Sparse reconstruction of blade tip-timing signals for multi-mode blade vibration monitoring

Lin, Jun; Hu, Zheng; Chen, Zhongsheng; Yang, Yongmin; Xu, Hailong

doi:10.1016/j.ymssp.2016.03.020

Cited by 125 publications

(43 citation statements)

References 24 publications

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“…Compressed sensing approaches have well performed in vibration analysis for non-uniform sampling signals. For instance, Lin et al [13] propose a sparse reconstruction method that has been adapted to the tip-timing technology. Note that, inherent hypothesis of such method does not allow engine speed variations.…”

Section: Spectral Analysis With Tip-timing Signalsmentioning

confidence: 99%

Blade vibration study by spectral analysis of tip-timing signals with OMP algorithm

Bouchain

Picheral

Lahalle

et al. 2019

Mechanical Systems and Signal Processing

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Blades vibrations must be measured in operations to validate blade design. Tip-timing is one of the classical measurement methods but its main drawback is the generation of sub-sampled and non-uniform sampled signals. Consequently tip-timing signals cannot be processed with conventional methods. Assuming that blade vibration signals yield to line spectra, we introduced a sparse signal model that uses speed variation of the engine. The usual solutions of inverse problems are given with the LASSO method. This paper presents a new approach based on a ℓ 0-regularization. It is solved with the OMP algorithm adapted to our model. Results from synthetic and real signals are presented to illustrate the efficiency of this method, including a real blade crack test case. The main advantages of the proposed method are to provide accurate estimations with a computational cost drastically reduced with respect to existing methods. Besides, the method does not need to set up regularization parameters while taking into account the speed variation of the engines. Finally, results show that this approach greatly reduces frequency aliasings caused by the low sampling frequency of the measured signals.

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Section: Spectral Analysis With Tip-timing Signalsmentioning

confidence: 99%

Blade vibration study by spectral analysis of tip-timing signals with OMP algorithm

Bouchain

Picheral

Lahalle

et al. 2019

Mechanical Systems and Signal Processing

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“…In order to overcome the shortcomings of contact measurement methods, more and more researchers are studying noncontact blade vibration monitoring methods. Nowadays, blade tip-timing (BTT) has become a promising approach of noncontact vibration monitoring [7][8][9]. A BTT method always uses the times at which the blade tips pass the casing-mounted probes to obtain all-blade vibrations simultaneously.…”

Section: Introductionmentioning

confidence: 99%

Undersampled Blade Tip‐Timing Vibration Reconstruction under Rotating Speed Fluctuation: Uniform and Nonuniform Sensor Configurations

Chen

Zhan

2019

Shock and Vibration

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Blade tip-timing (BTT) is a promising method of online monitoring rotating blade vibrations. Since BTT-based vibration signals are typically undersampled, how to reconstruct characteristic vibrations from BTT signals is a big challenge. Existing reconstruction methods are mainly based on the assumption of constant rotation speeds. However, rotating speed fluctuation is inevitable in many engineering applications. In this case, the BTT sampling process should be nonuniform, which will cause existing reconstruction methods to be unavailable. In order to solve this problem, this paper proposes a new reconstruction method based on nonlinear time transformation (NTT). Firstly, the effects of rotating speed fluctuation on BTT vibration reconstruction are analyzed. Next, the NTT of BTT sampling times under rotating speed fluctuation is presented. Then, two NTT-based reconstruction algorithms are derived for uniform and nonuniform BTT sensor configurations, respectively. Also several evaluation metrics of BTT vibration reconstruction under rotating speed fluctuation are defined. Finally, numerical simulations are done to verify the proposed algorithms. The results testify that the proposed NTT-based reconstruction method can reduce effectively the influence of rotating speed fluctuation and decrease the reconstruction error. In addition, rotating speed fluctuation has more bad effects on the reconstruction method under nonuniform sensor configuration than under uniform sensor configuration. For nonuniform BTT signal reconstruction under rotating speed fluctuation, more attentions should be paid on selecting proper angles between BTT sensors. In summary, the proposed method will benefit for detecting early blade damages by reducing frequency aliasing.

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“…Nevertheless, this method involves a high computation time. A compressed sensing approach has been developed in [6] based on a Sparse Reconstruction Method (denoted as SRM in this paper). An other ℓ 1 -regularized method, developped in [7] by the authors, has been proposed for spectral analysis of tip-timing signals.…”

Section: Introductionmentioning

confidence: 99%

“…An other ℓ 1 -regularized method, developped in [7] by the authors, has been proposed for spectral analysis of tip-timing signals. Note that, inherent hypothesis of [6] and [7] methods do not allow engine speed variations. Consequently, on real data, the rotation speed variations limit the length of the observation window and can lead to erroneous amplitudes estimations.…”

Section: Introductionmentioning

confidence: 99%

Sparse Method for Tip-Timing Signals Analysis with Non Stationary Engine Rotation Frequency

Bouchain

Vercoutter

Picheral

et al. 2018

2018 26th European Signal Processing Conference (EUSIPCO)

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Blades vibrations must be measured in operations to validate blade design. Tip-timing is one of the classical measurement methods but its main drawback is the generation of sub-sampled and non-uniform sampled signals. This paper presents a new sparse method for tip-timing spectral analysis that makes use of engine rotation variations. Assuming that blade vibration signals yield to line spectra, a sparse signal model is introduced as a linear system. The solution to the problem is obtained by ADMM (Alternating Direction Method of Multipliers) with a ℓ 1-regularization. Results for simulated and real signals are given to illustrate the efficiency of this method. The main advantages of the proposed method are to provide a fast solution and to take into account the variations of the rotation speed. Results show that this approach reduces frequency aliasings caused by the low sampling frequency of the measured signals.

show abstract

Sparse reconstruction of blade tip-timing signals for multi-mode blade vibration monitoring

Cited by 125 publications

References 24 publications

Blade vibration study by spectral analysis of tip-timing signals with OMP algorithm

Blade vibration study by spectral analysis of tip-timing signals with OMP algorithm

Undersampled Blade Tip‐Timing Vibration Reconstruction under Rotating Speed Fluctuation: Uniform and Nonuniform Sensor Configurations

Sparse Method for Tip-Timing Signals Analysis with Non Stationary Engine Rotation Frequency

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