Condition Monitoring And Evaluation Technique Of Reciprocating Compressor Based On Vibration Signal Analysis

Reciprocating compressors are used widely in production. Many stimulating sources exist in the compressor, and the structure of reciprocating compressor is very complicated. If their faults arise in the practical production, it would not only affect industrial process of production, but also bring a series of potential problems of safety. Thus, in order to ensure the compressor unit working safely, an economic and reliable reciprocating compressor fault diagnosis system is badly needed by factories,the system can be used to forecast, monitor and diagnose the faults of reciprocating compressors.Condition monitoring and evaluation is a science of identifing the equipment running status,they research reflection of the state of machine and plant unit in diagnostic information.The study includes three parts, equipment operation monitoring, trending forecast of its running and current status of the recognition of their diagnosis. With the new theories, new technologies and new methods continue to emerge, and maturing, machinery and equipment condition monitoring and assessment technology developed rapidly, This technology has been basically formed a disciplinary system, Is moving towards a virtuous circle road of industrialization.At the beginning of this paper, the fundamental theory and development situation of mechanical equipment fault diagnosis technology were analyzed synthetically; the main problems and development situation of compressor fault diagnosis technology were introduced. Secondly, the structure of 2D12 reciprocating compressors, simulation experiment of cylinder faults and detection technology of cylinder pressure signal were introduced, the fault mechanism of principal parts was analyzed, and the indicating diagrams of reciprocating compressor were normalized by segmentation reconfiguration method. Finally,I did a try to the compressor state prediction,using the largest Lyapunov exponent prediction model to predict in short-term and medium-term the state of the reciprocating compressor.