Chemical Sensing Strategies for Real-Time Monitoring of Transformer Oil: A Review

溶解气体分析 软件可移植性 化学传感器 状态监测 系统工程 变压器 软件部署 可用性 机油分析 计算机科学 变压器油 电气工程 嵌入式系统 工程类 电压 石油工程 物理化学 软件工程 化学 程序设计语言 人机交互 电极
作者
Chenhu Sun,Paul R. Ohodnicki,Emma Stewart
出处
期刊:IEEE Sensors Journal [Institute of Electrical and Electronics Engineers]
卷期号:17 (18): 5786-5806 被引量:96
标识
DOI:10.1109/jsen.2017.2735193
摘要

Power transformers are a central component in the field of energy distribution and transmission. The early recognition of incipient faults in operating transformers is substantially cost effective by lessening impromptu blackouts. A standout amongst the most responsive and dependable strategies utilized for assessing the health of oil filled electrical equipment is dissolved gas analysis (DGA). Nowadays, there is an expanding requirement for better nonintrusive diagnostic and online monitoring tools to survey the internal state of the transformers. Chemical sensors are viewed as a key innovation for condition monitoring of transformer health, coordinating the non-invasiveness with typical sensor features, such as cost, usability, portability, and the integration with the data networks. Low-cost chemical sensors-based DGA techniques are expected to drastically augment the diagnostic abilities empowering the deployment on a broader range of oil filled power assets. The recent development involves both specific sensors designed to detect individual dissolved gas in transformer oil and non-specific sensors, operated in near ambient conditions, with the potential to be applied in a DGA system. In this paper, general background and operating guidelines of DGA are presented to address the origin of the gas formation, methods for their detection and the interpretation of the results by data analytics. The recent significant interest and advancements in chemical sensors to DGA applications are reviewed. Future research perspectives and challenges for the development of novel DGA chemical sensors are also discussed.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
猛男航完成签到,获得积分10
刚刚
我是老大应助qujue001采纳,获得10
1秒前
1秒前
1秒前
豆豆发布了新的文献求助10
2秒前
2秒前
zyx030发布了新的文献求助10
2秒前
自信绮菱发布了新的文献求助10
2秒前
李健的小迷弟应助shuan采纳,获得30
2秒前
2秒前
英俊的筝发布了新的文献求助10
3秒前
4秒前
三金发布了新的文献求助10
4秒前
丹丹完成签到,获得积分10
5秒前
Owen应助热心市民王先生采纳,获得10
5秒前
英俊的铭应助重要的平文采纳,获得30
6秒前
6秒前
寻觅发布了新的文献求助10
6秒前
aojuan完成签到 ,获得积分10
7秒前
一鸣完成签到,获得积分20
8秒前
哦东东完成签到,获得积分10
8秒前
8秒前
平常的以冬完成签到,获得积分10
9秒前
紫色奶萨完成签到,获得积分10
9秒前
张对对发布了新的文献求助10
9秒前
卢皮卡发布了新的文献求助10
10秒前
XIEMIN发布了新的文献求助10
11秒前
调研昵称发布了新的文献求助10
12秒前
12秒前
寻觅完成签到,获得积分10
12秒前
uwu完成签到,获得积分10
13秒前
13秒前
14秒前
15秒前
细腻梦安完成签到,获得积分10
15秒前
16秒前
17秒前
YYY应助QR采纳,获得10
18秒前
大模型应助QR采纳,获得10
18秒前
18秒前
高分求助中
Production Logging: Theoretical and Interpretive Elements 2500
Востребованный временем 2500
Aspects of Babylonian celestial divination : the lunar eclipse tablets of enuma anu enlil 1500
Agaricales of New Zealand 1: Pluteaceae - Entolomataceae 1040
Healthcare Finance: Modern Financial Analysis for Accelerating Biomedical Innovation 1000
Classics in Total Synthesis IV: New Targets, Strategies, Methods 1000
지식생태학: 생태학, 죽은 지식을 깨우다 600
热门求助领域 (近24小时)
化学 医学 材料科学 生物 工程类 有机化学 生物化学 纳米技术 内科学 物理 化学工程 计算机科学 复合材料 基因 遗传学 物理化学 催化作用 细胞生物学 免疫学 电极
热门帖子
关注 科研通微信公众号,转发送积分 3459147
求助须知:如何正确求助?哪些是违规求助? 3053698
关于积分的说明 9037829
捐赠科研通 2742963
什么是DOI,文献DOI怎么找? 1504592
科研通“疑难数据库(出版商)”最低求助积分说明 695334
邀请新用户注册赠送积分活动 694644