A Weak Signal Detection Method for Bearing Based on QGA and Stochastic Resonance

GE Jiang hua; WANG Yan; WANG Ya ping; SUN Yong guo; Xu Di

doi:10.15938/j.jhust.2020.03.015

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A Weak Signal Detection Method for Bearing Based on QGA and Stochastic Resonance

更新时间：2026-08-31

- A Weak Signal Detection Method for Bearing Based on QGA and Stochastic Resonance
- Vol. 25, Issue 3, Pages: 94-101(2020)
- 作者机构：
  
  哈尔滨理工大学机械动力工程学院,哈尔滨,150080
- 作者简介：
- 基金信息：
- DOI：10.15938/j.jhust.2020.03.015
  CLC： TH165
- Published：2020
- 稿件说明：
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GE Jiang hua, WANG Yan, WANG Ya ping, et al. A Weak Signal Detection Method for Bearing Based on QGA and Stochastic Resonance[J]. 2020, 25(3): 94-101.
DOI：

GE Jiang hua, WANG Yan, WANG Ya ping, et al. A Weak Signal Detection Method for Bearing Based on QGA and Stochastic Resonance[J]. 2020, 25(3): 94-101. DOI： 10.15938/j.jhust.2020.03.015.

摘要

摘要:针对滚动轴承早期故障阶段振动信号微弱，信噪比低，提出量子遗传算法（quantum genetic algorithm，简称QGA）与随机共振相结合的微弱信号检测方法

提高信号信噪比并识别故障位置。首先，对大参数信号变尺度处理，并根据输入信号对噪声强度进行估计实现参数初始化；其次，以输出信噪比作为目标函数，通过QGA对系统的双参数进行自适应寻优；最后，通过系统的随机共振实现微弱信号信噪比的提高。仿真及实验结果表明，该方法充分考虑了系统参数之间的相互作用，能够有效提高信号信噪比，实现了早期故障阶段的微弱信号检测。

Abstract

Abstract:Aiming at the problems that the vibration signal is weak and the SNR is low in its early failure stage of rolling bearing

a weak signal detection method combining Quantum Genetic Algorithm (QGA) and Stochastic Resonance is proposed

which improves SNR and identifies fault location. Firstly

the large parameter signal is scale transformed and the noise intensity is estimated according to the input signal to realize the initialization of the parameters. Secondly

the output SNR is selected as the objective function

and the two parameter are dealt with adaptive optimization through the QGA; Finally

the SNR of weak signal is improved by stochastic resonance system. Simulation and experimental results show that the method fully considers the interaction between system parameters

and can effectively improve SNR

and achieve early detection of weak signal in failure stage.

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