Research on the Application of Image Feature Extraction in Mechanical Structure Recognition and Fault Diagnosis

被引:0
|
作者
Niu Z. [1 ]
Sun S. [1 ]
机构
[1] College of Mechanical & Electrical Engineering, Anyang Vocational And Technical College, Henan, Anyang
关键词
Fault diagnosis; Feature extraction; Grayscale covariance matrix; Image processing;
D O I
10.2478/amns-2024-1570
中图分类号
学科分类号
摘要
With the rapid development of modern industry and science and technology, in recent years the fault diagnosis method based on image processing has become a research hotspot in the field of mechanical fault diagnosis. In this paper, image characteristics are extracted from multiple aspects such as image texture, color, shape, etc. A grayscale symbiotic matrix image feature extraction method is proposed. On this basis, the algorithm for extracting gray symbiotic matrix time-frequency image features is designed. At the same time, the algorithm and parameters of mechanical structure identification are optimized to identify and diagnose mechanical faults. The results show that the grayscale symbiotic matrix time-frequency image feature extraction algorithm is able to accurately diagnose the wear-type faults, overwork-type faults, and short-circuit-type fault behavior of the mechanical equipment. All of them are able to obtain more than 80% accuracy, and all of them are able to reach 99.99% accurate detection of mechanical faults, which proves the effectiveness of the method of this research. © 2024 Zhenhua Niu et al., published by Sciendo.
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