Implement of Nonlinearity Correction for Temperature Frequency Characteristic of Quartz Tuning Fork Temperature Sensor
Quartz tuning fork temperature sensor has error in the layout of electrode and structure in the manufacturing process, so that the output of temperature-frequency characteristics is nonlinear in the entire temperature measurement range. A nonlinear correction method based on neural network is presented in this paper; neural network reverse modeling way is used for the method, and is implemented in system on programmable chip. Operation and correction is processed for the quartz tuning fork temperature sensor, the test results are used to verify the algorithm. The results confirmed the correctness and the achievement of the algorithm.
Metrology Quartz tuning fork temperature sensor Nonlinear Neural network
XU Jun YOU Bo WU Hong-li HU Li-hua
Harbin University of Science and Technology, Harbin, Heilongjiang 150080, China
国际会议
2008年国际温度与热物性测量会议(TEMP BEIJING 2008)
北京
英文
271-275
2008-10-20（万方平台首次上网日期，不代表论文的发表时间）