基于 RBF神经网络逼近算法的船舶支架减振器挤压测试系统

摘要

为了获得船舶支架减振器挤压形变量与环境温度关系，提出基于RBF神经网络逼近算法的船舶支架减振器挤压测试系统。该系统通过光栅位移传感器、温度传感器对位移数据和温度数据的采集，实现了数据存储和显示。并采用RBF神经网络逼近算法减小数据误差。最后通过MATLAB仿真和某舰船支架减振器实际测量，证明了该测试系统具有较高精度和准确性。%In order to obtain the relationship of the deformation quantity of ship bracket shock absorber and the environment temperature, in this paper we introduce an extruding detection system of ship bracket shock absorber which is based on the RBF neural network approxima-tion algorithm.The system uses grating displacement sensor and temperature sensor to collect displacement data and temperature data, and re-alises data storage and display.Moreover, the RBF neural network approximation algorithm is employed to reduce data errors.At last, through MATLAB simulation and actual measurement on the bracket shock absorber in a certain ship we prove that the system has a higher precision and accuracy.