Vehicle Monitoring And Fault Diagnosis Based On Chaos Ant Colony Algorithm

In recent years,with the continuous development of rail transit,urban rail transit has occupied a very important position.The safety of rail transit vehicles is a major factor affecting the development of urban rail transit.Vehicle suspension system is a key component of urban rail vehicles,The failure of suspension system will affect the ride comfort and safety of the vehicle directly.According to the data of rail vehicle operation,some parts of the suspension system will age and affect the performance of the vehicle with the increase of the service time of rail vehicles.However,regular inspection and maintenance of the rail vehicle is essential.Therefore,the fault diagnosis technology and condition monitoring method for rail vehicle suspension system play a decisive role in the stable operation and safe work of the vehicle.To seek an effective and stable suspension system fault diagnosis method has become the focus of rail transportation research at home and abroad.In the paper,based on the lateral dynamic model of the rail vehicle and the experimental platform for simulating the vertical dynamic system of the rail vehicle suspension,the research studies the application of chaotic ant colony algorithm to the parameter optimization estimation and fault diagnosis of the suspension system.Firstly,the vehicle lateral dynamics model is established,and the random excitation input is used to observe the vibration response of the vehicle model to complete the experimental verification of the dynamics model.The failure model is set by changing the suspension parameters of vehicle dynamics model.The time-domain samples generated by numerical simulation of the sixth-level orbital spectrum in the United States are used as the input of the dynamic model for simulation experiments.Secondly,collect and process the data of vehicle vibration,and the suspension system part parameters are solved according to the vehicle dynamics system relationship equation.Then the optimization characteristics of the chaotic ant colony algorithm are used to complete the optimal estimation of the vehicle suspension system parameters.By comparing the estimated value with the real value of the parameter,the fault diagnosiseffect is judged.Based on the unified experimental platform for simulating the vertical dynamics of vehicle suspension,the corresponding vertical dynamic model of the rail vehicle is established,and the vertical vibration response data of the experimental platform is collected to complete the calculation of the parameters of the test platform components.Optimize the parameters of the test bench and verify the feasibility of the algorithm.Simulation and experimental results show that the chaotic ant colony algorithm uses its ergodicity and randomness to obtain a good convergence effect in the optimal estimation of rail vehicle suspension system parameters,and achieves the fault diagnosis estimation effect of the vehicle suspension system.Finally,the results and algorithms used in this paper are summarized,and the research is further prospected.