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              [1]彭紅霞,文 豔,王 磊,等.基于兩層知識架構的電力設備差異化運維技術[J].高壓電器,2019,55(07):221-226.[doi:10.13296/j.1001-1609.hva.2019.07.032 ]
               PENG Hongxia,WEN Yan,WANG Lei,et al.Differential Operating Maintenance Technology of Power Equipment Based on Two-layer Knowledge Architecture[J].High Voltage Apparatus,2019,55(07):221-226.[doi:10.13296/j.1001-1609.hva.2019.07.032 ]
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              基于兩層知識架構的電力設備差異化運維技術()
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              《高壓電器》[ISSN:1001-1609/CN:61-11271/TM]

              卷:
              第55卷
              期數:
              2019年07期
              頁碼:
              221-226
              欄目:
              技術討論
              出版日期:
              2019-07-31

              文章信息/Info

              Title:
              Differential Operating Maintenance Technology of Power Equipment Based on Two-layer Knowledge Architecture
              作者:
              彭紅霞1 文 豔2 王 磊3 闫 冬1 王智傑1 徐 珂1 李亞錦4 于大洋4
              (1. 國網山東省電力公司菏澤供電公司, 山東 菏澤 274000; 2. 國網山東省電力公司, 濟南 250001; 3. 國網山東省 電力公司壽光供電公司, 山東 壽光 262700; 4. 山東大學電氣工程學院, 濟南 250061)
              Author(s):
              PENG Hongxia1 WEN Yan2 WANG Lei3 YAN Dong1 WANG Zhijie1 XU Ke1 LI Yajin4 YU Dayang4
              (1. Heze Power Supply Company of State Grid Shandong Electric Power Company, Shandong Heze 274000, China; 2. State Grid Shandong Electric Power Company, Jinan 250001, China; 3. Shouguang Power Supply Company of State Grid Shandong Electric Power Company, Shandong Shouguang 262700, China; 4. Shandong University, Jinan 250061, China)
              關鍵詞:
              兩層知識架構 相關關系 分塊統計 知識生成 差異化運維
              Keywords:
              two-layer knowledge architecture distance correlation block statistics knowledge generated differential operating maintenance
              DOI:
              10.13296/j.1001-1609.hva.2019.07.032
              摘要:
              針對電力設備運維數據質量不高、信息隔離以及數據扭曲等信息問題,提出兩層知識庫架構,以不同類型缺陷率和因素之間相關系數、不同特征組合下的設備缺陷率作爲知識表示,采用模型統一、分塊統計和動態排序算法,構建運維知識生成數學模型,通過運維樣本的不斷積累,更新運維知識庫中缺陷率和因素之間相關性和不同特征組合下的設備缺陷率,根據排序結果形成重點運維清單,提高現場運維缺陷識別的准確性。以電力公司運維缺陷數據爲基礎,分析和驗證了基于兩層架構的知識生成方法的有效性和正確性,可爲設備運維決策提供理論依據。
              Abstract:
              Aiming at the problems of low quality, information isolation and distortion of power equipment operation and maintenance data, a two-layer knowledge base architecture is proposed. A mathematical model for the knowledge generation of operation and maintenance and defect rate of equipment under different characteristic combinations are constructed by using model unification, block statistics and dynamic sorting algorithm, with the correlation coefficient between defect rate and factors as the knowledge representation. Through the continuous accumulation of operation and maintenance samples, defect rate of equipment under different characteristic combinations and the correlation between the defect rate and factors in the operation and maintenance knowledge base is updated, so as to improve the accuracy of defect diagnosis. Based on the defect data of power company operation and maintenance, the validity of the knowledge generation method based on two-layer architecture are analyzed and verified, which can provide theoretical basis for equipment operation and maintenance decision.

              參考文獻/References:

              [1] 王思齊. 基于物聯網的智能電網監控系統研究[J]. 電源技術, 2018,42(1):125-127. WANG Siqi. Research on smart grid monitoring system based on internet of things[J]. Chinese Journal of Power Sources, 2018,42(1):125-127.
              [2] 呂 軍,栾文鵬,劉日亮,等.基于全面感知和軟件定義的配電物聯網體系架構[J]. 電網技術,2018,42(10):3108-3115. LYU Jun, LUAN Wenpeng, LIU Riliang, et al. Architecture of distribution internet of things based on widespread sensing & software defined technology[J]. Power System Technology, 2018,42(10):3108-3115.
              [3] 戴 彥, 王劉旺, 李 媛,等. 新一代人工智能在智能電網中的應用研究綜述[J]. 電力建設, 2018, 39(10): 1-11. DAI Yan, WANG Liuwang, LI Yuan, et al. A brief survey on applications of new generation artificial intelligence in smart grids[J]. Electric Power Construction,2018,39(10):1-11.
              [4] 劉知遠,孫茂松,林衍凱,等. 知識表示學習研究進展[J]. 計算機研究與發展, 2016,53(2):247-261. LIU Zhiyuan,SUN Maosong,LIN Yankai,et al. Knowledge representation learning: A review[J]. Journal of Computer Research and Development, 2016,53(2): 247-261.
              [5] 劉 峤,韓明皓,楊曉慧, 等. 基于表示學習和語義要素感知的關系推理算法[J]. 計算機研究與發展, 2017, 54(8): 1682-1692. LIU Qiao, HAN Minghao, YANG Xiaohui,et al. Representation learning based relational inference algorithm with semantical aspect awareness[J]. Journal of Computer Research and Development, 2017, 54(8): 1682-1692.
              [6] 王耀輝, 李越陽. 電網隱性知識的概念圖構建方法[J]. 電測與儀表, 2013, 50(10):10-13. WANG Yaohui,LI Yueyang. Construction method for the concept maps of power grid tacit-knowledge[J]. Electrical Measurement & Instrumentation, 2013, 50(10):10-13.
              [7] 徐增林, 盛泳潘, 賀麗榮,等. 知識圖譜技術綜述[J]. 電子科技大學學報, 2016, 45(4):589-606. XU Zenglin,SHENG Yongpan,HE Lirong, et al. Review on knowledge graph techniques[J]. Journal of University of Electronic Science and Technology of China, 2016, 45(4):589-606.
              [8] 劉梓權,王慧芳. 基于知識圖譜技術的電力設備缺陷記錄檢索方法[J]. 電力系統自動化,2018,42(14):158-164. LIU Ziquan,WANG Huifang.Retrieval method for defect records of power equipment based on knowledge graph technology[J]. Automation of Electric Power Systems,2018,42(14):158-164.
              [9] 張延旭,胡春潮,黃 曙,等.基于Apriori算法的二次設備缺陷數據挖掘與分析方法[J]. 電力系統自動化,2017,41(19):147-151. ZHANG Yanxu,HU Chunchao,HUANG Shu, et al. Apriori algorithm based data mining and analysis method for secondary device defects[J]. Automation of Electric Power Systems,2017,41(19):147-151.
              [10] 黃天恩, 孫宏斌, 郭慶來, 等. 基于電網運行仿真大數據的知識管理和超前安全預警[J]. 電網技術, 2015, 39(11):3080-3087. HUANG Tian’en, SUN Hongbin, GUO Qinglai, et al. Knowledge management and security early warning based on big simulation data in power grid operation[J]. Power System Technology, 2015, 39(11):3080-3087.
              [11] 王新剛, 祝恩國, 朱彬若, 等. 基于“多表合一”系統的智能表異常診斷及處理方法研究[J]. 電測與儀表, 2018,55(2):86-91. WANG Xingang, ZHU Enguo, ZHU Binruo,et al. Study on abnormity diagnosis and treatment method of smart meters based on multiple metering system[J]. Electrical Measurement & Instrumentation, 2018,55(2):86-91.
              [12] 王 磊, 陳 青, 高湛軍. 輸電網故障診斷的知識表示方法及其應用[J]. 中國電機工程學報, 2012,32(4):85-92. WANG Lei CHEN Qing GAO Zhanjun. Representation and application of fault diagnosis knowledge in power transmission grids[J]. Proceeding of the CSEE, 2012,32(4):85-92.
              [13] 張 欣,李高揚,黃榮輝,等. 不同運行年限的GIS缺陷率統計分析與運維建議[J]. 高壓電器,2016,52(3):184-188. ZHANG Xin,LI Gaoyang,HUANG Ronghui,et al.Statistical analysis of defects and maintenance advice for gis in different operating years above 110 kV[J]. High Voltage Apparatus,2016,52(3):184-188.
              [14] 程建登,吳 斌,毛文俊,等.特高壓換流站故障統計與反措[J]. 高壓電器,2018,54(12):292-304. CHENG Jiandeng,WU Bin,MAO Wenjun,et al. Failure statistics and countermeasures of UHVDC converter stations[J]. High Voltage Apparatus,2018,54(12):292-304.
              [15] 曾令男, 丁建偉, 趙 炯, 等. 基于互信息的複雜裝備高維狀態監測數據相關性發現與建模[J]. 計算機集成制造系統, 2013, 19(12): 3018-3025. ZENG Lingnan,DING Jianwei,ZHAO Jiong, et al. Detecting and modeling for associations between high-dimension condition monitoring data of complex equipment based on mutual information[J]. Computer Integrated Manufacturing Systems, 2013, 19(12): 3018-3025.
              [16] 代傑傑, 宋 輝, 盛戈皞,等. 考慮複雜關聯關系深度挖掘的變壓器狀態參量預測方法[J]. 中國電機工程學報, 2019, 39(2): 621-628. DAI Jiejie, SONG Hui, SHENG Gehao,et al. A prediction method for power transformers state parameters based on deep association relation mining[J]. Proceedings of the CSEE, 2019, 39(2): 621-628.
              [17] 謝榮斌,張 登,林福昌,等.基于關聯規則與變權重的變壓器狀態評估方法[J]. 高壓電器,2014,50(1):133-135. XIE Rongbin,ZHANG Deng,LIN Fuchang,et al.Transformer condition assessment using association rules and variable weight[J]. High Voltage Apparatus,2014,50(1):133-135.
              [18] 徐祥海,楊 翾,時 銳,等.一種基于輸變電設備集中監控信息的試運行變電站風險評估方法[J].高壓電器,2018,54(4):245-249. XU Xianghai,YANG Xuan,SHI Rui,et al. Risk assessment method of substation in trial stage based on centralized monitoring of transmission and transformation equipment[J]. High Voltage Apparatus,2018,54(4):245-249.
              [19] SZéKELY G J, RIZZO M L, BAKIROV N K. Measuring and testing dependence by correlation of distances[J]. Annals of Statistics, 2007, 35(6):2769-2794.
              [20] RESHEF D N , RESHEF Y A , FINUCANE H K , et al. Detecting novel associations in large data sets[J]. Science, 2011, 334(60-62):1518-1524.

              備注/Memo

              備注/Memo:
              彭紅霞(1977—) ,女,本科,高級工程師,主要從事變電運維檢修研究工作。 文 豔 (1975—),女,碩士,高級工程師,主要從事電力系統及其自動化方面的研究。 于大洋(1979—),男,工學博士,副教授,研究方向爲電力系統建模與優化。收稿日期:2019-03-05; 修回日期:2019-04-17 基金項目:國網山東省電力公司科技項目(SGSDHZ00BDJS1800441)。 Project Supported by Science and Technology Project of State Grid Shandong Electric Power Company(SGSDHZ00BDJS1800441).
              更新日期/Last Update: 2019-07-15