提升小波改进阈值算法在输气管道泄漏信号降噪处理中的应用

Application of Lifting Wavelet Improved Threshold Algorithm in Noise Reduction Processing of Gas Pipeline Leakage Signal

摘要:

输气管道的泄漏检测对保障其管道的正常运行具有重要意义，但是在实际工作中，传感器检测到的信号会受到噪声的干扰。为了提高管道泄漏检测精度，采用一种不依赖于傅里叶变换的提升小波变换方法，并引入改进阈值函数对信号进行降噪处理，分别对比不同小波基函数，不同分解尺度利用改进阈值算法的降噪效果，确认db5小波函数作为最优提升小波函数，并对信号进行四层分解的信号处理信噪比最高，最后利用现场实验采集到的负压波信号进行传统小波去噪和提升小波改进阈值算法去噪的效果对比，其结果表明提升小波改进阈值算法的去噪效果优于传统小波算法的去噪效果，在管道泄漏检测的信号降噪中具有良好的应用价值。

Abstract:

The leak detection of the gas pipeline is important to ensure the normal operation of the pipeline, but in actual work, the signal detected by the sensor will be disturbed by noise. In order to improve the detection accuracy of pipeline leakage, a lifting wavelet transform method which does not depend on Fourier transform is adopted, and the improved threshold function is introduced to denoise the signal, and different wavelet basis functions are compared. The different decomposition scales are improved by using the improved threshold algorithm. The noise reduction effect is confirmed as the optimal lifting wavelet function of the db5 wavelet function, and the signal processing ratio of the four-layer decomposition of the signal is the highest. Finally, the traditional wavelet denoising and lifting wavelet improvement are performed by using the negative pressure wave signal collected by the field experiment. The comparison of the effect of threshold algorithm denoising shows that the denoising effect of the improved wavelet improved threshold algorithm is better than that of the traditional wavelet algorithm, and it has good application value in signal noise reduction of pipeline leakage detection.