Digital Twin Technology in Condition Monitoring of Wind Turbines
暫譯: 風力發電機狀態監測中的數位雙胞胎技術

Madushele, Nkosinathi, Olatunji, Obafemi O., Adedeji, Paul A.

Digital Twin Technology in Condition Monitoring of Wind Turbines
  • 出版商: CRC
  • 出版日期: 2026-02-10
  • 售價: $9,280
  • 貴賓價: 9.5 折 $8,816
  • 語言: 英文
  • 頁數: 376
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 1032250178
  • ISBN-13: 9781032250175
  • 相關分類: 控制系統 Control-systems

    • 海外代購書籍(需單獨結帳)

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商品描述

This book discusses the application of digital twin (DT) in condition monitoring of offshore and onshore wind turbines, including a pertinent framework to explain critical component Condition Monitoring and Fault Diagnosis. Frequently used tools and enabling technologies for DT are briefly discussed while the associated benefits and challenges are analyzed. It identifies the key issues which need to be addressed in the wind energy industry to optimally benefit from DT.

Features:

  • Exclusive title on application of DT in wind turbine condition monitoring
  • Develops DT framework for condition monitoring of wind turbine
  • Discusses industrial applications by wind turbine manufacturers and operators as case studies
  • Explores the interface between DT technology and condition monitoring
  • Extensively profiles recommendations for future research

This book is aimed at researchers and professionals in mechanical engineering, plant maintenance, wind engineering, and condition monitoring.

商品描述(中文翻譯)

本書討論數位雙胞胎（Digital Twin, DT）在海上及陸上風力發電機的狀態監測中的應用，包括一個相關框架來解釋關鍵組件的狀態監測和故障診斷。書中簡要討論了DT的常用工具和啟用技術，同時分析了相關的好處和挑戰。它確定了風能產業中需要解決的關鍵問題，以便最佳化地利用DT。

特色：
- 專門探討DT在風力發電機狀態監測中的應用
- 為風力發電機的狀態監測開發DT框架
- 以風力發電機製造商和運營商的案例研究討論工業應用
- 探索DT技術與狀態監測之間的介面
- 廣泛概述未來研究的建議

本書旨在針對機械工程、設備維護、風能工程和狀態監測領域的研究人員和專業人士。

作者簡介

Nkosinathi Madushele is a professional engineer registered with ECSA and holds a D.Eng. in Mechanical Engineering from the University of Johannesburg. He has industry and academic experience, having worked as a Junior Project Manager in construction and a Systems Engineer at ESKOM. He is currently the Head of the Department of Mechanical Engineering Science at the University of Johannesburg.

Obafemi O. Olatunji is a registered engineer, certified energy manager, and certified renewable energy professional with the Association of Energy Engineers. He holds a PhD in Mechanical Engineering focused on AI integration in energy systems. With ten years of experience in academia and industry, he is currently a program manager at UJ-PEETS, leading the energy and energy efficiency portfolio.

Paul A. Adedeji is an energy specialist at UJ-PEETS, focusing on AI and machine learning applications in renewable energy for resource prediction and condition monitoring. He holds a BSc. in Mechanical Engineering, MSc. in Industrial and Production Engineering, and a PhD. in Mechanical Engineering. He has published extensively on AI in wind and solar PV systems.

作者簡介(中文翻譯)

是一位註冊於 ECSA 的專業工程師，擁有約翰尼斯堡大學的機械工程博士學位。他擁有產業和學術經驗，曾擔任建築業的初級專案經理以及 ESKOM 的系統工程師。目前，他是約翰尼斯堡大學機械工程科學系的系主任。

是一位註冊工程師、認證能源經理及與能源工程師協會認證的可再生能源專業人士。他擁有專注於能源系統中 AI 整合的機械工程博士學位。擁有十年的學術和產業經驗，他目前是 UJ-PEETS 的計畫經理，負責能源及能源效率的相關業務。

是 UJ-PEETS 的能源專家，專注於可再生能源中 AI 和機器學習的應用，以進行資源預測和狀況監測。他擁有機械工程學士學位、工業與生產工程碩士學位，以及機械工程博士學位。他在風能和太陽能光伏系統中的 AI 方面發表了大量研究。

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