Fault Diagnosis Of Fan Bearing Based On Hidden Markov Model And Wavelet Analysis

Draught fan is a kind of rotating machinery,mainly rely on mechanical energy to improve gas pressure and to transport gas equipment.As the important parts of the fan,the performance of the rolling bearing directly affects the working condition of the fan.Because the rolling bearing of the fan has been in high speed in the working condition,it is also a particularly vulnerable part of the bearing.Therefore,it is of great significance to diagnose faults in rolling bearings of fans.As a statistical analysis model,hidden Markov model is a double random process.It is an important direction of signal processing.It has been successfully applied to speech recognition,behavior recognition and fault diagnosis.The main contents of this paper are as follows:(1)Introduce the failure mechanism of fan and analyze the corresponding frequency of various faults.The main failure modes and failure frequencies of rolling bearings are analyzed.The extraction method of characteristic frequency is expounded in detail.(2)A brief introduction to hidden Markov models is made,and the main problems and corresponding solutions of hidden Markov models are analyzed.It also classifies and introduces the types derived from hidden Markov models.(3)We designed the experiment,and introduced the design and establishment of modules from hardware selection,collocation and data acquisition of software design system.The experimental verification was carried out.(4)Noise reduction and energy analysis of the collected fault bearing data,and the hidden Markov model is applied to realize the bearing fault diagnosis.Through the experiment,it is proved that the fault diagnosis technology of fan bearing based on the hidden Markov model and wavelet analysis has the advantages of high accuracy,simple analysis,low cost,easy to operate interface and easy to expand function.It can detect and distinguish fan bearing faults effectively.Itprovides a basis for future fault diagnosis application of fan bearings.