Progress and Trends in Damage Detection Methods, Maintenance, and Data-driven Monitoring of Wind Turbine Blades – A Review

涡轮机 可再生能源 结构健康监测 涡轮叶片 工程类 风力发电 无损检测 分层(地质) 可靠性工程 状态监测 机械工程 结构工程 电气工程 生物 放射科 构造学 古生物学 医学 俯冲
作者
Kyungil Kong,Kirsten Dyer,Christopher J. Payne,Ian Hamerton,Paul M. Weaver
出处
期刊:Renewable Energy Focus [Elsevier]
卷期号:44: 390-412 被引量:52
标识
DOI:10.1016/j.ref.2022.08.005
摘要

In recent decades, renewable energy has attracted attention as a viable energy supply. Among renewable energy sources, offshore wind energy has been considerably growing since longer and larger wind turbine composite blades were deployed. The manufacture of the longer and larger composite blades leads to more wind energy production. However, the wind turbine composite blades are susceptible to damage and defects due to multiple structural loads and harsh operating environments in service. Hence, condition monitoring and maintenance of wind turbine composite blades require in-depth investigation to prevent structural damage and defects and to improve remaining lifetime of the composite structure. The types of damage and defects in wind turbine composite blades are typically delamination, debonding, and cracks, which are influenced by the intrinsic structural nonlinearities, manufacturing process stage, and harsh environmental impacts in service. For these reasons, the regular condition monitoring of the composite blades is required to assess degradation in performance and structural condition to minimise levelised energy costs for maintenance. To improve reliability and sustainability, data-driven inspection with digital twin technology is reviewed as a trend of condition monitoring frameworks. Advanced functional materials to potentially assist current non-destructive testing (NDT) methods or to be utilised as self-sensing performance are reviewed. From manufacturing to the system level, a comprehensive review on progress and trends of monitoring of wind turbine composite blades is carried out including physics-based NDT methods, data fusion in sensor networks, automated system, mechanics, and digital twin technology with the environmental coupling.
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
共享精神应助颠颠的哦采纳,获得10
刚刚
北风歌完成签到,获得积分10
3秒前
3秒前
加贝发布了新的文献求助10
3秒前
zouqi发布了新的文献求助10
3秒前
4秒前
漠尘完成签到,获得积分10
4秒前
聪慧小燕发布了新的文献求助10
5秒前
未耕发布了新的文献求助10
7秒前
怡然奄应助zhaoyuepu采纳,获得30
7秒前
sxmt123456789完成签到,获得积分10
8秒前
8秒前
徐瑶瑶发布了新的文献求助10
8秒前
10秒前
ceeray23应助徐捷宁采纳,获得10
11秒前
小崔完成签到,获得积分10
11秒前
今后应助ipainkiller采纳,获得10
12秒前
852应助linjane采纳,获得10
13秒前
neckerzhu发布了新的文献求助10
14秒前
盛夏吹过晚风完成签到,获得积分20
16秒前
17秒前
用户12306完成签到,获得积分10
18秒前
whh发布了新的文献求助10
19秒前
20秒前
爱吃芒果果儿完成签到 ,获得积分10
20秒前
哈哈发布了新的文献求助10
21秒前
一二发布了新的文献求助10
22秒前
22秒前
汉堡包应助TIGun采纳,获得10
26秒前
29秒前
29秒前
30秒前
加贝完成签到,获得积分10
31秒前
cx发布了新的文献求助10
32秒前
颠颠的哦发布了新的文献求助10
32秒前
毛豆应助发酱采纳,获得10
32秒前
33秒前
惜风完成签到,获得积分10
33秒前
academician发布了新的文献求助10
34秒前
ipainkiller发布了新的文献求助10
35秒前
高分求助中
中央政治學校研究部新政治月刊社出版之《新政治》(第二卷第四期) 1000
Hopemont Capacity Assessment Interview manual and scoring guide 1000
Classics in Total Synthesis IV: New Targets, Strategies, Methods 1000
Mantids of the euro-mediterranean area 600
【港理工学位论文】Telling the tale of health crisis response on social media : an exploration of narrative plot and commenters' co-narration 500
Mantodea of the World: Species Catalog Andrew M 500
Insecta 2. Blattodea, Mantodea, Isoptera, Grylloblattodea, Phasmatodea, Dermaptera and Embioptera 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 内科学 物理 纳米技术 计算机科学 基因 遗传学 化学工程 复合材料 免疫学 物理化学 细胞生物学 催化作用 病理
热门帖子
关注 科研通微信公众号,转发送积分 3434032
求助须知:如何正确求助?哪些是违规求助? 3031223
关于积分的说明 8941345
捐赠科研通 2719217
什么是DOI,文献DOI怎么找? 1491694
科研通“疑难数据库(出版商)”最低求助积分说明 689392
邀请新用户注册赠送积分活动 685523