Condition monitoring revolution
How advanced edge computing technology has shifted the boundaries of data collection in wind energy
Condition monitoring systems (CMS) have become an essential investment for new and existing fleets of wind turbines. Without a suitable system installed, windfarm owners and operators are largely in the dark regarding real time developments in turbine health.
Until recently, however, many assets were left out of the loop because ageing turbines in established markets – and many new turbines in emerging markets – don’t have CMS fitted due to historically high CAPEX costs. CMS systems with traditional piezoelectric (also known as ICP or IEPE) accelerometers were too expensive to justify the business case for many owners.
Driving down costs
ONYX Insight drove dramatic reductions in the cost of CMS using MEMS (Micro Electro-Mechanical Systems) sensor technology and low-cost edge computing. In this article, we explain how MEMS are applied to the wind sector, how this has transformed the condition monitoring market, and why the trend for advanced CMS will lead to better, smarter operations and maintenance (O&M) strategies.
What is MEMS technology?
MEMS sensors are microscopic devices, typically etched from a layer of silicon and mounted inside a tiny enclosure with integrated electronics. MEMS were first commercialised in the 1980s and today are mass-produced devices which feature in a huge number of home electronics and industrial applications.
For example, every car leaving the production line today has dozens of MEMS sensors including accelerometers, gyroscopes, pressure sensors, flow sensors and inclinometers. Mobile phones and video games use MEMS accelerometers and gyroscopes and it is estimated that over 10 billion MEMS sensors are produced globally every year.
How is MEMS transforming wind turbine monitoring?
MEMS allow advanced sensor data to be gathered economically, on a wider range of assets than ever before. To date, ecoCMS has been retrofitted on dozens of different turbine models. Every turbine installation requires a detailed work instruction to be developed – this describes the safe installation process, including sensor locations, cable routing, electrical installation and mounting details. ONYX Insight now have off-the-shelf work instructions available for all major turbine types.
Even today, many assets are fitted with so-called ‘legacy’ CMS which are no longer supported by the manufacturer. These often fail to match today’s capability in terms of specification and data standards. Crucially, they may be based on outdated technology with high failure rates, due to moving parts such as fans and rotating hard drives. ONYX Insight uses more cost-effective and up to date technology to solve these issues, leading many owners to remove outmoded CMS – as in one case where a customer replaced 600 legacy CMS units with ecoCMS.
How is a wider uptake of advanced edge computing unlocking a new approach to operations and maintenance in wind energy?
Installing advanced CMS to a fleet of turbines brings a wealth of benefits. Most significantly, it opens the door to predictive maintenance on assets which were not previously data rich. Using advanced AI tools, the right predictive maintenance partner can deliver savings of up to 30% from windfarm O&M budgets.
One of ONYX Insight’s customers, a large operator in the US, installed ecoCMS on 50 turbines. Within days, ONYX detected 10 drivetrain issues, which were then confirmed and repaired at an early stage, saving considerable time and money. The customer went on to install ecoCMS on an additional 300 turbines.
Below, we briefly outline three key benefits to windfarm owners and operators of adopting a predictive maintenance programme after installing an advanced CMS system such as ecoCMS.
- Repair schedule optimisation
Logistical costs are a key consideration during windfarm O&M. With a greater insight into asset health, operators can take a strategic approach to repair work, consolidating tasks and coordinating schedules by location.
These savings can quickly snowball. In North America, for example, crane costs are high and windfarms are large. Longer lead times in detecting faults allow multiple repairs to be addressed with one crane deployment. Where a main bearing is repaired consecutively on one turbine and a gearbox on a neighbouring turbine, the saving can be up to $300k.
- Life extension
By putting a smart predictive maintenance strategy into place from the start of an asset’s lifecycle, useful life can be extended by 25%. For ageing assets, where the warranty period has ended and the initial cost of the project has been paid back, an extra four to five years of profitable operation can lead to significant additional revenue for windfarm owners.
- Downtime reduction
Unscheduled downtime can severely impact the profitability of an asset, especially when it occurs during high wind seasons. By identifying potential issues at an embryonic stage, predictive maintenance can support engineering teams to schedule maintenance and repairs well ahead of a failure. This often leads to more favourable terms and pricing for spare parts due to longer lead times, unlocking savings from the overall OPEX budget of up to 17%.
Better data for analytics platforms and data scientists
ecoCMS is part of a new generation of advanced sensing technologies that allow flexible edge computing. Most CMS have a fixed or legacy set up, that is hard to change. This is no longer fit for purpose for renewable companies rolling out analytics platforms and building data science teams.
With adaptability at the edge on how data is recorded and pre-processed, the analyst can refine the inputs to machine learning models, very often making the difference between an ineffective algorithm and a highly valuable one.
Dr Ashley Crowther,
and Dr John Coultate,
Head of Product Development