LAMOST平衡系统的传感器优化布置

针对模态测试中的传感器优化布置问题，提出一种新的主元分析和组合MAC联合算法。首先，将多种传感器布置方法的结果形成原始特征数据矩阵，利用主元分析获得空间测点的主元和综合评价值，据此可以合理地大幅减少候选测点数目；其次，使用组合MAC法计算所有组合的MAC矩阵，取最大非对角元最小的一组作为最终选择；然后，以悬臂梁为例，分别用联合算法和4种传统算法对其进行传感器优化布置，通过3个评价准则的数值比较，证明联合算法的优越性；最后，将联合算法应用在望远镜LAMOST的平衡系统上，得到了两个方向上的传感器布置方案，进一步验证了联合算法的可行性。

Optimal Sensor Placement for the Balance System of LAMOST

An innovative united method based on principal component analysis (PCA) and the combination modal assurance criteria (CMAC) method is proposed for optimal sensor location. Firstly, using PCA, a raw data matrix is formed with the results of three optimal sensor location algorithms, and the principal components and comprehensive evaluation value are obtained, which can be used to choose candidate locations. Secondly, the MAC matrix of all combinations of the candidate locations is calculated and the points which meet the demand of minimum no-diagonal elements will be chosen. Results show that with the cantilever beam as a research object, the united method has better results than four traditional methods according to three evaluation criteria. Finally, the united method is used in the balance system of large area multi-object spectroscopic telescope (LAMOST) to get the sensor arrangement in two directions.