Patent Description:
<CIT> describes a component monitoring system structured to monitor circuit breaker assembly component characteristics. It is described that the component monitoring system includes a record assembly, a number of impulse sensor assemblies, a comparison assembly, and an output assembly. It is described that the record assembly includes selected nominal data for a selected circuit breaker component. It is described that he impulse sensor assemblies are structured to measure a number of actual component characteristics for a substantial portion of the circuit breaker assembly and to transmit actual component characteristic output data. It is described that the comparison assembly is structured to receive an electronic signal from the record assembly and the impulse sensor assemblies, to compare each impulse sensor assembly actual component characteristic output data to the selected nominal data and to provide an indication signal as to whether the impulse sensor assembly output data is acceptable when compared to the selected nominal data. It is described that the output assembly includes a communication assembly and an output device.

The operating mechanism of a circuit breaker (CB) is one of the main subsystems prone to failure of a switchgear. Most of the mechanical failure modes occurring in the mechanism can be detected by monitoring the travel curve that represents the position of the moving contact. Furthermore, the travel curve may also reveal electrical failure modes like contact ablation.

Today, travel curve monitoring is rarely applied in switchgears.

Furthermore, the existing solutions have following drawbacks:.

[<NUM>] - [<NUM>] are characteristic for position sensors applicable for travel curve measurements in CBs and can only be mitigated by selecting high-end solutions. This typically results in much higher cost making permanent installation unattractive.

There is a need to address these problems.

Therefore, it would be advantageous to have an improved technique to monitor a circuit breaker.

Claim <NUM> defines a system for monitoring a circuit breaker. Claim <NUM> defines a system for monitoring a two or three phase switchgear or control gear. Claim <NUM> defines a method for monitoring a circuit breaker. Claim <NUM> defines a system for training a neural network for monitoring a circuit breaker. Claim <NUM> defines a method for training a neural network for monitoring a circuit breaker. The invention and its scope of protection is defined by these independent claims. The following aspects and examples of the disclosure provide examples of how technical subject matters can be combined.

<FIG> shows an example of a system <NUM> for monitoring a circuit breaker. The system comprises at least one sensor <NUM>, and a processing unit <NUM>. The at least one sensor is configured to be located and utilized to obtain at least one sensor data of a main shaft of an operational circuit breaker <NUM>. The at least one sensor is configured to provide the at least one sensor data of the main shaft of the operational circuit breaker to the processing unit. The processing unit is configured to determine position and/or velocity information for a moveable contact of the operational circuit breaker. The determination comprises analysis of the at least one sensor data of the main shaft of the operational circuit breaker by a trained neural network implemented by the processing unit.

According to the invention, the neural network was trained on the basis of at least one sensor data of a main shaft of a calibration circuit breaker <NUM> and at least one sensor data of a moveable contact and/or pushrod of the calibration circuit breaker.

According to an example, the at least one sensor data of the main shaft of the calibration circuit breaker was acquired at the same time as the at least one sensor data of the moveable contact and/or pushrod of the calibration circuit breaker.

According to an example, the calibration circuit breaker was the same type or model as the operational circuit breaker.

According to an example, at least one sensor <NUM>, <NUM> utilized to obtain the at least one sensor data of the main shaft of the calibration circuit breaker was the same type or model as the at least one sensor <NUM> utilized to obtain the at least one sensor data of the main shaft of the operational circuit breaker.

According to an example, at least one sensor utilized to obtain the at least one sensor data of the main shaft of the calibration circuit breaker was located at the same or equivalent at least one location as the at least one sensor utilized to obtain the at least one sensor data of the main shaft of the operational circuit breaker.

According to the invention, the at least one sensor utilized to obtain the at least one sensor data of the main shaft of the operational circuit breaker comprises one or more of: acceleration sensor; main shaft angle sensor.

According to the invention, the at least one sensor <NUM> utilized to obtain the at least one sensor data of the moveable contact and/or pushrod of the calibration circuit breaker comprises one or more of: position sensor; velocity sensor.

According to an example, the position information and/or the velocity information for the moveable contact comprises a travel curve.

According to an example, the system comprises an output unit configured to output the position information and/or the velocity information for the moveable contact.

According to an example, the processing unit is configured to determine if the circuit breaker has a fault. The determination comprises analysis of the position information and/or the velocity information for the moveable contact.

<FIG> shows an example of a system <NUM> for monitoring a two or three phase switchgear or control gear. The system comprises two or three systems <NUM> as described above with respect to <FIG>, where one of the systems <NUM> is used for a circuit breaker of each of the two or three phases.

<FIG> shows a method <NUM> for monitoring a circuit breaker in its basic steps. The method comprises:.

According to the invention, the neural network was trained on the basis of at least one sensor data of a main shaft of a calibration circuit breaker and at least one sensor data of a moveable contact and/or pushrod of the calibration circuit breaker.

In an example, the at least one sensor data of the main shaft of the calibration circuit breaker was acquired at the same time as the at least one sensor data of the moveable contact and/or pushrod of the calibration circuit breaker.

In an example, the calibration circuit breaker was the same type or model as the operational circuit breaker.

In an example, at least one sensor utilized to obtain the at least one sensor data of the main shaft of the calibration circuit breaker was the same type or model as the at least one sensor utilized to obtain the at least one sensor data of the main shaft of the operational circuit breaker.

In an example, at least one sensor utilized to obtain the at least one sensor data of the main shaft of the calibration circuit breaker was located at the same or equivalent at least one location as the at least one sensor utilized to obtain the at least one sensor data of the main shaft of the operational circuit breaker.

According to the invention, the at least one sensor utilized to obtain the at least one sensor data of the moveable contact and/or pushrod of the calibration circuit breaker comprises one or more of: position sensor; velocity sensor.

In an example, the position information and/or the velocity information for the moveable contact comprises a travel curve.

In an example, the system comprises an output unit and the method comprises outputting the position information and/or the velocity information for the moveable contact.

In an example, the method comprises determining by the processing unit if the circuit breaker has a fault, wherein the determining comprises analysing the position information and/or the velocity information for the moveable contact.

<FIG> shows an example of a system <NUM> for training a neural network for monitoring a circuit breaker. The system comprises at least one first sensor <NUM>, <NUM>, at least one second sensor <NUM>, and a processing unit <NUM>, <NUM>. 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 <NUM>. 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 processing unit. 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. 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 processing unit. The processing unit is configured to train a neural network. 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. The trained neural network is configured to determine position and/or velocity information for a moveable contact of an operational circuit breaker <NUM> on the basis of analysis of at least one sensor data of a main shaft of the operational circuit breaker.

In an example, the calibration circuit breaker is the same type or model as for the operational circuit breaker.

In an example, the at least one first sensor (<NUM>, <NUM>) utilized to obtain the at least one sensor data of the main shaft of the calibration circuit breaker is the same type or model as at least one sensor (<NUM>) that will be utilized to obtain the at least one sensor data of the main shaft of the operational circuit breaker.

In an example, the at least one first sensor utilized to obtain the at least one sensor data of the main shaft of the calibration circuit breaker is located at the same or equivalent at least one location as the at least one sensor that will be utilized to obtain the at least one sensor data of the main shaft of the operational circuit breaker.

According to the invention, the at least one first sensor utilized to obtain the at least one sensor data of the main shaft of the calibration circuit breaker comprises one or more of: acceleration sensor; main shaft angle sensor.

According to the invention, the at least one second sensor (<NUM>) utilized to obtain the at least one sensor data of the moveable contact and/or pushrod of the calibration circuit breaker comprises one or more of: position sensor; velocity sensor.

<FIG> shows a method <NUM> for training a neural network for monitoring a circuit breaker in its basic steps. The method comprises:.

In an example, the method comprises acquiring at least one sensor data of the main shaft of the calibration circuit breaker at the same time as the at least one sensor data of the moveable contact and/or pushrod of the calibration circuit breaker.

The system for monitoring a circuit breaker, system for monitoring a two or three phase switchgear or controlgear, method for monitoring a circuit breaker, system for training a neural network for monitoring a circuit breaker, and method for training a neural network for monitoring a circuit breaker and now described in specific detail, where reference is made to <FIG>.

The condition monitoring and diagnosis of the operating mechanism of a circuit breaker (CB) is mainly based on travel curve measurements. The reason is that most of the failure modes can be captured by position or velocity sensors measuring the travel curve. However, acquiring such data is hard to achieve as it requires robust, reliable sensors fulfilling the requirements in installation space and lifetime of the CB.

The inventors realised that other types of sensors such as accelerometers that are more appropriate and can be easier to mount in the CB can be utilized in a completely different way and new way in order to derive this travel curve information. The inventors have applied methods of artificial intelligence (AI) for extracting the position of the moving contact for each pole from this other sensor data (for example the accelerometers), and thus enabling CB drive monitoring based on travel curves. In addition to the mechanical failures, the generated travel curves can be also used to monitor electrical failure modes as for instance contact ablation.

The solution involves using a sequence-to-sequence artificial intelligence (AI) model that first learns to generate the travel curve data from the other sensor data by training it with examples that contain both travel curve and further sensor measurements, e.g. accelerometers, rotary encoders for measuring the main shaft angle, etc..

Subsequently, the model is able to extract travel curve information also on data that was not used for the training of the model, and when the travel curve information is not available. The accuracy of this method is evaluated in two ways:.

Thus the solution utilizes a dataset with both travel curve signals and further sensor data, which were recorded simultaneously from the same device. Then use an artificial intelligence (AI) model is used to learn to generate the travel curves from the further sensor data (that was acquired at the same time as the travel curve signals) which could be accelerometer signals, angle measurements of the main shaft, etc..

Subsequently, the model is used to extract travel curve information also on data that was not used for the training of the model, and when the travel curve information is not available. Thus, travel curve data can be generated only for the "further sensor data" such as from accelerometers that can be more convenient placed and used, for a new circuit breaker of the same type or model as that used for generating the neural network model.

Thus, after the model is trained, the model can be used to diagnose the health of circuit breaker drives using only the measurement data from other sensors.

Claim 1:
A system (<NUM>) for monitoring a circuit breaker, the system comprising:
- at least one sensor (<NUM>); and
- a processing unit (<NUM>);
wherein the at least one sensor is configured to be located and utilized to obtain at least one sensor data of a main shaft of an operational circuit breaker (<NUM>), wherein the at least one sensor utilized to obtain the at least one sensor data of the main shaft of the operational circuit breaker comprises one or more of: acceleration sensor; main shaft angle sensor;
wherein the at least one sensor is configured to provide the at least one sensor data of the main shaft of the operational circuit breaker to the processing unit; and
wherein the processing unit is configured to determine position and/or velocity information for a moveable contact of the operational circuit breaker,
characterised in that the determination comprises analysis of the at least one sensor data of the main shaft of the operational circuit breaker by a trained neural network implemented by the processing unit;
wherein the neural network was trained on the basis of at least one sensor data of a main shaft of a calibration circuit breaker (<NUM>) and at least one sensor data of a moveable contact and/or pushrod of the calibration circuit breaker, wherein at least one sensor (<NUM>, <NUM>) utilized to obtain the at least one sensor data of the main shaft of the calibration circuit breaker comprises one or more of: acceleration sensor; main shaft angle sensor, wherein at least one sensor (<NUM>) utilized to obtain the at least one sensor data of the moveable contact and/or pushrod of the calibration circuit breaker comprises one or more of: position sensor; velocity sensor.