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Statistical Health Reasoning System of Power Generator Stator Windings against Water Absorption : 발전기 고정자 권선 흡습에 대한 통계적 추론 시스템 개발
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | 윤병동 | - |
dc.contributor.author | 박경민 | - |
dc.date.accessioned | 2017-07-14T03:32:45Z | - |
dc.date.available | 2017-07-14T03:32:45Z | - |
dc.date.issued | 2014-02 | - |
dc.identifier.other | 000000017600 | - |
dc.identifier.uri | https://hdl.handle.net/10371/123738 | - |
dc.description | 학위논문 (석사)-- 서울대학교 대학원 : 기계항공공학부, 2014. 2. 윤병동. | - |
dc.description.abstract | The power generator, as one of the most critical components in a power plant, is typically maintained through use of a time- or usage-based strategy. Either strategy could result in a substantial waste of remaining useful life (RUL), high maintenance costs, and/or low plant availability due to excess, untimely, or missed maintenance. Recently, the field of prognostics and health management has offered new general diagnostic and prognostic techniques to precisely assess health conditions and robustly predict the RUL of engineered systems, with the aim of addressing the aforementioned deficiencies. This paper explores a smart health reasoning system that can be used to assess the health condition of power generator stator windings and their levels of water absorption. The system monitors health based on capacitance measurements of the winding insulations. In particular, a new relative health measure, namely the Directional Mahalanobis Distance (DMD), is proposed to quantify the health condition of stator windings. This paper also proposes an empirical health classification rule, based upon the DMD, which factors in maintenance history. The proposed smart health reasoning system is validated using eight years field data from eight generators, each of which contains forty-two windings. | - |
dc.description.tableofcontents | Abstract i
List of Figures vii Nomenclature ix Abbreviations xi Chapter 1. Introduction 1 1.1 Motivation 1 1.2 Overview 2 1.3 Thesis Layout 3 Chapter 2. Literature Review 4 2.1 Prognostics and Health Management Techniques used to Support the Health Reasoning Function 4 2.2 Existing Tests to Detect Leaks or Water Absorption 5 2.3 Summary and Discussion 8 Chapter 3. Description of the Sensing Function and Data Analysis 9 3.1 Fundamentals of Capacitance Measurements 9 3.2 Capacitance Data Acquisition 12 3.3 Statistical Characterization of the Capacitance Data 15 3.4 Data Grouping 19 Chapter 4. Statistical Health Reasoning System 21 4.1 Review of Mahalanobis Distance 21 4.2 A New Concept of Statistical Distance: Directional Mahalanobis Distance 23 4.2.1 Data Projection 23 4.2.2 Transformation 26 4.3 Comparison of Performance of Mahalanobis Distance (MD) and Directional Mahalanobis Distance (DMD) 26 Chapter 5. Health Classification 31 5.1 Maintenance History Related to Water Absorption 31 5.2 Review of Scaled Mahalanobis Distance 32 5.3 Health Grade System 34 5.4 Validation Study 36 Chapter 6. Conclusion 39 Bibliography 40 APPENDIX A. 46 국문 초록 47 감사의 글 49 | - |
dc.format | application/pdf | - |
dc.format.extent | 3248323 bytes | - |
dc.format.medium | application/pdf | - |
dc.language.iso | en | - |
dc.publisher | 서울대학교 대학원 | - |
dc.subject | Power Generator | - |
dc.subject | Stator Winding | - |
dc.subject | Statistical Correlation | - |
dc.subject | Health Diagnostics | - |
dc.subject | Directional Mahalanobis Distance | - |
dc.subject | Water Absorption | - |
dc.subject.ddc | 621 | - |
dc.title | Statistical Health Reasoning System of Power Generator Stator Windings against Water Absorption | - |
dc.title.alternative | 발전기 고정자 권선 흡습에 대한 통계적 추론 시스템 개발 | - |
dc.type | Thesis | - |
dc.contributor.AlternativeAuthor | Kyung Min Park | - |
dc.description.degree | Master | - |
dc.citation.pages | xi, 51 | - |
dc.contributor.affiliation | 공과대학 기계항공공학부 | - |
dc.date.awarded | 2014-02 | - |
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