任韵君, 张建刚. 基于自适应欠阻尼系统随机共振方法的故障诊断[J]. 云南大学学报(自然科学版), 2022, 44(6): 1146-1154. doi: 10.7540/j.ynu.20220082
引用本文: 任韵君, 张建刚. 基于自适应欠阻尼系统随机共振方法的故障诊断[J]. 云南大学学报(自然科学版), 2022, 44(6): 1146-1154. doi: 10.7540/j.ynu.20220082
REN Yun-jun, ZHANG Jian-gang. Fault diagnosis based on stochastic resonance method of adaptive underdamped system[J]. Journal of Yunnan University: Natural Sciences Edition, 2022, 44(6): 1146-1154. DOI: 10.7540/j.ynu.20220082
Citation: REN Yun-jun, ZHANG Jian-gang. Fault diagnosis based on stochastic resonance method of adaptive underdamped system[J]. Journal of Yunnan University: Natural Sciences Edition, 2022, 44(6): 1146-1154. DOI: 10.7540/j.ynu.20220082

基于自适应欠阻尼系统随机共振方法的故障诊断

Fault diagnosis based on stochastic resonance method of adaptive underdamped system

  • 摘要: 为了进一步提高故障诊断的输出信噪比和滤波性能,提出了一种基于量子粒子群优化(Quantum Particle Swarm Optimization, QPSO)算法和欠阻尼FitzHugh-Nagumo势的自适应双稳态随机共振进行故障诊断的方法. 首先,研究了基于欠阻尼FitzHugh-Nagumo势的二维双势阱系统输出信噪比的解析式,验证了通过改变系统参数及阻尼系数可以进一步提高信噪比;然后,为了进一步提高输出信噪比,提出了一种基于欠阻尼FitzHugh-Nagumo势的自适应双稳态随机共振方法,该方法通过QPSO算法选择较优的系统参数和欠阻尼阻尼因子以得到最优系统;最后,将该方法用于仿真和实际的轴承故障检测中,结果表明该方法能有效地识别出内外圈的轴承故障,且与传统一阶变步长随机共振(Step-changed Stochastic Resonance, SCSR)相比,提出的方法能够获得更高的信噪比和滤波性能.

     

    Abstract: In order to further improve the output signal-to-noise ratio and filtering performance of fault diagnosis, a fault diagnosis method based on Quantum Particle Swarm Optimization (QPSO) algorithm is proposed. The algorithm is based on underdamped \textFitzHugh-Nagumo potential. The analytical expression of the output signal-to-noise ratio of the two-dimensional double potential well system based on the underdamped \textFitzHugh-Nagumo potential is firstly studied. It is verified that the signal-to-noise ratio can be further improved by changing the system parameters and damping coefficient. Secondly, in order to further improve the output signal-to-noise ratio, an adaptive bistable stochastic resonance method based on underdamped \textFitzHugh-Nagumo potential is proposed. The method is used in simulation and actual bearing fault detection. The results show that the method can effectively identify the bearing faults of the inner and outer rings. Compared with the traditional first-order variable step size SR (SCSR), the method proposed in this paper can obtain Higher signal-to-noise ratio and filtering performance.

     

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