吴勋,谢剑锋,杜航,黎灼佳,王志毅,刘志阳,刘刚
WU Xun,XIE Jianfeng,DU Hang,LI Zhuojia,WANG Zhiyi,LIU Zhiyang,LIU Gang

• 1:广东电网有限责任公司东莞供电局
• 2:华南理工大学电力学院(广东省绿色能源技术重点实验室)

摘要(Abstract)：

为提升高压电缆缓冲层烧蚀状态诊断的可靠性，探究了特征气体与烧蚀程度的关联机制。针对现有研究中对醛类气体定量分析不足的问题，通过空气与氮气环境下的缓冲层热解实验，结合气相色谱法（用于非醛类气体）和酚试剂分光光度法（用于醛类气体）进行定量分析，以研究产气特性。实验结果表明：在空气环境中，CO2（二氧化碳）是主要产物，醛类浓度与烧蚀质量损失呈正相关；在氮气环境中，CO（一氧化碳）和H2（氢气）的占比及醛类浓度升高。基于23组在运电缆气样检测与开窗验证数据，构建多元线性回归模型进行分析，验证了实验结果。研究结果明确了醛类气体与烧蚀程度的正相关性，并揭示了其与CO的负向关联特性，为综合评估缓冲层状态提供了新的参数依据。
To enhance the reliability of diagnosing ablation in high-voltage cable buffer layers, this paper investigates the correlation between characteristic gases and ablation severity. Addressing the lack of quantitative aldehyde analysis in prior research, pyrolysis experiments of the buffer layers were conducted in air and nitrogen environments, with gas chromatography(for non-aldehyde gases) and the phenol reagent spectrophotometry(for aldehyde gases) employed for quantitative analysis. Results show that in air, CO2(carbon dioxide) dominates, and aldehyde concentrations correlate positively with mass loss. Under nitrogen, CO(carbon monoxide) and H2(hydrogen) proportions increase alongside aldehydes. A multiple linear regression model, validated by 23 in-service cable gas samples and window tests, confirms aldehydes' strong positive correlation with ablation severity and negative correlation with CO. This work establishes aldehydes as a novel indicator for buffer layer assessment.

关键词(KeyWords)： 高压电缆;阻水缓冲层;醛类气体;烧蚀
high-voltage cable;water-blocking buffer layer;aldehyde gases;ablation

Abstract:

Keywords:

基金项目(Foundation): 中国博士后科学基金面上资助项目（2024M760942）;; 广东电网有限责任公司东莞供电局科技项目（031900KC23110060(GDKJXM20231243)

作者(Author): 吴勋,谢剑锋,杜航,黎灼佳,王志毅,刘志阳,刘刚
WU Xun,XIE Jianfeng,DU Hang,LI Zhuojia,WANG Zhiyi,LIU Zhiyang,LIU Gang

DOI: 10.19585/j.zjdl.202512011

参考文献(References)：

• [1]张泽晋，陈彦伊，廖雁群，等.高压电缆外护套特征阻抗建模及破损检测方法[J].浙江电力，2024,43(9):78-87.ZHANG Zejin,CHEN Yanyi,LIAO Yanqun,et al.Characteristic impedance modeling and damage detection method for high-voltage cable sheath[J].Zhejiang Electric Power,2024,43(9):78-87.
• [2]LI P F,CHEN Y B,HUANG H W,et al.Investigation of corrosion behavior of galvanized steel as submarine cable armor in seawater under weak magnetic fields[J].International Journal of Electrochemical Science,2023,18(9):100264.
• [3]彭向阳，姚驰，余欣，等.硅烷接枝聚丙烯的直流电性能与陷阱机制[J].高电压技术，2023,49(11):4480-4489.PENG Xiangyang,YAO Chi,YU Xin,et al.DC electrical properties and trap mechanism of silane-grafted polypropylene[J].High Voltage Engineering,2023,49(11):4480-4489.
• [4]严有祥，徐子峻，尤天鹏，等.高压电缆缓冲层烧蚀的成因分析[J].高压电器，2023,59(2):184-189.YAN Youxiang,XU Zijun,YOU Tianpeng,et al. Cause analysis of buffer layer ablation in high voltage cable[J].High Voltage Apparatus,2023,59(2):184-189.
• [5]孟晓凯，俞华，芦竹茂，等.高压交联聚乙烯电缆缓冲层烧蚀机理[J].高分子材料科学与工程，2025,41(1):136-144.MENG Xiaokai,YU Hua,LU Zhumao,et al. Erosion mechanisms of high voltage cross-linked polyethylene cable buffer layers[J].Polymer Materials Science&Engineering,2025,41(1):136-144.
• [6]高建，张浩然，张可，等.高压电缆缓冲层烧蚀缺陷超声检测实验[J].电力工程技术，2024,43(1):174-180.GAO Jian,ZHANG Haoran,ZHANG Ke,et al. Experiments on the ultrasonic detection of buffer layer ablation defects in high-voltage cables[J].Electric Power Engineering Technology,2024,43(1):174-180.
• [7]王伟平，周恒，梁国坚，等.110 kV单芯电缆缆芯暂态温度径向感知模型研究[J].智慧电力，2023(10):103-110.WANG Weiping,ZHOU Heng,LIANG Guojian,et al.Transient temperature radial sensing model for cable cores of 110 kV single core cables[J].Smart Power,2023(10):103-110.
• [8]袁建军，欧阳本红，夏荣，等.高压电缆局部放电在线监测装置有效性测评方法研究及现场应用[J].高电压技术，2023,49（增刊1）:17-23.
• [9]SAVILL T,JEWELL E.Techniques for in situ monitoring the performance of organic coatings and their applicability to the pre-finished steel industry:a review[J].Sensors,2021,21(19):6334.
• [10]何朝良，晏婷，马天宇，等.基于深度学习的在役高压电缆缺陷计算机断层扫描检测[J].光学学报，2025,45(2):0215001.HE Chaoliang,YAN Ting,MA Tianyu,et al. In-service high-voltage cable defect detection using computed tomography based on deep learning[J].Acta Optica Sinica,2025,45(2):0215001.
• [11]刘顺满，王健，程皓，等.高压XLPE电缆缓冲层烧蚀缺陷特征气体分析[J].广东电力，2022,35(6):116-125.LIU Shunman,WANG Jian,CHENG Hao,et al.Analysis on characteristic gas of ablative defect in buffer layer of high voltage XLPE cable[J].Guangdong Electric Power,2022,35(6):116-125.
• [12]LI Y,LIU Y M,ZHAO Q,et al. Mechanism of status evaluation for water blocking buffer layer of high-voltage cable based on characteristic gas analysis[J].IEEE Transactions on Dielectrics and Electrical Insulation,2024,31(4):2216-2225.
• [13]张浩然，高建，武康宁，等.基于温度测量和气体分析的高压电缆缓冲层烧蚀故障检测技术[J].高电压技术，2023,49(12):4929-4937.ZHANG Haoran,GAO Jian,WU Kangning,et al.Detection technology of buffer layer ablation failure in high voltage cables based on temperature measurement and gases analysis[J]. High Voltage Engineering,2023,49(12):4929-4937.
• [14]BUXBAUM L H.The degradation of poly(ethylene terephthalate)[J]. Angewandte Chemie International Edition in English,1968,7(3):182-190.
• [15]BEDNAS M E,DAY M,HO K,et al.Combustion and pyrolysis of poly(ethylene terephthalate).I.The role of flame retardants on products of pyrolysis[J].Journal of Applied Polymer Science,1981,26(1):277-289.
• [16]VIJAYAKUMAR C T,PONNUSAMY E,BALAKRISHNAN T,et al.Thermal and pyrolysis studies of copolyesters[J].Journal of Polymer Science:Polymer Chemistry Edition,1982,20(9):2715-2725.
• [17]KHEMANI K C.A novel approach for studying the thermal degradation,and for estimating the rate of acetaldehyde generation by the chain scission mechanism in ethylene glycol based polyesters and copolyesters[J].Polymer Degradation and Stability,2000,67(1):91-99.
• [18]孙丽敏.浅析气相色谱仪计量标准的重复性试验[J].化学分析计量，2016,25(1):70-72.SUN Limin.Analysis of repeatability test of gas chromatography measurement standard[J]. Chemical Analysis and Meterage,2016,25(1):70-72.
• [19]国家疾控局.公共场所卫生检验方法第2部分：化学性指标：GB/T 18204.2—2025[S].北京：中国标准出版社，2025.
• [20]LIAO C L,SHI J F,ZHANG M,et al.Optical chemosensors for the gas phase detection of aldehydes:mechanism,material design,and application[J]. Materials Advances,2021,2(19):6213-6245.
• [21]QI X M,CHEN Q,ZHOU H J,et al.Innovative development path of hands-on ability cultivation for college students combined with SPSS statistical analysis modeling based on innovation and entrepreneurship education orientation[J].Applied Mathematics and Nonlinear Sciences,2024,9(1):20241321.