Fault Diagnosis of On-load Tap-changer Based on Vibration Signal

Wenquan, Huang; Peng, Changqing; Jin, Liang; Liu, Jiacheng; Cai, Yuqi

doi:10.1088/1757-899x/605/1/012005

Cited by 6 publications

(6 citation statements)

References 9 publications

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“…After the trend term is removed by the polynomial fitting data, the usable speed signal is obtained. This is the speed test principal process [1] .…”

Section: Pump Mechanical Vibration Test 21 Speed Test Principlementioning

confidence: 99%

Vibration Test Measures for Pump Fault Diagnosis

Shi¹,

Liu²

2021

JERA

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The vibration measuring standard for compound machinery utilized in modern industrial production will be employed for the application of detecting technologies. The vibration intensity can be obtained by selecting the detecting method to obtain the speed of mechanical vibration, and technicians can examine whether the vibrating machinery is in a proper functioning state based on the value of vibration intensity, allowing for thorough fault diagnosis. In order to provide useful diagnosis ideas for technicians, this study examines the measurement of mechanical vibration and investigates the calculating method of mechanical vibration intensity.

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“…After the trend term is removed by the polynomial fitting data, the usable speed signal is obtained. This is the speed test principal process [1] .…”

Section: Pump Mechanical Vibration Test 21 Speed Test Principlementioning

confidence: 99%

Vibration Test Measures for Pump Fault Diagnosis

Shi¹,

Liu²

2021

JERA

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“…In [15,16], the status of each OLTC tap position is analyzed to compare its waveform with a reference; Spearman's Rank Correlation Coefficient was applied to select the reference waveform. In [17], the condition of the tap changer is evaluated in three steps. In the first step, each vibro-acoustic signal is divided into two parts: preparation, which involves the motor running and driving the mechanical structure, and in-position, which encompasses the operation of the tap-changer.…”

Section: Introductionmentioning

confidence: 99%

Using Deep Learning to Detect Anomalies in On-Load Tap Changer Based on Vibro-Acoustic Signal Features

Dabaghi-Zarandi,

Behjat,

Gauvin

et al. 2024

Energies

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An On-Load Tap Changer (OLTC) that regulates transformer voltage is one of the most important and strategic components of a transformer. Detecting faults in this component at early stages is, therefore, crucial to prevent transformer outages. In recent years, Hydro Quebec initiated a project to monitor the OLTC’s condition in power transformers using vibro-acoustic signals. A data acquisition system has been installed on real OLTCs, which has been continuously measuring their generated vibration signal envelopes over the past few years. In this work, the multivariate deep autoencoder, a reconstruction-based method for unsupervised anomaly detection, is employed to analyze the vibration signal envelopes generated by the OLTC and detect abnormal behaviors. The model is trained using a dataset obtained from the normal operating conditions of the transformer to learn patterns. Subsequently, kernel density estimation (KDE), a nonparametric method, is used to fit the reconstruction errors (regarding normal data) obtained from the trained model and to calculate the anomaly scores, along with the static threshold. Finally, anomalies are detected using a deep autoencoder, KDE, and a dynamic threshold. It should be noted that the input variables responsible for anomalies are also identified based on the value of the reconstruction error and standard deviation. The proposed method is applied to six different real datasets to detect anomalies using two distinct approaches: individually on each dataset and by comparing all six datasets. The results indicate that the proposed method can detect anomalies at an early stage. Also, three alarms, including ignorable anomalies, long-term changes, and significant alterations, were introduced to quantify the OLTC’s condition.

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“…The authors of references [ 15 , 16 ] presented a method in which a base waveform is selected by Spearman’s Rank correlation coefficient, and the condition of each OLTC tap position is evaluated by comparing its waveform with the base waveform. In reference [ 17 ], all vibro-acoustic signals of the OLTC are split into two parts. Each part is decomposed into 16 sub-components using wavelet packet transform, and the energy entropy of each sub-component is computed to achieve the condition assessment.…”

Section: Introductionmentioning

confidence: 99%

Power Transformers OLTC Condition Monitoring Based on Feature Extraction from Vibro-Acoustic Signals: Main Peaks and Euclidean Distance

Dabaghi-Zarandi

Behjat

Gauvin

et al. 2023

Sensors

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The detection of On-Load Tap-Changer (OLTC) faults at an early stage plays a significant role in the maintenance of power transformers, which is the most strategic component of the power network substations. Among the OLTC fault detection methods, vibro-acoustic signal analysis is known as a performant approach with the ability to detect many faults of different types. Extracting the characteristic features from the measured vibro-acoustic signal envelopes is a promising approach to precisely diagnose OLTC faults. The present research work is focused on developing a methodology to detect, locate, and track changes in on-line monitored vibro-acoustic signal envelopes based on the main peaks extraction and Euclidean distance analysis. OLTC monitoring systems have been installed on power transformers in services which allowed the recording of a rich dataset of vibro-acoustic signal envelopes in real time. The proposed approach was applied on six different datasets and a detailed analysis is reported. The results demonstrate the capability of the proposed approach in recognizing, following, and localizing the faults that cause changes in the vibro-acoustic signal envelopes over time.

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Fault Diagnosis of On-load Tap-changer Based on Vibration Signal

Cited by 6 publications

References 9 publications

Vibration Test Measures for Pump Fault Diagnosis

Vibration Test Measures for Pump Fault Diagnosis

Using Deep Learning to Detect Anomalies in On-Load Tap Changer Based on Vibro-Acoustic Signal Features

Power Transformers OLTC Condition Monitoring Based on Feature Extraction from Vibro-Acoustic Signals: Main Peaks and Euclidean Distance

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