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Related Experiment Video

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A Temperature Compensation Method for Piezo-Resistive Pressure Sensor Utilizing Chaotic Ions Motion Algorithm

Ji Li1, Guoqing Hu2,3, Yonghong Zhou4

  • 1Department of Mechanical and Electrical Engineering, School of Aerospace Engineering, Xiamen University, Xiamen 361005, China. 19920130154215@stu.xmu.edu.cn.

Sensors (Basel, Switzerland)
|October 19, 2016
PubMed
Summary
This summary is machine-generated.

This study presents a novel method using a hybrid kernel Least Squares Support Vector Machine (LSSVM) optimized by a chaotic ions motion algorithm to compensate for temperature effects in silicon piezo-resistive pressure sensors.

Keywords:
chaotic ions motion algorithmhybrid kernel LSSVMpiezoresistive pressure sensortemperature compensation

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Area of Science:

  • Sensor Technology
  • Machine Learning
  • Materials Science

Background:

  • Silicon piezo-resistive pressure sensors are sensitive to ambient temperature, affecting their linear output.
  • Temperature-induced errors necessitate compensation for accurate pressure measurements.

Purpose of the Study:

  • To develop and validate a robust temperature compensation method for silicon piezo-resistive pressure sensors.
  • To improve the accuracy and reliability of pressure sensor readings under varying temperatures.

Main Methods:

  • A hybrid kernel Least Squares Support Vector Machine (LSSVM) incorporating Radial Basis Function (RBF) and polynomial kernels was employed.
  • A chaotic ions motion algorithm was utilized to optimize the hyperparameters of the LSSVM model.
  • Temperature calibration data was used to train and validate the proposed compensation approach.

Main Results:

  • The proposed hybrid kernel LSSVM method demonstrated superior performance compared to other methods in temperature compensation.
  • Key performance metrics, including maximum and minimum absolute relative error, showed significant improvements.
  • The algorithm exhibited robustness and potential for engineering applications.

Conclusions:

  • The developed chaotic ions motion-optimized hybrid kernel LSSVM effectively compensates for temperature effects in silicon pressure sensors.
  • This approach offers a reliable foundation for advanced research in sensor compensation.
  • The method enhances the practical applicability of piezo-resistive sensors in diverse environments.