Abstract
Aiming at the problem existed in the application of N type thermocouple with big and small data samples, the LSSVM method for correcting nonlinear error of thermocouple sensor and RBF neural network using PSO are introduced. These methods are compared with some commonly used calibration methods, such as BP neural network, RBF neural network and ANFIS method. The result of experiment shows that the nonlinear calibration method based on LSSVM and PSO- RBF has higher precision than the methods based on BP, RBF or ANFIS. LSSVM method was used to test fire-path temperature in anode baking process, and satisfactory result was achieved. Test result proves that the method is effective.
This work is partially supported by Shanghai key scientific research project No.11510502700,and science and technology innovation focus of SHMEC No.12ZZ189,and Science Foundation of SIT (YJ2011-33) and (YJ2011-22).
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© 2012 Springer-Verlag Berlin Heidelberg
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Li, X., Sun, H., Xia, N., Wang, J. (2012). Nonlinear Calibration for N Thermocouple Sensor. In: Tan, Y., Shi, Y., Ji, Z. (eds) Advances in Swarm Intelligence. ICSI 2012. Lecture Notes in Computer Science, vol 7332. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31020-1_43
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DOI: https://doi.org/10.1007/978-3-642-31020-1_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31019-5
Online ISBN: 978-3-642-31020-1
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