通过随机共振在一块不对称的双稳定系统中进行增强的故障诊断
Yongge Li1, Qixiao Zhu1, Yong Xu1,2
1School of Mathematics and Statistics, Northwestern Polytechnical University, Xi'an 710072, China.
Chaos (Woodbury, N.Y.)
|January 29, 2024
概括
这项研究引入了一种新的零碎不对称的随机共振系统,以改善噪音环境中的弱故障信号检测. 该方法提高了信号与噪声比 (SNR) 以实现更可靠的故障诊断,即使在变化速度的情况下也是如此.
科学领域:
- 机械工程 机械工程
- 信号处理 信号处理
- 错误诊断 错误诊断 错误诊断 错误诊断 错误诊断 错误诊断
背景情况:
- 软弱的故障信号往往会被噪声所掩盖,阻碍了准确的故障诊断.
- 经典的双稳定随机共振 (CBSR) 有 output 和和不完美的优化等局限性.
- 从噪音数据中提取有用的故障特征是一个关键的挑战.
研究的目的:
- 提出一种新的零碎不对称的随机共振系统,以克服CBSR的局限性.
- 为了增强在强噪声的情况下提取弱故障信号.
- 提高故障诊断技术的准确性和可靠性.
主要方法:
- 开发一个零碎不对称的随机共振系统.
- 理论推导的输出信号与噪声比率 (SNR) 使用一个两个状态模型在波激发.
- 拟议方法应用于故障数据分析.
主要成果:
- 拟议的系统在输出SNR方面,与CBSR相比,表现优越.
- 在故障特征频率/顺序下达到更高的光谱峰值.
- 在固定的速度和时间变化的速度条件下有效的性能.
结论:
- 断片不对称的随机共振系统为弱故障信号处理提供了一个有前途的方法.
- 提供了新的理论指导,以提高故障诊断的准确性和可靠性.
- 在从噪音数据中提取故障特征方面优于经典方法.
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