ANN-based diagnosis of boiler four-tube leakage faults under different loads and operating modes

Four-tube leakage faults are among the most common faults in a large-scale power plant boiler unit, which may result in abnormal boiler shutdown, economic loss and even endanger the safety of operating personnel. Therefore, It is of great significance to grasp the rules of four-tube leakage faults and to recognize the fault type and location in real time with advanced fault diagnosis approach. With the help of a full-scope simulator, detailed fault simulation tests are carried out for the four-tube leakage faults of a 600MW supercritical boiler unit under different coordinated control modes. An intelligent fault diagnosis method, which combines artificial neural network (ANN) with symptom zoom technology, is applied to realize online fault diagnosis of four-tube leakage faults of varied severity at multiple load points and different operating modes. Fault diagnosis simulation tests show that this method can recognize the four-tube leakage faults correctly with certain engineering practicability.