The Novel Model of Fusion Temperature Error Compensation System by Neural Network and Smart Sensors
Dandan Cui, Zhang Cai-qian · Journal of Convergence Information Technology · 2013
Neural network is a non-linear statistical data modeling tool, commonly used for input and output of the complex relationships between modeling, or used to explore the patterns in the data. In this paper, the data fusion theory and neural network method is applied to the smart sensor error compensation, greatly improving the magnetic flux leakage testing sensor stability and accuracy. Here the intelligent sensor information fusion is applied to the error compensation. The detection device sensor components to add a temperature sensor is real-time record of working environment temperature. The paper proposes the novel model of fusion temperature error compensation system by neural network and smart sensors. Finally the experiments verify the validity of the method.