An Assessment on the Non-Invasive Methods for Condition Monitoring of Induction Motors

Irfan, Muhammad; Saad, Mohamad Naufal Mohamad; Ibrahim, Rosdiazli; Asirvadam, Vijanth S.; Alwadie, Abdullah; Sheikh, Muhammad Aman

doi:10.5772/67917

Cited by 19 publications

(10 citation statements)

References 139 publications

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“…These harmonic frequency models are available only for bearing defects, and models for impeller faults and pipe blockages do not exist. Thus, the MCSA technique cannot diagnose such faults [19][20][21]. The instant power technique has been suggested as an alternative non-invasive approach to MCSA for diagnosing bearing faults in an induction motor [22].…”

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

confidence: 99%

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

confidence: 99%

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

2019

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“…The most advanced and prospective methods lie in the group of signature analysis which are non-invasive [13] [11].…”

Section: Invasivementioning

confidence: 99%

Low Cost Data Acquisition System for Condition Assessment of Electric Motors

Gorbounov¹,

Dzhikov²

2018

International Advanced Research Journal in Science, Engineering

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The requirements for the effective control, safe and reliable operation of electrical motors and drives are constantly growing. Therefore an accepted maintenance strategy for the detection of nascent faults and for avoiding unexpected failures is the condition monitoring of their health status. This allows to perform preventive diagnostics and a planned repair instead of emergency one. This paper represents an ongoing research on elaborating a low cost data acquisition system for condition assessment of electric motors based on the typical profile of its current, voltage or vibration. This approach is typically non-invasive and is known as a signature analysis. Some typical fault conditions are systematized in the paper and some perspective methods for monitoring and diagnosis of faults in electric motors are discussed. An approach towards building such a system using low cost hardware and open source software is proposed.

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“…The bearing faults are the cause of 44% of motor breakdowns in the industry [ 11 ] and, for this reason, the focus of this paper is on the diagnostics of bearing failures. Bearings are designed to operate for long-running hours; however, they might fail prematurely, mainly due to dirt, contamination, excessive loading, misalignment, corrosion and lack of lubrication [ 12 ]. The most common and frequent types of bearing fault reported in the literature are dents, fretting, spalling, scratches, improper fits and holes in the raceways [ 11 , 12 , 13 , 14 , 15 ].…”

Section: Introductionmentioning

confidence: 99%

A Novel Feature Extraction and Fault Detection Technique for the Intelligent Fault Identification of Water Pump Bearings

Irfan

Alwadie

Głowacz

et al. 2021

Sensors

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The reliable and cost-effective condition monitoring of the bearings installed in water pumps is a real challenge in the industry. This paper presents a novel strong feature selection and extraction algorithm (SFSEA) to extract fault-related features from the instantaneous power spectrum (IPS). The three features extracted from the IPS using the SFSEA are fed to an extreme gradient boosting (XBG) classifier to reliably detect and classify the minor bearing faults. The experiments performed on a lab-scale test setup demonstrated classification accuracy up to 100%, which is better than the previously reported fault classification accuracies and indicates the effectiveness of the proposed method.

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An Assessment on the Non-Invasive Methods for Condition Monitoring of Induction Motors

Cited by 19 publications

References 139 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

Low Cost Data Acquisition System for Condition Assessment of Electric Motors

A Novel Feature Extraction and Fault Detection Technique for the Intelligent Fault Identification of Water Pump Bearings

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