LAPSE:2023.36333
Published Article
LAPSE:2023.36333
A Damage Identification Method Based on Minimum Mean Square Error Estimation for Wind Tunnel Flexible Plate Condition Monitoring System
Kang Yun, Mingyao Liu, Jingliang Wang, Cong Li
July 7, 2023
In this paper, we propose a damage identification method based on minimum mean square error estimation for a wind tunnel flexible plate condition monitoring system. Critical structural members of important equipment are large in size, and the measurement systems used to monitor their condition are often complex. The proposed damage identification method is based on the minimum mean squared error estimator and the generalized likelihood ratio test. It introduced activation function to generate the standard deviation of the data, which can then simulate the sensor output. A single sensor damage only affects a single dimension of the output data matrix of the measurement system. However, structural damage affects the output of multiple sensors. The damage identification method proposed in this paper can not only distinguish the sensor damage from the structure damage, but also locate the damaged sensor or structure damage location. This method can identify the measurement system output anomalies caused by structural damage and locate the approximate location of the damage. It can be applied to damage identification of important structural members such as flexible wind tunnel plates. The damage identification method proposed in this paper is of great significance for damage identification and localization of key components and sensor systems.
Keywords
damage identification, generalized likelihood ratio test, minimum mean square error estimation, wind tunnel flexible plate
Suggested Citation
Yun K, Liu M, Wang J, Li C. A Damage Identification Method Based on Minimum Mean Square Error Estimation for Wind Tunnel Flexible Plate Condition Monitoring System. (2023). LAPSE:2023.36333
Author Affiliations
Yun K: School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China; Henan Key Laboratory of Intelligent Manufacturing of Mechanical Equipment, College of Mechanical and Electrical Engineering, Zhengzhou University of Ligh [ORCID]
Liu M: School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China
Wang J: School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China
Li C: School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China
Journal Name
Processes
Volume
11
Issue
6
First Page
1791
Year
2023
Publication Date
2023-06-12
Published Version
ISSN
2227-9717
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Original Submission
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PII: pr11061791, Publication Type: Journal Article
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LAPSE:2023.36333
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doi:10.3390/pr11061791
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Jul 7, 2023
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CC BY 4.0
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Jul 7, 2023
 
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Calvin Tsay
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