Research And Application Of Heating Pipeline Leakage Detection Method Based On Infrasound Metho

With the acceleration of urbanization in our country,the areas with centralized heating are constantly expanding,making the safety and stable operation of heating systems increasingly concerning.However,the frequent occurrence of heating pipeline leakage accidents not only leads to economic losses and resource waste but also poses significant threats to people’s lives and property.To address this challenge,using intelligent technology to monitor pipeline leakage has become an urgent task in today’s society.This technology can not only effectively prevent leakage accidents but also bring enormous economic benefits to the heating system.In recent years,the infrasound method has received widespread attention due to its high sensitivity and broad applicability.This study focuses on the issues in the infrasound method,conducting research on leakage signal denoising,leakage identification,and leakage point localization,with the main content as follows:(1)Firstly,based on theoretical research,we analyze the noise situation in the infrasound signal of pipeline leakage.In response to the limitations of traditional denoising methods,this study proposes a parameter-optimized variational mode decomposition denoising algorithm.The algorithm introduces the energy entropy screening criterion,effectively filtering and reconstructing the components after signal mode decomposition.Through simulation and experimental verification,this method achieves better denoising results.(2)To address leakage identification,this paper presents a WT-UMAP-SVM pipeline leakage identification method.The method uses wavelet transform for time-frequency feature extraction,then applies the UMAP algorithm for feature dimension reduction,serving as input feature vectors for the support vector machine,ultimately completing leakage identification.This method better describes signal characteristics,reduces the dimensionality of feature space,improves computational efficiency,and achieves higher leakage detection accuracy and stability.(3)To solve the problem of large estimation errors in basic cross-correlation delay estimation,this study adopts generalized cross-correlation for delay estimation.After comparing the performance of different weighting functions in delay estimation,the weighting functions are optimized.Further,the leakage signals denoised by the parameter-optimized variational mode decomposition algorithm are combined with generalized cross-correlation delay estimation for leakage point localization.Experimental results show that this localization method has higher localization accuracy compared to traditional methods,effectively improving the accuracy and reliability of leakage detection.(4)To verify the effectiveness and applicability of the proposed methods,actual measurements were conducted on laboratory platforms and heating pipeline sites.By comparing the identification and localization results of different methods,it is confirmed that the methods proposed in this study have better performance in practical applications.