Title :
Static error correction of the sensor based on SVR
Author_Institution :
Dept. Phys. & Electr. Eng., Anqing Teachers Coll., Anqing, China
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.
Keywords :
computerised instrumentation; error correction; pressure sensors; regression analysis; support vector machines; SVR; measurement accuracy; nongoal parameter influence reduction; pressure sensor; sensor stability; static error correction; support vector machine for regression; temperature sensitivity coefficient; Accuracy; Error correction; Indexes; Sensitivity; Support vector machines; Temperature measurement; Temperature sensors; Matlab; SVR; error correction; pressure sensor;
Conference_Titel :
Natural Computation (ICNC), 2012 Eighth International Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4577-2130-4
DOI :
10.1109/ICNC.2012.6234714