【摘 要】
：
在对一台 AE-54型拖拉机发动机正常状态和喷油压力不足的故障状态下的振动信号进行动态采集和建立 AR 时序模型的基础上,计算了各测试点处4种距离函数值并对它们进行了敏感性
【机 构】
：
北京农业工程大学设备维修工程教研室,北京农业工程大学农业机器运用管理教研室,
论文部分内容阅读
在对一台 AE-54型拖拉机发动机正常状态和喷油压力不足的故障状态下的振动信号进行动态采集和建立 AR 时序模型的基础上,计算了各测试点处4种距离函数值并对它们进行了敏感性分析,最终选取了 Kullback-Leibler 信息量距离函数 D_(KL)作为诊断函数。考虑到各测试点间故障信号的传递性,导出对各测试点的 D_(KL)值进行加权处理的加权矩阵,从而得到一种新的判别函数。利用经加权处理的 D_(KL)诊断函数值,不仅能诊断出发动机有无故障,而且能诊断出故障点的位置。这种方法也可用于发动机其他类型的故障诊断中。
Based on the dynamic acquisition of the vibration signals and the establishment of the AR time series of the vibration signals of an AE-54 tractor engine under normal conditions and insufficient fuel injection pressure, four kinds of distance function values at each test point are calculated and their values Sensitivity analysis was carried out. Finally, the Kullback-Leibler information distance function D KL was selected as the diagnostic function. Considering the transmissibility of fault signals between test points, a weighted matrix is obtained by weighting D_ (KL) values at each test point, so that a new discriminant function is obtained. Using weighted D_ (KL) diagnostic function values, it can not only diagnose whether there is any fault in the engine, but also diagnose the position of the fault. This method can also be used in other types of engine fault diagnosis.
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