Selection of measurement parameters based on eigenvalues and eigenvectors
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摘要: 研究了航空发动机气路故障诊断中测量参数如何选择的问题。利用发动机故障诊断矩阵,提出了基于特征值和特征向量比较不同测量参数选择系统之间优劣的简易快速算法,该算法可以从几何角度直观地展现整体解空间和解矢量的方向等变化情况。通过一个单轴涡喷发动机测量系统对比案例有效地表明:地面测试系统的最大与最小特征值比为33,机载系统的最大与最小特征值比为1008,在该单轴涡喷发动机气路故障诊断方面,地面测试系统比机载系统明显更有利于气路故障诊断。该算法可用于优化机载发动机测量传感器布局、台架测量系统中测量传感器布局,指导工程中测量参数的选择等。Abstract: The problem of how to choose the parameters in the aero engine gas path fault diagnosis was studied. Using engine fault diagnosis matrix, a simple and fast algorithm based on eigenvalues and eigenvectors to compare the advantages and disadvantages between different measurement systems was proposed. The algorithm can directly show the change of the global solution space and the direction of vectors from a geometric perspective. A comparison case study of a single-axis turbojet engine test system showed that the maximum-minimum eigenvalue ratio of the ground test system was 33, and the maximum-minimum eigenvalue ratio of the airborne system was 1008. The ground test system is more advantageous to the fault diagnosis of the single-axis turbojet engine than the airborne system.The algorithm can be used to optimize the layout of sensors in airborne engines, measure sensor layout in bench measurement system, and guide the selection of measurement parameters in engineering.
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