Abstract: The close interval pipe-to-soil potential survey(CIPS)and the galvanostatic transient response method were used to detect the coating quality of buried pipelines.An algorithm was presented based on the dyadic wavelet transform for detecting the pipeline coating damage point with the ON and instant OFF CIPS potential and the difference between them.A six-layer wavelet Kohonen neural network model was set up to diagnosis the quality of pipeline coating with the galvanostatic transient response.The first to fifith layers of the model were used to pick up the information, and the last layer of the model was capable of self-training.The coating quality could be diagnosed quickly after the galvanostatic transient response was input to the model. The detection result of pipeline between Dagang and Cangzhou of Tianjin Dagang oil field was satisfactory.