基于相空间重构改进算法的混沌奇异谱分析及应用

doi:10.3969/j.issn.1000-1158.2021.10.07

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Abstract An improved algorithm for phase space reconstruction is proposed for the problem of embedding dimension and delay time uncertainty in chaotic singular spectrum analysis. The joint criterion is evaluated by the supplementary criterion, and the Cao algorithm is improved. An improved embedding dimension stability criterion embedding dimension using the improved Cao algorithm, can quickly and accurately determine the value of the embedding dimension, with accuracy and efficiency; The method of obtaining the delay time based on the maximum joint entropy based on symbol analysis can reduce the amount of calculation and reduce the error. The superiority of the proposed method is verified by numerical comparison experiments. The method is applied in the early fault identification of rolling bearings. The results show that the chaotic singular spectrum can clearly see the pattern distribution of different fault signals and realize the feature extraction of mechanical fault signals. Provide a new and effective way for early diagnosis of mechanical failure.

Key words： metrology chaotic singular spectrum feature extraction improved Cao algorithm symbolic analysis maximal joint entropy rolling bearing fault diagnosis

Received: 12 January 2020 Published: 18 October 2021

PACS:	TB936
	TB973

Fund:Key technology of MW advanced flywheel energy storage

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	Articles by authors
	ZHANG Li-guo
	LIU Wan
	ZHANG Shu-qing
	LIU Hai-tao
	DONG Wei
	SONG Shan-shan

Cite this article:

ZHANG Li-guo,LIU Wan,ZHANG Shu-qing, et al. Chaotic Singular Spectrum Analysis Based on Improved Phase Space Reconstruction Algorithm and Its Application[J]. Acta Metrologica Sinica, 2021, 42(10): 1299-1306.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2021.10.07 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2021/V42/I10/1299

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