Optimized under-actuated control of blade vibration system under wind uncertainty

Li, Nailu; Mu, Anle; Yang, Hua; Magar, Kaman Thapa

doi:10.1016/j.jsv.2019.115070

Cited by 6 publications

(1 citation statement)

References 28 publications

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“…Structural damage to high-speed rotary machines, such as aircraft engines, axial, bearing and centrifugal compressors, can cause catastrophic incidents and has received a great deal of attention [1][2][3]. Therefore, structural damage needs to be prevented and predicted to reduce maintenance costs significantly in advance [4,5].…”

Section: Introductionmentioning

confidence: 99%

Weak crack identification of compressor impeller with hybrid methods of PNNs and SVD

Jiang

Wang

Zhong

et al. 2021

Meas. Sci. Technol.

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Damage to a compressor impeller can sometimes cause serious accidents, heavy casualties and property loss, etc. Therefore, it is necessary to conduct damage monitoring and identification for the compressor impeller. A damage identification method based on probabilistic neural networks (PNNs) with modal information fusion is proposed for a compressor impeller. The modal shape of the compressor impeller can be acquired by experimental modal analysis. Combining waveform capacity dimension, a singular value decomposition is applied to extract damage feature information from the system modal shape. The two damage indicators are fused by a multi-dimensional feature vector. Finally, a PNN model is constructed and used to identify structural damage. The experimental results indicate that the proposed method is effective in detecting damage to the compressor impeller.

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