Triaxial micromachine accelerometer static correction method based on particle swarm optimization

Abstract

The invention discloses a triaxial micromachine accelerometer static correction method based on particle swarm optimization. The method includes the steps that a triaxial MEMS accelerometer and a relevant peripheral circuit are welded to a designated circuit board to form a test and using circuit of the accelerometer, and normal operation and data output of the accelerometer are guaranteed; the circuit board is fixed to a certain space point, and the circuit board can be freely rotated on three axial directions of space; the circuit board provided with the accelerometer is manually or automatically driven by an external device to rotate in the space, the rotating speed is smaller than 10 degrees per second, the rotation track of the accelerometer covers main distribution of a spherical surface, and actual output data of the accelerometer are recorded; after the collected data are preprocessed, an error estimation algorithm of the accelerometer is designed according to a standard PSO processing method; an error correction model of the accelerometer is set according to the estimated error model, and measurement accuracy of the accelerometer is improved. By the adoption of the method, random errors in the sampling process are effectively eliminated, and measurement accuracy of the MEMS accelerometer is further improved.

Description

technical field [0001] The invention relates to a static correction method of a three-axis micro-mechanical accelerometer based on particle swarm optimization. The method corrects main static errors such as zero bias, quantization error and orthogonality error in the output of the three-axis accelerometer according to a calculated error model. Background technique [0002] With the improvement of microelectromechanical systems (Microelectromechanical Systems, abbreviated as MEMS) manufacturing technology, the use of MEMS devices has been widely concerned and rapidly promoted, among which MEMS accelerometers are the most widely used. Due to the manufacturing reasons and usage methods of the MEMS sensor, there is a certain measurement error in the static output of the MEMS accelerometer, which limits its use effect, and it needs to be corrected to improve the measurement accuracy. [0003] At present, the most common static correction method used in engineering is the maximum ...

AI Technical Summary

Problems solved by technology

Due to the manufacturing reasons and usage methods of MEMS sensors, there is a certain measurement error in the static output of the MEMS accelerometer, which limits its use effect, and it needs to be corrected to improve the measurement accuracy

[0003] At present, the most common static correction method used in engineering is the maximum and minimum method, which can only estimate the scale factor error and zero position deviation, and is easily disturbed by random errors

Another commonly used correction method is to form an inertial measurement unit with a gyroscope for testing. Specifically, there is a combined calibration compensation method. This method mainly relies on the reference data provided by the rotating platform for error correction, and can simultaneously calibrate static and dynamic errors. This method has a perfect model and high accuracy of the correction effect, but in the correction process, the rotating platform needs to be operated many times, the correction process is complicated and cumbersome, and the cost of the rotating platform is beyond the tolerance of ordinary users

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