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Power system fault diagnosis device and method based on neural network

A fault diagnosis device and power system technology, applied in biological neural network models, fault locations, measurement devices, etc., can solve problems such as poor diagnostic reliability, achieve the effects of increasing processing speed, reducing quantity, and improving computing efficiency

Pending Publication Date: 2020-01-14
BEIJING SMARTCHIP MICROELECTRONICS TECH COMPANY +3
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Problems solved by technology

The inventors found that the diagnostic reliability of this method was poor

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  • Power system fault diagnosis device and method based on neural network
  • Power system fault diagnosis device and method based on neural network
  • Power system fault diagnosis device and method based on neural network

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Embodiment Construction

[0018] Below in conjunction with accompanying drawing, specific embodiment of the present invention is described in detail, but it should be understood that protection scope of the present invention is not limited by specific embodiment.

[0019] Unless expressly stated otherwise, throughout the specification and claims, the term "comprise" or variations thereof such as "includes" or "includes" and the like will be understood to include the stated elements or constituents, and not Other elements or other components are not excluded.

[0020]In order to solve the problems of the prior art, the present invention proposes a neural network power system fault diagnosis device and method, and a new pipeline structure accelerator is designed in the process of neural network hardware implementation, focusing on analyzing the pipeline used by adjacent convolutional layers. On the basis of the possibility of the structure, a weight-first and image-first data reordering method is propose...

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Abstract

The invention discloses a power system fault diagnosis device and method based on a neural network. The device has a pipeline accelerator based on an AlexNet neural network model. An off-chip memory of the pipeline accelerator is used for storing the collected power system data and the AlexNet neural network model; a multiplication matrix unit is used for executing convolution operation; a correction linear unit is used for performing activation operation; a pooling unit is used for carrying out normalization and pooling operation; a supplementary multiplier is used for carrying out multiplication operation; an on-chip memory is used for storing data output by the supplementary multiplier; a feeding unit is used for distributing data in the off-chip memory and the on-chip memory to the multiplication matrix unit; and a controller is used for controlling the data processing process of each unit according to the neural network model. The power system fault diagnosis device and method canextract the high-dimensional features of the current more accurately, can be more sensitive to fine current changes, and are higher in diagnosis reliability.

Description

technical field [0001] The present invention relates to the technical field of power detection, in particular to a neural network-based power system fault diagnosis device and method. Background technique [0002] During the construction of the smart grid with the UHV grid as the backbone grid in my country, the expansion of the power system scale and the improvement of the voltage level objectively require the configuration of power equipment with larger capacity and higher voltage level. The commissioning of large-capacity transformers puts forward higher requirements for relay protection, and traditional protection methods and protection methods are severely challenged. Longitudinal differential protection has been used as the main protection of transformers for a long time. Long-term operation experience shows that differential differential protection can effectively distinguish internal faults and external faults of transformers. The difficulty of protection lies in how...

Claims

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Application Information

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IPC IPC(8): G01R31/08G01R31/00G06N3/063G06N3/04
CPCG01R31/086G01R31/00G06N3/063G06N3/045
Inventor 李良庞振江于同伟王峥丁岳葛维春黄旭卢岩杨文
Owner BEIJING SMARTCHIP MICROELECTRONICS TECH COMPANY
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