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首页> 外文会议>1st international conference on transportation information and safety 2011.;vol. 1. >Expert Weight Allocation for Diesel Engine Condition Identification Based on Entropy Theory and Fuzzy Logic
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Expert Weight Allocation for Diesel Engine Condition Identification Based on Entropy Theory and Fuzzy Logic

机译：基于熵理论和模糊逻辑的柴油机状态识别专家权重分配

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Expert weight allocation is important for the diesel engine condition identification design. The weights of the expert information are affected by many levels. A new method based on the entropy theory and fuzzy logic for the expert weight allocation was proposed in this study. Firstly, the entropy theory was used to analyze the difference between the weights of different experts and the optimal weights to determine the expert assessment level. Thus, a comprehensive weight of condition identification was obtained. Then the fuzzy identification theory and the comprehensive weights were combined to identify the diesel engine condition. The experiment tests of six typical operational conditions were carried out using the diesel engine tester. The analysis results indicated that the six states of the diesel engine could be recognized correctly. The proposed method is effective for the diesel engine condition identification and has the importance of application.
机译：专家权重分配对于柴油机状态识别设计很重要。专家信息的权重受许多级别的影响。提出了一种基于熵理论和模糊逻辑的专家权重分配新方法。首先，利用熵理论分析不同专家权重与最优权重之间的差异，确定专家评估水平。因此，获得了状态识别的综合权重。然后结合模糊辨识理论和综合权重，对柴油机状态进行辨识。使用柴油发动机测试仪对六个典型运行条件进行了实验测试。分析结果表明，可以正确识别柴油机的六种状态。该方法对柴油机状态识别是有效的，具有重要的应用意义。

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