Empirical Mode Decomposition of Motor Current Signatures for Centrifugal Pump Diagnostics

Alabied, Samir; Haba, Usama; Daraz, Alsadak; Gu, Fengshou; Ball, Andrew

doi:10.23919/iconac.2018.8749109

Cited by 10 publications

(9 citation statements)

References 17 publications

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“…In this work, the current space vector spectrum has been proved to be useful in improving the reliability of online detection of rotor faults immune to BPF interference. In Alabied et al, 23 empirical mode decomposition (EMD) method has been exploited as a feasible tool to mitigate the noise effect in nonlinear current signature. In Sun et al, 24 the performance comparison between diagnosis methods based on vibration and current analysis for a centrifugal pump has been carried out.…”

Section: Introductionmentioning

confidence: 99%

Operation diagnosis for centrifugal pumps using stator current-based indicators

Han

Yuan

Luo

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part C:

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Motor current signature analysis (MCSA) used in the diagnosis of centrifugal pumps has become a hot topic due to its non-intrusive and cost-effective nature. Yet, traditional current-based diagnosis methods show limitations as massive computation and power frequency interference. Moreover, most of them focus on the fault detection, fewer discuss the applications in operation evaluation. Therefore in this article, the hydro-mechanical-electric coupling effect that exists in the induction motor-centrifugal pump system is analyzed systematically. On this foundation, novel indicators that can reflect the harmonic distortion and noise proportion of stator current signals, and further indicate the hydraulic stability and operation status are proposed. Theoretical and experimental analysis support this paper, and results have demonstrated that our proposed indicators can indicate the operation change, identify the optimal operation region, and reflect the development of cavitation for centrifugal pumps. These indicators have the advantages of easy calculation and identification, therefore can be conveniently compared with accepted standards and enable immediate remedial actions to be implemented to ensure the stable operation.

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Section: Introductionmentioning

confidence: 99%

Operation diagnosis for centrifugal pumps using stator current-based indicators

Han

Yuan

Luo

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part C:

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“…For WT, an optimal mother wavelet selection for VS preprocessing is very important, otherwise the WT will suffer from an oscillation effect. Empirical mode decomposition (EMD) [ 16 , 17 , 18 ], an adaptive signal decomposition technique, can overcome the shortcomings of WT. Unfortunately, EMD has mode mixing and it suffers from extreme interpolation.…”

Section: Introductionmentioning

confidence: 99%

Multistage Centrifugal Pump Fault Diagnosis Using Informative Ratio Principal Component Analysis

Ahmad

Nguyen

Ahmad

et al. 2021

Sensors

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This study proposes a fault diagnosis method (FD) for multistage centrifugal pumps (MCP) using informative ratio principal component analysis (Ir-PCA). To overcome the interference and background noise in the vibration signatures (VS) of the centrifugal pump, the fault diagnosis method selects the fault-specific frequency band (FSFB) in the first step. Statistical features in time, frequency, and wavelet domains were extracted from the fault-specific frequency band. In the second step, all of the extracted features were combined into a single feature vector called a multi-domain feature pool (MDFP). The multi-domain feature pool results in a larger dimension; furthermore, not all of the features are best for representing the centrifugal pump condition and can affect the condition classification accuracy of the classifier. To obtain discriminant features with low dimensions, this paper introduces a novel informative ratio principal component analysis in the third step. The technique first assesses the feature informativeness towards the fault by calculating the informative ratio between the feature within the class scatteredness and between-class distance. To obtain a discriminant set of features with reduced dimensions, principal component analysis was applied to the features with a high informative ratio. The combination of informative ratio-based feature assessment and principal component analysis forms the novel informative ratio principal component analysis. The new set of discriminant features obtained from the novel technique are then provided to the K-nearest neighbor (K-NN) condition classifier for multistage centrifugal pump condition classification. The proposed method outperformed existing state-of-the-art methods in terms of fault classification accuracy.

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“…In this paper, tools and methods that can be used to perform machine inspections in a non-invasive manner are critically reviewed from the published literature. In the absence of a formal definition of NII in the existing literature [18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35], we have categorised non-destructive by non-invasive tools and methods in two distinct categories. Later, we describe the use of these tools and methods under each category in detail.…”

Section: Introductionmentioning

confidence: 99%

Non-Invasive Inspections: A Review on Methods and Tools

Alotaibi

Asli

Khan

2021

Sensors

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Non-Invasive Inspection (NII) has become a fundamental tool in modern industrial maintenance strategies. Remote and online inspection features keep operators fully aware of the health of industrial assets whilst saving money, lives, production and the environment. This paper conducted crucial research to identify suitable sensing techniques for machine health diagnosis in an NII manner, mainly to detect machine shaft misalignment and gearbox tooth damage for different types of machines, even those installed in a hostile environment, using literature on several sensing tools and techniques. The researched tools are critically reviewed based on the published literature. However, in the absence of a formal definition of NII in the existing literature, we have categorised NII tools and methods into two distinct categories. Later, we describe the use of these tools as contact-based, such as vibration, alternative current (AC), voltage and flux analysis, and non-contact-based, such as laser, imaging, acoustic, thermographic and radar, under each category in detail. The unaddressed issues and challenges are discussed at the end of the paper. The conclusions suggest that one cannot single out an NII technique or method to perform health diagnostics for every machine efficiently. There are limitations with all of the reviewed tools and methods, but good results possible if the machine operational requirements and maintenance needs are considered. It has been noted that the sensors based on radar principles are particularly effective when monitoring assets, but further comprehensive research is required to explore the full potential of these sensors in the context of the NII of machine health. Hence it was identified that the radar sensing technique has excellent features, although it has not been comprehensively employed in machine health diagnosis.

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Empirical Mode Decomposition of Motor Current Signatures for Centrifugal Pump Diagnostics

Cited by 10 publications

References 17 publications

Operation diagnosis for centrifugal pumps using stator current-based indicators

Operation diagnosis for centrifugal pumps using stator current-based indicators

Multistage Centrifugal Pump Fault Diagnosis Using Informative Ratio Principal Component Analysis

Non-Invasive Inspections: A Review on Methods and Tools

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