Application of BP Neural Networks to Fault Diagnosis of Turbocharging System of Diesel Engine
BP神经网络在柴油机涡轮增压系统故障诊断中的应用

This paper applies BP neural networks to the fault diagnosis of turbine supercharging system of diesel engine. The keystone and algorithm of BP neural networks are simply introduced. Then, the BP algorithm is applied to train the networks. The trained networks can identify four kinds of fault diagnosises, including the jam in air filter of diesel engine, air resistance increase in air freezing refrigeration, the jam of intake and exhaust system, air resistance increase in turbo. Furthermore, the diagnosing results are consistent with the factual results. So the dignosing results are very reliable, and we can estimate the grade of the faults exactly.