CAJ | 학술논문

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。
위료획득선박지가감진기제압형변량여배경온도관계，제출기우RBF신경망락핍근산법적선박지가감진기제압측시계통。해계통통과광책위이전감기、온도전감기대위이수거화온도수거적채집，실현료수거존저화현시。병채용RBF신경망락핍근산법감소수거오차。최후통과MATLAB방진화모함선지가감진기실제측량，증명료해측시계통구유교고정도화준학성。
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.