Title :
Nonlinear compensation of capacitance weighing sensors based on Neural Networks with Orthonormal Functions
Author :
Li-ying Xu ; Li-Jun Li
Author_Institution :
Changsha Univ. of Sci. & Technol., Changsha, China
Abstract :
The relationship between output voltage and the loading of the capacitance weighing sensor is nonlinear. To obtain accurate measurement, it is necessary to compensate the nonlinearity. A nonlinear compensation method based on Neural Networks with Orthonormal Functions is proposed in this paper. The convergence of the neural network algorithm is researched. The result shows that the method proposed has high accurate. Therefore, the method proposed is effective and may be used for other applications.
Keywords :
capacitance measurement; capacitive sensors; computerised instrumentation; neural nets; accurate measurement; neural network algorithm; nonlinear capacitance weighing sensors compensation; orthonormal functions; Biological neural networks; Capacitance; Capacitive sensors; Convergence; Neurons; Sensor phenomena and characterization; Orthonormal Functions; capacitance weighing sensor; neural network; nonlinear compensation;
Conference_Titel :
Natural Computation (ICNC), 2011 Seventh International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-9950-2
DOI :
10.1109/ICNC.2011.6022165