A Method of Accelerometer Dynamic Model Parameter Identification Based on Full Phase Spectrum Estimation

Abstract

The invention discloses an accelerometer dynamic model parameter identification method based on all-phase spectrum estimation, which belongs to the field of measurement and control technologies. Aiming at the situation that parameter identification precision is directly influenced by spectrum leakage and measurement noise in accelerometer dynamic model parameter identification when adopting a frequency-domain method, the accelerometer dynamic model parameter identification method adopts double-window all-phase FFT (Fast Fourier Transformation) to obtain an autopower spectrum and a cross-power spectrum of input / output measurement data of an accelerometer, utilizes an Hv estimation method for estimating a frequency response function, and realizes accelerometer dynamic model parameter identification by means of a minimum error criterion function. The accelerometer dynamic model parameter identification method reduces the influence of spectrum leakage and measurement noise on the accelerometer dynamic model parameter identification result, improves the parameter identification precision, and is stable and reliable in calculation process.

Description

technical field [0001] The invention relates to a method for identifying parameters of an accelerometer dynamic model, which belongs to the technical field of measurement and control, in particular to a method for identifying parameters of an accelerometer dynamic model based on full phase spectrum estimation. Background technique [0002] As an inertial device for measuring vibration, accelerometers are widely used in aerospace, industrial control and other fields. The identification results of its dynamic model parameters directly affect the dynamic characteristic indicators. Improving the accuracy of accelerometer dynamic model parameter identification is of great significance in practical applications. [0003] The accelerometer can be equivalent to a single-degree-of-freedom spring-mass-damper system in the linear range, and the mass block is built in the accelerometer housing and supported by the spring and the damper. The electrical signal output of the sensitive elem...

AI Technical Summary

Problems solved by technology

[0004] In the process of parameter identification of the dynamic model of the frequency domain accelerometer, on the one hand, due to the high sampling frequency and the long length of the accelerometer output data, it is necessary to truncate the output data in the time domain, and the time domain truncation of the output data is essentially the Adding a rectangular window to the data produces a large spectrum leakage; on the other hand, due to the influence of measurement noise, the Fourier transform is directly performed on the input and output signals of the accelerometer, and the estimated frequency response function of the accelerometer is a biased estimate, and the obtained frequency response function exists large estimation error

Considering the influence of spectrum leakage and measurement noise comprehensively, especially when the frequency resolution is large, large errors will be generated, which will directly reduce the accuracy of accelerometer dynamic model parameter identification

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