Parameter Stability Analysis And Modeling Prediction Of Quartz Flexible Accelerometer

Quartz flexible accelerometer is one of the key sensitive devices of inertial navigation system,and its measurement error directly affects the accuracy and stability of the entire navigation system.The measurement error of the quartz flexible accelerometer is directly related to its own bias K₀and the scale factor K₁value.However,during the storage process of the accelerometer,due to internal and external environmental factors,K₀and K₁have occurred complex changes make it difficult to describe them accurately,which seriously affects the parameter stability of the accelerometer.In view of the above problems,this paper proposes a new method for modeling the stability of quartz flexible accelerometer.This method combines parameter preprocessing and parameter change modeling to establish a parameter stability model,solves the problems that existed in the parameter stability modeling of quartz flexible accelerometer,and the change of parameters is predicted accurately.Firstly,the parameter stability of quartz flexible accelerometer is analyzed.The influence factors of parameter stability were analyzed from two aspects:parameter time stability and environmental stress stability.On the basis of the parameter change mechanism model and the output of finite element analysis and simulation,the accelerated change model of the parameter stability of quartz flexible accelerometer was established,and then the stability of the quartz flexible accelerometer parameter was determined to have a certain rule,which laid a theoretical foundation for the subsequent parameter stability modeling.Secondly,the parameter stability modeling of quartz flexible accelerometer is studied.First,the advantages of empirical mode decomposition?EMD?in the pretreatment of parameter change sequence are analyzed,and the pretreatment of parameter change sequence with EMD is determined.Then,the least square multi-core support vector regression?MKLSSVR?mathematical model is established,the kernel function type of the model is determined according to the actual characteristics,and an adaptive artificial fish swarm optimization algorithm?AAFSA?is designed to optimize the key parameters of the model.The parameter stability model of quartz flexible accelerometer based on EMD and MKLSSVR was established.Finally,a short-term prediction is made on the parameter changes of the quartz flexible accelerometer.The model was verified first.The results show that the model can significantly reduce modeling errors and improve the accuracy of the model.Then the model was used to predict the parameter change of the quartz flexible accelerometer for 520 days as training data for the next 180 days.The results show that the model can perform the parameter change of the quartz flexible accelerometer in a short period For accurate prediction,the prediction error of each step is less than 2*10^-5g,and the prediction error index RMSE of each step is in the order of 10^-6g,which meets the requirements of practical application.In this paper,on the one hand,the parameter stability of the quartz flexible accelerometer is comprehensively analyzed,which lays a theoretical foundation for the modeling and prediction of parameter stability;Optimizing is of great significance to the error reduction of the parametric stability model of quartz flexible accelerometers,and to the accurate prediction of parameter changes in a short period of time.Therefore,the work done in this paper has certain practical value.