Aimed to improve the measurement precision of the capacitance method for petroleum water content

a nonlinear calibration technique based on neural networks is presented.Consider that the traditional BP algorithm has shortcomings of converging slowly and easily trapping a local minimum value

a combination algorithm using particle swarm optimization（PSO）and back propagation（BP）is adopted to train the neural network.It will enable the calibration process with an overall accuracy and a higher converging speed.Simulation results show that this method can effectively eliminate the impact of non-target parameters to the sensor output and has certain project value.