The invention relates to a method, a device (10) and an arrangement (1) for monitoring alternating current electric apparatuses (3), like e.g. power distribution transformers. The inventive method relies on an inductor antenna (11, 11′) suitable to detect the electromagnetic field at the frequency of the alternating current the apparatus (3) to be monitored is supplied with arranged in the vicinity of but distant to the apparatus (3) to be monitored and comprises the steps: —Detecting the electromagnetic field radiated by the electric apparatus (3) to be monitored; —Digitizing the detected electromagnetic field to obtain EMF-data; —Running a Fast-Fourier-Transformation on the digitized EMF-data to obtain FFT-transformed data; and—Monitoring the magnitudes of the FFT-transformed data at least at the frequency of the alternating current the apparatus (3) to be monitored is supplied with and its third harmonic for anomalies. The inventive device (10) and arrangement (1) are configured to perform the inventive method.

Systems, methods, and apparatus for corona detection using audio data are provided. In one example embodiment, the method includes obtaining, by one or more computing devices, audio data indicative of audio associated with an electrical system for at least one time interval. The method includes partitioning, by the one or more computing devices, the audio data for the time interval into a plurality of time windows. The method includes determining, by the one or more computing devices, a signal indicative of a presence of corona based at least in part on audio data collected within an identified time window of the plurality of time windows relative to audio data collected for a remainder of the time interval.

Provided are a live detection method and apparatus for a high-voltage switch cabinet. The live detection apparatus for a high-voltage switch cabinet includes a robot body and a back-end server. The robot body includes a host module, a power module, a detection module and a motion module. The power module is electrically connected to the host module and the motion module. The host module is communicably connected to the motion module and the detection module. The detection module includes a visible light camera, an infrared thermal imager, an non-contacting ultrasonic sensor and an ultrahigh-frequency sensor. The motion module includes a horizontal motion module, a vertical motion module and a rotating motion module. The horizontal motion module includes a motor-driven carrier and a laser navigation system. The vertical motion module is secured to the motor-driven carrier.

An arc-like radio frequency (RF) noise detector device is configured to detect and display RF noise on a residential circuit branch that cause or contribute to an arc fault circuit interrupter (AFCI) circuit breaker tripping. It includes a power cord with a plug to connect to a receptacle on a branch circuit of the AFCI circuit breaker to detect RF noise. It further includes a RF noise coupling circuit to receive power from a power entry module and coupled to an Application Specific Integrated Circuit (ASIC) to generate a Received Signal Strength Indicator (RSSI) signal from the detected RF noise. It further includes a power supply, a signal display device configured to receive and display the RSSI signal on a display screen to determine nature of a breaker trip event or likelihood of the breaker trip event and a battery to power the signal display device.

A system for acoustically detecting dielectric breakdown of, or partial discharge within, or on, an electrical device includes at least one electroacoustic (EA) transducer configured to detect an acoustic vibration of the electrical device, and a controller electrically connected to the at least one EA transducer. The controller is configured to receive a signal from the at least one EA transducer, and analyze the signal to determine whether the signal includes data associated with an acoustic vibration in a frequency range of dielectric breakdown and/or partial discharge of the electrical device. The applicability of such a system includes, but is not limited to, electronic parts or assembly screening, life characterization testing for materials and processes, diagnostic methods or aides, augmenting testing of components, assemblies or systems, and in service monitoring to support preventative or condition based maintenance to avert an in-service issues.

A system and method for use in environment with electrical equipment is provided. The system including a housing and at least one light source located on an exterior of the housing. The light source being activated when the system is in a switching mode of operation. At least one sensor is operably coupled to the housing and configured to measure at least one parameter associated with the electrical equipment. A computing device is disposed within the housing and coupled to communicate with the at least one light source and the at least one sensor.

A test device to localize a partial discharge in or at an electrical component may include at least one antenna to capture an electromagnetic wave caused by a partial discharge in the electrical component. The test device includes multiple microphones arranged in an environment around the electrical component. The microphones capture sound waves caused by the partial discharge. It is examined if an intensity of the electromagnetic wave exceeds a first limit value and/or the intensity of the sound wave captured by one of the multiple microphones exceeds a second limit value. Depending on the captured sound wave and/or the electromagnetic wave and on the examination relating to the first and/or second limit value, a location of the partial discharge can be determined.

The present disclosure provides a method for detecting an electrical discharge in an electrical apparatus. The method includes sensing an electromagnetic wave using an electrical sensor and generating an electric signal for a predetermined time period, sensing an acoustic wave using an acoustic sensor and generating an acoustic signal for the predetermined time period. The acoustic sensor is associated with at least one compartment of the electrical apparatus. Electrical data is generated based on a quasi-periodic characteristic of electric peak sequences of the electrical signal. Acoustic data is generated based on a quasi-periodic characteristic of acoustic peak sequences of the acoustic signal, wherein the electrical data is combined with the acoustic data to provide an operation status of the at least one compartment.

An experimental device for tripping properties of a high-voltage transmission line in a smoldering atmosphere, including a central information processor, a biomass fuel (BMF) property characterization module, a smoldering generation module, a smoldering smoke field property test module, a power frequency supply module and a tripping property test module. The experimental device and method for tripping properties of a high-voltage transmission line in a smoldering atmosphere, the present disclosure can explore the development conditions, processes, modes, properties and mechanisms of discharge in the smoldering atmosphere, and fully characterize the BMF such as forest vegetations from multiple aspects, to reproduce properties of forest vegetations in corridor areas of the high-voltage transmission line in multiple working conditions and reflect influences of properties of ground forest vegetations on the tripping properties of the high-voltage transmission lines.

A method for detecting an abnormal event in an insulator of an electrical conductor of a medium-voltage or high-voltage electrical device. The method includes: acquiring a set of successive samples of a vibration signal associated with the electrical conductor; determining a modelled value of a following sample based on the acquired set of samples and on a prediction model, the prediction model being obtained through machine learning of the vibration signal based on a set of samples acquired in reference conditions in which the electrical conductor is free from any abnormal event; acquiring the following sample of the vibration signal; calculating a difference between the value of the acquired sample and the modelled value; and if the calculated difference is greater than a predetermined threshold, detecting an abnormal event in the electrical conductor.