基于CWOA-BP的电缆接头阻水性能评估

为评估电缆接头阻水性,提出了一种基于CWOA-BP神经网络的电缆接头阻水性评估模型。对电缆冷缩接头进行阻水试验,选取电缆接头传感器上各项数据作为评估指标进行实例分析,并与BP、GA-BP、PSO-BP三种算法进行对比。仿真结果表明,新模型算法具有收敛速度快、预测精度高的优点,是一种有效可靠的电缆接头阻水性能评估模型。

Water Resistance Performance Evaluation of Cable Joints Based on CWOA-BP

To evaluate the water resistance of cable joints, this paper proposes a water resistance evaluation model for cable joints based on CWOA-BP neural network. The water-resistance experiment of cable cold-shrink joints is conducted. The data on the cable joint sensor are selected as an evaluation index for example analysis, and compared with the BP, GA-BP and PSO-BP. The simulation results show that the algorithm adopted by the new model has the advantages of fast convergence speed and high prediction accuracy. Thus, it is an effective and reliable evaluation model for cable joint water resistance performance.