Temperature Drift Calibration Method of TMR Magnetic Sensing System Based on Improved Neural Network
Due to the influence of environment and system heating,the actual operating temperature of TMR magnetic sensing system will fluctuate to a certain extent.As the temperature increases or decreases,the actual output of the TMR magnetic sensing system will produce certain errors,resulting in temperature drift of the output.In order to suppress the impact of temperature drift on the TMR magnetic sensing system,a back propagation(BP)neural network optimized by genetic algorithm(GA)is used to compensate the temperature drift phenomenon.By comparing the data before and after compensation,the average temperature drift of the TMR magnetic sensing system can be sharply re-duced two orders of magnitude.The proposed method has achieved perfect compensation and improved the perfor-mance and reliability of the TMR magnetic sensing system.
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