Density of Maxima Approach for Broken Bar Fault Diagnosis in Low Slip and Variable Load Conditions of Induction Motors

Deus, Danyelson Barros Bezerra de; Sobrinho, Carlos Alberto Nóbrega; Belo, Francisco Antônio; Brito, Alisson V.; Ramos, J. Galvão; Filho, Abel Cavalcante Lima

doi:10.1109/tim.2020.3003107

Cited by 16 publications

(4 citation statements)

References 29 publications

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“…The slip depends on the operation speed and motor load. As the mechanical load increases, the characteristic frequency of the BRB fault moves away from the fundamental frequency [22]. The slip frequency of the unloaded SCIM is minimal, and the twice slip frequencies under BRB faulty operation are close to the value of the supply frequency.…”

Section: Analysis Of Measured Stator Currentsmentioning

confidence: 91%

Analysis of a Three-Phase Induction Motor with a Double–Triple-Layer Stator Winding Configuration Operating with Broken Rotor Bar Faults

Muteba

2023

Machines

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This paper presents the performance analysis of a three-phase squirrel cage induction motor (SCIM) with a double–triple-layer (DTL) stator winding configuration operating with broken rotor bar (BRB) faults. The effects of BRB faults on the performance of specific parameters are analyzed under a steady-state regime. The SCIM is modeled using the two-dimensional finite element method (FEM) to study electromagnetic performance under healthy and BRB faulty conditions. To validate the finite element analysis (FEA) results, a prototype of an SCIM with a DTL stator winding configuration is tested for performance evaluation under healthy and BRB faulty conditions. The FEA and experimental (EXP) results of the SCIM with a DTL stator winding arrangement are compared with the results of the SCIM with a conventional double-layer (CDL) stator winding configuration. FEA and EXP results evidenced that the SCIM with a DTL stator winding configuration mitigates some of the adverse effects introduced by the BRB faults compared to the SCIM with a CDL stator winding of the exact specifications. Under loaded conditions, the SCIM with a DTL stator winding configuration reduced the magnitudes of the twice slip frequency sidebands caused by BRB faults from ±1.2 Hz for the SCIM with a CDL stator winding arrangement down to ±0.2 Hz and ±0.36 Hz when operating with 3BRB and 6BRB faults, respectively. The results also indicate that the SCIM with a DTL stator winding configuration has reduced the decibel sideband magnitude by 7.5 dB and 8 dB for unloaded and loaded conditions, respectively. This premise has positioned the SCIM with a DTL stator winding configuration as a strong candidate in applications where BRB faults are frequent, and the motor may be required to continue operating with a BRB fault until scheduled maintenance is in effect.

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Section: Analysis Of Measured Stator Currentsmentioning

confidence: 91%

Analysis of a Three-Phase Induction Motor with a Double–Triple-Layer Stator Winding Configuration Operating with Broken Rotor Bar Faults

Muteba

2023

Machines

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“…In this paper, FFT is used for BRB fault detection due to its high speed and ease of analyzing the FFT spectrum results to identify the dominant frequency of the BRB. Furthermore, FFT is widely applied in other articles [45,46] and provides the possibility to define an index for the detection of the severity of the fault and its type.…”

Section: Of 17mentioning

confidence: 99%

Mathematical Decomposition of Fault Signature using Multinomial Identity and Differentiating for Detection of Broken Rotor Bar in Induction Motor

Behnamnia¹,

Mardaneh²,

Jamshidpour³

2023

Preprint

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Fault detection at the early stage of development is of great importance in the maintenance of electric motors. In this regard, Motor Current Signature Analysis (MCSA) is cited in many articles to detect rotor bar fracture. The popularity of MCSA is due to its non-invasive and non-destructive nature, simplicity, and, compatibility with several signal processing tools. The vast variety of the signal processing tools which are commonly used for detecting the broken rotor bar fault is based on the Fast Fourier Transform (FFT) of the stator current signal and analysis of the produced Fourier spectrum; however, because of the small amplitude at the fault frequency relative to the main frequency amplitude, the former cannot be easily discriminated from the latter. Therefore, the peak at the fault frequency is hidden in the shadow of the main frequency component, hence the fault will not be detectable. As a solution to vanish the base frequency component, a method based on the Algebraic Identity of trinomial expansion is proposed in this paper which enables us to display the difference between the frequency of the fault signature and the base frequency. In this article, the fault of the broken rotor bars of the squirrel cage induction motor is revealed by the proposed method. In addition, a frequency weighting technique is presented to magnify the component at the fault related frequency compared to the lower frequencies. To validate the proposed methods, they are examined on the laboratory data obtained from three different operating conditions including the direct online start, the direct torque control, and the scalar control and the results show the ability of the proposed methods in fault detection of an induction motor.

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“…It constitutes an essential point of reliability and dependability of electrical systems. To identify the state of electrical machines, measurements are required, they can be based on vibration [4], acoustic waves [5], electromagnetism [6], stator current [7,8] or other, these measurements allow the extraction of engine characteristics.…”

Section: Introductionmentioning

confidence: 99%

Enhanced motor fault detection system based on a dual-signature image classification method using CNN

2023

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This paper proposes a new Motor Image Classification (MIC) approach based on a multi-signal conversion technique using Convolutional Neural Network (CNN). In this regard, two one-dimensional (1D) signals are combined and converted into a (2D) color image with motor information pixels. Initially, the vibration signal is converted into the frequency domain. Each point of this signal is firstly assigned a color according to its amplitude and then placed successively on a specific column to obtain a pixilated image. An outline is added to the image representing the internal motor temperature. Therefore, the vibratory and thermal situation of the engine is clearly represented in a Dual-Signature Image (DSI). Our system proves the efficiency of the color compared to grayscale images. It ensures fast and effective prevention, which results in a long service lifetime and maximum motor availability. The diagnostic success rate of our system is 99.93%.

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Density of Maxima Approach for Broken Bar Fault Diagnosis in Low Slip and Variable Load Conditions of Induction Motors

Cited by 16 publications

References 29 publications

Analysis of a Three-Phase Induction Motor with a Double–Triple-Layer Stator Winding Configuration Operating with Broken Rotor Bar Faults

Analysis of a Three-Phase Induction Motor with a Double–Triple-Layer Stator Winding Configuration Operating with Broken Rotor Bar Faults

Mathematical Decomposition of Fault Signature using Multinomial Identity and Differentiating for Detection of Broken Rotor Bar in Induction Motor

Enhanced motor fault detection system based on a dual-signature image classification method using CNN

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