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Real-time predictive maintenance for wind turbines using Big Data frameworks

Mikel Canizo, Enrique Onieva, Angel Conde, Santiago Charramendieta, Salvador Trujillo
2017 2017 IEEE International Conference on Prognostics and Health Management (ICPHM)  
This work presents the evolution of a solution for predictive maintenance to a Big Data environment.  ...  The proposed adaptation aims for predicting failures on wind turbines using a data-driven solution deployed in the cloud and which is composed by three main modules.  ...  The proposed application has adapted a predictive maintenance for wind turbines by using, at first, a Big Data processing framework to generate datadriven predictive models that are based upon historical  ... 
doi:10.1109/icphm.2017.7998308 dblp:conf/icphm/CanizoOCCT17 fatcat:wx6sy3pmjfc4rlf3yaico2qhou

Digital Twin Framework for Time to Failure Forecasting of Wind Turbine Gearbox: A Concept [article]

Mili Wadhwani, Sakshi Deshmukh, Harsh S. Dhiman
2022 arXiv   pre-print
In this preprint, we discuss the concept of a digital twin for time to failure forecasting of the wind turbine gearbox where a predictive module continuously gets updated with real-time SCADA data and  ...  Due to increased wear and tear, the maintenance aspect of a wind turbine is of critical importance.  ...  A digital Twin for a wind turbine is a computer program that uses real-time data to create a virtual space of a wind farm in the physical world [2] .  ... 
arXiv:2205.03513v1 fatcat:b2gewgzvzzcs3dowbnf2kiowje

Research on Digital Twin and Collaborative Cloud and Edge Computing Applied in Operations and Maintenance in Wind Turbines of Wind Power Farm [chapter]

Fuxing Li, Luxi Li, You Peng
2021 Advances in Transdisciplinary Engineering  
For the increasingly prominent problems of wind turbine maintenance, using edge cloud collaboration technology to construct wind farm equipment operation and maintenance framework is proposed, digital  ...  The cloud computing layer completes the big data calculation and storage from wind farm, except that, based on real-time data records, continuous simulation and optimization, correct failure prediction  ...  It is proposed to use edge-cloud oration technology to build an operation and maintenance platform for wind es on site, and to unify real-time measurement and control of wind turbines.  ... 
doi:10.3233/atde210263 fatcat:k4mccxxi4zemndkwxbbcnnx43e

Digital Twin Technologies for Turbomachinery in a Life Cycle Perspective: A Review

Rong Xie, Muyan Chen, Weihuang Liu, Hongfei Jian, Yanjun Shi
2021 Sustainability  
New digital twin technologies are discussed, including modelling, simulation, sensors, Industrial Internet of Things, big data, and AI technologies.  ...  , operation and maintenance phase, and recycle phase.  ...  For example, for the operation and maintenance of wind turbines, condition-based maintenance is preferred over preventive maintenance based on time. Sivalingam et al.  ... 
doi:10.3390/su13052495 fatcat:z5hi35qhkbbbxcewl23hwgjqmy

Digital Twins Collaboration for Automatic Erratic Operational Data Detection in Industry 4.0

Radhya Sahal, Saeed H. Alsamhi, John G. Breslin, Kenneth N. Brown, Muhammad Intizar Ali
2021 Applied Sciences  
A use case of Energy 4.0 fault diagnosis for wind turbines is described to present the use of the proposed framework and DTs collaboration to identify and diagnose the potential failure, e.g., malfunctioning  ...  This paper presents a conceptual framework for digital twins collaboration to provide an auto-detection of erratic operational data by utilizing operational data intelligence in the manufacturing systems  ...  Still, our proposed framework focuses on DTs' collaboration for erratic automatic operation data prediction for Energy 4.0 for wind turbines in smart manufacturing.  ... 
doi:10.3390/app11073186 fatcat:wucysis52zdj3mqpvdz4wluehi

An Overview of Digital Twin Concept for Key Components of Renewable Energy Systems

Qiying Li
2021 International Journal of Robotics and Automation Technology  
The majority of the research focusing on product design, maintenance of operation, condition monitoring and fault decision-making has provided many valuable contributions to academia and industrial fields  ...  , which can not only protect the environment, promote the technological diversification of the energy supply system, accelerate the adjustment of energy structure, but also has important significance for  ...  For key components of wind turbines, they placed virtual sensors in a 5MW numerical turbine in virtual space to predict Remaining Useful Life (RUL) and compare optimal operation and maintenance strategies  ... 
doi:10.31875/2409-9694.2021.08.4 fatcat:rhk76poqgfgptmd77huz5ecbqi

An integrated optimization framework for multi-component predictive analytics in wind farm operations & maintenance

I. Bakir, M. Yildirim, E. Ursavas
2021 Renewable & Sustainable Energy Reviews  
In this paper, an integrated framework that combines i) real-time degradation models used for predicting remaining life distribution of each component, with ii) mixed integer optimization models and solution  ...  Recent years have seen an unprecedented growth in the use of sensor data to guide wind farm operations and maintenance.  ...  A novel wind farm operations and maintenance framework that adapts to real-time sensor data to capture dynamic interactions among turbine components, turbines and wind farms is developed.  ... 
doi:10.1016/j.rser.2020.110639 fatcat:bjxeej7j7rektkwq4ku3bazffe

Artificial Intelligence Based Prognostic Maintenance of Renewable Energy Systems: A Review of Techniques, Challenges, and Future Research Directions [article]

Yasir Saleem Afridi, Kashif Ahmad, Laiq Hassan
2021 arXiv   pre-print
This paper provides an overview of the predictive/prognostic maintenance frameworks reported in the literature.  ...  To this aim, complex Data Analytics and Machine Learning (ML) techniques are being used to increase the overall efficiency of these prognostic maintenance systems.  ...  To this aim, an Artificial Neural Network (ANN) based framework was developed and trained using real-time sensory vibrations data to predict the remaining life percentage of a machine.  ... 
arXiv:2104.12561v1 fatcat:fd3zd2jtkjd45il3xiikevxr2y

Big Data Solutions for Efficient Operation of Microgrids

Simona Vasilica Oprea, Adela Bâra
2019 Ovidius University Annals: Economic Sciences Series  
The main goal is to develop a smart adaptive platform for Big Data analytics for microgrids efficient operation that involves monitoring and control of electrical appliances, generation and storage activities  ...  In this paper, we propose a big data solution architecture for the efficient operation of the microgrids that have emerged as a consequence of distributed generation, storage systems and advances of ICT  ...  Real-time data generated by sensors is collected, processed and analyzed predicting and optimizing the activities of the microgrid improving its operation.  ... 
doaj:456d6a6a231548e3a0daf431964ec4c9 fatcat:eltztuswrradhnjrsro3v3ypgq

Integrated condition monitoring of a fleet of offshore wind turbines with focus on acceleration streaming processing

Jan Helsen, Nicoletta Gioia, Cédric Peeters, Pieter-Jan Jordaens
2017 Journal of Physics, Conference Series  
Real-life offshore wind turbine data is used. Using this streaming approach for calculating bearing failure features on continuous acceleration data will support failure propagation detection.  ...  In order to obtain the insights to predict component failure, it is necessary to have an integrated clean dataset spanning all turbines of the fleet for a sufficiently long period of time.  ...  Furthermore the owners of the wind farm are acknowledged for their contributions in the measurement campaign.  ... 
doi:10.1088/1742-6596/842/1/012052 fatcat:2pg7rmhat5h7dkmdtvlwpfufy4

Predictive Maintenance für WEA-Strukturen [chapter]

C. T. Geiss
2019 Schwingungen von Windenergieanlagen 2019  
For most wind turbines, however, monitoring level 1 will not be accurate enough to predict a possible remaining useful service life (RUL), and detect and predict damages in the system.  ...  This prognosis is valid both for macro and micro economical frameworks, e.g. for the global environment as well as for the single wind turbine operator.  ... 
doi:10.51202/9783181023464-97 fatcat:4jply2eggbg4jdfrudtjh6t2ti

A Scalable Predictive Maintenance Model for Detecting Wind Turbine Component Failures Based on SCADA Data [article]

Lorenzo Gigoni, Alessandro Betti, Mauro Tucci, Emanuele Crisostomi
2019 arXiv   pre-print
In this work, a novel predictive maintenance system is presented and applied to the main components of wind turbines.  ...  The offline test used historical faults from six wind farms located in Italy and Romania, corresponding to a total of 150 wind turbines and an overall installed nominal power of 283 MW.  ...  The large amount of SCADA data (Historical and Real-Time) have been archived and preliminary preprocessed by means of the Big Data infrastructure Microsoft Data Lake Analytics, before feeding the model  ... 
arXiv:1910.09808v1 fatcat:iavc63mierbtzczmmmtbgvsx4q

Scientometric review of artificial intelligence for operations & maintenance of wind turbines: The past, present and future

Joyjit Chatterjee, Nina Dethlefs
2021 Renewable & Sustainable Energy Reviews  
However, wind turbines regularly suffer from operational inconsistencies, leading to significant costs and challenges in operations and maintenance (O&M).  ...  real-time decision support, along with possible strategies to overcome these problems.  ...  [70] utilised big data frameworks such as Apache Kafka, Apache Spark, Apache Mesos and HDFS to develop a real-time predictive maintenance system consisting of an online fault tolerant monitoring agent  ... 
doi:10.1016/j.rser.2021.111051 fatcat:wkahjceeijdadfdeg6lola2u4i

Offshore wind turbine fault alarm prediction

Alexios Koltsidopoulos Papatzimos, Philipp R. Thies, Tariq Dawood
2019 Wind Energy  
This paper quantifies this relationship and proposes a novel tool for predicting wind turbine fault alarms for a range of subassemblies, using wind speed statistics.  ...  The tool uses 5 years of operational data from an offshore wind farm to create a data-driven predictive model.  ...  This paper presents a tool for turbine alarm prediction, using wind speed statistics.  ... 
doi:10.1002/we.2402 fatcat:4ekcg4j3u5btdogq6ykksxlwwm

Overview of Wind Parameters Sensing Methods and Framework of a Novel MCSPV Recombination Sensing Method for Wind Turbines

Xiaojun Shen, Chongchen Zhou, Guojie Li, Xuejiao Fu, Tek Lie
2018 Energies  
The wind parameter predictive perception method can predict wind speed and wind power at multiple time scales statistically, but it has limited significance for the control of the action of wind turbines  ...  After analyzing wind turbines' arrangements and communication characteristics and the correlation of operation data between wind turbines, the paper proposes a novel recombination-sensing method route  ...  Based on the prediction model after parameter modification and the real-time data of the upstream wind turbines, the wind speed, wind direction and arrival time of the target wind turbine at multiple time  ... 
doi:10.3390/en11071747 fatcat:thbfcmfakbed3nspfp2kautrja
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