论文部分内容阅读
针对当前管道泄漏信号噪声大、定位误差大的问题,提出一种提高定位精度的新方法.泄漏信号经过总体平均经验模态分解(EEMD)之后,可以得到不同尺度的固有模态函数(IMF)分量,这些分量与原信号的相关系数可以作为信号重构的主要依据.这种自适应的降噪方法,不仅提高了重构信号的信噪比,还有效去除了模态混叠的干扰.然后,利用二次相关运算对两路降噪后的泄漏信号进行延时估计,再根据泄漏定位模型计算泄漏位置.最后,采用直接相关方法、基于经验模态分解(EMD)的相关方法以及本文提出的EEMD相关数据处理方法,分别对同组实验数据进行处理,对比定位误差.实验结果表明,EEMD相关方法相比前两种方法,有效抑制了模态混叠,提高了定位精度.
Aiming at the problem of large noise and large positioning error of pipeline leak signal, a new method to improve the positioning accuracy is proposed.After the EEMD of the leakage signal, the IMFs of different scales can be obtained, Component, the correlation coefficients between these components and the original signal can be used as the main basis for signal reconstruction.The adaptive noise reduction method not only improves the signal-to-noise ratio of reconstructed signal, but also effectively eliminates the interference of modal aliasing. Then, the quadratic correlation operation is used to estimate the delay of the two paths of noise-reduced signal and then the leakage location is calculated according to the leakage location model.Finally, using the direct correlation method, the correlation method based on empirical mode decomposition (EMD) The proposed EEMD-related data processing methods respectively deal with the same set of experimental data and compare the positioning errors.The experimental results show that compared with the former two methods, the EEMD-related method effectively suppresses the mode aliasing and improves the positioning accuracy.