METHODS AND SYSTEMS FOR DATA COLLECTION, LEARNING, AND STREAMING OF MACHINE SIGNALS FOR ANALYTICS AND PREDICTED MAINTENANCE USING THE INDUSTRIAL INTERNET OF THINGS

摘要

An industrial machine predictive maintenance system may include an industrial machine data analysis facility that generates streams of industrial machine health monitoring data by applying machine learning to data representative of conditions of portions of industrial machines received via a data collection network. The system may include an industrial machine predictive maintenance facility that produces industrial machine service recommendations responsive to the health monitoring data by applying machine fault detection and classification algorithms thereto. The system detects an operating characteristic of an industrial machine, such as vibration, using one or more sensors of a mobile data collector and identify, as a condition of the industrial machine, a characteristic for the industrial machine within the knowledge base. The system can determine severity of the condition and predict and execute a maintenance action to perform against the industrial machine based on the severity of the condition.