Abstract: A knowledge graph generation system includes an input unit and a knowledge graph generator. The input unit receives service reports, each comprising natural language; and provides the service reports to the knowledge graph generator. The knowledge graph generator implements a Large Language Model (LLM), utilizes the LLM to identify entries from the natural language in the service reports, wherein the identified entries comprise names and types of instruments, issues that need to be addressed for those instruments, and actions taken by service technicians to mitigate the issues. The identified entries form rules, each rule comprises a tuple of one instrument type, one issue, and an action step or series of action steps taken to mitigate the issue. The rules are used to generate a plurality of knowledge graph nodes. The knowledge graph generator utilizes the nodes to generate a knowledge graph.

Abstract: A fault state detection apparatus includes an input unit and a processing unit. The input unit receives condition monitoring data. The processing unit implements a trained machine learning algorithm to analyze the received condition monitoring data to determine if the received condition monitoring data is associated with a fault state. The trained machine learning algorithm was trained on the basis of a plurality of non-fault state condition monitoring data and associated ground truth information and on the basis of a plurality of fault state condition monitoring data and associated ground truth information. A subset of the plurality of fault state condition monitoring data was generated from one or more non-fault state condition monitoring data. Generation of fault state conditioning monitoring data in the subset of the plurality of fault state condition monitoring data comprises a transformation of non-fault state condition monitoring data to fault state condition monitoring data.

Abstract: A method for automatically supplying or locating data over a communication network comprising: configuring a data source to provide source data over the communication network, the source data being identified by a data identifier in a domain of identifiers; receiving a machine-readable description, the machine-readable description specifying at least one predicate that must be satisfied by the data; labeling data identified by the data identifier with labels at least in part indicative of data predicates that hold true for the data identified by the data identifier or that are satisfiable for the data identified by the data identifier; searching for the data based at least in part on the machine-readable description and the labels; obtaining a solution satisfying the predicate based on the search; and supplying the solution over the communication network to a data consumer.

Abstract: A rule utilization system for switchgear includes a deterministic rule engine; an input unit; and an output unit; wherein the input unit is configured to receive a request based on input from an operator relating to an operation to be performed on a switchgear; wherein the deterministic rule engine executes rules relating to the operation to be performed on the switchgear based on a request; utilization of the output unit calls a sensor system to measure and to receive a result of the measurement to call a software system to carry out an assessment of a part of the switchgear and utilization of the input unit to receive a result of the assessment of the part of the switchgear; wherein the rule engine generates an action for the operator; and wherein the output unit is configured to output the at least one action for the operator.

Abstract: A system for monitoring a circuit breaker includes at least one sensor and a processor. The at least one sensor is configured to be located and utilized to obtain at least one time series sensor data of at least one first part an operational circuit breaker. The at least one sensor is configured to provide the at least one time series sensor data of the at least one first part of the operational circuit breaker to the processor. The processor is configured to determine that at least one second part of the operational circuit breaker is operating correctly or has a fault, where the determination includes analysis of 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.

Abstract: A system for monitoring a switchgear includes an infrared camera; a processing unit; and an output unit. The infrared camera acquires a first infrared image having a first number of pixels, and the processing unit determines a pixel in the first infrared image with a maximum temperature. The processing unit utilizes a second number less than the first number to determine a temperature interval for the first infrared image equal to a difference between the maximum temperature in the first infrared image and a threshold temperature in the first infrared image. The processing unit is configured to determine that a hot spot exists in the switchgear using the temperature interval for the first infrared image.

Abstract: A system and method for monitoring a switchgear includes an infrared camera, a processing unit, and an output unit. The infrared camera acquires an infrared image of the switchgear, and the processing unit converts it into a binary image. Pixels in the infrared image having a temperature equal to or above a first threshold value are given the same first value. Pixels in the infrared image having a temperature below the first threshold value are given the same second value. The processing unit is configured to implement a Siamese neural network to determine if a hot spot exists in the infrared image.

Abstract: A system for monitoring a switchgear includes an infrared camera; a processing unit; and an output unit. The camera acquires a first infrared image. The processing unit determines a pixel in the first image with a maximum temperature and uses a second number of pixels to determine a temperature interval. The processing unit sorts the pixels in descending order of temperature to determine a threshold temperature and determines that a hot spot exists in the switchgear using the temperature interval for the first infrared image. The output unit is configured to output an indication of a fault in the switchgear when the determination has been made that a hot spot exists in the switchgear.

Abstract: A system and method for monitoring a device includes a temperature sensor, a processing unit, and an output unit. The temperature sensor acquires a temperature measurement during a heat-up phase of a component and provides a temperature measurement to the processing unit, which selects a simulated transient temperature distribution of the simulated component of the simulated device from a plurality of simulated transient temperature distributions of the simulated component of the simulated device. The selection comprises a comparison of the at least one temperature measurement with the plurality of simulated transient temperature distributions at an equivalent time point in the simulated heat-up to a time point at which the temperature measurement was acquired. When a hot spot is developing an output unit outputs an indication of a fault associated with the component.

Abstract: A medium voltage switchgear or controlgear monitoring system includes: an infrared camera; and a processing unit. The infrared camera is mounted within a medium voltage switchgear or controlgear. The infrared camera is configured to acquires an infrared image including image data of two or three current carrying parts of the switchgear or control gear. The two or three current carrying parts are the same current carry part of two or three equivalent systems within the switchgear or controlgear. The infrared camera provides the infrared image to the processing unit. The processing unit determines that the two or three current carrying parts are operating correctly or that one of the two or three current carrying parts has a fault. The determination includes analysis of the infrared image by an autoencoder implemented by the processing unit.

Abstract: A system for monitoring a switchgear includes multiple infrared cameras with fields of view; a processing unit; and an output unit. The cameras acquire multiple image data of a plurality of phases of the switchgear, and the processing unit determines whether there is a phase imbalance in a specific phase comprising a determination from a plurality of image data that temperature information for a plurality of component parts and/or a plurality of connections for that specific phase has an overall enhanced temperature compared to the temperature information for the same plurality of component parts and/or the same plurality of connections for one or more other phases of the plurality of phases. The output unit is configured to output information that a fault or load imbalance has occurred in a phase.

Abstract: A system for monitoring a switchgear includes: an infrared camera for acquiring at least one infrared image of the switchgear; a processing unit for determining a pixel in the at least one infrared image associated with a hottest temperature, determining e pixels in the at least one infrared image associated with a temperature that is within a threshold temperature of the hottest temperature, and determining that a hot spot exists in the switchgear as a determination, the determination being a utilization of the determined pixels in the at least one infrared image; and an output unit for outputting an indication of a fault in the switchgear based on the determined hot spot.

Abstract: A rule generation system for a switchgear includes a deterministic rule generator; an input unit; and an output unit; wherein the input unit is configured to receive a request from an operator for a rule relating to operation of a switchgear; wherein the input unit is configured to provide the request to the deterministic rule generator; wherein the deterministic rule generator is configured to implement a large language model; wherein the deterministic rule generator is configured to generate a switchgear operation rule, and wherein the generation of the switchgear operation rule comprises processing of the request by the large language model; and wherein the output unit is configured to output the switchgear operation rule.

Abstract: A circuit breaker monitoring system includes a vibration sensor, a processing unit, and an output unit. The vibration sensor is mounted to a circuit breaker and acquires temporal vibration data over at least a portion of a closing operation of the circuit breaker, which portion includes movement of a moveable contact towards a fixed contact. The vibration sensor provides the temporal vibration data to the processing unit, which converts the temporal vibration data into frequency vibration data and determines a vibration signal and a plurality of spectral indicators or a plurality of spectral points based on the vibration signal. The processing unit determines an indication of operational functionality of the circuit breaker the output unit outputs information relating to the indication of operational functionality of the circuit breaker.

Abstract: A switchgear event detection system includes sensors; a processing unit; and an output unit; wherein the sensors are mounted in and/or on a switchgear. The sensors acquire signals relating to an event inside the switchgear and/or outside the switchgear and in the vicinity of the switchgear, the signals being vibration/acoustic signals, which extend over a time window. The processing unit compares the signals with reference signals that relate to reference events. The processing unit classifies the event as a specific reference event when a match of the comparison exceeds a first threshold. The output unit outputs information on the event comprising utilization of information of the specific reference event stored in the database.

Abstract: A circuit breaker monitoring system includes a vibration sensor, a processing unit, and an output unit. The sensor is mounted to a circuit breaker and acquires temporal vibration data during a closing operation of the circuit breaker while a moveable contact moves towards a fixed contact. Temporal vibration data is provided to the processing unit, which determines operational functionality of the circuit breaker by use of a machine learning algorithm trained on a plurality of travel curve data. The output unit outputs information relating to the indication of operational functionality of the circuit breaker.

Abstract: An apparatus for monitoring a switchgear includes: an input unit; a processing unit; and an output unit. The input unit is provides the processing unit with a monitored infra-red image of a switchgear. The processing unit implements a machine learning classifier algorithm to analyse the monitored infra-red image and determine if there is one or more anomalous hot spots in the switchgear. The machine learning classifier algorithm has been trained based on a plurality of different training images, the plurality of training images including a plurality of synthetic infra-red images generated by an image processing algorithm. The output unit outputs information relating to the one or more anomalous hot spots.

Abstract: An apparatus for monitoring a switchgear includes: an input unit; a processing unit; and an output unit. The input unit provides the processing unit with a monitor infra-red image of a switchgear. The processing unit implements a machine learning classifier algorithm to analyse the monitor infra-red image and determine if there is one or more anomalous hot spots in the switchgear. The machine learning classifier algorithm has been trained based on a plurality of different training infra-red images, the plurality of training infra-red images including a plurality of synthetic infra-red images generated from a corresponding plurality of visible images. The output unit outputs information relating to the one or more anomalous hot spots.

Abstract: An apparatus for monitoring a switchgear includes: an input unit; a processing unit; and an output unit. The input unit is provides the processing unit with a monitor infra-red image of the switchgear. The processing unit implements a machine learning classifier algorithm to analyse the monitor infra-red image and determine if there is one or more anomalous hot spots in the switchgear. The machine learning classifier algorithm has been trained based on a plurality of different training infra-red images. The plurality of training infra-red images include a plurality of modified infra-red images generated from a corresponding plurality of infra-red images, each of the modified infra-red images having been modified to remove an effect of obscuration in the image. The output unit outputs information relating to the one or more anomalous hot spots.

Abstract: A system and method includes an infrared camera; a processing unit; and an output unit. The infrared camera is configured to acquire a plurality of infrared images of the device, wherein the plurality of infrared images comprises a first infrared image and a second infrared image acquired a time period after the first infrared image. The processing unit is configured to determine a pixel in the first infrared image with a hottest temperature and determine a pixel in the second infrared image with a hottest temperature. The processing unit is configured to determine a first number of pixels in the first infrared image that have a temperature within a threshold temperature of the hottest temperature of the first infrared image and determine a second number of pixels in the second infrared image that have a temperature within the threshold temperature of the hottest temperature of the second infrared image.