悬链式船舶链条机械磨损寿命预测准确度评估

Accuracy evaluation of mechanical wear life prediction for chain ship chain

为了提高悬链式船舶链条机械磨损寿命预测准确性能,设计了一种基于改进神经网络的悬链式船舶链条机械磨损寿命预测模型。首先对悬链式船舶链条机械磨损寿命预测研究现状进行分析,找到引起悬链式船舶链条机械磨损寿命预测精度的因素,然后收集悬链式船舶链条机械磨损寿命的历史数据,并采用BP神经网络建立悬链式船舶链条机械磨损寿命预测模型,并引入自适应遗传算法对BP神经网络的不足进行改进,最后采用仿真实验对悬链式船舶链条机械磨损寿命预测模型的准确度进行评估,结果表明,改进神经网络提高了悬链式船舶链条机械磨损寿命预测精度,预测结果比其他模型更加可靠。

In order to improve the accurate performance of the mechanical wear life prediction of the suspended chain ship chain, a model for predicting the wear life of the suspended chain ship chain based on improved neural network is designed. Firstly, the research status of mechanical wear life prediction of suspended chain ship chain is analyzed, and the factors that cause the prediction accuracy of the mechanical wear life of the chain ship chain are found. Then, the historical data of the wear life of the suspended chain ship chain machinery is collected, and the BP neural network is used to predict the wear life of the chain. The model is introduced, and the adaptive genetic algorithm is introduced to improve the shortage of BP neural network. Finally, the simulation experiment is used to evaluate the accuracy of the suspended chain ship chain mechanical wear life prediction model, and the result is more love. The improved neural network improves the prediction accuracy of the suspension chain ship chain mechanical wear life, and the prediction results are compared with that of the model. The model is more reliable.