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Condition monitoring of wind turbine drivetrains

Completed

Project description

ACMWind: Condition monitoring of wind turbine drivetrains via non-contact acoustic sensors

Background

The EU Agency for Safety and Health is currently amending wind turbine standards to ensure safer O&M tasks and increase the Probability of Detection (POD) for wind turbine defects. ISO have also identified such issues, and have initiated the development of QA standards tailored for the Condition Monitoring (CM) of wind turbines. Current CM systems are intrusive, and hence revoke the initial OEM warranty of drive train components. The combination of industrial and legislative factors is the key driver behind CMDrive: a bespoke and non-intrusive acoustic-analysis CM system, having a POD for drive-train defects of 90-98% within the range of operating limits.

CMDRive-pic

The CMDrive system has been installed and validated on-site, within the nacelle of a 2 MW onshore wind turbine. By utilising the acoustic vibrations emitted from the drive train a unique baseline for the specific wind turbine was generated that describes the normal/expected variations in the sound profile which correspond to ‘healthy operation’. However, a longer system trial is required to validate the acceptance criteria for the presence of faults/defects within specific drive-train components. This is one of the main technical scopes behind this FTI application. The simultaneous installation of many units, in an equal number of wind turbines, will help increase the validation process and hence, the readiness of this CM system.

Objectives

The overall goal is the development of a cost-effective condition monitoring system for wind turbine drive trains by using non-contact acoustic sensors. The possibility of defect detecting is aimed to reach as high as 90-98%, while the cost of the condition monitoring system is reduced by 60% compared with other condition monitoring system on the market.

Benefits

CMDrive is a disruptive innovation within the CM sector of the wind industry, as it aims to revolutionise the manner in which condition monitoring for wind turbines is carried out, shifting it from an intrusive (such as with Vibrational Analysis and Acoustic Emission), to a non-contact/non intrusive process. It will benefit the wind CM sector by addressing the stricter amendments of the wind turbine standard EN 50308, and facilitating the emendation of current ISO standards for the diagnosis of wind turbines. By Implementing the CMDrive, the maintenance routines will be optimised, leading to an increase in the yearly operating time for large turbines, from 95% to 98-99%. In addition, the CMDrive system will support the growth of a renewable source of energy, currently responsible for providing 10.2% of Europe’s electricity demand, and which is forecast to increase to 19.8% by 2020.

Project Partners

  • Inesco Ingenieros
  • Relex Italia
  • Innora
  • Brunel University London

 

For more information, please visit the CMDrive website.

 


Meet the Principal Investigator(s) for the project

Professor Tat-Hean Gan - Professional Qualifications - CEng. IntPE (UK), Eur Ing, BEng (Hons) Electrical and Electronics Engg (Uni of Nottingham), MSc in Advanced Mechanical Engineering (University of Warwick), MBA in International Business (University of Birmingham), PhD in Engineering (University of Warwick), Languages - English, Malaysian, Mandarin, Cantonese, Professional Bodies - Fellow of the British Institute of NDT, Fellow of the Institute of Engineering and Technology, Tat-Hean Gan has 10 years of experience in Non-Destructive Testing (NDT), Structural Health Monitoring (SHM) and Condition Monitoring of rotating machineries in various industries namely nuclear, renewable energy (eg Wind, Wave ad Tidal), Oil and Gas, Petrochemical, Construction and Infrastructure, Aerospace and Automotive. He is the Director of BIC, leading activities varying from Research and development to commercialisation in the areas of novel technique development, sensor applications, signal and image processing, numerical modelling and electronics hardware. His experience is also in Collaborative funding (EC FP7 and UK TSB), project management and technology commercialisation.