基于频谱细化技术的精密旋转轴承音频信号故障检测方法研究

Research on Fault Detection of Precise Swivel Bearing Based on the Audio Signal of Spectrum Zoom Technology

本文研究了基于复解析带通滤波器的复调制频谱细化方法(一种优化ZFFT算法)在精密旋转轴承音频信号故障检测上的应用;针对音频信号的特点,采用加汉宁窗三点卷积幅值校正法进行了误差校正。通过实验证明:该频谱细化技术可以得到高精度的音频信号频率细化谱线,为精密旋转轴承音频信号频谱的细化分析、特征提取、故障检测提供了一种简单有效的方法。

A multiple modulation zoom spectrum Fourier transform （ZFFT） algorithm based on the multiple analytical band-pass filter is presented to detect the fault condition of the precise swivel bearing using the audio signal. In view of the audio signal feature, an improved method of amplitude correction with hanning window of three point convolution is applied. The experimental results indicate that the spectrum zoom technology can obtain the refined spectral line with high precision, thus provide a simple and efficient method to do the zoom analysis, feature extraction and fault detection of audio signal spectrum of precise swivel bearing.