针对柴油机冷却系统状态识别,提出基于证据理论的多传感器信息融合方法.基于两个温度传感器的柴油机冷却系统状态,获取多源信号,采用各传感器测试数据与系统对应标准状态特征集的贴近度,确定基本概率分配矩阵,通过Demster-Shafer证据组合方法实现信息融合,并确定系统的运行状态.结果表明,该方法可以提高设备状态识别的确定性,为柴油机冷却系统状态识别提供一种新途径.
Abstract
Multi-sensors’ data fusion method based on Demster-Shafer theory was proposed for condition recognition of diesel engine cooling system. The signals were obtained from two thermal sensors at inlet and outlet pipes respectively by using by the fitness between standard condition characteristic set corresponding to system and test data of sensors, the basic probability assignment matrix was determined. The system operating condition was decided with the data fusion method based on Demster-Shafer theory. Results show that the mentioned method can increase the accuracy of decision obviously, so as to give a new way to the work of condition recognition of diesel engine cooling system.
关键词
柴油机 /
状态识别 /
证据理论 /
多传感器 /
信息融合
Key words
diesel engine /
condition recognition /
Dempster-shafer (DS) theory /
multi-sensors /
data fusion
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