Research On Failure Analysis And Fault Diagnosis Of The Gear Pump

The gear pump is the basic component of the hydraulic system,its working conditions will directly affect the smooth operation and sustainable production of the entire hydraulic system and even the equipment.Therefore,it is of great significance to study the fault mechanism and fault diagnosis process of gear pump.This paper takes the gear pump as the research object,using the fluid dynamics,dynamics,signal processing and information fusion multidisciplinary theories to analyze the working state of the gear pump,which can achieve the purpose of fault diagnosis and state analysis.Specific research contents are as follows:(1)Considering the characteristics of the internal flow field and the structure of the gear pump,the internal flow field model of the gear pump is established.Based on the characteristics of internal flow field parameters,the flow characteristics and common shock forms under the condition of internal flow excitation are analyzed.In addition,the structural characteristics of gear teeth of gear pump are studied,and the dynamic model of gear teeth is established.Based on the modal analysis,the natural frequency of gear pair is calculated.Next,based on the flow field model and the dynamic model of the gear pair,the simulation and numerical calculation of the tooth failure caused by the hydraulic shock in the internal flow field are studied.Then,stress and strain distribution of gear tooth surface in the excitation condition are analyzed,and the failure mechanism of the gear tooth caused by excitation condition of internal flow field is analyzed,which can obtain the failure modes and failure inducing factors of the gear pair in the flow field.(2)The order spectrum analysis method based on the optimal fractional Fourier transform is used to de-noise and extract the features of the non-stationary vibration signal in the gear pump starting process,and the characteristics of fault feature components are studied.In the process that fractional Fourier transform is used to de-noise vibration signals,the fractional order optimization method based on particle swarm algorithm is proposed.Compared with the step search method,this method can get more accurate results,and greatly reduce the amount of computation in the process of looking for order of fractional order.The band-pass filtering process is performed by using the energy aggregation center as the filter center in the fractional domain of the feature component,which can be better to improve the signal noise ratio(SNR)of the signal.According to the non-stationary features of the vibration signal during the start process of the gear pump,the order spectrum analysis is used to analyze the signal after the noise reduction,which canprecisely get the working state feature information of the gear pump.(3)Aiming at the conflicts among evidences in the fault diagnosis process of gear pump,the problem of conflicts among the evidences in the evidence source is improved,the conflicts among evidences are redistributed,and the evidence model is corrected,which can solve the strong conflicts among evidences,retain the useful information in the evidences.Then,the research on the status information of the gear pump is carried out,and the results are compared with the classical evidence theory.The results show that the proposed method can obtain conclusions with high reliability,which provides a theoretical basis for the fault diagnosis of gear pump.Through the study of the failure mechanism of the gear pump,the failure analysis of the gear pump is more clear and comprehensive.The fault of the gear pump is studied by using the vibration signal,and the fault diagnosis and condition monitoring of the gear pump are achieved.The experimental results show that the method proposed in this paper is effective and feasible,and has some advantages compared with other methods.