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

2019 ◽  
Vol 2019 ◽  
pp. 1-13
Author(s):  
Zhongsheng Chen ◽  
Jing He ◽  
Chi Zhan
Keyword(s):  
Signal Reconstruction ◽  
Reconstruction Error ◽  
Reconstruction Method ◽  
Reconstruction Algorithms ◽  
Rotating Speed ◽  
Rotating Blade ◽  
Reconstruction Methods ◽  
Speed Fluctuation ◽  
Blade Tip ◽  
Sensor Configuration

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.

scholarly journals Fractional Differential Equation-Based Instantaneous Frequency Estimation for Signal Reconstruction

2021 ◽  
Vol 5 (3) ◽  
pp. 83
Author(s):  
Bilgi Görkem Yazgaç ◽  
Mürvet Kırcı
Keyword(s):  
Differential Equation ◽  
Fractional Differential Equation ◽  
Frequency Estimation ◽  
Signal Reconstruction ◽  
Reconstruction Method ◽  
Reconstruction Algorithms ◽  
Instantaneous Frequency Estimation ◽  
Proposed Model ◽  
Fractional Differential ◽  
Instantaneous Frequencies

In this paper, we propose a fractional differential equation (FDE)-based approach for the estimation of instantaneous frequencies for windowed signals as a part of signal reconstruction. This approach is based on modeling bandpass filter results around the peaks of a windowed signal as fractional differential equations and linking differ-integrator parameters, thereby determining the long-range dependence on estimated instantaneous frequencies. We investigated the performance of the proposed approach with two evaluation measures and compared it to a benchmark noniterative signal reconstruction method (SPSI). The comparison was provided with different overlap parameters to investigate the performance of the proposed model concerning resolution. An additional comparison was provided by applying the proposed method and benchmark method outputs to iterative signal reconstruction algorithms. The proposed FDE method received better evaluation results in high resolution for the noniterative case and comparable results with SPSI with an increasing iteration number of iterative methods, regardless of the overlap parameter.

scholarly journals An Improved Circumferential Fourier Fit (CFF) Method for Blade Tip Timing Measurements

2020 ◽  
Vol 10 (11) ◽  
pp. 3675
Author(s):  
Zhibo Liu ◽  
Fajie Duan ◽  
Guangyue Niu ◽  
Ling Ma ◽  
Jiajia Jiang ◽  
...  
Keyword(s):  
Development Program ◽  
Time Of Arrival ◽  
Blade Vibration ◽  
Vibration Measurements ◽  
Rotating Speed ◽  
Resonance Analysis ◽  
Rotating Blade ◽  
Negative Effect ◽  
Frequency Identification ◽  
Blade Tip

Rotating blade vibration measurements are very important for any turbomachinery research and development program. The blade tip timing (BTT) technique uses the time of arrival (ToA) of the blade tip passing the casing mounted probes to give the blade vibration. As a non-contact technique, BTT is necessary for rotating blade vibration measurements. The higher accuracy of amplitude and vibration frequency identification has been pursued since the development of BTT. An improved circumferential Fourier fit (ICFF) method is proposed. In this method, the ToA is not only dependent on the rotating speed and monitoring position, but also on blade vibration. Compared with the traditional circumferential Fourier fit (TCFF) method, this improvement is more consistent with reality. A 12-blade assembly simulator and experimental data were used to evaluate the ICFF performance. The simulated results showed that the ICFF performance is comparable to TCFF in terms of EO identification, except the lower PSR or more number probes that have a more negative effect on ICFF. Besides, the accuracy of amplitude identification is higher for ICFF than TCFF on all test conditions. Meanwhile, the higher accuracy of the reconstruction of ICFF was further verified in all measurement resonance analysis.

scholarly journals A Non-Uniformly Under-Sampled Blade Tip-Timing Signal Reconstruction Method for Blade Vibration Monitoring

Sensors ◽  
2015 ◽  
Vol 15 (2) ◽  
pp. 2419-2437 ◽  
Author(s):  
Zheng Hu ◽  
Jun Lin ◽  
Zhong-Sheng Chen ◽  
Yong-Min Yang ◽  
Xue-Jun Li
Keyword(s):  
Signal Reconstruction ◽  
Vibration Monitoring ◽  
Reconstruction Method ◽  
Blade Vibration ◽  
Blade Tip

scholarly journals Reconstructed Order Analysis-Based Vibration Monitoring under Variable Rotation Speed by Using Multiple Blade Tip-Timing Sensors

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3235 ◽  
Author(s):  
Zhongsheng Chen ◽  
Jianhua Liu ◽  
Chi Zhan ◽  
Jing He ◽  
Weimin Wang
Keyword(s):  
High Speed ◽  
Rotation Speed ◽  
Reconstruction Algorithm ◽  
Vibration Monitoring ◽  
Reconstruction Algorithms ◽  
Monitoring Method ◽  
Vibration Signals ◽  
Order Analysis ◽  
Blade Tip ◽  
Sensor Configuration

On-line vibration monitoring is significant for high-speed rotating blades, and blade tip-timing (BTT) is generally regarded as a promising solution. BTT methods must assume that rotating speeds are constant. This assumption is impractical, and blade damages are always formed and accumulated during variable operational conditions. Thus, how to carry out BTT vibration monitoring under variable rotation speed (VRS) is a big challenge. Angular sampling-based order analyses have been widely used for vibration signals in rotating machinery with variable speeds. However, BTT vibration signals are well under-sampled, and Shannon’s sampling theorem is not satisfied so that existing order analysis methods will not work well. To overcome this problem, a reconstructed order analysis-based BTT vibration monitoring method is proposed in this paper. First, the effects of VRS on BTT vibration monitoring are analyzed, and the basic structure of angular sampling-based BTT vibration monitoring under VRS is presented. Then a band-pass sampling-based engine order (EO) reconstruction algorithm is proposed for uniform BTT sensor configuration so that few BTT sensors can be used to extract high EOs. In addition, a periodically non-uniform sampling-based EO reconstruction algorithm is proposed for non-uniform BTT sensor configuration. Next, numerical simulations are done to validate the two reconstruction algorithms. In the end, an experimental set-up is built. Both uniform and non-uniform BTT vibration signals are collected, and reconstructed order analysis are carried out. Simulation and experimental results testify that the proposed algorithms can accurately capture characteristic high EOs of synchronous and asynchronous vibrations under VRS by using few BTT sensors. The significance of this paper is to overcome the limitation of conventional BTT methods of dealing with variable blade rotating speeds.

The Application of Constrained Signal Reconstruction Methods in High Voltage Impulse Measurement

1988 ◽  
Vol 25 (2) ◽  
pp. 171-181
Author(s):  
D. M. Nagasaka ◽  
M. R. Raghuveer
Keyword(s):  
Least Squares ◽  
High Voltage ◽  
Iterative Reconstruction ◽  
Signal Reconstruction ◽  
Reconstruction Method ◽  
Inadequate Response ◽  
Constrained Least Squares ◽  
Measuring Systems ◽  
Reconstruction Methods ◽  
Impulse Measurement

Two methods of signal reconstruction — the constrained iterative reconstruction method (CIR) and the constrained least squares reconstruction method (CLSR) have been used to compensate for the inadequate response of two high voltage impulse measuring systems. Both methods have been shown to produce accurate estimates. However, the CIR method is favoured as it produces stable results under all of the presented conditions.

scholarly journals Quantized compressive sensing with RIP matrices: the benefit of dithering

2019 ◽  
Vol 9 (3) ◽  
pp. 543-586 ◽  
Author(s):  
Chunlei Xu ◽  
Laurent Jacques
Keyword(s):  
Compressive Sensing ◽  
Signal Reconstruction ◽  
Low Complexity ◽  
Reconstruction Error ◽  
Low Rank ◽  
Reconstruction Method ◽  
Single Realization ◽  
Uniform Quantization ◽  
Sensing Model ◽  
Quantized Observations

Abstract Quantized compressive sensing deals with the problem of coding compressive measurements of low-complexity signals with quantized, finite precision representations, i.e., a mandatory process involved in any practical sensing model. While the resolution of this quantization impacts the quality of signal reconstruction, there exist incompatible combinations of quantization functions and sensing matrices that proscribe arbitrarily low reconstruction error when the number of measurements increases. This work shows that a large class of random matrix constructions known to respect the restricted isometry property (RIP) is ‘compatible’ with a simple scalar and uniform quantization if a uniform random vector, or a random dither, is added to the compressive signal measurements before quantization. In the context of estimating low-complexity signals (e.g., sparse or compressible signals, low-rank matrices) from their quantized observations, this compatibility is demonstrated by the existence of (at least) one signal reconstruction method, the projected back projection, whose reconstruction error decays when the number of measurements increases. Interestingly, given one RIP matrix and a single realization of the dither, a small reconstruction error can be proved to hold uniformly for all signals in the considered low-complexity set. We confirm these observations numerically in several scenarios involving sparse signals, low-rank matrices and compressible signals, with various RIP matrix constructions such as sub-Gaussian random matrices and random partial discrete cosine transform matrices.

Image Reconstruction with the Fourier Coefficients for Magnetic Induction Tomography

2020 ◽  
Vol 16 (2) ◽  
pp. 156-163
Author(s):  
Jingwen Wang ◽  
Xu Wang ◽  
Dan Yang ◽  
Kaiyang Wang
Keyword(s):  
Inverse Problem ◽  
Image Reconstruction ◽  
Magnetic Induction ◽  
Fourier Coefficients ◽  
Signal Reconstruction ◽  
Reconstruction Algorithm ◽  
Reconstruction Method ◽  
Measurement Equation ◽  
Image Reconstruction Method ◽  
Magnetic Induction Tomography

Background: Image reconstruction of magnetic induction tomography (MIT) is a typical ill-posed inverse problem, which means that the measurements are always far from enough. Thus, MIT image reconstruction results using conventional algorithms such as linear back projection and Landweber often suffer from limitations such as low resolution and blurred edges. Methods: In this paper, based on the recent finite rate of innovation (FRI) framework, a novel image reconstruction method with MIT system is presented. Results: This is achieved through modeling and sampling the MIT signals in FRI framework, resulting in a few new measurements, namely, fourier coefficients. Because each new measurement contains all the pixel position and conductivity information of the dense phase medium, the illposed inverse problem can be improved, by rebuilding the MIT measurement equation with the measurement voltage and the new measurements. Finally, a sparsity-based signal reconstruction algorithm is presented to reconstruct the original MIT image signal, by solving this new measurement equation. Conclusion: Experiments show that the proposed method has better indicators such as image error and correlation coefficient. Therefore, it is a kind of MIT image reconstruction method with high accuracy.

Interpolation method for wideband signal reconstruction based on blade tip timing measurement

Measurement ◽  
2021 ◽  
Vol 176 ◽  
pp. 109168
Author(s):  
Suiyu Chen ◽  
Yongmin Yang ◽  
Haifeng Hu ◽  
Fengjiao Guan ◽  
Guoji Shen ◽  
...  
Keyword(s):  
Interpolation Method ◽  
Signal Reconstruction ◽  
Wideband Signal ◽  
Timing Measurement ◽  
Blade Tip

Global Inhomogeneity Index Evaluation of a DCT-based EIT Lung Imaging

2020 ◽  
Vol 6 (3) ◽  
pp. 36-39
Author(s):  
Rongqing Chen ◽  
Knut Möller
Keyword(s):  
Classical Method ◽  
Lung Imaging ◽  
Imaging Method ◽  
Reconstruction Method ◽  
Essential Information ◽  
Preliminary Results ◽  
Reconstruction Methods ◽  
Comparison Results ◽  
Index Evaluation ◽  
Inhomogeneity Index

AbstractPurpose: To evaluate a novel structural-functional DCT-based EIT lung imaging method against the classical EIT reconstruction. Method: Taken retrospectively from a former study, EIT data was evaluated using both reconstruction methods. For different phases of ventilation, EIT images are analyzed with respect to the global inhomogeneity (GI) index for comparison. Results: A significant less variant GI index was observed in the DCTbased method, compared to the index from classical method. Conclusion: The DCT-based method generates more accurate lung contour yet decreasing the essential information in the image which affects the GI index. These preliminary results must be consolidated with more patient data in different breathing states.

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