Static error correction of the sensor based on SVR

Ding Lei
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Abstract

To improve the stability of the sensor and to reduce the non-goal parameter's influence, a new static error correction method of the sensor based on support vector machine for regression (SVR) is presented. Experimental results show that the proposed method can decrease the temperature sensitivity coefficient of pressure sensor and improve the measurement accuracy of pressure validly. And judging from it's stability, it proves to be much better than traditional error correction methods.
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基于SVR的传感器静态误差校正
为了提高传感器的稳定性,减少非目标参数的影响,提出了一种基于支持向量机回归(SVR)的传感器静态误差校正方法。实验结果表明,该方法有效地降低了压力传感器的温度敏感系数,提高了压力的测量精度。从稳定性来看,它比传统的纠错方法要好得多。
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