In order to achieve light intensity compensation and reduce measurement error of fiber displacement sensor,a model of light intensity compensation and correction was proposed based on BP neural network optimized by Genetic Algorithm (GA).First,through the calibration experiment to the optical fiber displacement sensor,the original data was obtained.Then,the GA-BP neural network was used for modeling.Through the study on the encoding method,fitness function and parameters of GA,the global optimization capability of GA was used to optimize the weights and thresholds of traditional BP neural network,which made it less easier to fall into local extreme.Finally,the measured data was used to train the GA-BP network and the traditional BP network.The experimental results show that:compared with BP network,the GA-BP network has much smaller prediction error and higher compensation accuracy,and thus can realize the intensity compensation of the optical fiber displacement sensor.