System for monitoring a circuit breaker

A method for monitoring a circuit breaker, the method comprising:

• utilizing at least one operational sensor located to obtain at least one time series sensor data of at least one first part of an operational circuit breaker, the first part comprising a first part of the operational circuit breaker and the at least one operational sensor comprising one or more of an acceleration sensor and a main shaft angle sensor;
• providing the at least one time series sensor data of the at least one first part of the operational circuit breaker to a processor;
• and
• determining by the processor that at least one second part of the operational circuit breaker is operating correctly or that the at least one second part of the operational circuit breaker has a fault, the second part of the operational circuit breaker comprising one of a moveable contact and a pushrod of the operational circuit breaker, wherein the determining comprises analysing the at least one time series sensor data of the at least one first part of the operational circuit breaker by a trained neural network implemented by the processor,
• wherein the neural network was trained on a basis of at least one time series sensor data obtained by at least one first calibration sensor associated with of at least one first part of a calibration circuit breaker when the at least one first part of the calibration circuit breaker was operating correctly and at least one time series sensor data obtained by at least one second calibration sensor associated with at least one second part of the calibration circuit breaker when the at least one second part of the calibration circuit breaker was operating correctly, and wherein the calibration circuit breaker is a same model as the operational circuit breaker, and wherein the at least one first part of the calibration circuit breaker is a main shaft of the calibration circuit breaker and the at least one second part of the calibration circuit breaker comprises one or more of a moveable contact or a pushrod of the calibration circuit breaker.

A system for training a neural network for monitoring a 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 time series sensor data of at least one first part of a calibration circuit breaker,
• wherein the at least one first part of the calibration circuit breaker is a main shaft of the circuit breaker,
• wherein the at least one first sensor is configured to provide the at least one time series sensor data of the at least one first part 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 time series sensor data of at least one second part of the calibration circuit breaker, wherein the at least one second part of the calibration circuit breaker is a moveable contact and/or pushrod of the circuit breaker,
• wherein the at least one second sensor is configured to provide the at least one time series sensor data of the at least one second part of the calibration circuit breaker to the processor, and
• wherein the processor is configured to train the neural network,
• wherein the training of the neural network comprises utilization of the at least one time series sensor data of the at least one first part of the calibration circuit breaker and the at least one sensor data of the at least one second part of the calibration circuit breaker,
• wherein the trained neural network is configured to determine that at least one second part of an operational circuit breaker is operating correctly or that the at least one second part of the operational circuit breaker has a fault on a basis of analysis of the at least one time series sensor data of the at least one first part of the operational circuit breaker, and
• wherein the calibration circuit breaker is a same model as the operational circuit breaker, and wherein the neural network was trained on a basis of the at least one time series sensor data obtained by the at least one first sensor associated with the at least one first part of the calibration circuit breaker when the at least first part of the calibration circuit breaker was operating correctly and the at least one time series sensor data obtained by the at least one second sensor associated with the at least one second part of the calibration circuit breaker when the at least one second part of the calibration circuit breaker was operating correctly, wherein the at least one first part of the calibration circuit breaker is a main shaft of the calibration circuit breaker and the at least one second part of the calibration circuit breaker comprises one or more of a moveable contact or a pushrod of the calibration circuit breaker.

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

• utilizing at least one first sensor located to obtain at least one time series sensor data of at least one first part of a calibration circuit breaker, wherein the at least one first part of the calibration circuit breaker is a main shaft of the calibration circuit breaker;
• providing the at least one time series sensor data of the at least one first part of the calibration circuit breaker to a processor;
• utilizing at least one second sensor located to obtain at least one time series sensor data of at least one second part of the calibration circuit breaker, wherein the at least one second part of the calibration circuit breaker is a moveable contact and/or pushrod of the circuit breaker;
• providing the at least one time series sensor data of the at least one second part of the calibration circuit breaker to the processor;
• and
• training by the processor the neural network, wherein:
• the training of the neural network comprises utilizing the at least one time series sensor data of the at least one first part of the calibration circuit breaker and at least one sensor data of the at least one second part of the calibration circuit breaker,
• the trained neural network is configured to determine that at least one second part of an operational circuit breaker is operating correctly or that the at least one second part of the operational circuit breaker has a fault on a basis of analysis of at least one time series sensor data of the at least one first part of the operational circuit breaker, and
• the calibration circuit breaker is a same model as the operational circuit breaker and wherein the neural network was trained on a basis of the at least one time series sensor data obtained by the at least one first sensor associated with the at least one first part of the calibration circuit breaker when the at least one first part of the calibration circuit breaker was operating correctly and the at least one time series sensor data obtained by the at least one second sensor associated with the at least one second part of the calibration circuit breaker when the at least one second part of the calibration circuit breaker was operating correctly, wherein the at least one first part of the calibration circuit breaker is a main shaft of the calibration circuit breaker and the at least one second part of the calibration circuit breaker comprises one or more of a moveable contact or a pushrod of the calibration circuit breaker.