Modeling and Optimization for Fault Diagnosis of Electromechanical Systems Based on Zero Crossing Algorithm
The demand of system security and reliability in the modern industrial process is ever-increasing, and fault diagnosis technology has always been a crucial research direction in the control field. Due to the complexity, nonlinearity, and coupling of multitudinous control systems, precise system mode...
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Online Access: | http://dx.doi.org/10.1155/2020/9267838 |
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doaj-01dccffdff634084bc80ca9618561a412020-11-25T03:18:59ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472020-01-01202010.1155/2020/92678389267838Modeling and Optimization for Fault Diagnosis of Electromechanical Systems Based on Zero Crossing AlgorithmQing Chen0Tao Liu1Xing Wu2Hua Li3Key Laboratory for Advanced Equipment Intelligent Manufacturing Technology of Yunnan Province, Kunming University of Science and Technology, Kunming 650500, ChinaKey Laboratory for Advanced Equipment Intelligent Manufacturing Technology of Yunnan Province, Kunming University of Science and Technology, Kunming 650500, ChinaKey Laboratory for Advanced Equipment Intelligent Manufacturing Technology of Yunnan Province, Kunming University of Science and Technology, Kunming 650500, ChinaKey Laboratory for Advanced Equipment Intelligent Manufacturing Technology of Yunnan Province, Kunming University of Science and Technology, Kunming 650500, ChinaThe demand of system security and reliability in the modern industrial process is ever-increasing, and fault diagnosis technology has always been a crucial research direction in the control field. Due to the complexity, nonlinearity, and coupling of multitudinous control systems, precise system modeling for fault diagnosis is attracting more attention. In this paper, we propose an improved method of electromechanical systems fault diagnosis based on zero-crossing (ZC) algorithm, which can present the calculation model of zero-crossing rate (ZCR) and optimize the parameters of ZC algorithm by establishing a criterion function model to improve the diagnosis accuracy and robustness of ZC characteristic model. The simulation validates the influence of different signal-to-noise ratio (SNR) on ZC feature recognition ability and indicates that the within-between distance model is effective to enhance the diagnose accuracy of ZC feature. Finally, the method is applied to the diagnosis of motor fault bearing, which confirms the necessity and effectiveness of the model improvement and parameter optimization and verifies the robustness to the load.http://dx.doi.org/10.1155/2020/9267838 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Qing Chen Tao Liu Xing Wu Hua Li |
spellingShingle |
Qing Chen Tao Liu Xing Wu Hua Li Modeling and Optimization for Fault Diagnosis of Electromechanical Systems Based on Zero Crossing Algorithm Mathematical Problems in Engineering |
author_facet |
Qing Chen Tao Liu Xing Wu Hua Li |
author_sort |
Qing Chen |
title |
Modeling and Optimization for Fault Diagnosis of Electromechanical Systems Based on Zero Crossing Algorithm |
title_short |
Modeling and Optimization for Fault Diagnosis of Electromechanical Systems Based on Zero Crossing Algorithm |
title_full |
Modeling and Optimization for Fault Diagnosis of Electromechanical Systems Based on Zero Crossing Algorithm |
title_fullStr |
Modeling and Optimization for Fault Diagnosis of Electromechanical Systems Based on Zero Crossing Algorithm |
title_full_unstemmed |
Modeling and Optimization for Fault Diagnosis of Electromechanical Systems Based on Zero Crossing Algorithm |
title_sort |
modeling and optimization for fault diagnosis of electromechanical systems based on zero crossing algorithm |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2020-01-01 |
description |
The demand of system security and reliability in the modern industrial process is ever-increasing, and fault diagnosis technology has always been a crucial research direction in the control field. Due to the complexity, nonlinearity, and coupling of multitudinous control systems, precise system modeling for fault diagnosis is attracting more attention. In this paper, we propose an improved method of electromechanical systems fault diagnosis based on zero-crossing (ZC) algorithm, which can present the calculation model of zero-crossing rate (ZCR) and optimize the parameters of ZC algorithm by establishing a criterion function model to improve the diagnosis accuracy and robustness of ZC characteristic model. The simulation validates the influence of different signal-to-noise ratio (SNR) on ZC feature recognition ability and indicates that the within-between distance model is effective to enhance the diagnose accuracy of ZC feature. Finally, the method is applied to the diagnosis of motor fault bearing, which confirms the necessity and effectiveness of the model improvement and parameter optimization and verifies the robustness to the load. |
url |
http://dx.doi.org/10.1155/2020/9267838 |
work_keys_str_mv |
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