System for monitoring a circuit breaker

A method for monitoring an operational circuit breaker, the method comprising:

• utilizing at least one sensor located to obtain at least one sensor data of a main shaft of the operational circuit breaker;
• providing the at least one sensor data of the main shaft of the operational circuit breaker to a processor;
• and
• analyzing, by the processor, the at least one sensor data of the main shaft of the operational circuit breaker using a trained neural network to determine position and/or velocity information for a movable contact of the operational circuit breaker, and wherein the trained neural network is an artificial intelligence model that indicates a network of nodes that are used for predictive modeling and is trained using one or more datasets.

A system for training a neural network for monitoring an operational circuit breaker, the system comprising:

• at least one first sensor;
• at least one second sensor;
• and
• a processor;
• wherein the at least one first sensor is configured to be located and utilized to obtain at least one sensor data of a main shaft of a calibration circuit breaker;
• wherein the at least one first sensor is configured to provide the at least one sensor data of the main shaft of the calibration circuit breaker to the processor;
• wherein the at least one second sensor is configured to be located and utilized to obtain at least one sensor data of a moveable contact and/or pushrod of the calibration circuit breaker;
• wherein the at least one second sensor is configured to provide the at least one sensor data of the moveable contact and/or pushrod of the calibration circuit breaker to the processor;
• and
• wherein the processor is configured to train a neural network, wherein the training of the neural network comprises utilization of the at least one sensor data of the main shaft of the calibration circuit breaker and the at least one sensor data of the moveable contact and/or pushrod of the calibration circuit breaker, wherein the trained neural network is an artificial intelligence model that indicates a network of nodes that are used for predictive modeling, and wherein at least one sensor data of a main shaft of the operational circuit breaker is analyzed using the trained neural network to determine position and/or velocity information for a movable contact of the operational circuit breaker.

A method for training a neural network for monitoring an operational circuit breaker, the method comprising:

• utilizing at least one first sensor located to obtain at least one sensor data of a main shaft of a calibration circuit breaker;
• providing the at least one sensor data of the main shaft of the calibration circuit breaker to a processor;
• utilizing at least one second sensor located to obtain at least one sensor data of a moveable contact and/or pushrod of the calibration circuit breaker;
• providing the at least one sensor data of the moveable contact and/or pushrod of the calibration circuit breaker to the processor;
• and
• training, by the processor, a neural network, wherein the training of the neural network comprises utilizing the at least one sensor data of the main shaft of the calibration circuit breaker and the at least one sensor data of the moveable contact and/or pushrod of the calibration circuit breaker, wherein the trained neural network is an artificial intelligence model that indicates a network of nodes that are used for predictive modeling;
• and wherein at least one sensor data of a main shaft of the operational circuit breaker is analyzed using the trained neural network to determine position and/or velocity information for a movable contact of the operational circuit breaker.