Diagnostics & Prognostics team at client is a dynamic team working on challenging and high-value projects. Seated in the global Service department, we use state-of-the-art methods and tools to execute data driven maintenance of our global wind turbine fleet.Have relevant qualifications / experience with structural audio analysis.Are an open-minded team player with great communication skills and looking to take responsibility of high-profile projects.Are interested in renewable energy and in contributing positively to the climate.Responsibilities and tasks :
- Ownership of structural audio analysis concept.
- Evaluation of structural audio analysis model results and event-based reporting to local service organisation with actionable recommendations.
- Improving existing models and algorithms and exploring new use cases to further expand the scope.
- Following up and updating reported failures according to severity of the failure and supporting local service organisation for taking decisions of data driven maintenance.
Skills and qualifications :
- Ideally you should have a degree in mechanical and AI engineering or equivalent. Furthermore, we expect you to :
- Have at least seven years of experience of structural audio analysis of wind turbines.
- Possess strong knowledge of mechanical structures and bolt connections.
- Have worked previously with AI models and machine learning.
- Have field experience of investigating and troubleshooting wind turbine mechanical structures.
- Feel comfortable working in an English speaking environment (strong written and verbal skills in English needed).
- Have knowledge with operational aspects and procedures concerning diagnostics and analyses.
- Have capabilities of signal processing and acoustics.
- Are familiar with data acquisition hardware and network communications.
- Have previously worked with SQL database and Linux systems.
- Are experienced finding synergizes with wind turbine monitoring technics.
Skills Required
Signal Processing, Finite Element Analysis, Data Analysis, wind turbine design