为了分析和评估500 k V交联聚乙烯(XLPE)电力电缆线路的绝缘状况并开展电缆绝缘诊断,基于超高压电力电缆的局部放电机理和局部放电信号衰减特性,首次提出了应用分布式局部放电监测技术进行500 k V电力电缆在线监测的新模式。实践中发现...为了分析和评估500 k V交联聚乙烯(XLPE)电力电缆线路的绝缘状况并开展电缆绝缘诊断,基于超高压电力电缆的局部放电机理和局部放电信号衰减特性,首次提出了应用分布式局部放电监测技术进行500 k V电力电缆在线监测的新模式。实践中发现有3种现场局部放电提取信号方式可以满足500 k V电力电缆在线监测的实际需要。通过采用分布式时频分析技术,有效地解决了500 k V电力电缆绝缘缺陷的识别问题,提高了绝缘缺陷定位的精度。应用局部放电图谱库大数据分析技术及3图谱局部放电识别法,首次成功实现了500 k V电力电缆的绝缘诊断。开发了局部放电信号智能式进阶报警策略,提高了局部放电报警的可靠性。研究成果在国内首条长距离敷设的500 k V交联聚乙烯(XLPE)电力电缆线路上得到了成功应用。研究认为综合应用分布式时频分析、3图谱局部放电识别法和智能式进阶报警策略等分布式局部放电在线监测新技术,可以实现500 k V电力电缆绝缘缺陷的识别、定位和诊断;将对国内后续500 k V电力电缆开展局部放电监测和缺陷识别具有积极的指导意义。展开更多
A variation pixels identification method was proposed aiming at depressing the effect of variation pixels, which dilates the theoretical hyperspectral data simplex and misguides volume evaluation of the simplex. With ...A variation pixels identification method was proposed aiming at depressing the effect of variation pixels, which dilates the theoretical hyperspectral data simplex and misguides volume evaluation of the simplex. With integration of both spatial and spectral information, this method quantitatively defines a variation index for every pixel. The variation index is proportional to pixels local entropy but inversely proportional to pixels kernel spatial attraction. The number of pixels removed was modulated by an artificial threshold factor α. Two real hyperspectral data sets were employed to examine the endmember extraction results. The reconstruction errors of preprocessing data as opposed to the result of original data were compared. The experimental results show that the number of distinct endmembers extracted has increased and the reconstruction error is greatly reduced. 100% is an optional value for the threshold factor α when dealing with no prior knowledge hyperspectral data.展开更多
文摘为了分析和评估500 k V交联聚乙烯(XLPE)电力电缆线路的绝缘状况并开展电缆绝缘诊断,基于超高压电力电缆的局部放电机理和局部放电信号衰减特性,首次提出了应用分布式局部放电监测技术进行500 k V电力电缆在线监测的新模式。实践中发现有3种现场局部放电提取信号方式可以满足500 k V电力电缆在线监测的实际需要。通过采用分布式时频分析技术,有效地解决了500 k V电力电缆绝缘缺陷的识别问题,提高了绝缘缺陷定位的精度。应用局部放电图谱库大数据分析技术及3图谱局部放电识别法,首次成功实现了500 k V电力电缆的绝缘诊断。开发了局部放电信号智能式进阶报警策略,提高了局部放电报警的可靠性。研究成果在国内首条长距离敷设的500 k V交联聚乙烯(XLPE)电力电缆线路上得到了成功应用。研究认为综合应用分布式时频分析、3图谱局部放电识别法和智能式进阶报警策略等分布式局部放电在线监测新技术,可以实现500 k V电力电缆绝缘缺陷的识别、定位和诊断;将对国内后续500 k V电力电缆开展局部放电监测和缺陷识别具有积极的指导意义。
基金Projects(61571145,61405041)supported by the National Natural Science Foundation of ChinaProject(2014M551221)supported by the China Postdoctoral Science Foundation,China+3 种基金Project(LBH-Z13057)supported by the Heilongjiang Postdoctoral Science Found,ChinaProject(ZD201216)supported by the Key Program of Heilongjiang Natural Science Foundation,ChinaProject(RC2013XK009003)supported by the Program of Excellent Academic Leaders of Harbin,ChinaProject(HEUCF1508)supported by the Fundamental Research Funds for the Central Universities,China
文摘A variation pixels identification method was proposed aiming at depressing the effect of variation pixels, which dilates the theoretical hyperspectral data simplex and misguides volume evaluation of the simplex. With integration of both spatial and spectral information, this method quantitatively defines a variation index for every pixel. The variation index is proportional to pixels local entropy but inversely proportional to pixels kernel spatial attraction. The number of pixels removed was modulated by an artificial threshold factor α. Two real hyperspectral data sets were employed to examine the endmember extraction results. The reconstruction errors of preprocessing data as opposed to the result of original data were compared. The experimental results show that the number of distinct endmembers extracted has increased and the reconstruction error is greatly reduced. 100% is an optional value for the threshold factor α when dealing with no prior knowledge hyperspectral data.