Modeling and Optimization for Fault Diagnosis of Electromechanical Systems Based on Zero Crossing Algorithm
Joint Authors
Wu, Xing
Chen, Qing
Liu, Tao
Li, Hua
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-07-27
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Chen, Qing& Liu, Tao& Wu, Xing& Li, Hua. 2020. Modeling and Optimization for Fault Diagnosis of Electromechanical Systems Based on Zero Crossing Algorithm. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1202110
Modern Language Association (MLA)
Chen, Qing…[et al.]. Modeling and Optimization for Fault Diagnosis of Electromechanical Systems Based on Zero Crossing Algorithm. Mathematical Problems in Engineering No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1202110
American Medical Association (AMA)
Chen, Qing& Liu, Tao& Wu, Xing& Li, Hua. Modeling and Optimization for Fault Diagnosis of Electromechanical Systems Based on Zero Crossing Algorithm. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1202110
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1202110