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SBS_FD: Fault Diagnosis of Harmonic Reducers Based on Symmetrized Dot Pattern, Bag of Visual Word, and Support Vector Machine Jointed Method

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成果类型:
期刊论文
作者:
Xinming Han;Zhuo Long;Xiaoguang Ma;Jie Jia;Wenjie Chen;...
作者机构:
[Wenjie Lin] Guangdong Jiya Precision Machinery Technology Co., Ltd, Foshan, China
[Zhuo Long] School of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha, China
Foshan Graduate School, Northeastern University, Foshan, China
College of Information and Engineering, Northeastern University, Shenyang, China
[Wenjie Chen] Lancheng Lab, Midea Group, Foshan, China
语种:
英文
期刊:
2023 IEEE 13th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER)
年:
2023
页码:
939-944
机构署名:
本校为其他机构
院系归属:
电气与信息工程学院
摘要:
In order to realize fault diagnosis of harmonic reducers in real industrial scenarios, a fault diagnosis method based on image visual information, i.e., SBS_FD is proposed. Firstly, Symmetrized Dot Pattern images are obtained based on vibration signals, and Scale Invariant Feature Transform method is used to extract image information, wherein the mappings between fault signals and visual information are achieved. Then the bag of visual word and space pyramid matching method are used to process the visual information. Finally, the support vector machine is used for fault diagnosis. Comprehensiv...

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