Diagnostic technique for analysing the internal faults within power transformers based on sweep frequency response using adjusted R-square methodology

Gouda, Osama E.; El-Hoshy, Salah H.

doi:10.1049/iet-smt.2020.0048

Cited by 11 publications

(3 citation statements)

References 38 publications

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“…At the same time, other factors cause the remaining 1.13%. The R square value of 0.75, 0.50, and 0.25 belongs to the strong, moderate, and weak categories, respectively (Gouda et al, 2020). The results found that non-machine sound is a strong category.…”

Section: Effect Of Non-machine Noise On Hm Bearing Accuracymentioning

confidence: 83%

Sound-Based Health Monitoring of Induction Motor Considering Load and Measuring Distance Variations Using Frequency Calculation and Statistical Analysis

Karyatanti¹,

Harahab²,

Wibowo³

et al. 2023

JST

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Bearing is an important part of the induction motor, whose function is to help the rotor spin. It contributes the highest percentage of damage compared to other parts. When operated in this condition, it causes overheating, imbalance in the rotation of the rotor shaft, sparks, and noise pollution to the environment. A bearing monitoring system must be implemented and developed to avoid further damage. Furthermore, a non-invasive technique through sound signals was developed in this study. A sound signal is easy to overlap with the noise from other sources. Environmental noise is unavoidable during data collection, affecting health monitoring accuracy (HM). Therefore, this study aims to develop an HM method for sound-based induction motors based on measurement differences, load variation, frequency calculations, and statistics. The distance measured was used as an independent variable of the non-machine noise. The load variations were also applied as required, and the operation of the motor varies according to users’ needs. In an effort to prevent negative environmental impacts, noise monitoring was carried out from the motor operation, and the results showed an HM of accuracy of 83.09%. The best distance for performing HM conditions is 100 cm and 83.59 dB(A). The noise value does not exceed the industrial worker threshold. Therefore, close surveillance of the motor’s condition tends to be conducted with or without a load. It is because the load variation does not affect the accuracy of health monitoring.

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Section: Effect Of Non-machine Noise On Hm Bearing Accuracymentioning

confidence: 83%

Sound-Based Health Monitoring of Induction Motor Considering Load and Measuring Distance Variations Using Frequency Calculation and Statistical Analysis

Karyatanti¹,

Harahab²,

Wibowo³

et al. 2023

JST

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“…To evaluate the performances of above-mentioned PGPMs more precisely, Mean Absolute Error, Root of Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE) of each PGPM were evaluated and compared. Moreover, a R-square coefficient [26] is also introduced into the paper to calculate the fitting accuracy, which can be expressed by…”

Section: The Quantitative Comparison Of Resultsmentioning

confidence: 99%

An Improved Generating Energy Prediction Method Based on Bi-LSTM and Attention Mechanism

Zhang

et al. 2022

Electronics

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The energy generated by a photovoltaic power station is affected by environmental factors, and the prediction of the generating energy would be helpful for power grid scheduling. Recently, many power generation prediction models (PGPM) based on machine learning have been proposed, but few existing methods use the attention mechanism to improve the prediction accuracy of generating energy. In the paper, a PGPM based on the Bi-LSTM model and attention mechanism was proposed. Firstly, the environmental factors with respect to the generating energy were selected through the Pearson coefficient, and then the principle and implementation of the proposed PGPM were detailed. Finally, the performance of the proposed PGPM was evaluated through an actual data set collected from a photovoltaic power station in Suzhou, China. The experimental results showed that the prediction error of proposed PGPM was only 8.6 kWh, and the fitting accuracy was more than 0.99, which is better than existing methods.

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“…The coefficient of determination (R 2 ) describes the variation on the dependent variable. R 2 values (Gouda & El-Hoshy, 2020;Jain et al, 2021) indicated the limitations of the dependent variable (Liu & Wang, 2021;Outram et al, 2021). The value ~ one  independent variables provide all information on the dependent variable prediction (Liu & Wang, 2021;Taylor et al, 2021).…”

Section: Resultsmentioning

confidence: 99%

Contraction of Capital Investment in Retail Trade Sub-Sector Companies on the Indonesia Stock Exchange

Andy

Hengky

2021

BER

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This study aims to compare the investment contraction in the retail trade sub-sector on the Indonesia Stock Exchange (IDX). This study examines the effect of profitability as measured by ROE on capital structure as measured by DER in sub-sector companies in IDX during 2016-2020. This type of research uses verification research with explanatory survey method and sample method of a purposive-sampling in which there are 18 samples of retail company sub-sectors. Methods of data analysis using panel data regression with the results: Profitability has a negative and significant effect on capital structure.

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Diagnostic technique for analysing the internal faults within power transformers based on sweep frequency response using adjusted R-square methodology

Cited by 11 publications

References 38 publications

Sound-Based Health Monitoring of Induction Motor Considering Load and Measuring Distance Variations Using Frequency Calculation and Statistical Analysis

Sound-Based Health Monitoring of Induction Motor Considering Load and Measuring Distance Variations Using Frequency Calculation and Statistical Analysis

An Improved Generating Energy Prediction Method Based on Bi-LSTM and Attention Mechanism

Contraction of Capital Investment in Retail Trade Sub-Sector Companies on the Indonesia Stock Exchange

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