Sensitivity Temperature Drift Error Compensation of Piezoelectric Ceramic Sensor Based on Big Data

The sensitivity temperature drift compensation model established in this paper has an obvious effect on the sensitivity temperature drift error compensation control of the piezoelectric ceramic sensor. Without sensitivity temperature drift compensation, the load force of the piezoelectric ceramic sensor and the actual load force predicted by the sensitivity calibration result at room temperature are directly used. The error is large, and the maximum error is 29.16N. After compensation based on the temperature drift compensation model based on the improved Elman neural network sensitivity established in this paper, the maximum error between the predictive force of the compensation model and the actual loading force of the piezoelectric ceramic sensor is only 0.72N, which effectively guarantees the detection accuracy.