In-Situ Temperature Compensation Technology for Pressure Sensors Based on BP Neural Network
Due to the temperature drift of piezoresistive pressure sensors,existing software temperature compensation methods rely on additional temperature sensors to obtain temperature signals.To simplify this process,a pressure sensor in-situ temperature compensation method based on BP neural networks is proposed.Utilizing a multi-parameter measurement method,it can achieve in-situ temperature and pres-sure measurements of the sensor based solely on its electrical signals,without the need to introduce new sensors.Furthermore,it achieves pressure sensor temperature-pressure decoupling and temperature com-pensation through BP neural networks.The results show that the sensor output error is reduced to within±0.5%FS after compensation,with the zero-position temperature drift reduced from 0.021%FS/℃to 0.002 5%FS/℃,and the sensitivity temperature drift reduced from 0.15%FS/℃to 0.005 5%FS/℃,significantly reducing the zero-position temperature drift and sensitivity temperature drift.
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