Temperature Compensation System of Diesel Engine Piezoresistive Pressure Transducer Based on Neural Networks and LabVIEW

The work presented in this paper focuses on the output of temperature compensation system of diesel engine piezoresistive pressure transducer, it is nonlinear and influenced easily by environmental temperature. The paper studied the method of using improved neural network algorithm based on LabVLEW and MATLAB to increase the precision and efficiency of pressure detection. In order to eliminate the temperature influence, this paper proposed the method of using improved back propagation neural network on Lab VIEW platform, which realized the communication between LabVIEW and MATLAB. The experimental results show that, with the using of Matlab Script node, the system benefits from the huge computing power of MATLAB to train the network based on the static calibration data of transducer, and makes temperature compensation more efficient and accurate.