一种基于BP神经网络的压缩机状态预测方法

Intelligent condition forecasting models of compressors are built. After analysis of their characteristics, this dissertation brings forward the method of adopting BP network forecasting model to monitor thermodynamics parameters of compressors. This model is tested and applied in a compressor running field. The modeling results indicate that the model can be used in the performance prediction and fault diagnosis of the compressor. The method provides a new way for monitoring compressors condition.