An Online Fault Diagnosis System for Induction Motors via Instantaneous Power Analysis

Irfan, Muhammad; Saad, Nordin; Ibrahim, Rosdiazli; Asirvadam, Vijanth S.; Magzoub, Muawia A.

doi:10.1080/10402004.2016.1190043

Cited by 18 publications

(6 citation statements)

References 33 publications

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“…If balls are positioned at an equal distance then the load will be equally transformed to all balls. The balls of the bearing rotates between race ways [1][2][3][4][5]. Thus, to maintain the uniform motion of the shaft and to distribute the shaft load equally among all balls, the cage plays an important role.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Bearing Faulty Cage using Non-Intrusive Condition Monitoring Techniques

Irfan¹,

Alwadie²,

Saad³

et al. 2024

RE&PQJ

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The cage is an important element of the bearing. The cage is used to support the bearing balls and it maintains the fix distance between rotating balls. The defected cage could create defects in the balls and race ways of the bearing. It could lead to premature failure of the bearing which causes machine down time, production loss and huge maintenance cost. Traditionally, periodic checks of the bearing health are performed in industry but they did not avoid the bearing cage failures. Thus, it is essential to develop some real-time health monitoring system to analyze the status of bearing cage. Recent research developments on the bearing fault diagnosis have that non-intrusive stator current and power analysis techniques are most economical and simple as compared to intrusive vibration analysis technique. However, a limited research has been conducted to check and confirm the effectivity of stator current and power analysis techniques for the diagnosis of cage faults. Thus, the aim of this paper is to analyze cage faults using non-intrusive stator current and power analysis. The comparison of both techniques have been performed experimentally and it has been concluded that power analysis is a most suitable technique to diagnose cage faults.

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Section: Introductionmentioning

confidence: 99%

Analysis of Bearing Faulty Cage using Non-Intrusive Condition Monitoring Techniques

Irfan¹,

Alwadie²,

Saad³

et al. 2024

RE&PQJ

Self Cite

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“…The machine failures cause disturbances on the production lines and eventually creates financial losses in the form of production loss and maintenance cost. Thus, the reliable of operation of the gears gains importance and various strategies are adopted in the industry to protect the gears from faults and to predict the failures through various condition monitoring strategies to avoid the emergency shutdowns of the production lines [6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

The Fault Detection of Gears of Electromechanical Power Transmission System using Frequency Domain Approach

Alwadie¹,

Muhammad²,

Saad³

2024

RE&PQJ

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Electric motors are widely used in the industry and convert electrical power to mechanical power. Gears are connected with the motor shaft for frictionless power transmission. The power transmission efficiency is dropped when the gear teeth is damaged. It causes huge financial loss. There are various commercially available condition monitoring tools for the preventive maintenance and condition monitoring of the gearing systems. However, such tools and techniques are intrusive and costly. This paper presents a non-intrusive approach for timely detection of gear damages and can be integrated to existing condition monitoring systems to save time and cost. The proposed method is based on the analysis of power spectra of the frequency amplitude plots. The amplitude difference at gear harmonics gives indication of the presence of the fault. The proposed technique has been tested and validated at 1400 rpm and 1370 rpm of the motor which is operating at 75 % load and full load.

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“…Another issue with vibration-based diagnostics is the high cost of accelerometers. Furthermore, some motors in the plant are located in places where access to the motor for accelerometer installation is nearly impossible [ 15 , 16 , 17 , 18 , 19 , 20 ]. Similarly, temperature analysis, noise analysis and flux analysis techniques are invasive and involve high costs for the system development [ 21 ].…”

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 Online Fault Diagnosis System for Induction Motors via Instantaneous Power Analysis

Cited by 18 publications

References 33 publications

Analysis of Bearing Faulty Cage using Non-Intrusive Condition Monitoring Techniques

Analysis of Bearing Faulty Cage using Non-Intrusive Condition Monitoring Techniques

The Fault Detection of Gears of Electromechanical Power Transmission System using Frequency Domain Approach

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

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