考虑环境影响的电容型设备绝缘监测与故障诊断研究
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摘要
电容型设备绝缘在线监测与故障诊断技术是实现其状态维修的前提和基础。电容型设备绝缘在线监测会受到环境因素(温度、湿度、污秽等)的影响,研究考虑环境影响的电容型设备绝缘监测与故障诊断技术具有理论意义和实用价值。本文在环境因素对电容型设备介质损耗因数(tanδ)影响的试验方法、tanδ的修正方法、电容型设备故障诊断方法等方面进行了深入的研究,并开发了在线监测与故障诊断系统。完成的主要工作和取得的主要研究成果如下:
提出了全绝缘型人工气候室设计方案,计算分析了气候室内悬挂绝缘子和套管时的空间电场分布情况,并和金属材质气候室相比较,论证了该方案的优越性,据此方案研制的全绝缘人工气候室可调节温度、湿度和压力等参数,满足了人工气候试验的要求;开发了基于虚拟仪器技术的高压电容型设备绝缘特性自动测试系统,完成了人工气候室内变压器套管tanδ的在线测量试验,以此为基础分析了环境因素对电容型设备tanδ的影响情况,获得了tanδ与环境参数的关系曲线,建立了环境因素对tanδ影响的灰关联分析模型,得到了主要环境参数与电容型设备tanδ的灰关联度。
提出了基于最小二乘支持向量机的主要环境参数对tanδ影响的修正方法,将不同气候环境条件下测得的电容型设备tanδ修正为标准大气条件下的值,从而使不同气候条件下的监测数据及离线试验数据具有了等效性,采用遗传算法优化了支持向量机参数,有效提高了修正精度,实例修正结果和实际的在线监测数据修正结果均验证了该方法的有效性。
结合电容型设备的其他检测数据,提出了基于贝叶斯网络的电容型设备故障诊断方法,首次将贝叶斯网络方法引入到电容型设备的故障诊断中,并根据电容型设备故障诊断的特点改进了贝叶斯网络的推理过程,提高了该方法的实用性,诊断实例验证了该方法的有效性。
通过实例分析验证了将环境参数与tanδ的灰关联度作为特征量进行电容型设备故障诊断的可行性,提出了基于灰关联度物元模型的电容型设备可拓诊断方法,该方法即排除了环境因素对tanδ的影响,又可以进行准确的故障分类,诊断实例验证了该方法的有效性。
根据分布式电容型设备在线监测的需要,提出了多下位机同步采样控制方法,并开发了一套分层分布式电容型设备绝缘在线监测与故障诊断系统应用于实际工程,该系统采用就地数字化技术提高了抗干扰能力,经过测试与运行,系统运行可靠稳定,数据采集准确。
To monitor and diagnose the insulation condition of capacitive equipments on-line is the precondition and basis to realize the condition-based maintenance (CBM) for capacitive equipments. On-line monitoring and fault diagnosis of capacitive equipment’s insulation would be influenced by environmental factors (such as temperature , humidity , contamination etc.). Therefore, it is very useful and meaningful to study the insulation monitoring and diagnosis method of capacitive equipments considering influence of environment. The test method of dielectric dissipation factor(tanδ)changing law in different environments, the tanδ’s modified method and the method of capacitive equipment’s fault diagnosis were researched in this paper. At the same time, on-line monitoring and fault diagnosis system was developed. The main work accomplished includes the following.
In this paper, a new design proposal of fully insulated artificial climate chamber was put forward. The distribution of electric field in full space when insulators or bushing was hung in the chamber was analyzed. It was found that electrical field strength and potential around the the sample changed less in the fully insulated chamber than in conducting material phytotron, so it is closer the real condition. Based on the design, the first fully insulated large artificial climate chamber in China, in which temperature , humidity, and atmospheric pressure can be regulated, has been built in our laboratory. The paper developed an insulation parameters automatic test system of high voltage capacitive equipment based on LabVIEW. In the chamber, On-line tanδmeasurements of the capacitive transformer bushings were completed. The effects of environmental factors on tanδwere analyzed, and the curves between the tanδand the environment parameters were acquired. Then, a grey relational model to analyze the effects of main environmental factors on tanδwas built, and the grey relational grade between them was gained in this paper.
In this paper, a modified model of the effects of main environmental factors on tanδbased on Least Squares Support Vector Machine( LS-SVM ) was put forward. So the tanδvalue measured in different climate conditions could be modified into a tanδvalue in standard atmospheric conditions, thereby the on-line measured data and the test data in laboratory under different climate conditions were equivalent. The model parameters were optimized by genetic algorithm, which improved the accuracy of modified calculation. The effectiveness of this method was validated by modified results of the test data and on-line monitoring data.
Bayesian network method for capacitive equipment’s fault Diagnosis was presented by means of combining all kinds of monitor data based on Bayesian network theory. It is the first time that the paper introduced the Bayesian network theory into capacitive equipment’s fault diagnosis. Bayesian network’s reasoning process was improved based on the characteristics of capacitive equipment’s fault diagnosis in this paper. This method was proved to be effective by experiment.
The feasibility that using the grey relational grade of main environmental factors on tanδas new characteristic quantity to diagnose the capacitive equipments was proved by examples. And the extension diagnosis method of capacitive equipment’s faults based on matter-element model was advanced. This method can not only exclude the effects of environmental factors on tanδ, but also realize fault classification exactly. The method was proved to be successful by experiment.
A new control method of the synchronous data sampling on multi-lower computer system was developed according to the needs of distributed capacitive equipment on-line monitor. Base on this method, we developed an on-line insulation monitoring and fault diagnosis system for capacitive equipment, which was then applied in practice. This system took the locally digitizing process to improve anti-disturbing capability. In practical project , the operation of the system was stable and reliable, and the data sampling was accurate.
提出了全绝缘型人工气候室设计方案,计算分析了气候室内悬挂绝缘子和套管时的空间电场分布情况,并和金属材质气候室相比较,论证了该方案的优越性,据此方案研制的全绝缘人工气候室可调节温度、湿度和压力等参数,满足了人工气候试验的要求;开发了基于虚拟仪器技术的高压电容型设备绝缘特性自动测试系统,完成了人工气候室内变压器套管tanδ的在线测量试验,以此为基础分析了环境因素对电容型设备tanδ的影响情况,获得了tanδ与环境参数的关系曲线,建立了环境因素对tanδ影响的灰关联分析模型,得到了主要环境参数与电容型设备tanδ的灰关联度。
提出了基于最小二乘支持向量机的主要环境参数对tanδ影响的修正方法,将不同气候环境条件下测得的电容型设备tanδ修正为标准大气条件下的值,从而使不同气候条件下的监测数据及离线试验数据具有了等效性,采用遗传算法优化了支持向量机参数,有效提高了修正精度,实例修正结果和实际的在线监测数据修正结果均验证了该方法的有效性。
结合电容型设备的其他检测数据,提出了基于贝叶斯网络的电容型设备故障诊断方法,首次将贝叶斯网络方法引入到电容型设备的故障诊断中,并根据电容型设备故障诊断的特点改进了贝叶斯网络的推理过程,提高了该方法的实用性,诊断实例验证了该方法的有效性。
通过实例分析验证了将环境参数与tanδ的灰关联度作为特征量进行电容型设备故障诊断的可行性,提出了基于灰关联度物元模型的电容型设备可拓诊断方法,该方法即排除了环境因素对tanδ的影响,又可以进行准确的故障分类,诊断实例验证了该方法的有效性。
根据分布式电容型设备在线监测的需要,提出了多下位机同步采样控制方法,并开发了一套分层分布式电容型设备绝缘在线监测与故障诊断系统应用于实际工程,该系统采用就地数字化技术提高了抗干扰能力,经过测试与运行,系统运行可靠稳定,数据采集准确。
To monitor and diagnose the insulation condition of capacitive equipments on-line is the precondition and basis to realize the condition-based maintenance (CBM) for capacitive equipments. On-line monitoring and fault diagnosis of capacitive equipment’s insulation would be influenced by environmental factors (such as temperature , humidity , contamination etc.). Therefore, it is very useful and meaningful to study the insulation monitoring and diagnosis method of capacitive equipments considering influence of environment. The test method of dielectric dissipation factor(tanδ)changing law in different environments, the tanδ’s modified method and the method of capacitive equipment’s fault diagnosis were researched in this paper. At the same time, on-line monitoring and fault diagnosis system was developed. The main work accomplished includes the following.
In this paper, a new design proposal of fully insulated artificial climate chamber was put forward. The distribution of electric field in full space when insulators or bushing was hung in the chamber was analyzed. It was found that electrical field strength and potential around the the sample changed less in the fully insulated chamber than in conducting material phytotron, so it is closer the real condition. Based on the design, the first fully insulated large artificial climate chamber in China, in which temperature , humidity, and atmospheric pressure can be regulated, has been built in our laboratory. The paper developed an insulation parameters automatic test system of high voltage capacitive equipment based on LabVIEW. In the chamber, On-line tanδmeasurements of the capacitive transformer bushings were completed. The effects of environmental factors on tanδwere analyzed, and the curves between the tanδand the environment parameters were acquired. Then, a grey relational model to analyze the effects of main environmental factors on tanδwas built, and the grey relational grade between them was gained in this paper.
In this paper, a modified model of the effects of main environmental factors on tanδbased on Least Squares Support Vector Machine( LS-SVM ) was put forward. So the tanδvalue measured in different climate conditions could be modified into a tanδvalue in standard atmospheric conditions, thereby the on-line measured data and the test data in laboratory under different climate conditions were equivalent. The model parameters were optimized by genetic algorithm, which improved the accuracy of modified calculation. The effectiveness of this method was validated by modified results of the test data and on-line monitoring data.
Bayesian network method for capacitive equipment’s fault Diagnosis was presented by means of combining all kinds of monitor data based on Bayesian network theory. It is the first time that the paper introduced the Bayesian network theory into capacitive equipment’s fault diagnosis. Bayesian network’s reasoning process was improved based on the characteristics of capacitive equipment’s fault diagnosis in this paper. This method was proved to be effective by experiment.
The feasibility that using the grey relational grade of main environmental factors on tanδas new characteristic quantity to diagnose the capacitive equipments was proved by examples. And the extension diagnosis method of capacitive equipment’s faults based on matter-element model was advanced. This method can not only exclude the effects of environmental factors on tanδ, but also realize fault classification exactly. The method was proved to be successful by experiment.
A new control method of the synchronous data sampling on multi-lower computer system was developed according to the needs of distributed capacitive equipment on-line monitor. Base on this method, we developed an on-line insulation monitoring and fault diagnosis system for capacitive equipment, which was then applied in practice. This system took the locally digitizing process to improve anti-disturbing capability. In practical project , the operation of the system was stable and reliable, and the data sampling was accurate.
引文
[1]严璋,朱德恒.高电压绝缘技术[M].北京:中国电力出版社, 2002
[2]邱昌容,曹晓珑.电气绝缘测试技术[M].北京:机械工业出版社, 2004
[3]陈家斌.电气设备故障检测诊断方法及实例[M].北京:中国水利水电出版社, 2003
[4]施围,邱毓昌,张乔根.高电压工程基础[M].北京:机械工业出版社, 2006
[5]屈靖,郭剑波.“九五”期间我国电网事故统计分析[J].电网技术, 2004, 28(21): 60~68
[6]黄盛洁,姚文捷,马治亮等.电气设备绝缘在线监测和状态维修[M].北京:中国水利水电出版社. 2004
[7]关根志,贺景亮.电气设备的绝缘在线监测与状态维修[J].变压器, 2002, 39(S1): 1~5
[8]李燕青,律方成,刘国平等.我国电气设备状态维修的发展与实现[J].中国电力, 2003, 36(2): 16~19
[9]李慧敏,任敏哲,安永成.电气设备状态检修的探讨[J].西北电力技术, 2006, 1: 37~41
[10]刘有为,李光范,高克利等.制订《电气设备状态维修导则》的原则框架[J].电网技术, 2003, 27(6): 64~67
[11]胡文平,尹项根,张哲.电气设备在线监测技术的研究与发展[J].华北电力技术, 2003, 14(2): 23~26
[12] M. Wang,A.J. Vandermaar,K. D. Srivastava. Review of condition assessment of power transformers in service[J]. IEEE Electrical Insulation Magazine, 2002,18(6):12~25
[13] Jardine A K S. Optimizing condition based maintenance decisions[C]. In the proceedings of Reliability and Maintainability Symposium, Japan, 2002: 90~97
[14]苏鹏声,王欢.电力系统设备状态监测与故障诊断技术的分析[J].电力系统自动化, 2003, 27(1): 61~65
[15]中华人民共和国电力工业部.电力设备预防性规程DL/T 596-1996[M].北京:中国电力出版社, 1997
[16]中华人民共和国电力工业部.电力设备预防性规程DL/T 596-1996修订说明[M].北京:中国电力出版社, 1997
[17] Günther Ramm, Harald Moser. Calibration of Electronic Capacitance and Dissipation Factor Bridges[J]. IEEE Transactions on Instrumentation and Measurement, 2003, 52(2): 396~399
[18] W. H. Tang,K. Spurgeon, Z. J. Richardson. An Evidential Reasoning Approach to Transformer Condition Assessments[J]. IEEE Transaction Power Delivery,2004,19(4):1696~1703
[19]党瑞荣,付岳峰.电容型高压设备绝缘在线监测系统的设计[J].电测与仪表, 2008, 45(4): 22~24
[20] Alireza Setayeshmehr, Alireza Akbari, Hossein Borsi, et al. On-line Monitoring of Power Factor (tanδ) and Capacitance of Transformer Bushings[C]. Proceedings of the 5th International Symposium on High Voltage Engineering, Beijing, China, August, 2005: 400
[21] Lu Fangcheng, Wang Nan, Chen Zhiye. Measurement of tgδBased on Absolute and Comparative Method[C]. Proceedings of ISEIM2001, Japan, Nov, 2001: 344~346
[22] Nitaigour Premchand Mahalik. A Digital Meter for Measuring Dissipation Factor[C]. Proceedings of the 5m International Conference on Properties and Applications of Dielectric Materials, Seoid, Koreu, May, 1997: 1129~1131
[23]左自强,徐阳,曹晓珑等.计算电容型电容型设备介质损耗因数的相关函数法的改进[J].电网技术, 2004, 28(18): 53~57
[24]邓岳华,阮绵晖,刘味果.高压设备绝缘在线监测系统的现场应用与分析[J].电网技术. 2004, 28(16): 69~72
[25]方先存,刘云鹏,李军.电容型设备绝缘在线监测系统的开发与应用[J].高电压技术, 2008, 34(6): 6~9
[26] Yimei Jia, Fuheng Su, Jun Liu. An on~line insulation monitoring system based on fieldbus[C]. In Proceedings of 2001 ISEIM & ACEID, Himeji, Japan, November 2001: 769~772
[27]高振国.影响介损在线检测结果的因素分析及诊断策略[J].沈阳工程学院学报(自然科学版)[J]. 2007, 3(1): 41~43
[28]王楠,律方成,李艳涛等.影响介损在线检测准确性的因素分析与探讨[J].电工技术杂志. 2003, 21(1): 43~45
[29]杨雪峰.影响油纸电容式套管介质损耗因数(tanδ)增大或不稳定因素的分析[J].电瓷避雷器, 1999, 6: 14~19
[30]金维芳.电介质物理学[M].机械工业出版社, 1997
[31]胡兆斌.绝缘材料工艺学[M].化学工业出版社, 2005
[32]朱琦.变压器油高温介质损耗因数不稳定原因分析[J].变压器,1999,36(12): 36~37
[33]单平,罗勇芬,徐大可等.绝缘监测用高精度微电流传感器研究[J].电力自动化设备, 2002, 22(11): 4~6
[34] Yuting Yan,Xishan Wen,Jiamin Hu,et al. On-line Monitoring the Tangent of Dielectric Dissipation FactorδUsing Double Polarities Cross Zero Comparing Method[C]. Proceedings of the 5th International Symposium on High Voltage Engineering, Beijing, China, August, 2005: 362
[35] Günther Ramm, Harald Moser. From the Calculable AC Resistor to Capacitor Dissipation Factor Determination on the Basis of Time Constants[J]. IEEE Transactions on Instrumentation and Measurement, 2001,50(2): 286~289
[36] Wang Nan, Lu Fang-cheng, Liang Ying. Application of Improved Harmonic Analysis Approach In On-line Measuring Dissipation Factor of HV Capacitive Equipments[C]. ICEMI2003, Taiyuan, China, August, 2003: 630~634
[37]杨晓东,唐超,廖瑞金等.电容型设备改进型介损数字化测量方法的研究[J].高压电器, 2007, 34(6): 460~462
[38] Günther Ramm, Harald Moser. New Multifrequency Method for the Determination of the Dissipation Factor of Capacitors and of the Time Constant of Resistors[J]. IEEE Transactions on Instrumentation and Measurement, 2005, 54(2): 521~524
[39]徐志钮,律方成,汪佛池等.用加Hanning窗插值高阶正弦拟合法测介损角测量[J].高电压技术, 2007, 33(4): 05~35
[40]徐志钮,律方成,李和明.存在脉冲噪声情况下的介损角算法[J].电力自动化设备, 2008, 28(2): 45~48
[41] Djokic, B. So, E. Phase measurement of distorted periodic signals based on nonsynchronous digital filtering[J]. IEEE Transactions on Instrumentation and Measurement, 50(4): 864~867
[42]徐志钮,律方成,李和明.加Blackman-Harris窗插值算法仿真介损角测量[J].高电压技术,2007,33(3): 401~801
[43]王楠.电容型设备绝缘在线监测与故障诊断的研究(博士论文) [D].保定:华北电力大学, 2004
[44]柴旭峥,文习山,关根志等.绝缘在线监测采样数据的两种预处理算法[J].高电压技术, 2002, 28(9): 26~27
[45]由建,王文娣,陈少伟等.电流互感器介质损耗因数与温度的关系[J].变压器, 2006, 43 (11): 35~38
[46]孙立蓉,王华军.纸介质材料电子位移极化理论[J].绝缘材料, 2005, 38(4): 17~19
[47] N. Wang, F. C. Lu, H. M. Li. Analytical Processing of On-line Monitored Dissipation Factor Based on Morphological Filter[J]. IEEE Transactions onDielectrics and Electrical Insulation, 2004, 11(5): 840~846
[48]王楠,律方成.基于小波奇异性检测的在线监测数据处理[J].电工技术学报, 2003, 18(4): 61~64
[49]王楠,律方成,刘云鹏等.自适应广义形态滤波方法在介损在线监测数据处理中的应用研究[J].中国电机工程学报, 2004, 24(2): 161~165
[50]王楠,律方成,刘云鹏等.介损在线监测数据趋势提取方法的研究[J].高压电器, 2004, 40(1): 5~8
[51] Yang Li, Yang Minzhong, Yan Zhang, et al. Extraction of symptom for on-line diagnosis of power equipment based on method of time series analysis[C]. In: Proceedings of the 6th ICPADM, Xi’an, China, June 21-26,2000: 314~317
[52]王红斌.电容式电压互感器附加相位差对绝缘在线监测的影响[J].高压电器, 2003, 39(4): 64~65
[53] Pei Wang, M R Raghuveer, et al. A Digital Technique for The On~line Measurement of Dissipation Factor and Capacitance[J]. IEEE Transactions on Dielectric and Electrical Insulation, 2001, 8(2): 228~232
[54]史保壮,杨莉,冯德开等.智能技术在绝缘在线诊断系统中的应用[J].高压电器, 2001, 37(1): 32~34
[55]黄新红,廖瑞金,胡雪松等.“综合相对测量法”于介质损耗在线检测中的应用[J].高压电器, 2001, 37(6): 1~3
[56] Mark F Lachman, et al. On~line Diagnostic of High~voltage Bushings and Current Transformers Using the Sum Current Method[J]. IEEE Transactions on Power Delivery, 2000, 15(1): 155~162
[57]金之俭,黄结成.三相泄漏电流和的变化反映容性设备的绝缘状况[J].高电压技术, 2001, 27(6):12~13
[58] Baozhuang Shi, Li Yang, Hongbin Wang. Studies on the effect of influencing factors on condition monitoring of HV substation equipment[C]. In Proceedings of 2001 ISEIM & ACEID, Himeji, Japan, November 2001: 753~756
[59]王楠,律方成,李和明.灰关联分析在电容型设备绝缘故障诊断中的应用初探[J].高压电器, 2003, 39(5): 32~35
[60] Yin Dejun, Liu Beiying. Experience of condition based maintenance for power equipment insulation[C]. In Proceedings of 2001 ISEIM & ACEID, Himeji, Japan, November 2001: 198~200
[61] Shi Baozhuang, Yang Li, Wang Hongbin, et al. Instrumentation of online insulation monitoring of HV apparatus[C]. In: Proceedings of the 6th ICPADM, Xi’an, China,June, 2000: 713~716
[62] Shi Baozhuang, Yang Li, Wang Hongbin, et al. An online insulation diagnostic technique for HV apparatuses base on pertinency[C]. In: Proceedings of the 6th ICPADM, Xi’an, China, June 21-26, 2000: 705~708
[63] Allan D et al. New techniques for monitoring the insulation quality of in~service HV apparatus[J]. IEEE Transactions on Electrical Insulation, 1992, 27(3): 578~581
[64]徐师华.国内外人工气候控制装置应用发展的确概述[J].农业工程学报, 1989, 5(4): 16~21
[65]舒立春.复杂环境中绝缘子交流闪络特性及校正方法研究[博士学位论文].重庆:重庆大学,2002
[66]刘有为.应用新型人工气候室研究长串绝缘子的工频污闪特性[J].电网技术, 2002,26(3):46~48
[67]刘国强,赵凌志. Ansoft工程电磁场有限元分析[M].北京:电子工业出版社,2005
[68] National Instruments Corporation. Virtual Instruments. http://www.ni.com,2005
[69]胡文平,尹项根,张哲.基于虚拟仪器技术的电力设备在线监测[J].高压电器, 2003, 39(4): 38~40
[70]蒋兴良,舒立春,张永记,等.人工污秽下盐/灰密对普通悬式绝缘子串交流闪络特性的影响[J].中国电机工程学报,2006,26(15): 24~28
[71]孙才新,李俭,郑海平等.基于灰色面积关联度分析的电力变压器绝缘故障诊断方法[J].电网技术, 2002, 26(7): 24~29
[72]吕锋.灰色系统关联度之分辨系数的研究[J].系统工程理论与实践, 1997, 17(6): 49~54
[73]周宇阳,陈汉平,王炜哲等.故障诊断灰色数学模型[J].中国电机工程学报, 2002, 22(6): 146~151
[74]刘思峰,郭天榜,党耀国等.灰色系统理论及其应用[M].北京:科学出版社, 1999
[75]程岩,黄梯云.粗糙集中定量关联规则的发现及其规则约简的方法研究[J].管理工程学报, 2001, 15(3): 73~77
[76]张建兴,律方成,刘云鹏,谭磊,赵亚平.高压绝缘子泄漏电流与温、湿度的灰关联分析[J].高电压技术,2006,32(1): 40~41
[77]丁国成,律方成,李燕青,刘云鹏.灰关联分析用于分析环境因素对MOA在线监测的影响[J].高压电器, 2006, 42(3): 196~198
[78]杜树新,吴铁军.用于回归估计的支持向量机方法[J].系统仿真学报, 2005, 15(11): 1580~1586
[79]李凌均,张周锁,何正嘉.基于支持向量机的机械设备状态趋势预测研究[J].西安交通大学学报, 2004, 38(3): 230~234
[80]焦尚彬,刘丁,郑岗,张青.基于最小二乘支持向量机得绝缘子等值附盐密度预测[J].中国电机工程学报, 2006, 26(2): 149~153
[81]赵永平,孙健国.基于滚动窗法最小二乘支持向量机的稳健预测模型[J].模式识别与人工智能, 2008, 21(1): 1~5
[82]丁明,石雪梅.基于遗传算法的电力市场环境下电源规划的研究[J].中国电机工程学报, 2006, 26(21): 43~49
[83]孙力勇,张焰,蒋传文.基于矩阵实数编码遗传算法求解大规模机组组合问题[J].中国电机工程学报, 2006, 26(2): 82~87
[84] Riedman N,Geiger D,Goldszmidt M.Bayesian network classifiers[J].Machine Learning,l997,29:13l~163.
[85] Xiang, Y., Poole, D., Beddoes, M. P.. Multiply sectioned Bayesian networks and junction forests for large knowledge based systems[J], Computational Intelligence, 1993, 9 (2): 171~220.
[86] Fengzhan Tian, Hongwei Zhang, Yuchang Lu, et. al. Incremental Learning of Bayesian Networks[C]. Proceeding. Press of Japan Advanced Institute of Science and Technology(KSS’2001), Dalian, China, September 2001:169~178
[87] Zhang hongwei, Tian fengzhan, Lu yuchang. A general algorithm for approximate inference in Multiply Sectioned Bayesian network[J]. The Fourth International Symposium on Intelligent Data Analysis 2001, Cascais, Portugal, September 2001: 330~339
[88]胡卫华,朱永利.贝叶斯网络推理算法的研究和实现[N].华北电力大学学报,2004,31(5): 63~65.
[89] Wang Yongqiang, Lu Fangcheng, Li Heming. The Fault Diagnosis Method for Electrical Equipment Based on Bayesian Network[C],ICEMS2005,Nanjing, China, September 2005: 26~30
[90] Wang Yongqiang, Lu Fangcheng, Li Heming. The Fault Diagnosis Method for Power Transformer Based on BN And DGA[C]. ISEIM2005,Kitakyushu Japan, Jun., 2005: 476~479
[91]蒋国萍,陈英武.时间贝叶斯网络及其概率推理[J].管理科学学报,2007,10(2): 12~18
[92] Eitel J M, Lauria Peter J. Duchessi. A methodology for developing baysian networks: an application to information technology(IT) implementation[J]. Eropean Journal of Operational Research, 2007, 179: 234~252
[93]李雪,龚龙庆.基于贝叶斯网络的证据目标模型及推理算法研究.微电子学与计算机,2007,24(8): 149~151
[94]熊浩,孙才新,杜鹏,代姚,王谦.基于物元理论的电力变压器状态综合评估[J].重庆大学学报(自然科学版),2006,29(10):24~28.
[95]金文,陈长征,金志浩,闻邦椿.燃气轮发电机组多故障诊断的物元分析方法[J].中国电机工程学报, 2007,27(17): 57~60.
[96]黄文涛,赵学增,王伟洁,代礼周.基于物元模型的电力变压器故障的可拓诊断方法[J].电力系统自动化,2004,28(13): 45~49.
[97] Lifeng Liu, Caixin Sun, Quan Zhou. A novel electrical equipment on~line monitoring system based on geographic information system[C]. In Proceedings of 2001 ISEIM & ACEID, Himeji, Japan, November 2001: 205~208
[98] Zhang Guangchun, Tong Xiaoyang, Zou Siyi, et al. A novel insulation on-line monitoring and fault diagnosis system used for traction substation[C]. In: Conference Record of the 2002 IEEE International Symposium on Electrical Insulation, Boston, MA USA, April, 2002: 199~202
[99] Lin Du, Zhu Deheng, Li Fuqi, et al. A distributed on-line monitoring and diagnosis system of power equipment[C]. In Proceedings of the 6th ICPADM, Xi’an, China, June, 2006: 668~671
[100] Tu Yanming, Yan Ping, Guo Zhongjun. Predictive maintenance strategy based upon management information system[C]. In Proceedings of 2001 ISEIM & ACEID, Himeji, Japan, November 2001: 225~228
[101] Maragos P, Schafer R W. Morphological filters– Part II: Their relations to median, order-statistics, and stack filters[J]. IEEE Trans. On Acoustics, Speech and Signal Processing, 1987, 35(8): 1170~1184
[102] Jiangtao Xi, Chicharo J.F. A new algorithm for improving the accuracy of periodic signal analysis [J]. IEEE Trans on IM,1996,45(4):827~830
[103] Mallat. Singularity detection and processing with wavelets[J]. IEEE Trans on IT,1992,38(2): 617
[104] Huiping Zhang, Kexiong Tan. The analysis of on~line monitoring results for capacitive type equipment[C]. In Proceedings of 2001 ISEIM & ACEID,Himeji,Japan,November 2001: 100~103
[105] MAXIM data sheet of MAX125. Http://www.maximonline.com,2006
[106]吴文传,张伯明,汤磊.支持SCADA/PAS/DTS一体化的图形系统[J].电力系统自动化,2001,25(5): 45~49
[107] Wang Nan, Liang Ying, Lu Fangcheng. On-line Insulation Monitoring SystemBased on ASP Technique[C]. Riupeeec2003, Hongkong, August, 2003: 52~53
[2]邱昌容,曹晓珑.电气绝缘测试技术[M].北京:机械工业出版社, 2004
[3]陈家斌.电气设备故障检测诊断方法及实例[M].北京:中国水利水电出版社, 2003
[4]施围,邱毓昌,张乔根.高电压工程基础[M].北京:机械工业出版社, 2006
[5]屈靖,郭剑波.“九五”期间我国电网事故统计分析[J].电网技术, 2004, 28(21): 60~68
[6]黄盛洁,姚文捷,马治亮等.电气设备绝缘在线监测和状态维修[M].北京:中国水利水电出版社. 2004
[7]关根志,贺景亮.电气设备的绝缘在线监测与状态维修[J].变压器, 2002, 39(S1): 1~5
[8]李燕青,律方成,刘国平等.我国电气设备状态维修的发展与实现[J].中国电力, 2003, 36(2): 16~19
[9]李慧敏,任敏哲,安永成.电气设备状态检修的探讨[J].西北电力技术, 2006, 1: 37~41
[10]刘有为,李光范,高克利等.制订《电气设备状态维修导则》的原则框架[J].电网技术, 2003, 27(6): 64~67
[11]胡文平,尹项根,张哲.电气设备在线监测技术的研究与发展[J].华北电力技术, 2003, 14(2): 23~26
[12] M. Wang,A.J. Vandermaar,K. D. Srivastava. Review of condition assessment of power transformers in service[J]. IEEE Electrical Insulation Magazine, 2002,18(6):12~25
[13] Jardine A K S. Optimizing condition based maintenance decisions[C]. In the proceedings of Reliability and Maintainability Symposium, Japan, 2002: 90~97
[14]苏鹏声,王欢.电力系统设备状态监测与故障诊断技术的分析[J].电力系统自动化, 2003, 27(1): 61~65
[15]中华人民共和国电力工业部.电力设备预防性规程DL/T 596-1996[M].北京:中国电力出版社, 1997
[16]中华人民共和国电力工业部.电力设备预防性规程DL/T 596-1996修订说明[M].北京:中国电力出版社, 1997
[17] Günther Ramm, Harald Moser. Calibration of Electronic Capacitance and Dissipation Factor Bridges[J]. IEEE Transactions on Instrumentation and Measurement, 2003, 52(2): 396~399
[18] W. H. Tang,K. Spurgeon, Z. J. Richardson. An Evidential Reasoning Approach to Transformer Condition Assessments[J]. IEEE Transaction Power Delivery,2004,19(4):1696~1703
[19]党瑞荣,付岳峰.电容型高压设备绝缘在线监测系统的设计[J].电测与仪表, 2008, 45(4): 22~24
[20] Alireza Setayeshmehr, Alireza Akbari, Hossein Borsi, et al. On-line Monitoring of Power Factor (tanδ) and Capacitance of Transformer Bushings[C]. Proceedings of the 5th International Symposium on High Voltage Engineering, Beijing, China, August, 2005: 400
[21] Lu Fangcheng, Wang Nan, Chen Zhiye. Measurement of tgδBased on Absolute and Comparative Method[C]. Proceedings of ISEIM2001, Japan, Nov, 2001: 344~346
[22] Nitaigour Premchand Mahalik. A Digital Meter for Measuring Dissipation Factor[C]. Proceedings of the 5m International Conference on Properties and Applications of Dielectric Materials, Seoid, Koreu, May, 1997: 1129~1131
[23]左自强,徐阳,曹晓珑等.计算电容型电容型设备介质损耗因数的相关函数法的改进[J].电网技术, 2004, 28(18): 53~57
[24]邓岳华,阮绵晖,刘味果.高压设备绝缘在线监测系统的现场应用与分析[J].电网技术. 2004, 28(16): 69~72
[25]方先存,刘云鹏,李军.电容型设备绝缘在线监测系统的开发与应用[J].高电压技术, 2008, 34(6): 6~9
[26] Yimei Jia, Fuheng Su, Jun Liu. An on~line insulation monitoring system based on fieldbus[C]. In Proceedings of 2001 ISEIM & ACEID, Himeji, Japan, November 2001: 769~772
[27]高振国.影响介损在线检测结果的因素分析及诊断策略[J].沈阳工程学院学报(自然科学版)[J]. 2007, 3(1): 41~43
[28]王楠,律方成,李艳涛等.影响介损在线检测准确性的因素分析与探讨[J].电工技术杂志. 2003, 21(1): 43~45
[29]杨雪峰.影响油纸电容式套管介质损耗因数(tanδ)增大或不稳定因素的分析[J].电瓷避雷器, 1999, 6: 14~19
[30]金维芳.电介质物理学[M].机械工业出版社, 1997
[31]胡兆斌.绝缘材料工艺学[M].化学工业出版社, 2005
[32]朱琦.变压器油高温介质损耗因数不稳定原因分析[J].变压器,1999,36(12): 36~37
[33]单平,罗勇芬,徐大可等.绝缘监测用高精度微电流传感器研究[J].电力自动化设备, 2002, 22(11): 4~6
[34] Yuting Yan,Xishan Wen,Jiamin Hu,et al. On-line Monitoring the Tangent of Dielectric Dissipation FactorδUsing Double Polarities Cross Zero Comparing Method[C]. Proceedings of the 5th International Symposium on High Voltage Engineering, Beijing, China, August, 2005: 362
[35] Günther Ramm, Harald Moser. From the Calculable AC Resistor to Capacitor Dissipation Factor Determination on the Basis of Time Constants[J]. IEEE Transactions on Instrumentation and Measurement, 2001,50(2): 286~289
[36] Wang Nan, Lu Fang-cheng, Liang Ying. Application of Improved Harmonic Analysis Approach In On-line Measuring Dissipation Factor of HV Capacitive Equipments[C]. ICEMI2003, Taiyuan, China, August, 2003: 630~634
[37]杨晓东,唐超,廖瑞金等.电容型设备改进型介损数字化测量方法的研究[J].高压电器, 2007, 34(6): 460~462
[38] Günther Ramm, Harald Moser. New Multifrequency Method for the Determination of the Dissipation Factor of Capacitors and of the Time Constant of Resistors[J]. IEEE Transactions on Instrumentation and Measurement, 2005, 54(2): 521~524
[39]徐志钮,律方成,汪佛池等.用加Hanning窗插值高阶正弦拟合法测介损角测量[J].高电压技术, 2007, 33(4): 05~35
[40]徐志钮,律方成,李和明.存在脉冲噪声情况下的介损角算法[J].电力自动化设备, 2008, 28(2): 45~48
[41] Djokic, B. So, E. Phase measurement of distorted periodic signals based on nonsynchronous digital filtering[J]. IEEE Transactions on Instrumentation and Measurement, 50(4): 864~867
[42]徐志钮,律方成,李和明.加Blackman-Harris窗插值算法仿真介损角测量[J].高电压技术,2007,33(3): 401~801
[43]王楠.电容型设备绝缘在线监测与故障诊断的研究(博士论文) [D].保定:华北电力大学, 2004
[44]柴旭峥,文习山,关根志等.绝缘在线监测采样数据的两种预处理算法[J].高电压技术, 2002, 28(9): 26~27
[45]由建,王文娣,陈少伟等.电流互感器介质损耗因数与温度的关系[J].变压器, 2006, 43 (11): 35~38
[46]孙立蓉,王华军.纸介质材料电子位移极化理论[J].绝缘材料, 2005, 38(4): 17~19
[47] N. Wang, F. C. Lu, H. M. Li. Analytical Processing of On-line Monitored Dissipation Factor Based on Morphological Filter[J]. IEEE Transactions onDielectrics and Electrical Insulation, 2004, 11(5): 840~846
[48]王楠,律方成.基于小波奇异性检测的在线监测数据处理[J].电工技术学报, 2003, 18(4): 61~64
[49]王楠,律方成,刘云鹏等.自适应广义形态滤波方法在介损在线监测数据处理中的应用研究[J].中国电机工程学报, 2004, 24(2): 161~165
[50]王楠,律方成,刘云鹏等.介损在线监测数据趋势提取方法的研究[J].高压电器, 2004, 40(1): 5~8
[51] Yang Li, Yang Minzhong, Yan Zhang, et al. Extraction of symptom for on-line diagnosis of power equipment based on method of time series analysis[C]. In: Proceedings of the 6th ICPADM, Xi’an, China, June 21-26,2000: 314~317
[52]王红斌.电容式电压互感器附加相位差对绝缘在线监测的影响[J].高压电器, 2003, 39(4): 64~65
[53] Pei Wang, M R Raghuveer, et al. A Digital Technique for The On~line Measurement of Dissipation Factor and Capacitance[J]. IEEE Transactions on Dielectric and Electrical Insulation, 2001, 8(2): 228~232
[54]史保壮,杨莉,冯德开等.智能技术在绝缘在线诊断系统中的应用[J].高压电器, 2001, 37(1): 32~34
[55]黄新红,廖瑞金,胡雪松等.“综合相对测量法”于介质损耗在线检测中的应用[J].高压电器, 2001, 37(6): 1~3
[56] Mark F Lachman, et al. On~line Diagnostic of High~voltage Bushings and Current Transformers Using the Sum Current Method[J]. IEEE Transactions on Power Delivery, 2000, 15(1): 155~162
[57]金之俭,黄结成.三相泄漏电流和的变化反映容性设备的绝缘状况[J].高电压技术, 2001, 27(6):12~13
[58] Baozhuang Shi, Li Yang, Hongbin Wang. Studies on the effect of influencing factors on condition monitoring of HV substation equipment[C]. In Proceedings of 2001 ISEIM & ACEID, Himeji, Japan, November 2001: 753~756
[59]王楠,律方成,李和明.灰关联分析在电容型设备绝缘故障诊断中的应用初探[J].高压电器, 2003, 39(5): 32~35
[60] Yin Dejun, Liu Beiying. Experience of condition based maintenance for power equipment insulation[C]. In Proceedings of 2001 ISEIM & ACEID, Himeji, Japan, November 2001: 198~200
[61] Shi Baozhuang, Yang Li, Wang Hongbin, et al. Instrumentation of online insulation monitoring of HV apparatus[C]. In: Proceedings of the 6th ICPADM, Xi’an, China,June, 2000: 713~716
[62] Shi Baozhuang, Yang Li, Wang Hongbin, et al. An online insulation diagnostic technique for HV apparatuses base on pertinency[C]. In: Proceedings of the 6th ICPADM, Xi’an, China, June 21-26, 2000: 705~708
[63] Allan D et al. New techniques for monitoring the insulation quality of in~service HV apparatus[J]. IEEE Transactions on Electrical Insulation, 1992, 27(3): 578~581
[64]徐师华.国内外人工气候控制装置应用发展的确概述[J].农业工程学报, 1989, 5(4): 16~21
[65]舒立春.复杂环境中绝缘子交流闪络特性及校正方法研究[博士学位论文].重庆:重庆大学,2002
[66]刘有为.应用新型人工气候室研究长串绝缘子的工频污闪特性[J].电网技术, 2002,26(3):46~48
[67]刘国强,赵凌志. Ansoft工程电磁场有限元分析[M].北京:电子工业出版社,2005
[68] National Instruments Corporation. Virtual Instruments. http://www.ni.com,2005
[69]胡文平,尹项根,张哲.基于虚拟仪器技术的电力设备在线监测[J].高压电器, 2003, 39(4): 38~40
[70]蒋兴良,舒立春,张永记,等.人工污秽下盐/灰密对普通悬式绝缘子串交流闪络特性的影响[J].中国电机工程学报,2006,26(15): 24~28
[71]孙才新,李俭,郑海平等.基于灰色面积关联度分析的电力变压器绝缘故障诊断方法[J].电网技术, 2002, 26(7): 24~29
[72]吕锋.灰色系统关联度之分辨系数的研究[J].系统工程理论与实践, 1997, 17(6): 49~54
[73]周宇阳,陈汉平,王炜哲等.故障诊断灰色数学模型[J].中国电机工程学报, 2002, 22(6): 146~151
[74]刘思峰,郭天榜,党耀国等.灰色系统理论及其应用[M].北京:科学出版社, 1999
[75]程岩,黄梯云.粗糙集中定量关联规则的发现及其规则约简的方法研究[J].管理工程学报, 2001, 15(3): 73~77
[76]张建兴,律方成,刘云鹏,谭磊,赵亚平.高压绝缘子泄漏电流与温、湿度的灰关联分析[J].高电压技术,2006,32(1): 40~41
[77]丁国成,律方成,李燕青,刘云鹏.灰关联分析用于分析环境因素对MOA在线监测的影响[J].高压电器, 2006, 42(3): 196~198
[78]杜树新,吴铁军.用于回归估计的支持向量机方法[J].系统仿真学报, 2005, 15(11): 1580~1586
[79]李凌均,张周锁,何正嘉.基于支持向量机的机械设备状态趋势预测研究[J].西安交通大学学报, 2004, 38(3): 230~234
[80]焦尚彬,刘丁,郑岗,张青.基于最小二乘支持向量机得绝缘子等值附盐密度预测[J].中国电机工程学报, 2006, 26(2): 149~153
[81]赵永平,孙健国.基于滚动窗法最小二乘支持向量机的稳健预测模型[J].模式识别与人工智能, 2008, 21(1): 1~5
[82]丁明,石雪梅.基于遗传算法的电力市场环境下电源规划的研究[J].中国电机工程学报, 2006, 26(21): 43~49
[83]孙力勇,张焰,蒋传文.基于矩阵实数编码遗传算法求解大规模机组组合问题[J].中国电机工程学报, 2006, 26(2): 82~87
[84] Riedman N,Geiger D,Goldszmidt M.Bayesian network classifiers[J].Machine Learning,l997,29:13l~163.
[85] Xiang, Y., Poole, D., Beddoes, M. P.. Multiply sectioned Bayesian networks and junction forests for large knowledge based systems[J], Computational Intelligence, 1993, 9 (2): 171~220.
[86] Fengzhan Tian, Hongwei Zhang, Yuchang Lu, et. al. Incremental Learning of Bayesian Networks[C]. Proceeding. Press of Japan Advanced Institute of Science and Technology(KSS’2001), Dalian, China, September 2001:169~178
[87] Zhang hongwei, Tian fengzhan, Lu yuchang. A general algorithm for approximate inference in Multiply Sectioned Bayesian network[J]. The Fourth International Symposium on Intelligent Data Analysis 2001, Cascais, Portugal, September 2001: 330~339
[88]胡卫华,朱永利.贝叶斯网络推理算法的研究和实现[N].华北电力大学学报,2004,31(5): 63~65.
[89] Wang Yongqiang, Lu Fangcheng, Li Heming. The Fault Diagnosis Method for Electrical Equipment Based on Bayesian Network[C],ICEMS2005,Nanjing, China, September 2005: 26~30
[90] Wang Yongqiang, Lu Fangcheng, Li Heming. The Fault Diagnosis Method for Power Transformer Based on BN And DGA[C]. ISEIM2005,Kitakyushu Japan, Jun., 2005: 476~479
[91]蒋国萍,陈英武.时间贝叶斯网络及其概率推理[J].管理科学学报,2007,10(2): 12~18
[92] Eitel J M, Lauria Peter J. Duchessi. A methodology for developing baysian networks: an application to information technology(IT) implementation[J]. Eropean Journal of Operational Research, 2007, 179: 234~252
[93]李雪,龚龙庆.基于贝叶斯网络的证据目标模型及推理算法研究.微电子学与计算机,2007,24(8): 149~151
[94]熊浩,孙才新,杜鹏,代姚,王谦.基于物元理论的电力变压器状态综合评估[J].重庆大学学报(自然科学版),2006,29(10):24~28.
[95]金文,陈长征,金志浩,闻邦椿.燃气轮发电机组多故障诊断的物元分析方法[J].中国电机工程学报, 2007,27(17): 57~60.
[96]黄文涛,赵学增,王伟洁,代礼周.基于物元模型的电力变压器故障的可拓诊断方法[J].电力系统自动化,2004,28(13): 45~49.
[97] Lifeng Liu, Caixin Sun, Quan Zhou. A novel electrical equipment on~line monitoring system based on geographic information system[C]. In Proceedings of 2001 ISEIM & ACEID, Himeji, Japan, November 2001: 205~208
[98] Zhang Guangchun, Tong Xiaoyang, Zou Siyi, et al. A novel insulation on-line monitoring and fault diagnosis system used for traction substation[C]. In: Conference Record of the 2002 IEEE International Symposium on Electrical Insulation, Boston, MA USA, April, 2002: 199~202
[99] Lin Du, Zhu Deheng, Li Fuqi, et al. A distributed on-line monitoring and diagnosis system of power equipment[C]. In Proceedings of the 6th ICPADM, Xi’an, China, June, 2006: 668~671
[100] Tu Yanming, Yan Ping, Guo Zhongjun. Predictive maintenance strategy based upon management information system[C]. In Proceedings of 2001 ISEIM & ACEID, Himeji, Japan, November 2001: 225~228
[101] Maragos P, Schafer R W. Morphological filters– Part II: Their relations to median, order-statistics, and stack filters[J]. IEEE Trans. On Acoustics, Speech and Signal Processing, 1987, 35(8): 1170~1184
[102] Jiangtao Xi, Chicharo J.F. A new algorithm for improving the accuracy of periodic signal analysis [J]. IEEE Trans on IM,1996,45(4):827~830
[103] Mallat. Singularity detection and processing with wavelets[J]. IEEE Trans on IT,1992,38(2): 617
[104] Huiping Zhang, Kexiong Tan. The analysis of on~line monitoring results for capacitive type equipment[C]. In Proceedings of 2001 ISEIM & ACEID,Himeji,Japan,November 2001: 100~103
[105] MAXIM data sheet of MAX125. Http://www.maximonline.com,2006
[106]吴文传,张伯明,汤磊.支持SCADA/PAS/DTS一体化的图形系统[J].电力系统自动化,2001,25(5): 45~49
[107] Wang Nan, Liang Ying, Lu Fangcheng. On-line Insulation Monitoring SystemBased on ASP Technique[C]. Riupeeec2003, Hongkong, August, 2003: 52~53