PREDICTION OF DANGER DEGREE OF CORROSION INDUCED BY STRAY CURRENT FOR METRO BY USING BP ARTIFICAL NEURAL NETWORK
用BP模型预测地铁杂散电流腐蚀危险性

On the basis of chlorine ion concentration in the environment and the polarity voltage positive offset data of the buried metal structure influenced by stray current,by adopting artificial neural networks' method,a prediction model of dangerous degree of stray current corrosion for metro was proposed.Carrying out training with one group of selected swatches,the prediction model was established,and then by using the model,we predicted the stray current corrosion of the whole roadbed drainage net and side-wall structures of Guangzhou metro line No.1.The result showed that the model can predict the dangerous degree of stray current corrosion for metro.