Asymmetrical Fault Detection in Induction Motors Through Elimination of Load Torque Oscillations Effects in the Slight Speed Variations and Steady-State Conditions

Bazghandi, Reza; Marzebali, Mohammad Hoseintabar; Abolghasemi, Vahid

doi:10.1109/jestie.2022.3204485

Cited by 8 publications

(2 citation statements)

References 36 publications

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“…After introducing the TOEO, its application is developed for the healthy and faulty stator current in IM. Higher order differential energy operators for a continuous-time signal 𝑦(𝑡) are defined as follows [31]:…”

Section: Third-order Energy Operator Of Current Signaturementioning

confidence: 99%

Enhanced Multi-Synchro-Squeezing Transform for Fault Diagnosis in Induction Machine Based on Third-Order Energy Operator of Stator Current Signature

Bazghandi,

Marzebali,

Abolghasemi

2024

IEEE Access

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In traditional motor current signature analysis (MCSA) approach, the spectral leakage of the fundamental supply frequency can obscure the characteristic fault component under low-load or no-load conditions. Furthermore, most time-frequency (TF) methods often have low resolution and are not qualified to produce a narrow band in the output. In this paper, we employ multi-synchro-squeezing transform (MSST) to show its effectiveness in fault detection of induction machines, for the first time. The key innovation of this work is merging MSST (due to its high time-frequency resolution) with the third-order energy operator (TOEO) (due to its high accuracy in fault detection). Specifically, TOEO is used to overcome the leakage effects of the supply frequency, through a demodulation approach for asymmetric fault detection along with MSST technique. The proposed method was evaluated for induction machine fault detection in both steadystate and transient conditions. Both analytical and experimental results confirm that the proposed method can excellently reveal the fault characteristic frequency in steady-state and transient mode, instead of the sideband frequencies.

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Section: Third-order Energy Operator Of Current Signaturementioning

confidence: 99%

Enhanced Multi-Synchro-Squeezing Transform for Fault Diagnosis in Induction Machine Based on Third-Order Energy Operator of Stator Current Signature

Bazghandi,

Marzebali,

Abolghasemi

2024

IEEE Access

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“…Many sensors can collect signals and data for condition monitoring of IMs and fault detection. These sensors can measure various parameters such as voltage [9] and current [10][11][12], stray flux [13,14], singular value decomposition of the stator current [15], load torque analysis [16], neural network-based detection [17], etc. Some of these methods are invasive and rarely noticed.…”

Section: Introductionmentioning

confidence: 99%

A Novel Mode Un-Mixing Approach in Variational Mode Decomposition for Fault Detection in Wound Rotor Induction Machines

et al. 2023

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Condition monitoring of induction machines (IMs) with the aim of increasing the machine’s lifetime, improving the efficiency and reducing the maintenance cost is necessary and inevitable. Among different types of methods presented for mechanical and electrical fault tracing in induction machines, stator current signature analysis has attracted great attention in recent decades. This popularity is mainly due to the non-invasive nature of this technique. A non-recursive method named variational mode decomposition (VMD) is used for the decomposition of any signal into several intrinsic mode functions (IMFs). This technique can be employed for detection of faulty components in a current signature. However, mode mixing of extracted IMFs makes the mechanical and electrical fault detection of IMs complicated, especially in the case where fault indices emerge close to the supply frequency. To achieve this, we rectify the signal of stator current prior to applying VMD. The main advantage of the presented approach is allowing the fault indices to be properly demodulated from the main frequency to avoid mode mixing phenomenon. The method shows that the dominant frequencies of the current signal can be isolated in each IMFs, appropriately. The proposed strategy is validated to detect the rotor asymmetric fault (RAF) in a wound rotor induction machine (WRIM), in both transient and steady-state conditions.

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Broken Bar Detection of Axial-Flux Induction Machines Through Advanced Transient Current Signature Analysis

Madariaga-Cifuentes,

Ruiz-Sarrio,

Antonino-Daviu

et al. 2024

2024 International Conference on Electrical Machines (ICEM)

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Asymmetrical Fault Detection in Induction Motors Through Elimination of Load Torque Oscillations Effects in the Slight Speed Variations and Steady-State Conditions

Cited by 8 publications

References 36 publications

Enhanced Multi-Synchro-Squeezing Transform for Fault Diagnosis in Induction Machine Based on Third-Order Energy Operator of Stator Current Signature

Enhanced Multi-Synchro-Squeezing Transform for Fault Diagnosis in Induction Machine Based on Third-Order Energy Operator of Stator Current Signature

A Novel Mode Un-Mixing Approach in Variational Mode Decomposition for Fault Detection in Wound Rotor Induction Machines

Broken Bar Detection of Axial-Flux Induction Machines Through Advanced Transient Current Signature Analysis

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