.1049/ip-cds:19960267.

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22

Zhang, Yong, Jing Qiu, Guanjun Liu, and Zhiao Zhao. "Fault Sample Generation for Virtual Testability Demonstration Test Subject to Minimal Maintenance and Scheduled Replacement." Mathematical Problems in Engineering 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/645047.

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Virtual testability demonstration test brings new requirements to the fault sample generation. First, fault occurrence process is described by stochastic process theory. It is discussed that fault occurrence process subject to minimal repair is nonhomogeneous Poisson process (NHPP). Second, the interarrival time distribution function of the next fault event is proposed and three typical kinds of parameterized NHPP are discussed. Third, the procedure of fault sample generation is put forward with the assumptions of minimal maintenance and scheduled replacement. The fault modes and their occurrence time subject to specified conditions and time period can be obtained. Finally, an antenna driving subsystem in automatic pointing and tracking platform is taken as a case to illustrate the proposed method. Results indicate that both the size and structure of the fault samples generated by the proposed method are reasonable and effective. The proposed method can be applied to virtual testability demonstration test well.

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23

Du, Hai Lian, Zhan Feng Wang, Feng Lv, and Tao Xin. "The Fault Recognition of Motor Based on the Fusion of Neural Network and D-S Evidence Theory." Applied Mechanics and Materials 157-158 (February 2012): 861–64. http://dx.doi.org/10.4028/www.scientific.net/amm.157-158.861.

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In order to reflect the motor from various aspects and realize the motor system state failure mode automatic identification and accurate diagnosis, neural network combined with the D-S evidence theory to form the motor fault diagnosis system. In data fusion level, fault characteristic is classified; and then the fault feature is extracted by the BP neural network and the local fault of the motor is diagnosed, as a result, the independent evidence is obtained; at last the D-S evidence theory fusion algorithm is used on the evidence to achieve the fault of the motor accurate diagnosis.Broken test proved that the diagnosis system improves the motor of the fault diagnosis of accuracy, and can meet the needs of real-time diagnosis. The diagnostic test proved that the diagnosis system improves the accuracy of motor fault diagnosis, and can satisfy the diagnosis in real-time.

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24

Lee, Changkyu, Byeongho Choi, Daegon Park, Youngho Koo, Sangchul Shim, and Kyogun Chang. "Software Design about Integrated Fault Diagnosis for the Propulsion System of the Tracked Amphibious Assault Vehicle." Journal of the Korea Institute of Military Science and Technology 24, no. 4 (August 5, 2021): 457–66. http://dx.doi.org/10.9766/kimst.2021.24.4.457.

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This paper describes the design of model-based fault diagnosis software to apply to the propulsion system in tracked amphibious assault vehicle which consists of an engine, a transmission, a cooling system, and two waterjets. This software includes specific functions to detect the failures regarding sensor malfunctions, mechanical malfunctions, control errors, and communication errors. This software generates the proper malfunction codes which are classified as the warning and caution. In order to validate the fault diagnosis software, the manual and automatic test are performed using the test program with 32 test cases. Test results show that the designed fault diagnosis software is reliable and effective for applying to the propulsion system.

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25

Kato, Toshiji, Genyo Ueta, and Satoshi Ishii. "Automatic Diagnosis of Fault Locations in Power Transformer Impulse Test using Self-Organizing Map." IEEJ Transactions on Power and Energy 122, no. 12 (2002): 1330–36. http://dx.doi.org/10.1541/ieejpes1990.122.12_1330.

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26

Ballé, Peter, and Dominik Fuessel. "Closed-loop fault diagnosis based on a nonlinear process model and automatic fuzzy rule generation." Engineering Applications of Artificial Intelligence 13, no. 6 (December 2000): 695–704. http://dx.doi.org/10.1016/s0952-1976(00)00049-x.

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27

Füssel, Dominik, Peter Ballé, and Rolf Isermann. "Closed Loop Fault Diagnosis Based on a Nonlinear Process Model and Automatic Fuzzy Rule Generation." IFAC Proceedings Volumes 30, no. 18 (August 1997): 349–54. http://dx.doi.org/10.1016/s1474-6670(17)42426-8.

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28

Kim, Jaehyun, and Yangsun Lee. "A Study on the Automatic Generation Program of Pattern Based Fault Diagnosis System using ANTLR." International Journal of Control and Automation 12, no. 9 (September 30, 2019): 1–12. http://dx.doi.org/10.33832/ijca.2019.12.9.01.

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29

Jin, Fu Lu, Yun Peng Li, and Hong Rui Wang. "Design and Implementation on Auto Test Set of an Airborne Radar." Advanced Materials Research 756-759 (September 2013): 489–92. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.489.

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To automatic test the function and performance of an airborne radar, changeable test adapter is adopted to implement the hardware and software design of the automatic test set of the antenna, transceiver and indicator of the radar based on AT89C52. Problems such as t the different types of interfaces, the various kinds of signals and the test of microwave signal are solved successfully and the objectives of resource sharing and automatic test are realized. The test software is designed by modular structure, and with the help of automatic test set hardware, the required test items of the radar system are experimented and the test process control succeeded. Experiment results show that the automatic test set performs steadily and the results meet the requirements of the airborne radar. The set has the advantages of intelligent, manageable and reducing artificial errors. It provides effective guarantees for radars maintenance, fault diagnosis and fault detection, and has a wide application prospect with low cost.

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30

Lu, Shyue-Kung, Fu-Min Yeh, and Jen-Sheng Shih. "Fault Detection and Fault Diagnosis Techniques for Lookup Table FPGAs." VLSI Design 15, no. 1 (January 1, 2002): 397–406. http://dx.doi.org/10.1080/1065514021000012011.

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In this paper, we present a novel fault detection and fault diagnosis technique for Field Programmable Gate Arrays (FPGAs). The cell is configured to implement a bijective function to simplify the testing of the whole cell array. The whole chip is partitioned into disjoint one-dimensional arrays of cells. For the lookup table (LUT), a fault may occur at the memory matrix, decoder, input or output lines. The input patterns can be easily generated with a k-bit binary counter, where k denotes the number of input lines of a configurable logic block (CLB). Theoretical proofs show that the resulting fault coverage is 100%. According to the characteristics of the bijective cell function, a novel built-in self-test structure is also proposed. Our BIST approaches have the advantages of requiring less hardware resources for test pattern generation and output response analysis. To locate a faulty CLB, two diagnosis sessions are required. However, the maximum number of configurations is k + 4 for diagnosing a faulty CLB. The diagnosis complexity of our approach is also analyzed. Our results show that the time complexity is independent of the array size of the FPGA. In other words, we can make the FPGA array C-diagnosable.

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31

Banerjee, Aritra, and Abhijit Chatterjee. "Automatic Test Stimulus Generation for Diagnosis of RF Transceivers Using Model Parameter Estimation." IEEE Transactions on Very Large Scale Integration (VLSI) Systems 23, no. 12 (December 2015): 3114–18. http://dx.doi.org/10.1109/tvlsi.2014.2385863.

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32

Liu, Xue Xia. "Study on Implementation Technology of the Hydraulic System of Certain Engineering Equipment." Advanced Materials Research 503-504 (April 2012): 206–10. http://dx.doi.org/10.4028/www.scientific.net/amr.503-504.206.

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The model suitable to the fault test and diagnosis of hydraulic system of certain engineering equipment is described. The corresponding hardware and software platforms are developed, which can realize data acquisition, processing and fault diagnosis. Based on the multi-thread and multi-panel control technology, the parallel processing and order execution of tasks are achieved. The channel configuration files and system parameter configuration files are made, which can implement automatic signal acquisition. The corresponding remote test and diagnosis system is build based on C/S mode.

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33

Peng, Dong Hui, Fei Ye, Xin Wang, and Chuan Hai Jiao. "The Research of the Grass-Roots Level Radar Equipment Maintenance and Detecting Expert System Model." Applied Mechanics and Materials 602-605 (August 2014): 1793–96. http://dx.doi.org/10.4028/www.scientific.net/amm.602-605.1793.

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In view of the grass-roots level radar equipment maintenance and testing difficulty is big, the efficiency is low, limited technical conditions, etc, put forward a kind of intelligent fault diagnosis expert system model suitable for the radar equipment, and focus on the basic structure of the model, knowledge acquisition and the relevant reasoning mechanism. According to the characteristics of the grass-roots level radar fault diagnosis, the system combines automatic test technology and expert system and can improve the efficiency and reliability of fault diagnosis.

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Xu, Chun Mei, Hao Zhang, and Dao Gang Peng. "A Fault Diagnosis Method Based on Improved Grey Correlation Grade for Turbine Generator Unit." Advanced Materials Research 383-390 (November 2011): 5045–49. http://dx.doi.org/10.4028/www.scientific.net/amr.383-390.5045.

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Analyzing grey correlation grade method, a fault diagnosis method of improved grey correlation grade is presented for turbine generator unit. The method calculates weight according to test sample, and then calculates the weighted grey correlation grade. And for the characteristics of turbine generation unit, a fault diagnosis method based on improved grey correlation grade is presented. Simulation results show that the proposed method can successfully diagnose all fault of turbine generation unit, and fault isolation capability is much stronger than traditional grey relation.

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35

Jegadeeshwaran, R., and V. Sugumaran. "Fuzzy classifier with automatic rule generation for fault diagnosis of hydraulic brake system using statistical features." International Journal of Fuzzy Computation and Modelling 1, no. 3 (2015): 333. http://dx.doi.org/10.1504/ijfcm.2015.069958.

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36

Zhao, Bai Ting, Xiao Fen Jia, and Yong He. "Design of Mine Ventilator Fault Diagnosis System." Applied Mechanics and Materials 596 (July 2014): 110–13. http://dx.doi.org/10.4028/www.scientific.net/amm.596.110.

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The common faults of mine ventilator are researched in this paper, and rotor misalignment, unbalance, oil whirl, surge and other faults and fault characterization of the generation mechanism are analyzed. The faults diagnosis system is designed based on rough neural network. First, the characteristics of the type of fault for fan failure data collection, including vibration and temperature signals. Then, the pretreated sample data using rough set attribute reduction method to delete redundant attributes. Finally, the sample data is divided into training and testing samples, were used to train and test the neural network classifier. Experiments show that the system is reliable, diagnostic yield, improved ventilator system security, expanding the scope of application of rough sets.

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Tang, Gong Min, Fu Jun Liu, and Xiang Bin Sun. "Research and Design on SOA-Based Equipment ATS Architecture." Applied Mechanics and Materials 513-517 (February 2014): 403–7. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.403.

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By analyzing the current problems in equipment automatic test system, we describe the concept, the basic working principle and advantages of service-oriented architecture (SOA), then introduce the web service architecture and the standards of establishing service-oriented architecture. The architecture model of automatic test system on SOA-based equipment was designed, and was used to realize the unified description of equipment automatic test (including fault diagnosis) information. This effectively improves the equipment's capability in performance detection and maintenance support.

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38

Yu, Kun, and Fang Wang. "Research and Design on Intelligent Decision Support System Frame for Vehicle Maintenance." Advanced Materials Research 765-767 (September 2013): 3–7. http://dx.doi.org/10.4028/www.scientific.net/amr.765-767.3.

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This paper analyzes current research results of IDSS and researches the knowledge of vehicle maintenance. By using technologies such as expert system (ES), Data warehouse (DW), fault tree automatic generation, intelligent interface etc. based on the development process and characteristics of IDSS, this paper combines both virtual maintenance and fault diagnosis together, presenting an intelligent decision support system framework for vehicle maintenance with intelligent , interaction and integration.

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39

Chae, Hyeona, Byoungju Choi, and Hoon Jang. "Software-Implemented Fault Injection Test Case Generation Technique for Safety Diagnosis of Automotive Software." KIISE Transactions on Computing Practices 26, no. 1 (January 31, 2020): 1–11. http://dx.doi.org/10.5626/ktcp.2020.26.1.1.

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Vishnubhotla, Sarma R. "Implementation of a Test Generation Algorithm for Hardware Fault Diagnosis in Asynchronous Sequential Circuits." SIMULATION 65, no. 4 (October 1995): 225–38. http://dx.doi.org/10.1177/003754979506500401.

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Yang, Zhenyu. "Automatic Condition Monitoring of Industrial Rolling-Element Bearings Using Motor’s Vibration and Current Analysis." Shock and Vibration 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/486159.

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An automatic condition monitoring for a class of industrial rolling-element bearings is developed based on the vibration as well as stator current analysis. The considered fault scenarios include a single-point defect, multiple-point defects, and a type of distributed defect. Motivated by the potential commercialization, the developed system is promoted mainly using off-the-shelf techniques, that is, the high-frequency resonance technique with envelope detection and the average of short-time Fourier transform. In order to test the flexibility and robustness, the monitoring performance is extensively studied under diverse operating conditions: different sensor locations, motor speeds, loading conditions, and data samples from different time segments. The experimental results showed the powerful capability of vibration analysis in the bearing point defect fault diagnosis. The current analysis also showed a moderate capability in diagnosis of point defect faults depending on the type of fault, severity of the fault, and the operational condition. The temporal feature indicated a feasibility to detect generalized roughness fault. The practical issues, such as deviations of predicted characteristic frequencies, sideband effects, time-average of spectra, and selection of fault index and thresholds, are also discussed. The experimental work shows a huge potential to use some simple methods for successful diagnosis of industrial bearing systems.

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Cao, Wen Bin, Guo Shun Chen, and Gang Niu. "The Study on Test Technologies of C³I Network Equipments." Applied Mechanics and Materials 278-280 (January 2013): 835–39. http://dx.doi.org/10.4028/www.scientific.net/amm.278-280.835.

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C3I network equipments, with complex architecture, deal with quantities of information from the aspect of time and space, which makes them difficult to support. This paper adopts automatic test and diagnosis techniques, analog networking technique and active test method to satisfy the requirements of timeliness, intelligence and high precision in fault location. A virtual network environment is built to complete the network equipments’ test. It is significant to the complex network equipments’ test and diagnosis.

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Ran, Sheng Yi, and Yu Shu Xiong. "Research on Elimination of Electric Power System Fault Based on Electrical Engineering Automatic Control Technology." Advanced Materials Research 898 (February 2014): 771–74. http://dx.doi.org/10.4028/www.scientific.net/amr.898.771.

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In this paper we introduce the computer software fault analysis system to the power fault detection system, and design power fault elimination system of electrical engineering automatic control, and do simulation and experimental study on the performance. When using the turbine blade of electric machinery to detect fault, we can get the automated troubleshooting displacement curve, and using computer simulation to get the electric mechanical stress distribution nephogram. To further verify the effectiveness of the algorithm, we test the frequencies for eight different units, and obtain eight different sets of five order fault diagnosis frequency, and draw the frequency spectrum distribution of frequency response. It provides the theory reference for the automation of power system fault exclusion.

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Ding, Guo Bao, Zhi Cheng Huo, Lian Bing Wang, and Dan Li. "A New Method for Electronic Circuit Fault Knowledge Acquisition Using PSPICE." Advanced Materials Research 753-755 (August 2013): 2511–14. http://dx.doi.org/10.4028/www.scientific.net/amr.753-755.2511.

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A new method for electronic circuit fault knowledge automatic generation Using PSpice has been put forward based on summarizing development of the intelligent fault diagnosis technology. A new algorithm of generating fault knowledge automatically has been designed by analysing the structure characteristics of the CIR file. The algorithm of search automatically has been designed by analysing the structure characteristic of the OUT file. The DC fault dictionary method has been improved and the fault order according to the minimum distance will guide the user to remove the fault. In the end, through these technologies, the fault knowledge query system has been empoldered. The feasibility of the proposed method has been proved by experiment results.

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Simani, Silvio. "Residual generator fuzzy identification for automotive diesel engine fault diagnosis." International Journal of Applied Mathematics and Computer Science 23, no. 2 (June 1, 2013): 419–38. http://dx.doi.org/10.2478/amcs-2013-0032.

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Safety in dynamic processes is a concern of rising importance, especially if people would be endangered by serious system failure. Moreover, as the control devices which are now exploited to improve the overall performance of processes include both sophisticated control strategies and complex hardware (input-output sensors, actuators, components and processing units), there is an increased probability of faults. As a direct consequence of this, automatic supervision systems should be taken into account to diagnose malfunctions as early as possible. One of the most promising methods for solving this problem relies on the analytical redundancy approach, in which residual signals are generated. If a fault occurs, these residual signals are used to diagnose the malfunction. This paper is focused on fuzzy identification oriented to the design of a bank of fuzzy estimators for fault detection and isolation. The problem is treated in its different aspects covering the model structure, the parameter identification method, the residual generation technique, and the fault diagnosis strategy. The case study of a real diesel engine is considered in order to demonstrate the effectiveness the proposed methodology.

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Liu, Sheng Rui. "Based on LabNIEW Environment Auto Fault Detection Research of Virtual Test System." Applied Mechanics and Materials 727-728 (January 2015): 855–58. http://dx.doi.org/10.4028/www.scientific.net/amm.727-728.855.

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Virtual test system based on software as the core of intelligent system based on computer technology. In LabNIEW environment are introduced, on the auto electric power steering, car trouble related performance was tested. Car trouble vary widely, the characteristics of the dynamic and uncertainty, in view of the present automobile fault detection of real-time detection of the existence of difference, the data is not convenient to undertake unity management problems, this paper used the GPS, GPRS and CAN bus technologies, design a set of automatic control system. With the development of era, the existing Petri net reasoning algorithm cannot have satisfied nowadays car diagnostic technology, aiming at this situation, this paper proposes a modified algorithm, with fuzzy reasoning algorithm of Petri net optimization, finally, the fault diagnosis. According to diagnosis, combining wavelet analysis and the principle of artificial immune system, put forward a kind of based on wavelet transform and the fault diagnosis system of the immune system. According to the characteristics of the wavelet analysis, it is used to analyze the unstable signal, signal feature vector as raw data, using the improved negative selection algorithm for himself - he analysis the original data.

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Pomeranz, I., S. M. Reddy, and S. Venkataraman. "$z$-Diagnosis: A Framework for Diagnostic Fault Simulation and Test Generation Utilizing Subsets of Outputs." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 26, no. 9 (September 2007): 1700–1712. http://dx.doi.org/10.1109/tcad.2007.895758.

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Trothe, Max Emil S., Hamid Reza Shaker, Muhyiddine Jradi, and Krzysztof Arendt. "Fault Isolability Analysis and Optimal Sensor Placement for Fault Diagnosis in Smart Buildings." Energies 12, no. 9 (April 26, 2019): 1601. http://dx.doi.org/10.3390/en12091601.

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Faults and anomalies in buildings are among the main causes of building energy waste and occupant discomfort. An effective automatic fault detection and diagnosis (FDD) process in buildings can therefore save a significant amount of energy and improve the comfort level. Fault diagnosability analysis and an optimal FDD-oriented sensor placement are prerequisites for effective, efficient and successful diagnostics. This paper addresses the problem of fault diagnosability for smart buildings. The method used in the paper is a model-based technique which uses Dulmage-Mendelsohn decomposition. To the best of our knowledge, this is the first time that this method is used for applications in smart buildings. First a dynamic model for a zone in a real-case building is developed in which faults are also introduced. Then fault diagnosability is investigated by analyzing the fault isolability of the model. Based on the investigation, it was concluded that not all the faults in the model are diagnosable. Then an approach for placing new sensors is implemented. It is observed that for two test scenarios, placing additional sensors in the model leads to full diagnosability. Since sensors placement is key for an effective FDD process, the optimal placement of such sensors is also studied in this work. A case study of campus building OU44 at the University of Southern Denmark is considered. The results show that as the system gets more complicated by introducing more faults, additional sensors should be added to achieve full diagnosability.

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Andrejevic-Stosovic, Miona, and Vanco Litovski. "Hierarchical approach to diagnosis of electronic circuits using ANNs." Journal of Automatic Control 20, no. 1 (2010): 45–52. http://dx.doi.org/10.2298/jac1001045a.

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In this paper, we apply artificial neural networks (ANNs) to the diagnosis of a mixed-mode electronic circuit. In order to tackle the circuit complexity and to reduce the number of test points hierarchical approach to the diagnosis generation was implemented with two levels of decision: the system level and the circuit level. For every level, using the simulation-before-test (SBT) approach, fault dictionary was created first, containing data relating the fault code and the circuit response for a given input signal. Also, hypercomputing was implemented, i.e. we used parallel simulation of large number of replicas of the original circuit with faults inserted to achieve fast creation of the fault dictionary. ANNs were used to model the fault dictionaries. At the topmost level, the fault dictionary was split into parts simplifying the implementation of the concept. During the learning phase, the ANNs were considered as an approximation algorithm to capture the mapping enclosed within the fault dictionary. Later on, in the diagnostic phase, the ANNs were used as an algorithm for searching the fault dictionary. A voting system was created at the topmost level in order to distinguish which ANN output is to be accepted as the final diagnostic statement. The approach was tested on an example of an analog-to-digital converter.

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Byun, Yeun-Sub, Baek-Hyun Kim, and Rag-Gyo Jeong. "Sensor Fault Detection and Signal Restoration in Intelligent Vehicles." Sensors 19, no. 15 (July 27, 2019): 3306. http://dx.doi.org/10.3390/s19153306.

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This paper presents fault diagnosis logic and signal restoration algorithms for vehicle motion sensors. Because various sensors are equipped to realize automatic operation of the vehicle, defects in these sensors lead to severe safety issues. Therefore, an effective and reliable fault detection and recovery system should be developed. The primary idea of the proposed fault detection system is the conversion of measured wheel speeds into vehicle central axis information and the selection of a reference central axis speed based on this information. Thus, the obtained results are employed to estimate the speed for all wheel sides, which are compared with measured values to identify fault and recover the fault signal. For fault diagnosis logic, a conditional expression is derived with only two variables to distinguish between normal and fault; further, an analytical redundancy structure and a simple diagnostic logic structure are presented. Finally, an off-line test is conducted using test vehicle information to validate the proposed method; it demonstrates that the proposed fault detection and signal restoration algorithm can satisfy the control performance required for each sensor failure.

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