Broken Bar Diagnosis for Squirrel Cage Induction Motors Using Frequency Analysis Based on MCSA and Continuous Wavelet Transform

Granda, Danilo; Aguilar, Wilbert G.; Arcos-Avilés, Diego; Sotomayor, Danny

doi:10.3390/mca22020030

Cited by 12 publications

(2 citation statements)

References 50 publications

(96 reference statements)

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“…The importance of early detection of fault locations and time in electric generators has caught the researchers' attention because it prevents the spread of damage and increases generator life [7]− [11]. Wavelet transform (WT) is a technique of signal analysis based on the use of region windows of variable size.…”

Section: Introductionmentioning

confidence: 99%

Novel strategy for fault e-diagnosis of wind energy conversion systems using wavelet analysis based on Rt-Lab and Arduino

Cheriet¹,

Hazzab²,

Bekri³

et al. 2023

IJPEDS

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The diagnosis of wind energy conversion systems (WECS) turns out to be necessary because of their relatively high cost of operation and maintenance. Wind turbines are hard-to-access structures, and they are often located in remote areas. Therefore, a remote diagnosis (e-diagnosis) is required. This paper proposes an alternative approach for the e-diagnosis of a WECS based on the discrete wavelet transform (DWT) and frequency analysis of the aero generator stator currents. To validate this approach, real-time hardware in the loop (HIL) is used to simulate in real-time the mathematical model of the induction generator on the OPAL-RT OP5600 platform to generate the stator currents and the rotor speed. The DWT is applied to the current signal, to generate the DWT signal, which has a huge number of points that are not supported for direct transmission by the Arduino Mega RobotDyn because of its limited sample time. The absolute values of the DWT peak points (MDWT) are sent as point’s packages form to the diagnosis station via the ESP8266 integrated Wi-Fi board of the Arduino Mega RobotDyn to monitor the SCIG states and determine the number of broken bars.

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Section: Introductionmentioning

confidence: 99%

Novel strategy for fault e-diagnosis of wind energy conversion systems using wavelet analysis based on Rt-Lab and Arduino

Cheriet¹,

Hazzab²,

Bekri³

et al. 2023

IJPEDS

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show abstract

“…Among all the electric machines used in industrial facilities, induction motors (IMs) are the most widely spread since their ability to transform electrical energy into mechanical energy make them essential for many industrial processes [1]. Additionally, their reliability and robustness results in a low cost and effort related with their maintenance [2,3].…”

Section: Introductionmentioning

confidence: 99%

Fundamental Frequency Suppression for the Detection of Broken Bar in Induction Motors at Low Slip and Frequency

et al. 2020

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Broken rotor bar (BRB) is one of the most common failures in induction motors (IMs) these days; however, its identification is complicated since the frequencies associated with the fault condition appear near the fundamental frequency component (FFC). This situation gets worse when the IM slip or the operation frequency is low. In these circumstances, the common techniques for condition monitoring may experience troubles in the identification of a faulty condition. By suppressing the FFC, the fault detection is enhanced, allowing the identification of BRB even at low slip conditions. The main contribution of this work consists of the development of a preprocessing technique that estimates the FFC from an optimization point of view. This way, it is possible to remove a single frequency component instead of removing a complete frequency band from the current signals of an IM. Experimentation is performed on an IM operating at two different frequencies and at three different load levels. The proposed methodology is compared with two different approaches and the results show that the use of the proposed methodology allows to enhance the performance delivered by the common methodologies for the detection of BRB in steady state.

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A Review of Fault Diagnosis Methods for Marine Electric Propulsion System

Deng

Zou

et al. 2022

Proceedings of IncoME-VI and TEPEN 2021

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show abstract

Broken Bar Diagnosis for Squirrel Cage Induction Motors Using Frequency Analysis Based on MCSA and Continuous Wavelet Transform

Cited by 12 publications

References 50 publications

Novel strategy for fault e-diagnosis of wind energy conversion systems using wavelet analysis based on Rt-Lab and Arduino

Novel strategy for fault e-diagnosis of wind energy conversion systems using wavelet analysis based on Rt-Lab and Arduino

Fundamental Frequency Suppression for the Detection of Broken Bar in Induction Motors at Low Slip and Frequency

A Review of Fault Diagnosis Methods for Marine Electric Propulsion System

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