Predictive maintenance technology is widely embraced in the wind energy industry.
Fremont, CA: The Internet of Things (IoT) and predictive maintenance are two instances of IT technologies for the renewable energy field that have earlier demonstrated their value. Most wind farm operators employ SCADA data for remote monitoring and management.
Yet, the efficiency of SCADA-based predictive maintenance is damaged by a lack of visibility into the changing downtime. Therefore, operators actively investigate IoT-driven wind turbine predictive maintenance to complement customary methods (or even replace SCADA).
Wind turbine farms are open to natural disasters, for example, lightning strikes, excessive icing, earthquakes, and other natural disasters. Following unexpected maintenance, personnel must run diagnostics to identify the impact, which might cause operations to stall for a long time.
IoT sensors can successfully replace humans in the preliminary damage assessment, resulting in more productive on-site visits. Suppose one of the turbines is struck by lightning, for example.
In that case, a sensor may gather data about the current that traveled through each blade, evaluate any changes in performance, and send the information in real time to the central control system, which will warn the team.
Thus, the maintenance crew will know where they are required to go, what effect the strike had, and which blades must be diagnosed. Then, the team will just need to halt the affected wind turbines and reduce downtime during the visit.
Also, machine learning algorithms can compare present performance to historical records and scan past maintenance reports to estimate the present state of the blade and offer technicians extra recommendations on whether it should be checked immediately or if maintenance can be postponed. Such details can greatly help in the optimization of maintenance schedules and the advancement of on-site planning visits.
