ABSTRACT

Aiming at the difficulty of leak detection of urban hazardous chemical pipelines, this paper proposes a method for locating pipeline leaks based on the complementary ensemble local mean decomposition (CELMD) and maximum correlation kurtosis deconvolution (MCKD) secondary noise reduction. First, white noise with opposite sign was added to the original leak signal in pairs, and the noisy signal was decomposed to obtain a series of product functions (PF). Second, select the PF component containing the main leakage information according to the correlation coefficient, and perform the initial noise reduction. Then, the maximum correlation kurtosis deconvolution (MCKD) was used to perform secondary noise reduction on the filtered PF component; Finally, the PF component obtained after two screening was reconstructed, and the pipeline leakage location was completed by calculating the delay parameters of AE signal by cross-correlation. The experimental results show that compared with the cross-correlation method and the ELMD method, the method has higher recognition accuracy and positioning accuracy.

摘要

针对城市危化品管道泄漏检测难的问题，提出了一种基于互补集成局部均值分解（CELMD）和最大相关峰态反卷积（MCKD）二次降噪的管道泄漏定位方法。首先，将符号相反的白噪声成对添加到原始泄漏信号中，并将噪声信号分解以获得一系列乘积函数（PF）。其次，根据相关系数选择包含主要泄漏信息的PF分量，进行初始降噪。然后，使用最大相关峰态反卷积（MCKD）对滤波后的PF分量进行二次降噪；最后对两次筛选后得到的PF分量进行重构，并通过互相关计算AE信号延迟参数完成管道泄漏定位。实验结果表明，与互相关法和ELMD法相比，该方法具有更高的识别精度和定位精度。