Using logistic regression model to construct insulator spark detection system

碩士 === 國立高雄應用科技大學 === 電子工程系碩士班 === 101 === Purpose: In this study, we constructed an insulator spark detection system, which integrated visual image monitoring devices and an analysis system to reduce the complexity of the insulator spark detection system. Materials and Methods: The image of an insu...

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Main Authors: Wei-Hsiang Huang, 黃暐翔
Other Authors: Tsair-Fwu Lee
Format: Others
Language:zh-TW
Published: 2013
Online Access:http://ndltd.ncl.edu.tw/handle/30075912103453204113
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spelling ndltd-TW-101KUAS03930132015-10-13T22:18:22Z http://ndltd.ncl.edu.tw/handle/30075912103453204113 Using logistic regression model to construct insulator spark detection system 應用邏輯斯迴歸模型建構絕緣礙子火花偵測系統 Wei-Hsiang Huang 黃暐翔 碩士 國立高雄應用科技大學 電子工程系碩士班 101 Purpose: In this study, we constructed an insulator spark detection system, which integrated visual image monitoring devices and an analysis system to reduce the complexity of the insulator spark detection system. Materials and Methods: The image of an insulator spark was captured by a video capture device, such as a video monitoring device or webcam. The captured images were used as the input for image pre-processing, insulator spark characteristic detection, and area and brightness analysis. The result was then applied to the construction of a logistic regression model of current leakage for identifying the relationship between the brightness of the insulator spark and current leakage, which is used in warning operations of current leakage at different degrees of leakage. Results: The characteristics of insulator spark were extracted and identified clearly after the pre-processing of the insulator spark image. The analysis of the logistic regression model of current leakage showed that the variables chosen by Omnibus examination were significant (p-value of <0.05). Hosmer-Lemeshow examination was suitable when the p-value was >0.05. The estimated area under the receiver operation characteristic curve (AUC) was 0.997, which is above the average value. The prediction of current leakage of an insulator spark and warning operations can be implemented based on the cut point, spark brightness, and the relationships that are induced from the logistic regression model of insulator spark. Consequently, reliable and usable insulator spark detection can be constructed for operators. Conclusion: This paper demonstrates that the accuracy of prediction of current leakage using a logistic regression model is acceptable. Nevertheless, more studies are needed for practical application. Tsair-Fwu Lee 李財福 2013 學位論文 ; thesis 91 zh-TW
collection NDLTD
language zh-TW
format Others
sources NDLTD
description 碩士 === 國立高雄應用科技大學 === 電子工程系碩士班 === 101 === Purpose: In this study, we constructed an insulator spark detection system, which integrated visual image monitoring devices and an analysis system to reduce the complexity of the insulator spark detection system. Materials and Methods: The image of an insulator spark was captured by a video capture device, such as a video monitoring device or webcam. The captured images were used as the input for image pre-processing, insulator spark characteristic detection, and area and brightness analysis. The result was then applied to the construction of a logistic regression model of current leakage for identifying the relationship between the brightness of the insulator spark and current leakage, which is used in warning operations of current leakage at different degrees of leakage. Results: The characteristics of insulator spark were extracted and identified clearly after the pre-processing of the insulator spark image. The analysis of the logistic regression model of current leakage showed that the variables chosen by Omnibus examination were significant (p-value of <0.05). Hosmer-Lemeshow examination was suitable when the p-value was >0.05. The estimated area under the receiver operation characteristic curve (AUC) was 0.997, which is above the average value. The prediction of current leakage of an insulator spark and warning operations can be implemented based on the cut point, spark brightness, and the relationships that are induced from the logistic regression model of insulator spark. Consequently, reliable and usable insulator spark detection can be constructed for operators. Conclusion: This paper demonstrates that the accuracy of prediction of current leakage using a logistic regression model is acceptable. Nevertheless, more studies are needed for practical application.
author2 Tsair-Fwu Lee
author_facet Tsair-Fwu Lee
Wei-Hsiang Huang
黃暐翔
author Wei-Hsiang Huang
黃暐翔
spellingShingle Wei-Hsiang Huang
黃暐翔
Using logistic regression model to construct insulator spark detection system
author_sort Wei-Hsiang Huang
title Using logistic regression model to construct insulator spark detection system
title_short Using logistic regression model to construct insulator spark detection system
title_full Using logistic regression model to construct insulator spark detection system
title_fullStr Using logistic regression model to construct insulator spark detection system
title_full_unstemmed Using logistic regression model to construct insulator spark detection system
title_sort using logistic regression model to construct insulator spark detection system
publishDate 2013
url http://ndltd.ncl.edu.tw/handle/30075912103453204113
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