Data presented to the delegation at Wind Energy Update’s 8th Annual Wind O&M Dallas 2016 conference in mid-April, unveiled how 45.9% of the U.S. fleet has condition-monitoring systems (CMS) installed of the close of 2015. While considerable fluctuations in penetration rates exist between turbine class range – 4.5% in sub 1.5 MW turbines compared to 91.8% in the over 2.3 MW class – these figures provided by Aaron Barr, Technology Advisor at MAKE Consulting, would have been inconceivable just a few years ago.
Now we are seeing the envelope of O&M solutions pushed once again with a SaaS offering from Buffalo, NY -based Sentient Science moving deeper into the realm of prognostics and challenging how predictive CMS can be.
“We have brought to the table a deep learning about the physics of actual componentry through material science, which is failing in wind turbine machines,” said Elias Taverez, Executive Vice-President for Sales. “We are able to offer a prognostic approach to addressing failures which had previously not been seen in the industry.”
Taverez says DigitalClone Technology stands apart from CMS thoughts ability to advance the O&M proposition from failure diagnosis to failure prognosis.
“The industry is rife with a host of solutions in CMS, which essentially means they run and monitor their machines until a failure is detected, then they go and fix it,” Taverez contends. “The challenge with this approach is that the operator is notified of a failure after it has already occurred, so they are doing corrective maintenance rather than preventative maintenance.”
By contrast, the prognostic approach does more than speed up the repair horizon and limit outlay through avoidance of catastrophic failure as is the case with CMS. “It brings the conversation about what to do at the most cost effective horizon.”
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