基于旋转编码器信号的滚动轴承故障特征增强提取

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Abstract For the occasion when the fault characteristics of rolling bearings are weak and the installation of vibration sensors is limited, the fault characteristics are not easy to extract. In this paper, combined with the advantages of short signal transmission path and little interference of rotary encoder, this paper proposes a method for enhancing the fault characteristics of rolling bearings based on instantaneous angular speed (IAS) signal of rotary encoder. Firstly, the de-phasing algorithm (DPA) is used to suppress the strict periodic components such as the frequency conversion and its harmonics; secondly, the bearing fault impact component is enhanced by multi-point optimization minimum entropy deconvolution adjusted (MOMEDA); finally, the enhanced signal is analyzed in the spectrum to extract the bearing fault impact characteristics. The effectiveness of the proposed method is verified by simulation and measured data of bearing outer ring.

Key words： Rolling bearing Encoder Instantaneous angular speed De-phase algorithm MOMEDA Fault feature extraction

Received: 12 April 2022 Published: 28 April 2023

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	Articles by authors
	ZHU Yungui
	GUO Yu
	ZOU Xiang
	TIAN Tian
	XU Wantong

Cite this article:

ZHU Yungui,GUO Yu,ZOU Xiang, et al. Enhanced extraction of rolling bearing fault features based on rotary encoder signals[J]. JOURNAL OF VIBRATION AND SHOCK, 2023, 42(8): 119-125.

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http://jvs.sjtu.edu.cn/EN/ OR http://jvs.sjtu.edu.cn/EN/Y2023/V42/I8/119

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