Winding Mechanical Fault Diagnosis Technique of Power Transformer Based on Time-Frequency Vibration Analysis

Zhan, Cao; Ji, Shengchang; Liu, Yong; Zhu, Lingyu; Shi, Yuhang; Ren, Fuqiang

doi:10.1109/cmd.2018.8535963

Cited by 6 publications

(3 citation statements)

References 12 publications

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“…Vibration is a common phenomenon present in various mechanical systems and structures, ranging from rotating machinery like motors, pumps, and turbines to bridges, buildings, and vehicles. When a mechanical system operates, it generates vibrations that can be caused by factors such as imbalances, misalignments, wear, resonance, structural weaknesses, or other mechanical faults [26][27][28][29][30][31][32][33][34][35][36][37][38].…”

Section: -Introductionmentioning

confidence: 99%

“…It involves the measurement, analysis, and interpretation of vibration signals to identify potential issues, such as faults, anomalies, or mechanical problems .Vibration is a common phenomenon present in various mechanical systems and structures, ranging from rotating machinery like motors, pumps, and turbines to bridges, buildings, and vehicles. When a mechanical system operates, it generates vibrations that can be caused by factors such as imbalances, misalignments, wear, resonance, structural weaknesses, or other mechanical faults [26][27][28][29][30][31][32][33][34][35][36][37][38].Vibration analysis utilizes specialized sensors, such as accelerometers, to capture the vibrations induced by systems or structures. These sensors measure the acceleration, velocity, or displacement of the vibrating component, converting the mechanical vibrations into electrical signals [39][40][41][42][43][44][45][46][47][48][49][50][51][52].Once the vibration signals are obtained, they are analyzed using various techniques and tools, including time-domain analysis, frequency-domain analysis, statistical analysis, wavelet analysis, and advanced signal processing algorithms .…”

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confidence: 99%

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Application of vibration analysis for the diagnosis of rotating machines

Mohamedi

2023

Preprint

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By examining the RPM profile, analysts can identify any deviations or anomalies in the vibration patterns at different speeds. This information can help identify potential faults or imbalances within the rotating machinery. For example, unbalanced rotors or misalignment issues may manifest as increased vibration amplitudes at specific speeds. With a comprehensive understanding of the RPM profile, analysts can make informed decisions regarding maintenance and repairs. By identifying the specific speed ranges where vibrations are problematic, they can schedule maintenance activities accordingly. This proactive approach can help prevent unexpected breakdowns and costly repairs.

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Section: -Introductionmentioning

confidence: 99%

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confidence: 99%

Application of vibration analysis for the diagnosis of rotating machines

Mohamedi

2023

Preprint

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“…When the transformer is running under abnormal conditions, its vibration signal contains abundant fault characteristic information, and due to current fluctuations and changes in the leakage magnetic field, the frequency components in the vibration signal will change accordingly in the time domain. Expressed as feature information in the time-frequency domain [9,10]. Theories and experiments prove the feasibility of using vibration characteristic information to judge the health status of transformer winding [11,12].…”

Section: Introductionmentioning

confidence: 99%

Application of Improved Symplectic Geometry Mode Decomposition Algorithm in Evaluation System of Transformer Winding Short‐Circuit Withstand Ability

Wang

Guo

2021

IEEJ Transactions Elec Engng

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During the operation of the power transformer, the fault location often occurs in the winding, and the fault phenomenon caused by insufficient short-circuit withstand ability of the winding is particularly prominent. Based on this problem, this article proposes an improved symplectic geometry mode decomposition (ISGMD) algorithm to evaluate the short-circuit withstand ability of winding. The realization method is to use the algorithm to perform time-frequency decomposition of the vibration signal of the transformer, calculate time-domain eigenvalues of the symplectic geometry components to constitute the eigenvector, utilize principal component analysis to reduce dimensionality of the data. Finally, apply the obtained data to train and test the extreme learning machine. The correctness of the algorithm is analyzed by simulating vibration signals. At last, the experiment is designed and the evaluation standard is proposed, and the practicability of the intelligent evaluation model based on the method is verified.

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Review of Vibration-Based Structural Health Monitoring Using Deep Learning

2020

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With the rapid progress in the deep learning technology, it is being used for vibration-based structural health monitoring. When the vibration is used for extracting features for system diagnosis, it is important to correlate the measured signal to the current status of the structure. The measured vibration responses show large deviation in spectral and transient characteristics for systems to be monitored. Consequently, the diagnosis using vibration requires complete understanding of the extracted features to discard the influence of surrounding environments or unnecessary variations. The deep-learning-based algorithms are expected to find increasing application in these complex problems due to their flexibility and robustness. This review provides a summary of studies applying machine learning algorithms for fault monitoring. The vibration factors were used to categorize the studies. A brief interpretation of deep neural networks is provided to guide further applications in the structural vibration analysis.

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Winding Mechanical Fault Diagnosis Technique of Power Transformer Based on Time-Frequency Vibration Analysis

Cited by 6 publications

References 12 publications

Application of vibration analysis for the diagnosis of rotating machines

Application of vibration analysis for the diagnosis of rotating machines

Application of Improved Symplectic Geometry Mode Decomposition Algorithm in Evaluation System of Transformer Winding Short‐Circuit Withstand Ability

Review of Vibration-Based Structural Health Monitoring Using Deep Learning

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