基于周期势函数的自适应二阶欠阻尼随机共振信号增强方法

doi:10.3969/j.issn.1000-1158.2019.04.22

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Abstract Aiming at the problem that the faulty vibration signal of rolling bearing is difficult to extract under noisy environment, an adaptive second-order underdamped stochastic resonance signal enhancement method based on periodic potential function is proposed. The method uses particle swarm optimization to measure system parameters and damping. The adaptive matching of the coefficients realizes the stochastic resonance of multiple pseudo-enhanced frequency bands, and is more suitable for multi-fault signal extraction in engineering practice. The test of fault signal and the engineering experiment show that: 1) The adaptive second-order under-damped stochastic resonance method based on periodic potential function significantly improves the output signal-to-noise ratio, the main peak of the fault characteristic frequency is prominent. The sideband interference is less, the machine is easy to fault, and the false positive rate is low. 2) With the increase of noise intensity, although the output signal-to-noise ratio is reduced, the adaptive second-order underdamped stochastic resonance method based on periodic potential function, the detection effect is still better than the adaptive first-order stochastic resonance method based on periodic potential function. 3) The adaptive second-order under-damped stochastic resonance method based on periodic potential function is more adaptable to noise, in noisy environment, there are obvious advantages for the extraction of weak fault signals.

Key words： metrology fault diagnosis rolling bearing periodic potential function underdamping SNR

Received: 16 July 2018 Published: 10 June 2019

PACS:	TB936
	TB973

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	Articles by authors
	CHEN Jian
	TAO Shan-yong
	WANG Wei
	Lü Wu-yang

Cite this article:

CHEN Jian,TAO Shan-yong,WANG Wei, et al. Adaptive Second-order Underdamped Stochastic Resonance Signal Enhancement Method Based on Periodic Potential Function[J]. Acta Metrologica Sinica, 2019, 40(4): 681-685.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2019.04.22 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2019/V40/I4/681

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