SAW Torque Sensor Gyroscopic Effect Compensation by Least Squares Support Vector Machine Algorithm Based on Chaos Estimation of Distributed Algorithm.

Wei Han,Yihan Cao,Miaomiao Xu,Xiongzhu Bu

doi:10.3390/s19122768

Abstract

As this study examined the issue of surface acoustic wave (SAW) torque sensor which interfered in high rotational speed, the gyroscopic effect generated by rotation was analyzed. Firstly, the SAW coupled equations which contained torque and rotation loads were deduced, and the torque calculation error caused by rotation was solved. Following this, the hardware of the SAW gyroscopic effect testing platform and the turntable experiment were designed to verify the correctness of the theoretical calculation. Finally, according to the experimental data, the gyroscopic effect was compensated by multivariate polynomial fitting (MPF), Gaussian processes regression (GPR), and least squares support vector machine algorithms (LSSVM). The comparison results showed that the LSSVM has the obvious advantage. For improving the function of LSSVM model, chaos estimation of distributed algorithm (CEDA) was proposed to optimize the super parameters of the LSSVM, and numerical simulation results showed that: (1) CEDA is superior to traditional estimation of distributed algorithms in convergence speed and anti-premature ability; (2) the performance of CEDA-LSSVM is better than genetic algorithms (GA)-LSSVM and particle swarm optimization (PSO)-LSSVM. After compensating by CEDA-LSSVM, the magnitude of the torque calculation relative error was 10−4 in any direction. This method has a significant effect on reducing gyroscopic interference, and it lays a foundation for the engineering application of SAW torque sensor.

Highlights

In mechanical transmission systems, torque is one of the most valuable mechanical quantities to evaluate the system performance, and to reflect both power and condition of the machinery
It isIt of significance to work on rotationalsituations, situations,which whichcannot cannotbebe ignored with high speed is great of great significance to work the method of the torque sensor gyroscopic effecteffect for improving the accuracy and on compensation the compensation method of surface acoustic wave (SAW)
chaos estimation of distributed algorithm (CEDA)-least squares support vector machine algorithms (LSSVM) in x3 direction was slightly inferior to Gaussian processes regression (GPR), but much better than multivariate polynomial fitting (MPF), and the error magnitude was www.mdpi.com/journal/sensors www.mdpi.com/journal/sensors

Summary

Introduction

Torque is one of the most valuable mechanical quantities to evaluate the system performance, and to reflect both power and condition of the machinery. The research on gyroscopic effect interference and the compensation method of the SAW torque sensor is still in the exploratory stage, and the corresponding research report cannot be found. V. Kalinin et al [10] developed a wireless temperature and torque sensor based compensation method. The gyroscopic effect sensor calibration is difficult, and the accuracy and compensation effect are affected by the caused by rotation is a spatial problem, which cannot guarantee that the compensation structure can processing error. The hardware method is not suitable for the gyroscopic effect compensation of the SAW algorithms should be designed to compensate for the interference error. The influence of the torque sensor with the SAW torque sensor with gyroscopic effects under high rotating situations is studied.

Model of SAW Torque Sensor under High Rotational Speed

The LSSVM Parameter Optimization based on CEDA

Performance Analysis of CEDA

Conclusions

Findings

Implementing