Methods and systems for data collection, learning, and streaming of machine signals for part identification and operating characteristics determination using the industrial Internet of Things

A method of machine learning-based part recognition, comprising:

• applying a target part imaging template to an image validating procedure that determines if a captured image meets an image capture validation criterion;
• retrieving, with an external device, part descriptive information from a smart RFID data storage associated with a specific industrial machine, wherein the retrieving the part descriptive information includes retrieving images of parts of the specific industrial machine from a network stored digital twin of a smart RFID element disposed with the specific industrial machine;
• performing image analysis by processing the captured image with image analysis rules that facilitate detecting candidate parts of the specific industrial machine being present in the captured image;
• recognizing one or more parts of the candidate parts as a part of the specific industrial machine based on similarity of a candidate part with the images of parts of the specific industrial machine;
• and
• adapting at least one of the target part imaging template, the image analysis rules, or the part recognition based on feedback produced from machine learning of the recognized one or more parts, thereby improving at least one of image capture, image analysis or the part recognition.

A method of machine learning-based part recognition, comprising:

• applying a target part imaging template to an image validating procedure that determines if a captured image meets an image capture validation criterion;
• retrieving, with an external device, part descriptive information from a smart RFID data storage associated with a specific industrial machine, wherein retrieving the part descriptive information includes retrieving images of parts of the specific industrial machine;
• performing image analysis by processing the captured image with image analysis rules that facilitate detecting candidate parts of the specific industrial machine being present in the captured image;
• recognizing one or more parts of the candidate parts as a part of the specific industrial machine based on similarity of a candidate part with the images of parts of the specific industrial machine;
• and
• adapting at least one of the target part imaging template, the image analysis rules, or the part recognition based on feedback produced from machine learning of the recognized parts, thereby improving at least one of image capture, image analysis or the part recognition, wherein the feedback produced by the machine learning facilitates updating a most recently captured image of the part in the smart RFID data storage deployed with the specific industrial machine.

A machine part recognition system, comprising:

• a smart RFID data storage associated with a specific industrial machine, the smart RFID data storage is configured to store part descriptive information including images of parts of the specific industrial machine;
• an external device external to the specific industrial machine, the external device configured for:
• applying a target part imaging template to an image validating procedure that determines if a captured image meets an image capture validation criterion;
• retrieving the part descriptive information and the images of parts from the smart RFID data storage associated with the specific industrial machine;
• performing image analysis by processing the captured image with image analysis rules that facilitate detecting candidate parts of the specific industrial machine being present in the captured image;
• recognizing one or more parts of the candidate parts as a part of the specific industrial machine based on similarity of a candidate part with the images of parts of the specific industrial machine;
• and
• adapting at least one of the target part imaging template, the image analysis rules, or the part recognition based on feedback produced from machine learning of the recognized parts, thereby improving at least one of image capture, image analysis, or the part recognition.