Fault Diagnosis And Research Of Crankshaft Based On Vibration Signal Analysis

As a difficult problem in vehicle after-sales maintenance,the crankshaft fault diagnosis of vehicle engine is also the most technical field in the current vehicle maintenance inspection.With the popularization of current vehicles,the vehicle after-sales maintenance market is expanding,how to improve the efficiency of fault diagnosis analysis and the reduction of its dependence on the experience of maintenance and inspection personnel have become an urgent problem to be solved in the field of vehicle engine crankshaft diagnostic analysis.In this context,according to the current research theory and technology status quo,a fault diagnosis analysis method based on time-frequency coherent analysis to analysis of vehicle engine crankshaft vibration signal is proposed.Combined with BP neural network analysis,the automatic diagnosis analysis and judgment of vehicle engine crankshaft fault is realized,and the vehicle is effectively improved.Based on the original automatic signal analyzer,the automatic analysis and identification of typical faults is realized by developing PC software.The main research contents of this paper are as follows:The main research contents of this paper are as follows:1)This paper analyzes the research status of the engine crankshaft fault diagnosis method,combines the background of the research topic,determines the basic technical direction and research content of this article,and summarizes the main work in the research process of the subject.This paper summarizes the relevant principles,methods and research status of the fault vibration signal measurement and analysis of the engine crankshaft.2)The general process of fault diagnosis and analysis based on vibration signals of vehicle engines,the principle and method of vibration signals testing,and the theory of time-frequency coherent estimation are analyzed and explained in detail.The theoretical basis for signal extraction and processing based on time-frequency coherent estimation analysis is determined.The feature signal extraction method and principle of time-frequency coherence are emphatically introduced.3)The design of a crankshaft diagnosis scheme for a vehicle engine,through the design and integration of several modules such as the extraction of detection signals,in-depth learning of BP neural networks,autonomous learning,large data storage,and fault recovery judgment.The detailed programming design of the software system is completed based on the LabView platform.Through PVTAS100 vibration signal analyzer,PIX SimMotor signal simulator and other hardware selection,a simple and automatic engine crankshaft fault diagnosis platform was realized.4)Based on the above designed system,the operation of the engine crankshaft fault diagnosis automatic platform is first tested,and the three fault modes of the crankshaft vibration failure are applied to the common engine shaft failure,the crankshaft fracture failure,and the Silicon oil shock absorber.It not only verifies the feasibility of running the system,but also verifies the reliability and automation of the system through its accurate automatic recognition and judgment results.