一种基于参数自适应的时频分布方法及应用

A Time-Frequency Distribution Method Based on Parameter Adaptation and Its Application

机械设备在运行过程中发生故障时将出现非平稳动态信号,且大多是频谱随时间有较大变化的时变信号,因此在分析时就需要采用在时域和频域均能保持较高分辨率的方法。本文提出的基于线性调频Chirplet基函数分解的参数自适应时频分布分析方法,可根据非平稳信号的局部时频特性,自主设定时频分析基函数的基本参数并进行自适应分解,所构造的正的、无交叉项干扰的参数自适应时频分布可以准确地刻画非平稳信号的时频特征。通过仿真和实际信号对比表明:所提方法能够较好地描述非平稳信号的时变特征,在时域和频域同时具有很好的局部性,有很好的时间分辨率和频率分辨率,且没有交叉项干扰,在实际应用中可以较好地体现机械设备故障信号的特征,为机械设备故障、桥梁结构损伤等工程应用中的智能诊断提供一种新途径。

Non-stationary dynamic signals will occur when mechanical equipment fails during operation,and most of them are time-varying signals with large changes in frequency over time.Therefore,it is necessary to maintain both time and frequency domains in the analysis.High resolution method.The proposed parameter adaptive timefrequency distribution analysis method based on chirplet-based function decomposition of chirplet can automatically set the basic parameters of time-frequency analysis basis function and adaptively decompose according to the local time-frequency characteristics of non-stationary signals.The positive,time-frequency distribution of the parameter with no cross-interference can accurately characterize the time-frequency characteristics of the non-stationary signal.The simulation and actual signal comparison experiments show that the proposed method can describe the time-varying characteristics of non-stationary signals well,and has good locality in both time and frequency domains,with good time resolution and frequency resolution.There is no cross-interference,which can better reflect the characteristics of mechanical equipment fault signals in practical applications,and provide an advantageous way for intelligent diagnosis in engineering applications such as mechanical equipment failure and bridge structure damage.