Fault diagnosis using BP neural networks for municipal solid waste incineration
基于BP神经网络的垃圾焚烧过程故障诊断

A municipal solid waste (MSW) incineration process fault diagnosis model is established, which is based on a back propagation (BP) neural network. The network is trained with gradient descent approach. Optimal stopping rule is used to avoid overfitting and improve training speed as well as generalization ability. The test on real-time data shows that the method can correctly recognize different process operating conditions.