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基于有序样品聚类和模糊理论发动机状态监测研究
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Research on Condition Monitoring of Engines Based on Orderly Sample Clustering and Fuzzy Theory
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    摘要:

    提出基于有序样品聚类和模糊理论发动机状态监测研究方法。利用有序样品聚类方法,对油液铁谱分析数据进行分类,实现了发动机的状态监测;利用模糊理论方法,结合发射光谱分析数据判断发动机的异常磨损部位。采用该方法对康明斯6BT5.9型柴油发动机状态进行监测,确定发动机可能出现异常磨损的部位,与发动机解体实际检查结果一致,证明上述研究方法对发动机异常磨损部位的确定具有一定的适用性。

    Abstract:

    An engine condition monitoring research method was proposed based on orderly sample clustering and Fuzzy theory.Orderly sample clustering method was applied to divide oil ferrography data into several categories and the engine condition monitoring was realized.Fuzzy theory method was applied to find out the location of the abnormal friction pairs of engine in combination with atom emission spectrum analysis data.The method was adopted for the conditioning monitoring of the diesel engine Cummings 6BT59,the possible abnormal wear position was determined,and the results were in accordance with the actual inspection results of engine dissemble.It is proved that the above research method is suitable for identifying the abnormal wear portion of engine.

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刘玉兵,杨川,王晓东.基于有序样品聚类和模糊理论发动机状态监测研究[J].润滑与密封,2017,42(7):117-120.
. Research on Condition Monitoring of Engines Based on Orderly Sample Clustering and Fuzzy Theory[J]. Lubrication Engineering,2017,42(7):117-120.

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  • 在线发布日期: 2018-02-27
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