Methods and systems for detecting operating conditions of an industrial machine using the industrial internet of things

A system for detecting operating characteristics of an industrial machine, comprising:

• at least one data capture device configured to capture raw data of a point of interest of the industrial machine;
• a computer vision system that:
• generates one or more image data sets using the raw data captured,
• identifies one or more values corresponding to a portion of the industrial machine within the point of interest represented by the one or more image data sets,
• compares the one or more values to corresponding predicted values, wherein:
• (i) the predicted values correspond to characteristics of the portion of the industrial machine that indicate that the industrial machine is operating within acceptable or expected tolerances, and (ii) the predicted values are generated based on training data sets generated by a deep learning system that correlates data with an indicator of an outcome,
• generates a variance data set based on the comparison of the one or more values and the corresponding predicted values, the variance data set representing a difference between the one or more values and the corresponding predicted values,
• detects an operating characteristic of the industrial machine based on the variance data by utilizing a classification model trained to identify the operating characteristic based on variance data, wherein the operating characteristic represents a possible or present issue relating to an operation of the industrial machine, and
• generates data indicating the detection of the operating characteristic;
• and
• a predictive maintenance platform that processes the data indicating the detection of the operating characteristic to identify a maintenance action representing an action which may be taken to prevent or resolve the possible or present issue relating to an operation of the industrial machine.