针对现有的船舶机舱的环境监测报警系统无法对船舱火灾进行预警的缺点，设计一种基于BP神经网络的船舱温度预警系统。对船舱某一固定点的温度进行模拟仿真得到预测结果，并通过与实际测得的温度数据比较验证系统仿真得到结果的正确性。实验证明，该船舱温度预测模型预测的结果与真实测得的温度数据比较具有相对较高的准确性，可以达到温度预测的效果，对船舶机舱对火灾进行预警具有一定意义。
Aiming at the existing ship engine room environment monitoring alarm system is unable to cabin fire warning defects, design a based on BP neural network cabin temperature warning system. The cabin of a fixed point temperature of simulation prediction results were obtained, and compared with the actual measured temperature data comparison to verify the correctness of the simulation results. Experiments show that, the cabin temperature prediction model for the prediction of the results and the real measured temperature data comparison with relatively high accuracy, can achieve the effect of temperature prediction, of ship engine room fire warning has a certain significance.
2017,39(1): 145-149 收稿日期：2016-05-30
DOI：10.3404/j.issn.1672-7619.2017.01.030
分类号：TP277
作者简介：王明强(1964-),男,教授,研究方向为现代机械设计理论与方法、现代机电产品及工程开发。
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