Design and Development of an Augmented Reality (AR) Enhanced Predictive Maintenance System with Artificial Intelligence (AI) for Industrial Mobile Robot.

Abstract:

The technology relates to a method for operation of a predictive maintenance system for motorized machines. The method includes extracting sensor data from a plurality of plug and play sensors strategically positioned to capture relevant information associated with a motor performance. The method further includes transmitting the extracted sensor data to an edge processing industrial personal computer (PC). The method further includes performing a pre-processing of the sensor data using a Fast Fourier Transform (FFT) technique. The method further includes feeding the pre-processed sensor data into a machine learning model for at least one of an anomaly detection, a failure detection, and a failure forecast. The method further includes selecting predictions generated by the machine learning model in a centralized dashboard. The method further includes iteratively training a machine learning model implemented within the predictive maintenance system.