Physical constraints fused equiangular tight frame method for Blade Tip Timing sensor arrangement

Physical constraints fused equiangular tight frame method for Blade Tip Timing sensor arrangement
复制标题

叶尖正时传感器布置的物理约束融合等角紧框架法

DOI:
10.1016/j.measurement.2019.05.107
复制
发表时间:
2019-10
期刊:
影响因子:
5.6
通讯作者:
Chen Xuefeng
Chen Xuefeng
中科院分区:
工程技术2区
文献类型:
--
作者:
Wu Shuming;Zhao Zhibin;Yang Zhibo;Tian Shaohua;Yang Laihao;Chen Xuefeng

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由于叶片的非接触特性,叶尖定时(BTT)方法越来越多地应用于旋转叶片的健康监测。然而,BTT数据通常是高度欠采样的,因为只有少数传感器可以安装在外壳上。由于安装的传感器数量有限,这种安排可能对BTT数据质量产生重大影响。与以往研究的穷举方法不同,本文提出了一种以优化目标为导向的传感器配置数学模型。考虑到采样矩阵的量纲特性,本文不再采用单个矩阵相干值作为优化目标,而是采用等角紧框架矩阵作为整个采样矩阵的目标。此外,本文首先考虑了实际安装的物理约束和模态先验对传感器布置的影响。然后采用交替最小化法求解融合物理约束的等角紧框架法。此外,考虑到以往振动参数识别算法在振幅恢复和噪声滤波方面的不足,采用基于迭代重加权l1范数的参数识别方法,从高度欠采样的BTT数据中获得振幅重建精度较高的振动参数。仿真和实验结果验证了所提方法的有效性。
Blade Tip Timing (BTT) method is increasingly implemented for rotating blade health monitoring for its non-contact property. However, the BTT data is usually highly undersampled as only a few sensors could be installed on the case. Due to the limited number of sensors installed, the arrangement can have a significant impact on BTT data quality. Different from the exhaustive method used in previous researches, in this paper, a mathematical model guided by optimizing objective is proposed for sensor configuration. Considering the dimensional characteristics of the sampling matrix, this paper no longer uses a single matrix coherence value as the optimization target, but adopts the Equiangular tight frame matrix as the goal of the whole sampling matrix. Moreover, this paper first considers the physical constraints of the actual installation and modal prior on the sensor arrangement. The physical constraints fused equiangular tight frame method is then solved by an alternating minimization approach. In addition, considering the disadvantages of the previous vibration parameter identification algorithms in terms of amplitude recovery and noise filtering, an iterative reweighted L1-norm based parameter identification method is applied to obtain the vibration parameters from the highly undersampled BTT data with better amplitude reconstruction accuracy. Both the simulation and experiment results are given to verify the effectiveness of the developed methods.
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