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Predictive maintenance for wave energy devices

RISKMAN: An online, risk driven condition monitoring, predictive maintenance management and design upscaling tool for wave energy devices

Background

RISKMAN is a maintenance management tool which will be developed as an enabling technology for reducing wave energy convertor (WEC) devices levelised cost of electricity (LCOE) to compete with other energy systems. RISKMAN aims to provide a step reduction in Albertern WaveNet WECs capital and operational expenditure (CAPEX/OPEX) and increase in availability times through:

  • Condition Monitoring of critical components of the WEC arrays by a suite of embedded complementary sensors;
  • Transmitting sensor output (electrical) signals to onshore in real time through electro-optical conversion and fibre optic cables for cloud computing;
  • Assembly of the historic data into a reliability database, essentially a library of structural health signatures and norms; and
  • construction of a risk driven predictive maintenance system (PMS) which combines the database with mathematical models to determine for each component a probability distribution function to give the RISK of failure over any time period.

 

RISKMAN Project
RISKMAN Project

Objectives

Condition monitoring of critical components of wave energy devices. Development of risk driven predictive maintenance system combining mathematical models and big data analysis.

Benefits

Reduction in CAPEX/OPEX through condition monitoring of WECs providing improved security of supply and reduction in levelised cost of electricity to compete with other renewable energy systems.

Project Partners


Meet the Principal Investigator(s) for the project

Professor Tat-Hean Gan

Related Research Group(s)

woman engineer

Brunel Innovation Centre - A world-class research and technology centre that sits between the knowledge base and industry.


Partnering with confidence

Organisations interested in our research can partner with us with confidence backed by an external and independent benchmark: The Knowledge Exchange Framework. Read more.


Project last modified 12/10/2023