Method and system of partial discharge recognition for diagnosing electrical networks

Inactive Publication Date: 2020-08-27
ORMAZABAL CORP TECH A I E
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Problems solved by technology

Partial discharges have harmful effects on the environment in which they occur.
In a solid or liquid medium, they produce a slow but continuous degradation, which ends in the total dielectric breakdown of the insulating medium.
However, there are other consequences that are not detectable with the naked eye, such as heat generation, power losses, mechanical erosion of the surfaces that are ionically bombarded, interference with radio waves, etc.
If they occur and go unnoticed, they can have very serious consequences.
Replacement or repair of damaged electrical network elements can be very costly and can result in a network outage over a long period of time, as well as mean significant economic losses for the electricity companies.
In short, performing a thorough control can save a great deal of time and money.
However, the use of non-real signals in the CNN training step has the disadvantage that later, when performing recognition of signals acquired by sensors in the field, the accuracy of the result or “output” obtained is lower or the result is less reliable.
The generation of these patterns will depend on the partial discharge rate in each cycle and the number of cycles considered to have a representative pattern, so it comprises the inconvenienc

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  • Method and system of partial discharge recognition for diagnosing electrical networks
  • Method and system of partial discharge recognition for diagnosing electrical networks

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Embodiment Construction

[0015]The present invention refers to a method of recognizing partial discharges, also referred as PD, in particular for diagnosing live electrical networks, which is intended to solve each and every one of the problems mentioned above. This method comprises a series of steps, among which there is a signal post-processing step, which by combining this step and an artificial neural network such as a convolutional neural network (CNN), makes it possible to recognize the sources of partial discharges with a high degree of accuracy, so that it helps in the management of the facilities, understanding by management all those tasks that allow the optimization of the maintenance of the electrical network, determining where to carry out an intervention with the purpose of avoiding faults, service outages that leave the consumers without electrical supply, and minimizing the costs for the electrical companies providing them with different analyses, alarms, etc.

[0016]The method of recognizing par

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Abstract

The method of the present invention makes it possible to recognize partial discharges acquired by means of sensors in electrical networks, comprising a series of steps, among which are a post-processing step (13) of the acquired signals and a recognition step (17) of said signals by means of a convolutional neural network (CNN). The method also includes adaptation (15) and training (16) steps of the neural network, as well as a step to build a library (14) of partial discharge signals from known sources that serve as training of the convolutional neural network (CNN).

Description

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Claims

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Application Information

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Owner ORMAZABAL CORP TECH A I E
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