用于风力涡轮机扭矩传感器蠕变分析的算法

Algorithms Pub Date : 2024-02-07 DOI:10.3390/a17020077
Jacek G. Puchalski, J. Fidelus, Paweł Fotowicz
{"title":"用于风力涡轮机扭矩传感器蠕变分析的算法","authors":"Jacek G. Puchalski, J. Fidelus, Paweł Fotowicz","doi":"10.3390/a17020077","DOIUrl":null,"url":null,"abstract":"One of the fundamental challenges in analyzing wind turbine performance is the occurrence of torque creep under load and without load. This phenomenon significantly impacts the proper functioning of torque transducers, thus necessitating the utilization of appropriate measurement data analysis algorithms. In this regard, employing the least squares method appears to be a suitable approach. Linear regression can be employed to investigate the creep trend itself, while visualizing the creep in the form of a non-linear curve using a third-degree polynomial can provide further insights. Additionally, calculating deviations between the measurement data and the regression curves proves beneficial in accurately assessing the data.","PeriodicalId":502609,"journal":{"name":"Algorithms","volume":"113 9","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Algorithms Utilized for Creep Analysis in Torque Transducers for Wind Turbines\",\"authors\":\"Jacek G. Puchalski, J. Fidelus, Paweł Fotowicz\",\"doi\":\"10.3390/a17020077\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"One of the fundamental challenges in analyzing wind turbine performance is the occurrence of torque creep under load and without load. This phenomenon significantly impacts the proper functioning of torque transducers, thus necessitating the utilization of appropriate measurement data analysis algorithms. In this regard, employing the least squares method appears to be a suitable approach. Linear regression can be employed to investigate the creep trend itself, while visualizing the creep in the form of a non-linear curve using a third-degree polynomial can provide further insights. Additionally, calculating deviations between the measurement data and the regression curves proves beneficial in accurately assessing the data.\",\"PeriodicalId\":502609,\"journal\":{\"name\":\"Algorithms\",\"volume\":\"113 9\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Algorithms\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/a17020077\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Algorithms","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/a17020077","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

分析风力涡轮机性能的基本挑战之一是在负载和无负载情况下出现的扭矩蠕变。这种现象严重影响扭矩传感器的正常工作,因此需要使用适当的测量数据分析算法。在这方面,采用最小二乘法似乎是一种合适的方法。线性回归可用于研究蠕变趋势本身,而使用三度多项式将蠕变以非线性曲线的形式可视化,则可提供进一步的见解。此外,计算测量数据与回归曲线之间的偏差也有助于准确评估数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Algorithms Utilized for Creep Analysis in Torque Transducers for Wind Turbines
One of the fundamental challenges in analyzing wind turbine performance is the occurrence of torque creep under load and without load. This phenomenon significantly impacts the proper functioning of torque transducers, thus necessitating the utilization of appropriate measurement data analysis algorithms. In this regard, employing the least squares method appears to be a suitable approach. Linear regression can be employed to investigate the creep trend itself, while visualizing the creep in the form of a non-linear curve using a third-degree polynomial can provide further insights. Additionally, calculating deviations between the measurement data and the regression curves proves beneficial in accurately assessing the data.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Label-Setting Algorithm for Multi-Destination K Simple Shortest Paths Problem and Application A Quantum Approach for Exploring the Numerical Results of the Heat Equation Enhancing Indoor Positioning Accuracy with WLAN and WSN: A QPSO Hybrid Algorithm with Surface Tessellation Trajectory Classification and Recognition of Planar Mechanisms Based on ResNet18 Network Computational Test for Conditional Independence
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1