The Decision making System for Condition Monitoring of Induction Motors Based on Vector Control Model

Alwadie, Abdullah

doi:10.3390/machines5040027

Cited by 9 publications

(8 citation statements)

References 52 publications

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“…Although their study has overcome the shortcomings of MCSA, the scope of the study was limited to only an induction of motor bearing faults. Another attempt was made by the authors of [28] to diagnose bearing faults using the frequency spectrum of Park's transformation axis. The drawback of their study was the extensive and lengthy calculations for the frequencies of the faulty bearings.…”

Section: Results and Analysismentioning

confidence: 99%

“…Park's vector analysis of the motor current has been used by some researchers to analyze the bearing, eccentricity, and rotor faults [25][26][27][28]. In their work, the three-phase current has been converted to a two-phase current, and the frequency analysis of the two-phase current spectrum gives information about the machine health.…”

Section: Appl Sci 2019 9 X For Peer Review 2 Of 15mentioning

confidence: 99%

“…In their work, the three-phase current has been converted to a two-phase current, and the frequency analysis of the two-phase current spectrum gives information about the machine health. Although the frequency spectrum of the two-phase current gives better information about the machine faults, the intensive mathematical computation is a major limitation [28]. Furthermore, the capability of the two-phase analysis technique to diagnose centrifugal pump faults has never been investigated in previously published research.…”

Section: Appl Sci 2019 9 X For Peer Review 2 Of 15mentioning

confidence: 99%

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Design of a Novel Electric Diagnostic Technique for Fault Analysis of Centrifugal Pumps

2019

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Centrifugal pumps are the fundamental components of most industries. They are used in almost every industry to transfer liquid through pipes. The breakdown of a pump causes heavy production losses, and hence, the development of an economical and user-friendly condition monitoring system is vital in order to estimate the health of a pump in a timely manner, and to avoid an unscheduled breakdown. The intrusive condition monitoring techniques (such as vibration analysis and acoustic emission) developed for the fault diagnosis of pumps utilize expensive vibration sensors, and these sensors need to be installed on the pump body for data collection. Non-intrusive techniques (such as motor current analysis) have been proven to be economical, but have limited capabilities for diagnosing the incipient faults in pumps operating in a noisy industrial environment. The electric diagnostic technique (EDT) proposed in this paper does not require the purchase of extra sensors, and instead utilizes the existing sensors, which are usually installed on the machines, to measure and display the motor line current and voltage. The EDT has been developed in the Laboratory Virtual Instrument Engineering Workbench (LabVIEW) so as to measure the three-phase line current, and then transform it into two-phase d–q currents. These d–q currents are plotted as patterns, and the statistical features of these patterns are used to segregate the centrifugal pump fault types. Detailed experiments and evaluations have been performed in order to check the viability of the developed EDT technique.

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Section: Results and Analysismentioning

confidence: 99%

Section: Appl Sci 2019 9 X For Peer Review 2 Of 15mentioning

confidence: 99%

Section: Appl Sci 2019 9 X For Peer Review 2 Of 15mentioning

confidence: 99%

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Design of a Novel Electric Diagnostic Technique for Fault Analysis of Centrifugal Pumps

2019

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“…In recent years, bearing monitoring has received considerable attention due to the criticality of bearings faults [22,[45][46][47][48][49][50]. In particular, some works proposed in the literature have already modeled the degradation of bearings as a hidden process.…”

Section: Case Studymentioning

confidence: 99%

Homogeneous Continuous-Time, Finite-State Hidden Semi-Markov Modeling for Enhancing Empirical Classification System Diagnostics of Industrial Components

et al. 2018

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This work presents a method to improve the diagnostic performance of empirical classification system (ECS), which is used to estimate the degradation state of components based on measured signals. The ECS is embedded in a homogenous continuous-time, finite-state semiMarkov model (HCTFSSMM), which adjusts diagnoses based on the past history of components. The combination gives rise to a homogeneous continuous-time finite-state hidden semi-Markov model (HCTFSHSMM). In an application involving the degradation of bearings in automotive machines, the proposed method is shown to be superior in classification performance compared to the single-stage ECS.

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“…Early fault detection methods relied solely on threshold settings [4], but produced limited success with a high false positive detection rate [5]. A thresholding method is unable to foresee a potential fault developing, unless the threshold is set unnecessarily lower than optimal.…”

Section: Introductionmentioning

confidence: 99%

Railway Point-Operating Machine Fault Detection Using Unlabeled Signaling Sensor Data

Mistry

Lane

Allen

2020

Sensors

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In this study, we propose a methodology for the identification of potential fault occurrences of railway point-operating machines, using unlabeled signal sensor data. Data supplied by Network Rail, UK, is processed using a fast Fourier transform signal processing approach, coupled with the mean and max current levels to identify potential faults in point-operating machines. The method developed can dynamically adapt to the behavioral characteristics of individual point-operating machines, thereby providing bespoke condition monitoring capabilities in situ and in real time. The work described in this paper is not unique to railway point-operating machines, rather the data pre-processing and methodology is readily applicable to any motorized device fitted with current sensing capabilities. The novelty of our approach is that it does not require pre-labelled data with historical fault occurrences and therefore closely resembles problems of the real world, with application for smart city infrastructure. Lastly, we demonstrate the problems faced with handling such data and the capability of our methodology to dynamically adapt to diverse data presentations.

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The Decision making System for Condition Monitoring of Induction Motors Based on Vector Control Model

Cited by 9 publications

References 52 publications

Design of a Novel Electric Diagnostic Technique for Fault Analysis of Centrifugal Pumps

Design of a Novel Electric Diagnostic Technique for Fault Analysis of Centrifugal Pumps

Homogeneous Continuous-Time, Finite-State Hidden Semi-Markov Modeling for Enhancing Empirical Classification System Diagnostics of Industrial Components

Railway Point-Operating Machine Fault Detection Using Unlabeled Signaling Sensor Data

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