Error Analysis Of Rotor-chamber Automata Testing System

Rotor-chamber automata is the core part of rotor-chamber gun,which provides power for gun loading and firing.There are some errors in the test system of rotor-chamber,and error is the key index to measure the accuracy of test system.Therefore,it is of great practical significance to study the error of the test system of rotor-chamber automata.Error prediction and tracing are two methods of error analysis: forward and backward,which provide the basis for error correction and are effective measures to guarantee the accuracy of test system.This academic dissertation studies from the following aspects:(1)The error source of the rotor-chamber automata test system.In this academic dissertation,the error sources of rotor-chamber testing system are analyzed from two aspects of random error and system error.The random errors of the test system of the rotor-chamber include clock pulse interpolation errors and drift errors,and the system errors include sensor errors,signal conditioning and acquisition errors,and data processing errors.Among them,sensor error is the main source of testing system error,this academic dissertation mainly for sensor error modeling.(2)Error predicting of the rotor-chamber automata test system.Automata rotor-chamber works in high pressure,high temperature,vibration and other complex environments,resulting in the acquisition of information distortion and uneven problems,Back Propagation Neural Network(BPNN)is used to model and predict the error of the rotor-chamber test system.In the parameter selection of BP neural network,Particle Swarm Optimization(PSO)and Bat Algorithm(BA)are used to optimize BP neural network parameters.By establishing BPNN,PSO-BPNN and BA-BPNN models and comparing with MAPE,RMSE and other evaluation indexes,experimental results show that BA-BPNN has higher error prediction ability than PSO-BPNN and BPNN.(3)Error tracing of the rotor-chamber automata test system.The sensor error data collected are nonlinear and non-stationary.Ensemble Empirical Mode Decomposition(EEMD)algorithm is used to decompose the sensor error data,and performed Hilbert transform on the single error obtained by the decomposition,analyzed the amplitude-frequency characteristics of the error signals.Allan variance was calculated for the noise component in the decomposition result,and the logarithmic curve of the random error was obtained to trace the random error.BA-BPNN network was used to fit the systematic error components in the decomposition results to trace the systematic error.Experimental results show that the error tracing method proposed in this academic dissertation is feasible.In order to reduce the error,improve the test accuracy of the rotor-chamber automata test system,this academic dissertation analyzes the test principle,error source,error predicting,error tracing and other aspects of the rotor-chamber automata test system,and provides a basis for error correction of the test system.