Underground Pipeline Detection Magnetic Anomaly Signal Processing

With the continuous development of the economy and the accelerating process of urbanization,underground pipelines are gradually intensive,forming a large-scale network structure.These pipelines are an important part of the urban infrastructure.They are like the nerves and blood vessels in the human body and bear the important task of transmitting information and delivering energy.Therefore,the exploration and positioning of underground pipelines is of great significance.Magnetic anomaly detection is an effective pipeline detection method with advantages of high efficiency,low cost,and simple operation.By collecting and analyzing magnetic anomaly signals,it is possible to realize important researches such as positioning of underground pipelines.However,in actual detection,magnetic anomaly signals are often disturbed by random noise,magnetic burial bodies,etc.,and it is difficult to directly invert effective information.Pipeline magnetic anomaly signal processing has become a very valuable research content.In view of the noise and abnormality superposition and other disturbances in the detection of magnetic anomaly pipelines,the magnetic anomaly signal is denoised by empirical mode decomposition,wavelet transform,neural network algorithm,etc.The upward continuation method is applied to weaken the superposition anomaly.Through MATLAB simulation experiments and actual measurement data for algorithm verification,the results show that various algorithms can cancel the noise to a certain extent,improve the signal to noise ratio of magnetic anomaly signals,and provide more accurate data support for subsequent magnetic anomaly inversion.