Nanoprecise receives patent for its automated predictive maintenance solution

Nanoprecise announced that the U.S. Patent and Trademark Office has issued a patent for its AI-based predictive maintenance system, under U.S. Patent No. 11,188,065, titled, System and Method for Fault Diagnosis and Prognosis for Rotating Equipment.

RotationLF analyzes complex machine health data automatically, using a combination of AI and physics-based models, to minimize learning cycles and provide fast return on investment. The CEEMDAN algorithm is incorporated in to the RotationLF process to analyze large amounts of output parameters of the equipment, identify anomalies and pinpoint faults that have the potential to cause downtime.

“We have helped countless asset-intensive organizations to reduce machine downtime and enhance performance & reliability of their assets,” said Sunil Vedula, CEO, Nanoprecise. “It is an incredible achievement for us to be granted a patent that officially recognizes our innovation and initiative towards helping manufacturers achieve their maintenance goals.”

The MachineDoctor sensor is installed on the rotating equipment and senses different parameters, which are then analyzed locally for anomalies before being discarded or sent to the cloud for more intensive review. The cloud server processes the signal through the RotationLF software, which uses CEEMDAN algorithm along with Wavelet Neural Network to detect faults and predict the Remaining Useful Life of the rotating equipment.