海底电缆绝缘油传感器的标定方法研究及优化*

doi:10.11978/2025141

热带海洋学报 ›› 2026, Vol. 45 ›› Issue (1): 188-197.doi: 10.11978/2025141CSTR: 32234.14.2025141

• 海洋调查与观测 • 上一篇

海底电缆绝缘油传感器的标定方法研究及优化^*

庄瑞雪¹(), 许占堂², 施震²(), 张军¹, 谢梦圆¹, 熊兰兰³, 胡鑫³, 赵科泉⁴

¹暨南大学广州市可见光通信重点实验室, 广东广州 510632
²热带海洋环境实验室(中国科学院南海海洋研究所), 广东广州 510301
³广东省海洋发展规划研究中心, 广东广州 510220
⁴中国科学院大学, 北京 100049

收稿日期:2025-08-20 修回日期:2025-09-03 出版日期:2026-01-10 发布日期:2026-01-30
通讯作者: 施震。email: shizhen@scsio.ac.cn
作者简介:
庄瑞雪(2000—), 女, 广东省汕尾市人, 硕士研究生, 从事光学设计和光谱分析应用研究。email: 2441403626@qq.com
*感谢暨南大学光学组全体成员的指导, 感谢中国科学院南海海洋研究所海洋光学组老师、同学对现场试验的支持
基金资助:
自然资源部2024年度部省合作项目(2024ZRBSHZ103); 充油海缆绝缘液体微量检测方法研究(QT2023-09-79); 广东省基础与应用基础研究基金(2025A1515012033)

Research and optimization on calibration of marine cable insulation oil sensors^*

ZHUANG Ruixue¹(), XU Zhantang², SHI Zhen²(), ZHANG Jun¹, XIE Mengyuan¹, XIONG Lanlan³, HU Xin³, ZHAO Kequan⁴

¹Guangdong Provincial Engineering Technology Research Center on Visible Light Communication, Jinan University, Guangzhou 510632, China
²Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China
³Guangdong Center for Marine Development Research, Guangzhou 510220, China
⁴University of Chinese Academy of Sciences, Beijing 100049, China

Received:2025-08-20 Revised:2025-09-03 Online:2026-01-10 Published:2026-01-30
Contact: SHI Zhen. email: shizhen@scsio.ac.cn
Supported by:
2024 Annual Ministry-Provincial Cooperation Project of the Ministry of Natural Resources(2024ZRBSHZ103); Research on Trace Detection Methods for Insulating Liquids in Oil-filled Submarine Cables(QT2023-09-79); Basic and Applied Basic Research Foundation of Guangdong Province(2025A1515012033)

摘要/Abstract

摘要：

海底电缆绝缘油传感器主要应用于海水中极低浓度绝缘油检测, 相比常规的水中油类传感器而言, 绝缘油检测对传感器标定流程和标准溶液制备提出了更严格的要求。本文提出新型标定方案, 设计了非接触式倒置标定结构, 通过避免探头接触溶液减少污染风险, 提升操作便利性与标定准确性; 采用了超声乳化技术制备标准溶液, 更接近海水溢油事故中自然形成的水油乳液状态; 系统探究了标定影响因素, 验证环境光干扰可忽略, 但需控制液面高度以降低气液界面信号干扰。与行业标准方法对比显示, 本方案标定结果的相对偏差为6%~10%, 在目标浓度范围内具备优异准确性。该方法为海洋生态环境监测提供了高可靠性技术支持。

关键词: 绝缘油, 传感器, 紫外荧光法, 标定

Abstract:

Marine cable insulation oil sensors are primarily applied for detecting extremely low concentrations of insulating oil in seawater. Compared to conventional water-oil sensors, the detection of insulating oil imposes stricter requirements on sensor calibration processes and the preparation of standard solutions. This paper introduces a novel calibration scheme that features a non-contact inverted calibration structure designed to reduce contamination risks, thereby enhancing operational convenience and calibration accuracy. Additionally, ultrasonic emulsification technology is employed to prepare standard solutions that more closely resemble the natural water-oil emulsion state formed during seawater oil spill accidents. A systematic investigation into calibration-influencing factors reveals that environmental light interference is negligible, whereas controlling the liquid level height is critical to minimize signal interference at the gas-liquid interface. A subsequent comparative analysis with industry-standard methods demonstrates that the relative deviation of the calibration results under this scheme ranges from 6% to 10%, exhibiting excellent accuracy within the target concentration range. This method provides highly reliable technical support for marine ecological environment monitoring.

Key words: insulating oil, sensor, ultraviolet fluorescence method, calibration

中图分类号:

P714.4

庄瑞雪, 许占堂, 施震, 张军, 谢梦圆, 熊兰兰, 胡鑫, 赵科泉. 海底电缆绝缘油传感器的标定方法研究及优化^*[J]. 热带海洋学报, 2026, 45(1): 188-197.

ZHUANG Ruixue, XU Zhantang, SHI Zhen, ZHANG Jun, XIE Mengyuan, XIONG Lanlan, HU Xin, ZHAO Kequan. Research and optimization on calibration of marine cable insulation oil sensors^*[J]. Journal of Tropical Oceanography, 2026, 45(1): 188-197.

图/表 7

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参考文献 38

[1]	郭晶晶, 王岚云, 2015. 紫外法和荧光法测定海水油类质控指标研究[J]. 化学工程与装备, (11): 199-204, 228 (in Chinese).
[2]	黄宏新, 2011. 高压充油电缆检测基础问题的研究[D]. 北京: 华北电力大学.
	HUANG HONGXIN, 2011. Research on fundamental issue of high-pressure[D]. Beijing: North China Electric Power University (in Chinese with English abstract).
[3]	李建超, 邓琥, 武志翔, 等, 2012. 水中油在线荧光检测系统的标定研究[J]. 自动化与仪表, 27(4): 53-56.
	LI JIANCHAO, DENG HU, WU ZHIXIANG, et al, 2012. Calibration of online system of examing oil-in-water using fluorescence[J]. Automation & Instrumentation, 27(4): 53-56 (in Chinese with English abstract).
[4]	李义, 禹海清, 董建芳, 等, 2010. 加标回收在水质分析中的应用及回收率计算方法[J]. 岩矿测试, 29: 597-600.
	LI YI, YU HAIQING, DONG JIANFANG, et al, 2010. Application of standard addition in water quality analysis and calculation methods for recovery rates[J]. Rock and Mineral Analysis, 29: 597-600 (in Chinese with English abstract).
[5]	梁树生, 朱志雄, 2024. 荧光法和紫外法测定海水中石油类的对比研究[J]. 广东化工, 51(20): 16-19.
	LIANG SHUSHENG, ZHU ZHIXIONG, 2024. Comparative study on the determination of petroleum in seawater by fluorescence and ultraviolet methods[J]. Guangdong Chemical Industry, 51(20): 16-19 (in Chinese with English abstract).
[6]	柳杰, 傅明利, 冯宾, 等, 2025. 基于荧光法的海底电缆绝缘油示踪检测装置[J]. 高电压技术: 1-11.
	LIU JIE, FU MINGLI, FENG BIN, et al, 2025. The tracer detection device for insulating oil in submarine cables based on the fluorescence method[J]. High Voltage Technology: 1-11 [2025-09-03]. https://doi.org/10.13336/j.1003-6520.hve.20242082 (in Chinese with English abstract).
[7]	栾晓宁, 王春艳, 李颖, 等, 2009. 从浓度定量分析探讨异丙醇作原油萃取剂的可行性[J]. 海洋湖沼通报, 31(2): 151-156.
	LUAN XIAONING, WANG CHUNYAN, LI YING, et al, 2009. Discussion on the feasibility of isopropanol as an extractant of crude oil on the basis of concentration quantitative analysis[J]. Transactions of Oceanology and Limnology, 31(2): 151-156 (in Chinese with English abstract).
[8]	罗登林, 丘泰球, 卢群, 2005. 超声波技术及应用(Ⅱ): 声化学技术在日化工业中的应用[J]. 日用化学工业, 35(6): 393-395.
	LUO DENGLIN, QIU TAIQIU, LU QUN, 2005. Ultrasound and its applications (Ⅱ): Applications of sonochemistry in daily chemical industry[J]. China Surfactant Detergent & Cosmetics, 35(6): 393-395 (in Chinese with English abstract).
[9]	马国明, 秦炜淇, 王思涵, 等, 2025. 海底电缆状态分布式光纤监测技术研究综述[J]. 中国电机工程学报, 45(1): 370-388.
	MA GUOMING, QIN WEIQI, WANG SIHAN, et al, 2025. Review of submarine cable condition monitoring based on distributed optical fiber sensing[J]. Proceedings of the CSEE, 45(1): 370-388 (in Chinese with English abstract).
[10]	彭三兵, 张鹏, 何斌, 等, 2024. 基于紫外荧光法的海上平台钻井液含油率检测研究[J]. 山东化工, 53(23): 189-191, 197.
	PENG SANBING, ZHANG PENG, HE BIN, et al, 2024. The test study of drilling fluid oil content in offshore platform based on ultraviolet fluorescence method[J]. Shandong Chemical Industry, 53(23): 189-191, 197 (in Chinese with English abstract).
[11]	王赛男, 许赞, 刘亮, 等, 2023. 一种便携式荧光测油仪在海上溢油应急监测中的适用性研究[J]. 中国环境监测, 39(3): 190-196.
	WANG SAINAN, XU ZAN, LIU LIANG, et al, 2023. Study on the applicability of a portable fluorescent oil-in-water analyzer to emergency monitoring of offshore oil spill[J]. Environmental Monitoring in China, 39(3): 190-196 (in Chinese with English abstract).
[12]	新疆维吾尔自治区市场监督管理局, 2021. 水质石油类的测定荧光光度法(DB 65/T 4369—2021)[S].
	Xinjiang Uygur Autonomous Region Market Supervision and Administration Bureau, 2021. Water quality-determination of petroleum-hydrocarbons-fluorescence spectrophotometric method (DB 65/T4369-2021)[S]. (in Chinese).
[13]	薛晓杰, 王诚熹, 姜巍巍, 2018. 正己烷紫外分光光度法测定地表水中石油类的方法改进[J]. 净水技术, 37(S1), 34-35, 60.
	XUE XIAOJIE, WANG CHENGXI, JIANG WEIWEI, 2018. Improvement of determination of petroleum in surface water by ultraviolet spectrophotometry with n-hexane[J]. Water Purification Technology, 37(S1): 34-35, 60.
[14]	杨铨, 冯伟, 邢龙辉, 等, 2024. 油液监测黏度传感器标定方法优化研究[J]. 润滑与密封, 49(5): 171-176.
	YANG QUAN, FENG WEI, XING LONGHUI, et al, 2024. Optimization of calibration method for viscosity sensor in oil monitoring[J]. Lubrication Engineering, 49(5): 171-176 (in Chinese with English abstract).
[15]	杨书会, 王延圣, 王文亮, 等, 2024. 多糖乳液的制备、乳化特性的影响因素及其应用研究进展[J]. 食品工业科技, 45(14): 398-407.
	YANG SHUHUI, WANG YANSHENG, WANG WENLIANG, et al, 2024. Research progress in preparation, influencing factors of emulsifying properties and application of polysaccharide emulsion[J]. Science and Technology of Food Industry, 45(14): 398-407 (in Chinese with English abstract).
[16]	叶欣, 张雪容, 王珏, 2010. 自动萃取仪对水中油类的萃取效率研究[J]. 福建分析测试, 19(3): 46-48.
	YE XIN, ZHANG XUERONG, WANG YU, 2010. Study on the extraction efficiency of oils in water by automatic extraction equipment[J]. Fujian Analysis & Testing, 19(3): 46-48 (in Chinese with English abstract).
[17]	张飞, 2015. 水中石油类和动植物油类萃取方式的比对研究[J]. 环境与发展, 27(2): 95-97.
	ZHANG FEI, 2015. Comparative studies of the methods to extract the amount of the petroleum oil and animal and plant oils contained in water[J]. Environment and Development, 27(2): 95-97 (in Chinese with English abstract). doi: 10.1016/j.envdev.2018.07.004
[18]	赵广立, 冯巍巍, 付龙文, 等, 2014. 基于紫外荧光法检测水中油含量的浸入式传感装置的研究[J]. 海洋通报, 33(1): 77-83.
	ZHAO GUANGLI, FENG WEIWEI, FU LONGWEN, et al, 2014. Research on a submersible oil-in-water detection probe based on ultraviolet fluorescence analysis technique[J]. Marine Science Bulletin, 33(1): 77-83 (in Chinese with English abstract).
[19]	中华人民共和国国家质量监督检验检疫总局, 2006. 荧光分光光度计( JJG 537-2006)[S].
	General administration of quality supervision, inspection and quarantine of the People's Republic of China, 2006. Fluorescence Spectrophotometer (JJG 537-2006)[S]. (in Chinese).
[20]	中华人民共和国国家质量监督检验检疫总局, 中国国家标准化管理委员会, 2007. 海洋监测规范第4部分:海水分析(GB 17378. 4-2007)[S]. 北京: 中国标准出版社.
	General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China, Standardization Administration of the People's Republic of China, 2007. Specifications for marine monitoring-Part 4: seawater analysis (GB 17378. 4-2007)[S]. Beijing: Standards Press of China (in Chinese).
[21]	ABOU SAMRA R M, ALI R R, 2024. Tracking the behavior of an accidental oil spill and its impacts on the marine environment in the Eastern Mediterranean[J]. Marine Pollution Bulletin, 198: 115887. doi: 10.1016/j.marpolbul.2023.115887
[22]	ALARURI S D, 2019. Multiwavelength laser induced fluorescence (LIF) LIDAR system for remote detection and identification of oil spills[J]. Optik, 181: 239-245. doi: 10.1016/j.ijleo.2018.12.073
[23]	BOOTH A, FLECK J, PELLERIN B A, et al 2023. Field techniques for fluorescence measurements targeting dissolved organic matter, hydrocarbons, and wastewater in environmental waters: Principles and guidelines for instrument selection, operation and maintenance, quality assurance, and data reporting[R/OL]// CALIFORNIA WATER SCIENCE CENTER, NEW YORK WATER SCIENCE CENTER, OREGON WATER SCIENCE CENTER, CARIBBEAN-FLORIDA WATER SCIENCE CENTER. Collection of water data by direct measurement. techniques and methods. Reston: U.S. Geological Survey [2025-09-03]. https://doi.org/10.3133/tm1D11.
[24]	BUSTAMANTE S, MANANA M, ARROYO A, et al, 2024. Evolution of graphical methods for the identification of insulation faults in oil-immersed power transformers: a review[J]. Renewable and Sustainable Energy Reviews, 199: 114473. doi: 10.1016/j.rser.2024.114473
[25]	DE CAROLIS G, ADAMO M, PASQUARIELLO G, 2014. On the estimation of thickness of marine oil slicks from sun-glittered, near-infrared MERIS and MODIS imagery: the Lebanon oil spill case study[J]. IEEE Transactions on Geoscience and Remote Sensing, 52(1): 559-573. doi: 10.1109/TGRS.2013.2242476
[26]	EYKELBOSH A, 2014. Short- and long-term health impacts of marine and terrestrial oil spills[R/OL]. Vancouver, B C: Prepared for the Regional Health Protection Program, Office of the Chief Medical Health Officer, Vancouver Coastal Health Office of the Chief Medical Health Officer, Vancouver Coastal Health [2025-09-03]. https://www.vch.ca/media/VCH-health-impacts-oilspill.pdf.
[27]	GARCIA-PINEDA O, STAPLES G, JONES C E, et al, 2020. Classification of oil spill by thicknesses using multiple remote sensors[J]. Remote Sensing of Environment, 236: 111421. doi: 10.1016/j.rse.2019.111421
[28]	LEIFER I, LEHR W J, SIMECEK-BEATTY D, et al, 2012. State of the art satellite and airborne marine oil spill remote sensing: Application to the BP Deepwater Horizon oil spill[J]. Remote Sensing of Environment, 124: 185-209. doi: 10.1016/j.rse.2012.03.024
[29]	LU YINGCHENG, SHI JING, HU CHUANMIN, et al, 2020. Optical interpretation of oil emulsions in the ocean-Part II: Applications to multi-band coarse-resolution imagery[J]. Remote Sensing of Environment, 242: 111778. doi: 10.1016/j.rse.2020.111778
[30]	OTREMBA Z, PISKOZUB J, 2004. Modelling the bidirectional reflectance distribution function (BRDF) of seawater polluted by an oil film[J]. Optics Express, 12(8): 1671-1676. pmid: 19474993
[31]	PAHLAVANZADEH F, KHALOOZADEH H, FOROUZANFAR M, 2025. Oil pipeline multiple leakage detection and localization based on sensor fusion[J]. Engineering Failure Analysis, 167: 109038. doi: 10.1016/j.engfailanal.2024.109038
[32]	RESCH-GENGER U, HOFFMANN K, HOFFMANN A, 2008. Standardization of fluorescence measurements: criteria for the choice of suitable standards and approaches to fit-for-purpose calibration tools[J]. Annals of the New York Academy of Sciences, 1130: 35-43. doi: 10.1196/nyas.2008.1130.issue-1
[33]	SINGH H, BHARDWAJ N, ARYA S K, et al, 2020. Environmental impacts of oil spills and their remediation by magnetic nanomaterials[J]. Environmental Nanotechnology, Monitoring & Management, 14: 100305.
[34]	TIANG S S L, LOW L E, ALI I, et al, 2024. Recent advances in ultrasonic cavitation technologies for emulsion preparation: a mini review. Current Opinion in Chemical Engineering[J], 45: 101046.
[35]	UDEPURKAR A P, CLASEN C, KUHN S, 2023. Emulsification mechanism in an ultrasonic microreactor: Influence of surface roughness and ultrasound frequency[J]. Ultrasonics Sonochemistry, 94: 106323. doi: 10.1016/j.ultsonch.2023.106323
[36]	WU W H, ESKIN D G, PRIYADARSHI A, et al, 2021. New insights into the mechanisms of ultrasonic emulsification in the oil-water system and the role of gas bubbles[J]. Ultrasonics Sonochemistry, 73: 105501. doi: 10.1016/j.ultsonch.2021.105501
[37]	XIE BEIBEI, YUAN LI, KONG DEMING, et al, 2021. Analysis of fluorescence simulation and experiments for sea surface oil film based on LIF[J]. Applied Optics, 60(18): 5439-5450. doi: 10.1364/AO.426451
[38]	ZAJAREVICH N, SLEZAK V, PEURIOT A, et al, 2013. Photoacoustic detection of perfluorocarbon tracers in air for application to leak detection in oil-filled cables[J]. International Journal of Thermophysics, 34(8): 1444-1450. doi: 10.1007/s10765-013-1446-7

组别	空白信号值	0.52mg·L⁻¹信号值	0.79mg·L⁻¹信号值
实验组(阳光照射)测量值	0.0182008	0.0578266	0.0768013
	0.0182312	0.057790875	0.0766355
	0.0181955	0.0579012	0.0764461
平均值	0.01821±(4.8×10⁻⁴)	0.05782±(8.7×10⁻⁴)	0.07663±(6.8×10⁻⁴)
对照组(遮光条件)测量值	0.018188	0.0578846	0.0767259
	0.0182776	0.0578263	0.0769018
	0.0182434	0.0579099	0.0762525
平均值	0.001824±(5.1×10⁻⁴)	0.05787±(6.3×10⁻⁴)	0.07663±(7.4×10⁻⁴)
P	0.83199	0.80012	0.99593

编号	加标浓度/(mg·L^-1)	水样浓度/(mg·L^-1)	回收率
1	1.970	0.132	97.31%
2	2.007	0.131	99.36%
3	2.003	0.130	99.16%
4	0.945	0.138	106.95%
5	0.945	0.132	107.65%
6	0.945	0.131	107.70%

样品编号	测定次数	本方法测量浓度/(mg·L⁻¹)	荧光光度法测量浓度/(mg·L⁻¹)	相对偏差
1	1	0.384	0.366	6.11%
	2	0.383	0.377
	3	0.380	0.338
	平均值	0.382	0.360
2	1	0.788	0.772	5.72%
	2	0.791	0.753
	3	0.791	0.718
	平均值	0.790	0.748
3	1	1.982	1.791	9.49%
	2	1.987	1.792
	3	1.991	1.860
	平均值	1.987	1.814
4	1	3.594	3.379	5.88%
	2	3.604	3.410
	3	3.605	3.415
	平均值	3.601	3.401

海底电缆绝缘油传感器的标定方法研究及优化^*

Research and optimization on calibration of marine cable insulation oil sensors^*

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海底电缆绝缘油传感器的标定方法研究及优化*

Research and optimization on calibration of marine cable insulation oil sensors*

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海底电缆绝缘油传感器的标定方法研究及优化^*

Research and optimization on calibration of marine cable insulation oil sensors^*