改进的变尺度-凸峰微弱信号检测方法

Haiping Li, R. Tian, Qiang Xue, Yangkun Zhang, Xiaolong Zhang
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引用次数: 6

摘要

在校正检测域法和消除盲域法的基础上,对微弱信号频率识别的变尺度-凸峰法进行了改进。对于待测微弱信号的初始相位,采用随机Melnikov方法得到混沌阈值的解析表达式。阐明了相位对混沌阈值的影响,从而识别出微弱信号的频率。具体来说,将周期内的初始相位分为可检测域和盲域。在可检测域中,当频率识别出现偏差时,引入了可检测域的校正方法。具体来说,利用牛顿插值法给出了校正偏差的计算公式,提高了频率识别的精度。在盲域中,通过构造检测方程给出了消除盲域的方法。通过数值仿真和电路实验验证了改进的变尺度-凸峰法的可行性。通过将识别频率值与理论故障频率值进行比较,确定了高速列车轮对轴承的故障位置。分别在初始相位处于频率可检测域和盲域时采用改进的变尺度-凸峰法。检测效果的准确率可达96.69%,最小信噪比(SNR)可达- 50.857 db。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improved Variable Scale-Convex-Peak Method for Weak Signal Detection
Based on the rectification of detectable domain method and elimination of blind domain method, the variable scale-convex-peak method for the identification frequency of weak signal is improved. For the initial phase of weak signal to be detected, the analytic expression of chaotic threshold is obtained by using stochastic Melnikov method. The influence of phase on chaotic threshold is clarified, which leads to that the frequency of weak signal can be identified. Specifically, the initial phase in a period is divided into the detectable domain and the blind domain. In the detectable domain, when the frequency identification deviates, the rectification of detectable domain method is introduced. Specifically, the Newton interpolation method is used to give the calculation formula to rectify the deviation, which improves the accuracy of frequency identification. In the blind domain, the elimination of blind domain method is given by constructing the detection equations. The feasibility of the improved variable scale-convex-peak method is verified by numerical simulation and circuit experiment. Furthermore, by comparing the identified frequency value with the theoretical fault frequency value, the fault location of the wheelset bearing of high-speed train is determined. The improved variable scale-convex-peak method is applied when the initial phase is in the frequency detectable domain or the blind domain, respectively. The accuracy of the detection effect can be 96.69%, and the minimum signal-to-noise ratio(SNR) can be - 50.8757dB.
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