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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.
Aiming at the state recognition of diesel engine cooling system, a multi-sensor information fusion method based on evidence theory is proposed. Based on the state of diesel engine cooling system with two temperature sensors, multi-source signals are obtained, and the closeness of test data and corresponding standard state feature sets are obtained. The basic probability distribution matrix is determined and the information fusion is achieved by the Demster-Shafer evidence combination method, and the running status of the system is determined. The results show that this method can improve the certainty of equipment status identification and provide a new way for the state recognition of diesel engine cooling system.