Deliverable Reports

Abstracts for the public project deliverables and links to the full documents can be found below:

Deliverable D1.1: Collection of failure data for onshore and offshore wind farms

Abstract: Wind turbines are complex systems consisting of a variety of critical components (e.g. tower, blades, rotor hub, sensors, gearbox, power electronics, yaw, brake mechanism, controller, anemometer, etc.). Failure of any of these critical components will most likely result in unnecessary downtime and associated costs due to the loss of production and repair requirements. Depending on the type of component and mode of failure the effect on the overall downtime, repair timescale and financial losses can vary significantly. Thus, gearbox failures may result in far longer downtime and maintenance costs than failures associated with sensors. Furthermore, certain types of failures may result in significant damage to other components or even complete loss of the wind turbine. For example, an overheating bearing causing combustion of the lubricating oil will probably lead to the complete loss of all the equipment installed on the nacelle. Also failure of the braking mechanism under severe windy conditions may also result in catastrophic structural failure of the blades and possibly the wind turbine itself.

The purpose of this deliverable report is to present the data collected with the help of the industrial partners of the consortium about the failure modes that affect wind turbines. Due to confidentiality issues the distinction between onshore and offshore wind farm data is not always straightforward but the report contains sufficient detail in order to enable satisfactory conclusions to be drawn with regards to the main problems faced in wind turbine operation whether these are onshore or offshore. To the extent that it has been possible public releases have been considered to increase the amount of useful information contained in this report. According to the findings the gearbox condition is a critical factor for both onshore and offshore wind farms as it can result in significant downtime and repair costs. Although wind turbine manufacturers and operators demand that the gearbox is designed for an operational lifetime of at least 20 years this is far from being achieved. According to reports most operators are faced with gearbox refurbishment or even replacement at least twice or thrice within a 20 year period of operation. In recent wind energy projects the costs associated with gearbox problems are always taken into consideration during budgetary planning.

Link to full report: D1.1 report

 

Deliverable D1.2: Assessment of condition monitoring systems employed

Abstract: In this deliverable report the consortium has collected, analysed and evaluated the information available on existing commercial, pre-commercial and research-based condition monitoring systems with respect to their technical characteristics, efficiency, reliability, cost and easiness of installation on non-instrumented wind turbines. At the same time, the operational requirements set by wind turbine manufacturers and operators for the minimisation of occurrence of faults and failures have been assessed and are presented in this report. The efficiency and reliability of existing systems have been compared with the operational requirements as these have been set by wind turbine operators and manufacturers in order to optimise wind turbine operation. The results that have been presented in this report have been taken into account in order to ensure that a substantial step-change in the efficiency and reliability of wind turbine operation will be realised and demonstrated by the end of the OPTIMUS project.

Link to full report: D1.2 report

 

Deliverable D1.3: Analysis of collected data and definition of key reliability issues for wind turbines

Abstract: A significant amount of data has been collected from reports in the literature as well as the wind turbine operators involved in the OPTIMUS consortium. From the data collected and their correlation it has been revealed that for offshore wind turbines the gearbox remains the Achilles tendon of Operation and Maintenance (O&M). It has been revealed that offshore wind turbines suffer much higher gearbox failure rates than onshore wind turbines often resulting in complete gearbox replacements much earlier than anticipated. In some instances replacement gearboxes are required to be procured within a period of few months for offshore wind turbines whilst for onshore ones this period is normally extended to 6-7 years. Furthermore, onshore wind turbine gearboxes may not always require complete replacement but instead component replacement coupled with oil changes may suffice to extend the operation of the existing gearbox by up to a few more years before another extensive refurbishment or complete replacement is required.

From the limited information available on power converters it appears that the failure rates reported for both onshore and offshore wind turbines are similar or worse in onshore wind turbines. However, due to the small data sample the consortium questions the accuracy of these results. Higher failure rates are anticipated for offshore wind turbines, particularly due to the aggressive environment under which they operate.

Other components which have been reported to suffer high failure rates include the yaw and pitch systems. The control system of offshore wind turbines has also been highlighted as one of the components resulting in high periods of downtime. SCADA alarms related to the control system cannot normally be reset remotely and require access to the wind turbine by maintenance personnel in order to verify the alarm.

The wind turbine tower and foundation have so far been of least concern particularly for offshore wind turbines. Failures have only been reported for onshore wind turbines. Blade and rotor related failures according to the reports in hand appear to be higher in onshore wind turbines.

It should be emphasised that the available data do not contain information about the way maintenance has been carried out and how often complete replacements of certain wind turbine components such as the gearbox have been performed. This would influence of course the number of failures recorded and thus the failure rates as well. Investigation of offshore wind turbine gearbox reliability from published articles, papers and reports available in the literature has clearly shown that extensive gearbox replacement has been carried out in several wind farms much earlier than anticipated by the design lifetime. Replacement before failure has actually occurred means that the failure data collected are not truly representative. Therefore, it is extremely difficult to produce a quantitative reliability model. Instead we need to resort in a qualitative approach which takes into account all the known facts as well as the actual data available. It would be highly inappropriate not to question the data that have been published particularly for offshore wind farms without considering factual reports that seem to contradict the conclusions drawn from the analysis of the data alone.

Link to full report: D1.3 report

 

Deliverable D1.4: Development of energy costing model

Abstract: This document focuses on the energy costing model needed to calculate the whole lifecycle costs of wind turbines. The outcomes obtained by the model will be essential to evaluate the validity of the technology developed by the consortium.

The energy costing model will be linked with the overall wind turbine reliability model previously developed in task 1.3 (Analysis of collected data and definition of key reliability issues for wind turbines), and its theoretical cost saving benefit will be demonstrated during the field trials in WP3 (Condition monitoring of wind turbine electrical and power control systems) and WP5 (Cost-effective condition monitoring technology for wind turbines).

Link to full report: D1.4 report

 

Deliverable D2.2: Drive-train failure root cause analysis

Abstract: Wind energy is the most widely implemented renewable energy source in the world. Complex multi-MW wind turbines are currently being installed. Projects involving utility-scale wind turbines require an optimum level of reliability, availability, maintainability and safety (RAMS), in order to guarantee their financial viability in the forthcoming years.

In this deliverable report, the condition of industrial drive systems of wind turbines is qualitatively considered by fault tree analysis (FTA). Drive system involves components such as gearbox, shafts or bearings. The literature and expertise show us that these components present high failure rates and downtimes. The reliability of the drive system must be improve to reduce the operation and maintenance costs. The analysis developed in this work seed light on the importance of those elements of the drive system that should be considered to improve RAMS.

Link to full report: D2.2 report

 

Deliverable D4.1: Analysis of the effect of variable loads on condition monitoring measurements

Abstract: The variable loads that occur during normal wind turbine operation are a major problem for the valid analysis of condition monitoring data particularly when the gearbox is concerned. In this report the methods for analysing and removing the effects of variable loads on wind turbine condition monitoring have been discussed. Three types of condition monitoring measurements have been considered, including single Acoustic Emission (AE)/vibration data measurements without loading information, AE/vibration sensor data with loading information, and multiple channel vibration data without loading information. To deal with these different situations, three methods have been studied. For single sensor AE/vibration measurements, the Key Performance Index (KPI) methods can distinguish the differences between the normal and abnormal turbine operating conditions, with variable loading conditions taken into account. For AE/vibration sensor data with corresponding loading information, a baseline model method can be used to find the relationship between the feature of data measurement and loading conditions so as to take the loading conditions into account. Moreover, when the difference between the real measurement and baseline model output does not fall inside an a priori determined tolerance range, potentially abnormal/changed behaviours can be captured. It has been shown that, for the gearbox condition monitoring, the vibration baseline model is more sensitive than the AE baseline model to capture the abnormal/changed turbine behaviours. However, for the generator, the AE baseline model is much more sensitive than the vibration baseline model for condition monitoring. Finally, to deal with the multiple-channel measurements, transmissibility analysis is employed to reduce the loading effects on condition monitoring results. By using this approach, the differences between the normal and abnormal conditions can be revealed by evaluating the transmissibility functions determined from the multiple sensor data. Future work will be focused on the thresholds determination for both KPI and baseline model methods, as well as the definition of transmissibility based damage indicators.

Link to full report: D4.1 report

 

Deliverable D5.1: Assessment of condition monitoring requirements for onshore and offshore wind turbines

Abstract: In order to implement a cost-effective condition monitoring methodology the consortium has assessed the condition monitoring requirements for onshore and offshore wind turbines in terms of benefit achieved versus investment cost as well as part of insurance requirements. In determining this, the differences in failure modes and maintenance issues influencing onshore and offshore wind turbines have also been considered.

Wind turbine manufacturers and operators have shown strong demand for the development of accurate condition monitoring systems for the evaluation of the key wind turbine components in order to achieve substantial improvement in the efficiency of maintenance activities by reducing the need for reactive or corrective maintenance to the lowest possible level.

The consortium of this project is involved in the development and demonstration of an integrated condition monitoring system based on a modular design, which will enable the accurate and reliable diagnosis and prognosis of gearbox and power electronic faults. The OPTIMUS system combines the use of acoustic emission sensors and vibration sensors which can be integrated with oil particle sensors for the detection and prognosis of gearbox faults with current, voltage, vibration and temperature sensors for the assessment of the turbine’s power electronics. Integration of the aforementioned sensors allows the full assessment of the condition of two critical wind turbine components through the application of a single monitoring system based on a modular design which will also take into account generator currents and electric power output measurements.

Link to full report: D5.1 report

 

Deliverable D5.4: Field-based evaluation of achieved reliability

Abstract: The wind turbines instrumented in task 5.2 will be used to evaluate and demonstrate the achieved OPTIMUS prognostics methodology and data fusion techniques. The results obtained will be used to determine accurately the optimum condition monitoring methodology in order to keep related costs to a minimum whilst optimising availability of instrumented wind turbines and reducing downtime to an absolute minimum. Data from Acciona AW1500 turbines at the Vedadillo wind farm are considered within this task.

In this report, assessment methods and models based on fatigue life estimation are evaluated and demonstrated based on suggestions made in WP5.3. A variety of approaches have been considered and presented in this report. Each approach has been evaluated in terms of its own advantages and disadvantages and also the level of complexity of its implementation.

Using statistical comparison, detailed life estimation or fatigue damage is conducted to suggest the optimum maintenance strategy. Miner’s rule and Paris’ law with a crack propagation model are used to assess the risk of fatigue failure on the main shaft bearing.

Since frequency analysis methods are the most widely used condition monitoring methods, different numerical studies were carried out including Fourier transmissibility and Wavelet analyses methods.

Additional work was also carried out to develop a customised automated signal processing application which calculates around frequencies of interest based on gearbox specifications. The developed platform enables users to model and calculate three types of system which includes; (i) a simple bearing system consisting of a simple shaft with one or more bearings, (ii) a simple gear system consisting of one or more simple gear stages either parallel, planetary or a mix of both and (iii) a complex gearbox consisting of a combination of both bearing and gear stages with multiple stages of planetary and parallel gear meshing.

The work presented in this report also carried out a drivetrain reliability analysis as a first step towards defining the specification of a prognostic model applicable to the main bearing and gearbox of a wind turbine. This included amongst other models, the development of a main bearing life model, load monitoring, torque and bending moments. An additional life model of a generic 1.5 MW wind turbine was also developed. This was based on an existing gearbox design and knowledge of common design procedures.

Furthermore, this report also discusses the requirement for combined condition monitoring techniques and prognostic models to enhance diagnostic approaches and consequently reducing operational expenditure.

Link to full report: D5 4 report

 

Deliverable D6.3: Organisation of workshops

Abstract: As part of the strong commitment of the consortium to disseminate the key findings and outcomes of the OPTIMUS project to the wider scientific and industrial community, consortium members participated or organised a number of workshop-related events during the project. Participation in other workshops or organisation of additional workshops has also been planned after the end of the project. The activities in which the consortium members were involved, have been of varying intensity and targeting various types of audiences such as undergraduate and postgraduate students, academics, and professional members from the industry with technical and/or managerial background. In addition, the consortium members were proactive throughout the project in inviting colleagues from academia and industry to join an Advisory Group. This activity will continue beyond the end of the project as dissemination will continue strongly.

The Advisory Group members have been consulted individually during the course of the project.  However, a general workshop involving members of the Advisory Group will take place in early 2017. The event is organised by ORE Catapult and will be adjoined to a major industry event to maximise attendance, e.g. Scottish Renewables Annual Conference & Exhibition. During the project a number of special sessions were organised by Dr Mayorkinos Papaelias of the University of Birmingham in the form of special sessions at the CM conferences of 2014 and 2015. These events were open for participation to representatives from the consortium partners, Advisory Group Members and colleagues from the rest of the scientific community (academic and non-academic). Also, the Universities of Birmingham, Sheffield and UCLM carried out a number of seminars for undergraduate and postgraduate students. Workshops were also organised on annual basis in Daegu, Korea in collaboration with Kyungpook National University. At these events hosted by Professor Dongik Lee (KNU), Professor Zi-Qiang Lang (University of Sheffield – 2013), Dr Mayorkinos Papaelias (University of Birmingham – 2014) and Professor Fausto Pedro Garcia Marquez (Universidad de Castilla-La Mancha – 2015) presented the progress of the OPTIMUS project to a wide audience of postgraduate and academic staff members from KNU.

Apart from the workshops organised directly by the consortium and KNU, the University of Birmingham and TERNA Energy also took the opportunity of presenting some of the key findings of the OPTIMUS project to industrial events where they were invited as guest speakers. Participation to such events is expected to continue beyond the lifetime of the project. For example Dr Papaelias (UOB) is due to participate to the Wind Power Big Data and IoT, held in Berlin, Germany, 19-20th of October 2016. The event which is organised by BIS has attracted participation from industrial companies, research institutes and higher education establishments.

Link to full report: D6.3 report

 

Deliverable D8.2: Executive summary and public report

Abstract: The OPTIMUS project was a three year FP7 project funded by the European Community under Grant Agreement Number 322430.  The project ran from 2013 – 2016 and involved a total of 13 partners from 6 EU countries, including research organisations, SMEs, large industrial organisations and academia.  There were three main aims of the OPTIMUS project: a) to improve reliability within the wind power generation industry by delivering the prognostic technology necessary to evolve to predictive maintenance strategies, substantially reduce unexpected wind turbine failures and unnecessary costs and minimise downtime; b) to improve the efficiency of maintenance procedures and operational reliability of wind turbines and c) to support the implementation of the European Wind Initiative of the SET-Plan (SEII) and contribute significantly towards achieving the reliability, socioeconomic and environmental targets that have been set for the European wind energy industry by 2020.

In order to achieve these objectives, the consortium first undertook an assessment of current condition monitoring systems and gearbox designs, as well as an investigation into power converter and drivetrain failures.  An energy costing model was developed as part of work package, WP1.  In parallel, a dynamic drivetrain model was created (WP2), following analysis of each major mechanical component.  Once this was done, fatigue life models were created based on a 1.5MW drivetrain and a 750kW drivetrain.

Four different condition monitoring systems were installed on two different types of wind turbines, to monitor the power electronics and drive trains:

  • At Vedadillo Wind Farm (Spain) two different systems were employed on ACCIONA AW-1500 turbines:
    • INDRA installed both drivetrain condition monitoring (to measure vibration at different points of the drivetrain and the rotational speed of the high-speed gearbox shaft) and inverter condition monitoring (to monitor the power converter components’ electrical parameters)
    • INGETEAM installed inverter condition monitoring to monitor the power converter components’ electrical parameters)
  • At Chilikoka Wind Farm (Greece) TERNA, Feldman & UOB installed both vibration and acoustic emission systems on a Vestas V-47 turbine;
  • At Profitis Ilias Wind Farm (Greece), D2S installed vibration monitoring systems on a Vestas V-47 turbine.

The data from each of these turbines was collected and analysed.  A model was developed to estimate the loss of life of power electronics during wind turbine operation (WP3) and data collected from the instrumented turbines was used to validate the model.  Work was undertaken to look at the removal of variable load effects as part of work package, WP4.  Prognostic fault detection, methodology and data fusion tasks were carried out as part of WP5.  In addition to exploitation, dissemination and project management tasks, work was carried out to determine what can be done to update industry standards / guidelines and develop training procedures.

Valuable data and insights were gained during the project which have allowed the consortium to identify several readily exploitable results.  These results will be progressed by the relevant project partners after the end of the project and, where necessary, will be protected via the appropriate method (e.g. trade secret, copyright, trademark or patent).

The project findings and deliverables have been widely disseminated at both national and international level, through conference papers, journal publications and published books.

Several significant project results have been identified by the project’s Exploitation Manager and the relevant partners have submitted the details to the OPTIMUS Knowledge Portfolio.  Future work is planned which will fully exploit the project outcomes, mainly through follow-on demonstration projects with end-users.

Link to full report: D8.2 report

 

Other

Last updated: 8/6/17

  • BSc Engineering, Final Project: Modelo Del Coste Del Ciclo De Vida Para Los Sistemas De Monitorización De Detección De Hielo En Palas, Cesar Muñoz Muñoz, Supervisor: Fausto Pedro García Márquez, University of Castilla-La Mancha, January 2014
  • Ph.D thesis: Novel approaches for maintenance management on wind turbines, Raul Ruiz de la Hermosa Gonzalez-Carrato, Supervisor: Fausto Pedro García Márquez, University of Castilla-La Mancha, July 2014 https://ruidera.uclm.es/xmlui/handle/10578/4173
  • BSc Engineering, Final Project: Diseño De Un Sistema Monitorizacion Del Estado De Palas De Aerogeneradores, Sergio Malo Peces, Supervisor: Fausto Pedro García Márquez, University of Castilla-La Mancha, July 2014
  • MSc Engineering, Final Project: Diseño Y Elaboración De Un Sistema De Detección De Hielo En Palas, Carlos Quiterio Gomez Muñoz, Supervisor: Fausto Pedro García Márquez, University of Castilla-La Mancha, September 2014
  • MSc Engineering, Final Project: A Novel Quantitative Approach for Decision Making Analysis Via Binary Decision Diagrams, Alberto Pliego Marugán, Supervisor: Fausto Pedro García Márquez, University of Castilla-La Mancha, September 2014
  • BSc Engineering, Final project: Diseño De Un Sistema De Monitorización De La Integridad Estructural, Carlos Quiterio Gomez Muñoz, Supervisor: Fausto Pedro García Márquez, University of Castilla-La Mancha, December 2014
  • Ph.D thesis: New Methods for Structural Health Monitoring and Damage Localization, Xueyan Zhao, University of Sheffield, December 2014. http://etheses.whiterose.ac.uk/8085/
  • Ph.D thesis: Dr Moussa, Supervisor: Professor Dongik Lee, Kyungpook National University, 2015.
  • BEng. (1st Class Honours), Final Year Project: Condition monitoring of wind turbine gearboxes, Mr Taoran Wang, Supervisor: Dr Mayorkinos Papaelias, The University of Birmingham, June 2016. https://www.researchgate.net/project/Condition-monitoring-of-wind-turbine-gearbox
  • Ph.D thesis: New approaches on fault detection and diagnosis for structures maintenance management, Carlos Quiterio Gomez Muñoz, Universidad de Castilla-La Mancha, July 2016. https://ruidera.uclm.es/xmlui/bitstream/handle/10578/12471/TESIS%20G%c3%b3mez%20Mu%c3%b1oz.pdf?sequence=1&isAllowed=y
  • Ph.D thesis: Approaches for qualitative and quantitative analysis of complex systems: Algorithms and Case Studies, Alberto Pliego Marugán, Universidad de Castilla-La Mancha, July 2016.

Books

Last updated: 8/6/17

Title: Logistic Management Employing Tabu Search and Neural Network Algorithms: A Case Study

Date: 2014 Contributors: Isidro Peña García-Pardo and Fausto Pedro García Marquez Other details: Managing Complexity, Chapter 26, pp. 225-231, Publisher Springer, ISBN 978-3-319-04705-8, doi: 10.1007/978-3-319-04705-8_26 https://link.springer.com/chapter/10.1007/978-3-319-04705-8_26

Title: Advanced Business Analytics

Date: 2015 Editors: Fausto Pedro García Marquez and Benjamin Lev Other details: Publisher Springer, ISBN 978-3-319-11414-9, doi: 10.1007/978-3-319-11415-6 https://link.springer.com/book/10.1007/978-3-319-11415-6

Chapter 1: Decision Making Approach for Optimal Business Investments

Contributors: A. Pliego and Fausto Pedro García Marquez

Other details: pp. 1-20, ISBN 978-3-319-11414-9, doi: 10.1007/978-3-319-11415-6_1

https://link.springer.com/chapter/10.1007%2F978-3-319-11415-6_1#page-1

 

Chapter 3: Economic viability analytics for wind energy maintenance management

Contributors: J.M. Pinar, E. Segura and Fausto Pedro García Marquez

Other details: pp. 39-54, ISBN 978-3-319-11414-9, doi: 10.1007/978-3-319-11415-6_3

https://link.springer.com/chapter/10.1007/978-3-319-11415-6_3#page-1

 

Chapter 5: How Business Analytics Should Work

Contributors: Marco Antonio Villegas-Garcia, Fausto Pedro García Marquez and Diego José Pedregal Tercero

Other details: pp. 93-108, ISBN 978-3-319-11414-9, doi: 10.1007/978-3-319-11415-6_5

https://link.springer.com/chapter/10.1007/978-3-319-11415-6_5

 

Chapter 8: Use of Excellence Models as a Management Maturity Model (3M)

Contributors: Jose Ramón García Aranda and Fausto Pedro García Marquez

Other details: pp. 165-179, ISBN 978-3-319-11414-9, doi: 10.1007/978-3-319-11415-6_8

https://link.springer.com/chapter/10.1007/978-3-319-11415-6_8

 

Title: Handbook of Research on Trends and Future Directions in Big Data and Web Intelligence

Date: 2015 Editors: Noor Zaman, Mohamed Elhassan Seliaman, Mohd Fadzil Hassan and Fausto Pedro García Marquez Other details: Publisher IGI Global, 2015, ISBN 9781466685055, doi: 10.4018/978-1-4666-8505-5 http://www.igi-global.com/book/handbook-research-trends-future-directions/124160

Chapter 8: Big Data and Web Intelligence for Condition Monitoring. A Case Study on Wind Turbines

Contributors: C.Q. Gómez, M.A. Villegas, Fausto Pedro García Márquez and D.J. Pedregal

Other details: pp. 149-163, ISBN 9781466685055, doi: 10.4018/978-1-4666-8505-5.ch008

http://www.igi-global.com/chapter/big-data-and-web-intelligence-for-condition-monitoring/150217

https://www.researchgate.net/publication/297056175_Big_data_and_web_intelligence_for_condition_monitoring_A_case_study_on_wind_turbines

 

Chapter 10: Big Data and Web Intelligence: Improving the Efficiency on Decision Making Process via BDD

Contributors: Alberto Pliego and Fausto Pedro García Marquez

Other details: pp. 190-207, ISBN 9781466685055, doi: 10.4018/978-1-4666-8505-5.ch010

http://www.igi-global.com/chapter/big-data-and-web-intelligence/137025

 

Title: Condition monitoring and fault diagnosis in wind energy systems

Date: 2015 Contributors: J.M. Pinar and Fausto Pedro García Márquez Other details: Eco-friendly Innovations in Electricity Transmission and Distribution Networks, Editorial Elsevier, Chapter 11, pp. 221-242. ISBN 9781782420101, 2015. doi: 10.1016/B978-1-78242-010-1.00011-2 https://www.elsevier.com/books/eco-friendly-innovations-in-electricity-transmission-and-distribution-networks/bessede/978-1-78242-010-1 https://books.google.co.uk/books?hl=en&lr=&id=LM3tAwAAQBAJ&oi=fnd&pg=PA221&dq=info:7W8UUAeI1Z8J:scholar.google.com&ots=-hSpizmRE1&sig=MjgYJCm3z3kIMQq9DcfPF27Hs_I&redir_esc=y#v=onepage&q&f=false

Title: Big Data and Web Intelligence: Improving the Efficiency on Decision Making Process via BDD

Date: 2016 Contributors: Alberto Pliego and Fausto Pedro García Márquez Other details: Big Data: Concepts, Methodologies, Tools and Applications, Chapter 12, pp. 229-246, Publisher IGI Global, ISBN 9781466698406, doi: 10.4018/978-1-4666-9840-6 http://www.igi-global.com/book/big-data-concepts-methodologies-tools/140960

Title: Non-Destructive Testing

Date: 2016 Editors: F. P. García Márquez, M. Papaelias and Noor Zaman Other details: Publisher INTECH. Open access free of charge. doi: 10.5772/61596 https://www.intechopen.com/books/non-destructive-testing

Title: Big Data Management

Date: 2017 Editors: F. P. García Marquez and B. Lev Other details: Publisher Springer, ISBN 978-3-319-45497-9 https://link.springer.com/book/10.1007/978-3-319-45498-6

Title: Renewable Energies Business Outlook 2050

Date: July 2017 Editors: F. P. García Márquez, M. Papaelias and A. Karyotakis Other details: Publisher Springer http://www.springer.com/gb/book/9783319453620

Title: Non-Destructive Testing and Condition Monitoring Techniques for Renewable Energy Industrial Assets

Date: September 2017 Contributors: M. Papaelias, F. P. García Márquez and A.

Journals

Last updated: 8/6/17

Title: Wind turbine reliability analysis

Date: 2013 Contributors: J.M. Pinar, Fausto Pedro García Márquez, A. Tobias and M. Papaelias Other details: Renewable and Sustainable Energy Reviews, Vol. 23, pp. 463-472 http://www.sciencedirect.com/science/article/pii/S1364032113001779 https://www.researchgate.net/publication/257548621_Wind_turbine_reliability_analysis

Title: A new ranking method approach for decision making in maintenance management

Date: 2014 Contributors: Fausto Pedro García Márquez, A. Pliego, J. Lorente and Juan Ramón Trapero Arenas Other details: Lecture Notes in Electrical Engineering Volume 241, Springer, 2014, pp. 23-39. doi: 10.1007/978-3-642-40078-0-2 https://link.springer.com/chapter/10.1007/978-3-642-40078-0_2 https://www.google.co.uk/url?sa=t&rct=j&q=&esrc=s&source=web&cd=2&cad=rja&uact=8&ved=0ahUKEwiAl8Xjq6vUAhVMIcAKHRtiDp0QFgguMAE&url=http%3A%2F%2Fwww.springer.com%2Fcda%2Fcontent%2Fdocument%2Fcda_downloaddocument%2F9783642400773-c2.pdf%3FSGWID%3D0-0-45-1432961-p175370275&usg=AFQjCNFYy2toYV_rLsl91EsbRWRb02yoSg

Title: Acoustic emission study of fatigue crack propagation in extruded AZ31 magnesium alloy

Date: 2014 Contributors: Zhiyuan Han, Hongyun Luo, Chuankai Sun, Junrong Li, Mayorkinos Papaelias and Claire Davis Other details: Materials Science and Engineering A, Vol. 597, pp. 270-278, Elsevier, doi: 10.1016/j.msea.2013.12.083, March 2014 http://www.sciencedirect.com/science/article/pii/S0921509313014664

Title: Decision making process via binary decision diagram

Date: 2014 Contributors: A. Pliego, Fausto Pedro García Márquez and J. Lorente Other details: International Journal of Management Science and Engineering Management. Online (7 pages) [C, Journal Rankings for ARC FoR: 0102 — Applied Mathematics], July 2014 http://dx.doi.org/10.1080/17509653.2014.946977 https://ruidera.uclm.es/xmlui/bitstream/handle/10578/12099/Journal-Filadelfia-completo.pdf?sequence=1&isAllowed=y

Title: Pattern recognition by wavelet transforms using macro fibre composites transducers

Date: 2014 Contributors: R. Ruiz, Fausto Pedro García Márquez, V. Dimlaye and D. Ruiz Other details: Mechanical Systems and Signal Processing. Vol. 48 (1-2,3), pp. 339–350, 2014. doi: 10.1016/j.ymssp.2014.04.002, October 2014 http://www.sciencedirect.com/science/article/pii/S0888327014001022 https://www.researchgate.net/profile/Diego_Ruiz-Hernandez/publication/262859802_Pattern_recognition_by_wavelet_transforms_using_macro_fibre_composites_transducers/links/55a046ea08ae967fb3e97542.pdf

Title: A novel approach to fault detection and diagnosis on wind turbines

Date: 2014 Contributors: C.Q. Gómez, R. Ruiz, J.R. Trapero and Fausto Pedro García Márquez Other details: Global NEST Journal, Vol. 16 (6), pp. 1029-1037. 2014, December 2014 https://journal.gnest.org/sites/default/files/Submissions/gnest_01354/gnest_01354_published.pdf

Title: Decision making via binary decision diagrams: a real case study

Date: 2014 Contributors: A. Pliego, Fausto Pedro García Márquez and J. Lorente Other details: Lecture Notes in Electrical Engineering (Springer), Vol. 180 pp. 215-222. 2014. [SCImago 0.11; Source Normalized Impact per Paper 0.122] doi: 10.1007/978-3-642-55182-6_19 https://link.springer.com/chapter/10.1007%2F978-3-642-55182-6_19 https://ruidera.uclm.es/xmlui/bitstream/handle/10578/12191/Decision%20Making%20via%20Binary%20Decision%20Diagrams%20A%20Real%20Case%20Study.pdf?sequence=2

Title: Maintenance management of wind turbines structures via MFCs and wavelet transforms

Date: 2015 Contributors: R. Ruiz, Fausto Pedro García Márquez and V. Dimlaye Other details: Renewable & Sustainable Energy Reviews. Vol. 48, pp. 472-482, 2015. doi: 10.1016/j.rser.2015.04.007 http://www.sciencedirect.com/science/article/pii/S1364032115002774 https://www.researchgate.net/publication/276500171_Maintenance_management_of_wind_turbines_structures_via_MFCs_and_wavelet_transforms

Title: Improving the efficiency on decision making process via BDD

Date: 2015 Contributors: A. Pliego and Fausto Pedro García Márquez Other details: Advances in Intelligent Systems and Computing, Serie 362, Volume 362, 2015, pp. 1395-1405, Editorial Springer, Print ISBN 978-3-662-47240-8 Online ISBN 978-3-662-47241-5, Series ISSN 2194-5357, doi: 10.1007/978-3-662-47241-5_116 https://link.springer.com/chapter/10.1007/978-3-662-47241-5_116 https://www.researchgate.net/publication/282373806_Improving_the_Efficiency_on_Decision_Making_Process_via_BDD

Title: Economic viability study for offshore wind turbines maintenance management

Date: 2015 Contributors: E. Segura, J.M. Pinar and Fausto Pedro García Márquez Other details: Advances in Intelligent Systems and Computing, Serie 362, Volume 362, 2015, pp. 235-244, Editorial Springer, Print ISBN 978-3-662-47240-8 Online ISBN 978-3-662-47241-5, Series ISSN 2194-5357, doi: 10.1007/978-3-662-47241-5_19 https://link.springer.com/chapter/10.1007/978-3-662-47241-5_19 https://ruidera.uclm.es/xmlui/bitstream/handle/10578/12197/Economic%20Viability%20Study%20for%20Offshore%20Wind%20Turbines%20Maintenance%20Management.pdf?sequence=1

Title: Methods and tools for the operational reliability optimisation of large-scale industrial wind turbines

Date: 2015 Contributors: R. Ruiz, Fausto Pedro García Márquez, M. Papaelias and A. Karyotakis Other details: Advances in Intelligent Systems and Computing, Serie 362, Volume 362, 2015, pp. 1175-1188, Editorial Springer, Print ISBN 978-3-662-47240-8 Online ISBN 978-3-662-47241-5, Series ISSN 2194-5357, doi: 10.1007/978-3-662-47241-5_99 https://link.springer.com/chapter/10.1007/978-3-662-47241-5_99 https://www.researchgate.net/publication/282375379_Methods_and_Tools_for_the_Operational_Reliability_Optimisation_of_Large-Scale_Industrial_Wind_Turbines

Title: Competitiveness based on logistic management: a real case study

Date: 2015 Contributors: Fausto Pedro García Márquez, Isidro Peña Garcia Pardo and Marta Ramos M. Nieto Other details: Annals of Operations Research, Vol. 233, Issue 1, pp. 157-169, October 2015, doi:10.1007/s10479-013-1508-z https://link.springer.com/article/10.1007/s10479-013-1508-z https://www.researchgate.net/publication/262859871_Competitiveness_based_on_logistic_management_a_real_case_study

Title: Maintenance management of icing blades in wind turbines

Date: 2015 Contributors: R. R. de la Hermosa, Fausto Pedro García Márquez and J.M. Pinar Other details: Condition Monitor, Issue 334, pp. 5-10, ISSN 0268-8050, 2015 http://www.bindt.org/shopbindt/subscriptions/condition-monitor/condition-monitor-print-europe.html#.WTfOSsa1u70

Title: Identification of critical components of wind turbines using FTA over time

Date: 2016 Contributors: Fausto Pedro García Márquez, J.M. Pinar, A. Pliego and M. Papaelias Other details: Renewable Energy. Vol 87, Part 2, Pages 869-883, March 2016. doi: 10.1016/j.renene.2015.09.038 http://www.sciencedirect.com/science/article/pii/S0960148115303177 https://www.researchgate.net/publication/283487354_Identification_of_critical_components_of_wind_turbines_using_FTA_over_the_time

Title: An experimental study on the applicability of acoustic emission for wind turbine gearbox health diagnosis

Date: 2016 Contributors: J. L. F. Chacon, E. A. Andicoberry, V. Kappatos, M. Papaelias, C. Selcuk and T-H. Gan Other details: Journal of Low Frequency Noise, Vibration and Active Control, Vol. 35 (1), pp. 64-76, March 2016 http://journals.sagepub.com/doi/pdf/10.1177/0263092316628401

Title: Generalised transmissibility damage indicator with application to wind turbine component condition monitoring

Date: 2016 Contributors: L. Zhang, Z-Q. Lang and M Papaelias Other details: IEEE Transactions on Industrial Electronics, June 2016 http://ieeexplore.ieee.org/abstract/document/7491354/ http://eprints.whiterose.ac.uk/108113/

Title: Vibration-based tools for the optimisation of large-scale industrial wind turbines

Date: 2016 Contributors: R. R. Hermosa de la Gonzalez-Carrato, F. P. G. Márquez and M. Papaelias Other details: International Journal of Condition Monitoring, Vol. 6 (2), pp. 33-37, June 2016 http://www.ingentaconnect.com/contentone/bindt/ijcm/2016/00000006/00000002/art00002 http://pure-oai.bham.ac.uk/ws/files/30171912/Raul_et_al_Vibration_based_tools_International_Journal_of_Condition_Monitoring_2016.pdf

Title: Optimal maintenance management of offshore wind farms

Date: 2016 Contributors: A. P. Marugán, F. P. G. Márquez and J. M. Pinar Perez Other details: Energies, Vol. 9 (1), pp. 46, 2016, doi: 10.3390/en9010046 http://www.mdpi.com/1996-1073/9/1/46/htm http://www.mdpi.com/1996-1073/9/1/46

Title: A new fault location approach for acoustic emission techniques in wind turbines

Date: 2016 Contributors: C.Q. Gómez Munoz and F. P. G. Márquez Other details: Energies, Vol. 9 (1), pp. 40, 2016, doi: 10.3390/en9010040 http://www.mdpi.com/1996-1073/9/1/40/htm http://www.mdpi.com/1996-1073/9/1/40

Title: Ice detection using thermal infrared radiometry on wind turbine blades

Date: 2016 Contributors: C.Q. Gómez Munoz, F. P. G. Márquez and J. M. Sanchez Tomas Other details: Measurement, Vol. 93 (11), pp. 157-163, November 2016 http://www.sciencedirect.com/science/article/pii/S0263224116303566 https://www.researchgate.net/publication/304746648_Ice_Detection_Using_Thermal_Infrared_Radiometry_on_Wind_Turbine_Blades

Title: Economic viability analysis for icing blades detection in wind turbines

Date: 2017 Contributors: J. M. Pinar Pérez, F. P. G. Márquez and D. Ruiz Hernández Other details: Journal of Cleaner Production, Vol. 135, pp. 1150-1160, November 2016 http://www.sciencedirect.com/science/article/pii/S0959652616309143 https://www.researchgate.net/publication/305077728_Economic_viability_analysys_for_icing_blades_detection_in_wind_turbines

Title: Calculus of the defect severity with EMATs by analysing the attenuation curves of the guided wave

Date: 2017 Contributors: Carlos Q. Gómez, Fausto P. Garciá, Alfredo Arcos, Liang Cheng, Maria Kogia and Mayorkinos Papaelias Other details: Smart Structures and Systems, An International Journal, Vol. 19, No. 2, February 2017, doi: 10.12989/sss.2017.19.2.195 http://technopress.kaist.ac.kr/?page=container&journal=sss&volume=19&num=2 https://www.researchgate.net/publication/311875116_Calculus_of_the_Defect_Severity_with_EMATs_by_Analysing_the_Attenuation_Curves_of_the_Guided_Waves

Title: Optimal decision-making via binary decision diagrams for investments under a risky environment

Date 2017 Contributors: A. P. Marugán, F. P. G. Marquez and B. Lev Other details: International Journal of Production Research, pp. 1-16, March 2017 http://www.tandfonline.com/doi/abs/10.1080/00207543.2017.1308570

Title: Wavelet transforms and pattern recognition on ultrasonic guides waves for frozen surface state diagnosis

Date: 2017 Contributors: C.Q. Gómez Muñoz, A. Arcos Jiménez and F. P. G. Márquez Other details: Renewable Energy, March 2017  https://doi.org/10.1016/j.renene.2017.03.052

Conference papers 2015

Last updated: 8/6/17

 

Conference papers 2014

Last updated: 8/6/17

 

  • A. Pliego, Fausto Pedro García Márquez, “Quantitative Analysis of Probability Applied to Decision Making Process” (ref. M20001), Proceedings of the Advances in Conference on Innovation, Service and Management ICISM2014, Taichung, Taiwan, April 2014. pp. 1-4.
  • X. Yi, C. Ng, P. McKeever, C. Little, S. Hillmansen, “Life estimation modelling for power electronics used in wind turbines”, The Institution of Engineering and Technology’s 7th International Conference on Power Electronics, Machines and Drives (IET PEMD 2014), Manchester, UK, April 2014.  http://ieeexplore.ieee.org/document/6836868/?section=abstract
  • Invited Keynote Conference Paper: A. Karyotakis, R. Bucknall, “The optimisation of Operation and Maintenance Strategies of Offshore wind farms and the importance of advanced Condition Monitoring”, special OPTIMUS session at 11th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, Manchester, UK, June 2014.  http://www.proceedings.com/24193.html
  • X.Y. Zhao and Z.Q. Lang, “A novel health probability-based engineering system condition and health monitoring method”, special OPTIMUS session at 11th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, Manchester, UK, June 2014.  http://www.proceedings.com/24193.html
  • W. Yang, C.H. Ng, P. McKeever, “Reliable wind turbine condition monitoring with the aid of a non-dimensional criterion”, special OPTIMUS session at 11th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, Manchester, UK, June 2014.  http://www.proceedings.com/24193.html
  • A. Govahianjahromi and D. Lee, “Intelligent fault prognostics for wind turbine pitch system based on wind induced vibration analysis”, special OPTIMUS session at 11th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, Manchester, UK, June 2014.  http://www.proceedings.com/24193.html  http://www.proceedings.com/24193.html
  • M. Entezami, E. Stewart, S. Kent, C. Roberts, “Experimental comparison of acoustic and vibration based analysis techniques for condition monitoring of roller bearings”, special OPTIMUS session at 11th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, Manchester, UK, June 2014.  http://www.proceedings.com/24193.html
  • S. Kerkyras, V. Karakassidis, A. Karyotakis and M. Papaelias, “Accurate diagnosis of the condition of industrial wind turbine gearboxes using integrated acoustic emission and vibration analysis”, special OPTIMUS session at 11th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, Manchester, UK, June 2014.  http://www.proceedings.com/24193.html
  • A. Pliego, Fausto Pedro García Márquez, “Fault Tree Dynamic Analysis” (Ref. 115), special OPTIMUS session at 11th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, Manchester, UK, June 2014.  http://www.proceedings.com/24193.html
  • S. Hajiabady, J.E. Camacho Cuesta, F. Polo, V.Requena, M. Murillo, C. Roldán, S. Hillmansen, P. Tricoli and M. Papaelias, “Condition Monitoring of Power Electronics in Wind Turbines”, special OPTIMUS session at 11th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, Manchester, UK, June 2014.  http://www.proceedings.com/24193.html
  • N. Angelopoulos, S. Ojo, M. Papaelias, G.F. Fernando, “Structural Health Monitoring of E-Glass fibre bundles using acoustic emission”, special OPTIMUS session at 11th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, Manchester, UK, June 2014.  http://www.proceedings.com/24193.html
  • A. Pliego, Fausto Pedro Garcia Márquez, “Decision Making via Binary Decision Diagrams: A Real Case Study”, Proceedings of the Eighth International Conference on Management Science and Engineering Management (ICMSEM 2014), Universidade Nova de Lisboa, Lisbon, Portugal, 20th-26th 2014.  http://dx.doi.org/10.1080/17509653.2014.946977   https://ruidera.uclm.es/xmlui/bitstream/handle/10578/12191/Decision%20Making%20via%20Binary%20Decision%20Diagrams%20A%20Real%20Case%20Study.pdf?sequence=2&isAllowed=y
  • A. Pliego and Fausto Pedro García Márquez, “Improving the Efficiency on Decision Making Process via BDD”, 8th International Conference on Industrial Engineering and Industrial Management, XX International Conference on Industrial Engineering and Operations Management International IIE Conference 2014, Malaga, Spain, July, 2014. pp. 1-8.  https://link.springer.com/chapter/10.1007/978-3-662-47241-5_116
  • S. Hajiabady, S. Kerkyras, P. Tricoli, S. Hillmansen, M. Papaelias, “Efficient diagnostic condition monitoring for industrial wind turbines”, IET 3rd Renewable Power Generation Conference (RPG™), Napoli, Italy, September 2014.  http://digital-library.theiet.org/content/conferences/10.1049/cp.2014.0932  http://ieeexplore.ieee.org/document/6993325/
  • Invited Conference Paper: Z. Q. Lang, “Loading Independent Wind Turbine Condition Monitoring: A Baseline Model Approach”, Workshop on Health Monitoring of Offshore Wind Farms (HEMOW), Nanjing, China, September 2014.  http://www.hemow.eu/2nd-Hemow-workshop-programme-final.pdf
  • J.M. Pinar, C.Q. Gómez, E. Segura and Fausto Pedro García Marquez, “A novel study of life cycle cost model of ice in blades condition monitoring systems for a wind turbine”, The Energy and Environment Knowledge Week Congress – E2KW, Toledo, Spain, October 2014.  https://www.researchgate.net/publication/301202620_A_novel_study_of_life_cycle_cost_model_of_ice_in_blades_condition_monitoring_systems_for_a_wind_turbine
  • R. Ruiz and Fausto Pedro García Marquez, “Wind turbines maintenance management based on fault detection and diagnosis”, The Energy and Environment Knowledge Week Congress – E2KW, Toledo, Spain, October 2014.  https://www.researchgate.net/publication/301898083_Wind_turbines_maintenance_management_based_on_fault_detection_and_diagnosis
  • J.E. Camacho, V. Requena, F. Polo, L. Moreno, T. Vanhonacker, B. Stallaert, A. Karyotakis, O. Panagoiliopoulos, V. Karakassidis, Zi-Qiang Lang, C. Roldán, M. Murillo, I. Esparza, G. Auer, I. Zalacain, J. Errea, Fausto Pedro García Márquez, D. Pedregal, D. Lee, S. Hillmansen, P. Tricoli, G. Fernando and M. Papaelias, “Demonstration of Methods and Tools for the Optimisation of Operational Reliability of Large-Scale Industrial Wind Turbines” (Ref. 49), 1st International Conference on Renewable Energies Offshore (RENEW 2014), Lisbon, Portugal, November 2014, pages 931-936.  https://www.crcpress.com/Renewable-Energies-Offshore/Soares/p/book/9781138028715
  • M. Papaelias, V. Dimlaye, J. Jeminez, G. Ye and L. Constantinou, “Safeguarding the Pathway to Cost Competitive Tidal Energy”, 1st International Conference on Renewable Energies Offshore (RENEW 2014), Lisbon, Portugal, November 2014.  https://www.crcpress.com/Renewable-Energies-Offshore/Soares/p/book/9781138028715

Conference papers 2016

Last updated: 8/6/17