A Novel Method for Identification of Synchronous Resonance Frequency of Blades Based on Random Arrangement of Tip-timing Probes
A Novel Method for Identification of Synchronous Resonance Frequency of Blades Based on Random Arrangement of Tip-timing Probes
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DOI：
10.1016/j.jsv.2022.117264
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发表时间：
2022-08
影响因子：
4.7
通讯作者：
Hongkun Li;Jiannan Dong;Zhenfang Fan;Daitong Wei;Yugang Chen
中科院分区：
文献类型：
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作者：
Hongkun Li;Jiannan Dong;Zhenfang Fan;Daitong Wei;Yugang Chen
叶尖正时(BTT)信号具有欠采样特性，导致高频信息混叠到低频段，特别是同步谐振频率混叠问题更加严重。为了实现同步谐振中欠采样信号的频率识别，提出了一种基于针尖定时探头随机排列的多尺度循环反向优化排列方法。首先，基于已知欠采样信号和未知原始信号在频域的联系建立稀疏频率恢复模型，并采用压缩感知(CS)的子空间追踪(SP)算法进行频率恢复。然后，在探头随机排列的情况下，在多个尺度上调整理想探头的个数，循环选择基准探头，得到多组解。最后，使用目标频率权重来克服参数化压缩矩阵的受限等距特性(RIP)的限制，以确定最优恢复频率。通过BTT实验验证了该方法的有效性。
Blade tip-timing (BTT) signal suffers from the undersampling feature, which causes the high-frequency information to be aliased to the low-frequency band, especially the aliasing problem of the synchronous resonance frequency more serious. In order to realize the frequency identification of undersampled signals in synchronous resonance, a novel multiscale cyclic-reverse optimized arrangement (MC-ROA) method based on the random arrangement of tip-timing probes is proposed in this paper. Firstly, a sparse model for frequency recovery is built based on the link between the known undersampled signals and the unknown original signals in the frequency domain, and the subspace pursuit (SP) algorithm of compressive sensing (CS) is used for frequency recovery. Then, under the random arrangement of probes, the number of ideal probes is adjusted at multiple scales and the datum probes are selected cyclically to obtain multiple sets of solutions. Finally, the target frequency weights are used to overcome the limitations of the restricted isometry property (RIP) of the parameterized compression matrix to determine the optimal recovery frequency. The BTT experiments are given to verify the effectiveness of the proposed method.