Thermocouple sensor non-linearity compensation based on orthogonal polynomial basis functions neural network

Author

A-long, Yu

Author_Institution

Sch. of Phys. & Electron. Electr. Eng., Huaiyin Normal Univ., Huaiyin, China

fYear

2011

fDate

15-17 July 2011

Firstpage

7074

Lastpage

7076

Abstract

This paper presents a new method to compensate thermocouple sensor non-linearity based on orthogonal polynomial basis functions neural network. The artificial neural network module is used to realize Chebyshev artificial neural network. The mathematical model is established based on Chebyshev artificial neural network for non-linearity compensation. The principle and training algorithms of orthogonal polynomial basis functions neural network and neural network module are introduced. The results show that non-linearity compensation method has the advantages of high precision, good real time and strong robustness, etc. The maximum non-linearity error is 0.15%.

Keywords

computerised instrumentation; neural nets; polynomials; thermocouples; training; Chebyshev artificial neural network; orthogonal polynomial basis functions neural network; thermocouple sensor nonlinearity compensation; training algorithms; Adaptive systems; Artificial neural networks; Chebyshev approximation; Ethics; Physics; Polynomials; Thermal resistance; neural network module; non-linearity compensation; polynomial basis functions neural network; sensor; thermocouple;

fLanguage

English

Publisher

ieee

Conference_Titel

Mechanic Automation and Control Engineering (MACE), 2011 Second International Conference on

Conference_Location

Hohhot

Print_ISBN

978-1-4244-9436-1

Type

conf

DOI

10.1109/MACE.2011.5988679

Filename

5988679