Life Prediction for Silicon Pressure Sensor Based on SVR

Abstract:

In order to improve the reliability of silicon pressure sensor, life prediction for silicon pressure sensor should be performed. Life prediction for silicon pressure sensor based on support vector regression is proposed in the paper. Grid method is used to determine the parameters of support vector regression in the process of training support vector regression model. Life for silicon pressure sensor under the conditions of different pressures is given in the experimental analysis. The comparison of the errors and mean errors between support vector regression and BP neural network indicates that life prediction accuracy of support vector regression for silicon pressure sensor is higher than that of BP neural network.

• Periodical: Applied Mechanics and Materials (Volume 187)
• Pages: 241-244
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.187.241
• Online since: June 2012
• Authors: Zhi Hua Zhai, Ping Li Wu
• Keywords: Life Prediction, Sensor, Silicon Pressure, Support Vector Regression (SVR)

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