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In order to solve the problem of great variety and diagnostic difficulty of the aluminum cell’ fault,a layered fault diagnosis expert system based on BP neural network and expert system was designed,which included former layer classification and after layer prediction. Based on the analysis for the frequency spectrum of the cell resistance signal,the fault feature information was extracted to classify the fault,A former layer classifier based on BP network was established to diagnose the obvious features of faults. Furthermore,with fault diagnosis rules and control rules as well as the consummate knowledge of expert system,the remaining fault was diagnosed according to the former layer classification results. The overall design of fault diagnosis system was achieved by setting the rules and combining the former layer classification and after layer prediction. The simulation results and theoretical analysis show that the system can effectively forecast the single and compound fault and then improve the diagnostic accuracy,ensure the working conditions of the aluminum cell.