Research Of Fault Diagnosis System For Air Conditioner Compressor Based On DBN

Air conditioning compressors are the most critical core components in air conditioning systems.Failures in the event of an abnormal condition will affect the normal operation of the entire system.Especially in industrial production,many productions must maintain the accuracy and stability of temperature conditions to ensure the quality of product production.Therefore,the research on the accurate monitoring and fault diagnosis of the operating state of air-conditioner compressors plays a key role in ensuring the good operation of mechanical equipment and product guarantee for industrial production.This paper takes air-conditioning compressor as the research object,and carries out a series of research work on the monitoring and analysis of various operating parameters of air-conditioning compressors and the fault diagnosis of the body.The main contents are as follows: Firstly,through the theoretical explanation of the system and various practical application analysis,the basic research background and specific significance of the subject are introduced in detail,and the research status of the related technologies of fault diagnosis system and deep belief network is analyzed.development trend.The basic algorithm for the final use of the system is determined by analysis.Secondly,the research analyzes the basic principles and specific training methods of deep belief network,and introduces the concept of dynamic learning rate on the original basis to improve the training process of deep belief network and improve the training efficiency of model network.Then the deep belief network model is used to monitor the operating state of the air conditioner compressor,and the effectiveness of the method is proved by comparison with other methods.Thirdly,the basic working principle of the air conditioner compressor is basically explained,and various types of faults and causes of the compressor are studied and analyzed.A basic knowledge system has been formed,and an expert system for common faults of airconditioning compressors has been established.When the abnormal state of the air conditioner compressor is monitored by the deep belief network model,the expert system infers the specific fault cause according to the fault phenomenon and gives a fault solution.Finally,this paper uses C# and Matlab to develop a web-based air conditioning compressor fault diagnosis system,including real-time acquisition and storage of operational status data,monitoring and analysis of operational status and fault diagnosis.Finally,the system can quickly and accurately diagnose and analyze the fault of the air conditioner compressor,which is easy to use and easy to manage,and has high use value.