An operating condition information-guided iterative variational mode decomposition method based on Mahalanobis distance criterion for surge characteristic frequency extraction of the centrifugal compressor

Hou, Yaochun; Wu, Peng; Wu, Dazhuan

doi:10.1016/j.ymssp.2022.109836

Cited by 16 publications

(3 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…From each scale, a rotating machine health-sensitive indicator is calculated using the Wasserstein distance. To harness fault-related non-stationary variations in the VS for CP health diagnosis, TFD techniques such as WPT, variational mode decomposition (VMD), and empirical mode decomposition (EMD) can be employed [21][22][23]. Tiwari et al [24] identified the health conditions of a CP using WPT and SVM.…”

Section: Related Research Studiesmentioning

confidence: 99%

A Technique for Centrifugal Pump Fault Detection and Identification Based on a Novel Fault-Specific Mann–Whitney Test

Ahmad,

Kim,

Kim

2023

Sensors

View full text Add to dashboard Cite

This work presents a technique for fault detection and identification in centrifugal pumps (CPs) using a novel fault-specific Mann–Whitney test (FSU Test) and K-nearest neighbor (KNN) classification algorithm. Traditional fault indicators, such as the mean, peak, root mean square, and impulse factor, lack sensitivity in detecting incipient faults. Furthermore, for defect identification, supervised models rely on pre-existing knowledge about pump defects for training purposes. To address these concerns, a new centrifugal pump fault indicator (CPFI) that does not rely on previous knowledge is developed based on a novel fault-specific Mann–Whitney test. The new fault indicator is obtained by decomposing the vibration signature (VS) of the centrifugal pump hierarchically into its respective time-frequency representation using the wavelet packet transform (WPT) in the first step. The node containing the fault-specific frequency band is selected, and the Mann–Whitney test statistic is calculated from it. The combination of hierarchical decomposition of the vibration signal for fault-specific frequency band selection and the Mann–Whitney test form the new fault-specific Mann–Whitney test. The test output statistic yields the centrifugal pump fault indicator, which shows sensitivity toward the health condition of the centrifugal pump. This indicator changes according to the working conditions of the centrifugal pump. To further enhance fault detection, a new effect ratio (ER) is introduced. The KNN algorithm is employed to classify the fault type, resulting in promising improvements in fault classification accuracy, particularly under variable operating conditions.

show abstract

Section: Related Research Studiesmentioning

confidence: 99%

A Technique for Centrifugal Pump Fault Detection and Identification Based on a Novel Fault-Specific Mann–Whitney Test

Ahmad,

Kim,

Kim

2023

Sensors

View full text Add to dashboard Cite

show abstract

“…In addition, the VMD method also adds a Wiener filter to the mode updating process, so it has good noise robustness [34]. Thanks to these advantages, VMD has become a research hotspot in the field of mechanical fault diagnosis [35,36]. However, VMD needs to preset the key parameters of decomposition, which often leads to over-decomposition and under-decomposition problems.…”

Section: Introductionmentioning

confidence: 99%

Sparse random similarity feature decomposition and its application in gear fault diagnosis

Liu¹,

Cheng²,

Hu³

et al. 2023

Meas. Sci. Technol.

View full text Add to dashboard Cite

As a new signal decomposition method, sparse random mode decomposition (SRMD) does not depend on signal sampling process and has good anti-mode aliasing performance. However, SRMD needs to preset decomposition parameters and cannot perform accurate decomposition for strong noise interference signal. Thus, this paper proposes a sparse random similarity feature decomposition (SRSFD) method to overcome the problems of SRMD. Firstly, SRSFD utilizes the windowed sinusoidal function to randomly generate time-frequency features. Then, by solving sparse optimization problem, the sparse random feature approximation of the input signal can be obtained, and its corresponding time-frequency features can be applied to reconstruct the initial signal components. Finally, the initial signal components are regrouped by using periodic similarity to obtain the final components. The analysis results of simulation and actual gear fault signals show that SRSFD can effectively achieve adaptive signal decomposition, and has better decomposition performance and noise robustness compared with existing methods.

show abstract

“…However, VMD also has drawbacks, such as non-adaptability. To improve the performance of VMD [12,13], the iterative VMD (IVMD) method was proposed by Hou to overcome the under-decomposition or overdecomposition [14]. The adaptive VMD (AVMD) method was proposed by Gu based on gray wolf optimization algorithm and applied it to early bearing fault diagnosis [15].…”

Section: Introductionmentioning

confidence: 99%

Empirical Ramanujan decomposition and iterative envelope spectrum for fault diagnosis

Cheng

Yang

et al. 2023

Meas. Sci. Technol.

View full text Add to dashboard Cite

Ramanujan Fourier mode decomposition (RFMD) obtains components by scanning from low frequency to high frequency, which will cause too many components, and then the fault information in mode components is incomplete. Based on this, the empirical Ramanujan decomposition (ERD) method is proposed in this paper. Firstly, ERD uses the optimized lowest minima technique to segment the spectrum and determine the segmentation boundary and the number of components. Subsequently, ERD constructs the filter banks for filtering and retains the spectral components corresponding to the main frequency band. Finally, the time domain components are recovered by the inverse Ramanujan Fourier transform. To further improve the capability of envelope spectrum (ES), an iterative envelope spectrum (IES) method is proposed. IES enhances the periodic components through iterative envelope to make the fault feature more conspicuous. The analysis results of simulation and experimental signals show that the ERD and IES can extract fault features effectively.

show abstract

An operating condition information-guided iterative variational mode decomposition method based on Mahalanobis distance criterion for surge characteristic frequency extraction of the centrifugal compressor

Cited by 16 publications

References 52 publications

A Technique for Centrifugal Pump Fault Detection and Identification Based on a Novel Fault-Specific Mann–Whitney Test

A Technique for Centrifugal Pump Fault Detection and Identification Based on a Novel Fault-Specific Mann–Whitney Test

Sparse random similarity feature decomposition and its application in gear fault diagnosis

Empirical Ramanujan decomposition and iterative envelope spectrum for fault diagnosis

Contact Info

Product

Resources

About