Fault Detection,Diagnosis & Improvement Of Hydraulic System Of Compactors

Hydraulic system plays the role of power transmission in the working process of soil compactor,but its complex structure often leads to its failure,which leads to serious consequences.How to monitor and diagnose the hydraulic system fault of the soil compressor is always a difficult problem.Commonly used hydraulic system fault diagnosis methods are: fault tree analysis method,data mining fault diagnosis method,expert system,signal processing method,machine learning internal fault diagnosis method,multivariate statistical analysis method.The research on the intelligent fault diagnosis algorithm of hydraulic system is mainly the evaluation of the performance and characteristics of large-scale mechanical equipment and the research of intelligent decision-making decision-making.Some scholars have carried out some intelligent fault diagnosis models for hydraulic system fault diagnosis of different machines and equipments.Good results have been obtained through experiments or simulations,but there are also some shortcomings.In view of this,based on the soil pressure machine hydraulic system fault monitoring and diagnosis as the research subject,first,a brief overview of the selected topic background and research significance,at home and abroad about soil pressure machine hydraulic system generalizes the present state and the related research of fault diagnosis,and soil pressure machine working principle of hydraulic system and the common failure mechanism and failure monitoring and diagnosis of the commonly used method;After a brief overview of the topic selection and research significance,the research status of hydraulic system fault at home and abroad is summarized,and the working principle and basic fault types of hydraulic system of soil press are analyzed.Based on principal component analysis method is proposed to extract the fault feature,and then USES the improved principal component analysis(pca)to the axial plunger pump as an example of dimension,through two kinds of fuzzy reasoning and fuzzy neural network algorithm for pattern recognition,fault based on principal component analysis and fuzzy neural network is established the soil pressure machine hydraulic system fault diagnosis model.The simulation results show that this model is fault-tolerant and robust for hydraulic system fault diagnosis of soil press,and avoids the shortcoming that the standard neural network is easy to fall into local convergence.Diagnostic accuracy as high as 97% and average accuracy increased by 16%.This model can be widely used in fault diagnosis of hydraulic system of soil press.