Control And Fault Detection Of Shock Absorber Test System

As an important part of the automobile suspension system,the performance of the shock absorber has a direct impact on the overall comfort of the vehicle.Therefore,it is very important to test the performance of the shock absorber.The shock absorber test bench consists of the mechanical execution part and the software test part.The control of the electro-hydraulic servo system and the analysis of the test result are the key points and difficulties of the shock absorber test.Electro hydraulic servo control system,the excitation source of the test bench,must be able to impose a sinusoidal excitation on the shock absorber to ensure that the shock absorber test is carried out correctly.Because the electro-hydraulic servo system has nonlinear and time-varying characteristics,the traditional PID control strategies have been unable to meet the requirements of control system,and the PID neural network can well meet PID for the lack of controlling on nonlinear systems.However,the BP neural network algorithm is easy to fall into the local minimum,and the convergence speed is slow.The particle swarm optimization algorithm is often used to optimize the weights of neural network to reduce the probability of neural network falling into the local minima.The standard particle swarm optimization(PSO)algorithm has the problem of premature convergence and low precision.Aiming at this problem,this paper proposes a new method to calculate the inertia weight instead of the linear weight of standard PSO.Experiments and comparison of several control algorithms had been done,the new method is better than others.Shock absorber indicator diagram is an important mean to measure the external characteristics of the shock absorber,fast and accurate identification of shock absorber indicator diagram is important to improve the level of production automation.In this paper,a multi-feature pattern matching algorithm based on chain code is proposed to classify the fault diagram.First,the indicator diagram of pretreatment and record the maximum tensile damping force and maximum compression damping force value.For the pretreatment of the indicator diagram of cross cutting,respectively,and calculated the segmentation shown in diagram of each part of the chain code sequence and then calculated its symmetry,chain code length,area of the three eigenvalues.Finally,the characteristic parameters are coded according to the coding principle,and the encoded values are matched with the coding of the type library to obtain the fault type of the samples.The experimental results show that the algorithm can correctly identify the 12 kinds of fault types of the indicator diagram in the 14 basic types.