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Digitalization key to reducing wind O&M costs, says ONYX InSight

By Michelle Froese | March 29, 2019

From micro-electro mechanical sensors (MEMS) for gathering turbine data, to machine learning algorithms that improve data analysis, it is important for wind owners and operators to embrace these technologies to maintain their position in the industry, shares ONYX InSight, a joint venture. The company combines Romax Technology’s 30 years of expertise in software, services, and data analytics for gearbox, bearings and rotating machinery with Castrol’s global reach and knowledge of wind turbine lubrication.

Bruce Hall, CEO, ONYX InSight (L) and Richard Smith, Principal Engineer, ONYX InSight discuss ONYX's main bearing grease flushing rig with Technical Symposium delegates.

Bruce Hall, CEO, ONYX InSight (left) and Richard Smith, Principal Engineer, ONYX InSight discuss the company’s main bearing grease flushing rig with delegates at its March Technical Symposium.

“Operators that continue to rely on traditional O&M practices to manage their profitability and overlook the rise of disruptive digital technologies risk losing out,” said Dr John Coultate, Head of Product Development with ONYX InSight. “Failure to embrace these technologies and apply them appropriately will see them overtaken by competitors able to reliably and profitably operate wind farms at lower cost.”

According to more than half (55%) of the asset and operations managers who attended ONYX InSight’s European Technical Symposium this month, embracing disruptive digital technologies for the collection and analysis of wind-turbine data offers the best route to reducing the costs of operations and maintenance programs.

A majority of attendees recognized the need for involving specialists to implement and harness the kinds of digital technologies that could be seen as disruptive. More than half said they recognized the need for third-party expertise to support digital integration and analysis of turbine data.

MEMS sensors, which lie at the heart of the digital disruption of wind-turbine monitoring are produced annually in their billions at significantly lower cost than the piezoelectric sensors they are replacing. Greater versatility means MEMS sensors can be used to capture much more data about turbine behavior. The sensors’ digital data outputs also eliminate the need for additional costly signal conditioning, making it easier for operators to run data analysis using another disruptive technology, machine learning.

“The technology is here to stay, the only barrier to adoption is access to quality data,” said Dr Xiaoqin Ma, Head of Technology at ONYX InSight. “Machine learning can make sense out of large quantity of data that human analysts might find overwhelming. With vast amounts of data being collected through hundreds of channels from every single turbine every second, ML is essential for understanding turbine condition and reducing the cost of maintenance programs.”

Dr Ma and Dr Coultate were speaking to more than 50 wind asset and operations managers from across Europe, at the ONYX InSight Technical Symposium. Presentations and panel discussions focused on the technology trends and adoption by wind farm operators looking to drive lifetime extension and reduce the cost of operations and maintenance.

“Properly trained machine learning algorithms, backed up by intelligent engineering experience, can add real value to the wind energy industry,” added Ma. “Without the right support for quality data inputs and guidance from experts, however, users of machine learning, disappointed by its outputs, risk overlooking a powerful tool that will drive OPEX cost reductions into the future.”

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