Non-linearity Estimation and Temperature Compensation of Capacitor Pressure Sensors Using Least Square Support Vector Regression

Xiaoh Wang
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引用次数: 10

Abstract

A new nonlinear compensation technique to capacitor pressure sensor (CPS) based on least square support vector regression (LSSVR) is proposed. In this technique, LSSVR is used as an inverse model of the CPS; therefore, the proposed technique can automatically compensate the effect of the associated non-linearity to estimate the applied pressure. Furthermore, the flexibility of the proposed technique effectively compensates any variation of the CPS's output occurring due to change in environmental temperature. The results of actual CPS compensation experiment indicate that this LSSVR approach is a useful alternative to the existing ones. This technique would be useful for other types of sensors such as thermocouples, flow sensors, magnetometer etc., possessing similar nonlinear response characteristics. The presented method has a potential future in the field of instrumentation and measurement.
基于最小二乘支持向量回归的电容式压力传感器非线性估计与温度补偿
提出了一种基于最小二乘支持向量回归(LSSVR)的电容压力传感器非线性补偿方法。在该技术中,LSSVR被用作CPS的逆模型;因此,该方法可以自动补偿相关非线性的影响,以估计施加的压力。此外,所提出的技术的灵活性有效地补偿了由于环境温度变化而产生的CPS输出的任何变化。实际CPS补偿实验结果表明,LSSVR方法是一种有效的替代方法。该技术可用于其他类型的传感器,如热电偶、流量传感器、磁力计等,具有类似的非线性响应特性。该方法在仪器仪表和测量领域具有广阔的应用前景。
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