2 nd July 2019

1. PMB, WP3 - Novel Condition Monitoring and Fault Detection Techniques and Technologies - Progress Report – Simon Hogg 2nd July 2019

2. Recruitment WP 3.1, WP 3.2 & WP 3.5 – no change to report since last meeting. All PDRA & PhD resources required for these projects have been recruited and are active on the research. WP3.3 & WP 3.4 - systems level fault detection and isolation with condition monitoring. These projects have been combined into a single project resourced by one 36 month PDRA. A suitable PDRA, Dr YanhuaLiu, has been identified. Dr Liu was scheduled to start on the project in May this year, but this was delayed due to Visa issues. Dr Liu has now been appointed as PDRA at Hull for 36 months from 15thJuly.

3. Progress against tasks for each Work Package and plan for next 3 months • WP3.1. Determining the condition of lubricated components through monitoring of oil condition. • PDRA Richard Williams (Durham University). • Project agreement still to be put in place (DU, Ørsted& CC Jensen as partners) – waiting for project agreement for WP2.4 to be finalised and used as a template. NDA in place with CC Jensen. • Oil monitoring sensors and equipment procured from CC Jensen and installed on two Ørstedtest turbines in January 2019. • Coming to the end of planned 6 month data will collection period using the CC Jensen instrumentation on the test turbine to provide the baseline dataset for the project. • Regular monthly conference calls are being held between DU, Ørsted & CC Jensen. • Durham has access to Oil CM data and SCADA data from test turbines. Preliminary data quality checking is being done. • The plan for the next 3 months is to start to investigate and develop methods for linking the Oil CM and SCADA data for improved CM of oil lubricated components, using the first 6 months of test data that is now available. • WP3.2. Condition monitoring of wind turbine bearings through fusion of vibration-based health monitoring and acoustic emission (AE) features. • PhD student Matthew (Sheffield University)started Oct 2018. Progress to date includes: • Implemented a representative test case in the lab, measuring vibration and AE with a seeded fault. • Implemented a new means of online clustering for AE data. • Produced a conference paper for the International Conference on Structural Health Monitoring (IWSHM), Title: Assessing the likelihood of damage at the start of a structural health monitoring campaign. To be presented in Stanford, Sept 2019 • Presented his work at a technical meeting with Siemens-Gamesain June 2019. • Plans for the next 6 months are to develop a localisation method that will work with the clustering algorithm and look at damage progression data to be provided by SGRE.

4. Progress against tasks for each Work Package and plan for next 3 months • WP3.3. Systems level integration of fault detection and isolation with condition monitoring. • WP3.4. Verification and validation of fault detection and condition monitoring schemes. • CM is an off-line approach to health monitoring (structure and components) but Control-based Fault Monitoring is necessarily an on-line approach. Hence, original WP3.3 & WP3.4 identified as unsuitable and original plan not followed. • Conference call held on 10th May (Patton, Liu, Dervilis & Hogg) to discuss a potential refocussing of the project towards developing active control techniques for minimising the dynamic loading on wind turbine structures. Patton will produce a revised project specification for approval by the Project Management Board and the EPSRC. • New project emerging: ‘Fault-tolerant Asymmetrical Load Reduction Control for Large Offshore Wind Turbines.’ • Dr Yanhua Liu will start work on project on 15th July 2019. • Plan for next 3 months is to start work on comparison of existing Load Mitigation/FTC designs (Hull) with Gaussian Learning [model-free] strategy and to prepare a journal paper on work completed in this area from an earlier project.

5. Progress against tasks for each Work Package and plan for next 3 months • WP3.5. Generator and converter fault analyses, including open- and short-circuits, and health and condition monitoring. • PhD student Zeting Mei (Oct 18 -) ‘Fault Modelling and Diagnostics of Permanent Magnet Machines for Wind Power Applications.’ • 2D FE simulation of PM machines under steady-state condition completed. • Considering simulation of parallel windings and faulty condition • Plan for the next 3 months: Dynamic simulation of faulty permanent magnet generator in Matlab/Simulink • PhD student Matthew Fenton-Jones (Sept 18 -) ‘Fault Analysis and Reliability of Wind Turbine Power Electronics.’ • Many interactions with SGRE, topics identified. • Initial experimental set-up completed. • System modelling work started. • Plan for the next 3 months: Preparation and completion of first round of experimental studies, planning for future long term studies, continuation of system modelling and continued interaction with SGRE.

6. WP3 Risks from earlier PMB reports that are still open: • Project delays caused by execution of project agreement for WP3.1 now also involving CC Jensen.Project agreement still not signed but not holding up the work, which is progressing under NDA’s. Project agreement is being progressed. • New WP3 Risks identified this Quarter: • Re-scoping of specification for WP3.3/3.4 is not approved. Risks and Opportunities

7. Nothing new to report since last meeting. Outcomes and Outputs

8. Sustainable control & Predictive maintenance Software sensing system Nonlinear wind field WP 3.3 &3.4 Fault-tolerant Load Reduction Control for Large Offshore Wind Turbines Measurements Wind knowledge Sustainablecontroller (CPC+IPC) Reconfiguration Mechanism Fault information Reference Fault monitoring Measurements Fault indicator FTC Improved reliability & lifetime Reduced operation & maintenance Reduced fatigue loading

9. f f OWT WP 3.3 &3.4 Fault-tolerant Load Reduction Control for Large Offshore Wind Turbines Controlling blade pitch HydraulicPitch Actuator Accumulator V1 C1 Pump Station Pitch Sensor - Reference + CPC+IPC Generator speed error Bending moments

10. Proposed on-line fault-tolerant strategy using unknown input observer framework for pitch sensor faults WP 3.3 &3.4 Fault-tolerant Load Reduction Control for Large Offshore Wind Turbines Consider all the “fault effects” acting in both rotor & tower system • LQR-based IPC • PI-based IPC