基于BP神经网络的压风机故障诊断方法研究

Study on the Fault Detection and Diagnosis Technique of Air Compressor Based on BP Neural Network

针对压风机依赖人工操作、效率低、控制方式落后等问题,分析螺杆式压风机的常见故障类型和振动信号之间的关系,建立压风机的故障诊断模型,提出基于BP神经网络的压风机故障诊断方法,并利用Visual C#语言和Matlab软件开发了BLT-500型螺杆式压风机的在线故障诊断系统。

Based on air compressors depending on manual operation completely, low efficiency, and backward control method, the relationship between the fault type and the vibration signal of the air compressor was analyzed, the fault diagnosis method of air compressor based on BP （Back Propagation） neural network was proposed, the fault diagnosis model of air compressor was studied. In addition, an online fault diagnosis system of BLT-500 air compressor was developed by using Visual C# language and Matlab software.