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Optical fiber network link defect data detection method based on deep belief network

A technology of deep belief network and optical fiber network, applied in biological neural network models, electrical components, neural architectures, etc., can solve problems such as difficulty in ensuring data integrity and accuracy, impact of data loss detection results, and reduced detection accuracy

Pending Publication Date: 2022-07-29
STATE GRID FUJIAN ELECTRIC POWER CO LTD
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Problems solved by technology

Once the data is unbalanced, the results of data loss detection will be seriously affected, and the detection accuracy will also be significantly reduced.
In addition, the existing technology can only judge whether the data link is interrupted based on the mutual response message between the source node and the IP address between the source node, and cannot perform non-destructive testing for abnormal data interfered by external environment and other noises, which is difficult Ensuring data integrity and accuracy

Method used

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  • Optical fiber network link defect data detection method based on deep belief network

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Embodiment Construction

[0024] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0025] It should be noted that the following detailed description is exemplary and intended to provide further explanation of the application. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0026] It should be noted that the terms used herein are for the purpose of describing particular embodiments only and are not intended to limit exemplary embodiments in accordance with the present application; as used herein, unless the context clearly dictates otherwise, the singular forms are also intended to include Plural forms, furthermore, should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they indicate the presence of features, steps, operations, devices, compo...

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Abstract

The invention provides an optical fiber network link defect data detection method based on a deep belief network. The method comprises the following steps: step 1, acquiring optical fiber network link data; step 2, de-noising processing is carried out on the optical fiber network link defect data; step 3, performing data interpolation processing; step 4, carrying out data equalization processing; 5, performing scale processing on the data; step 6, discretizing the long sequence, and segmenting the long sequence into segments with fixed sizes; 7, extracting statistical features, signal features and physical features; 8, defect data identification is carried out, and data detection is completed. According to the technical scheme, data defects caused by various reasons can be effectively detected.

Description

technical field [0001] The invention relates to the technical field of optical fiber network data, in particular to an optical fiber network link defect data detection method based on a deep confidence network. Background technique [0002] As the State Grid attaches more and more importance to data assets, in the past two years, the progress of the information network construction of Fujian Electric Power Company has been further accelerated, and the business source system and data transmission volume that need to be monitored are also increasing. This puts forward higher requirements for network link monitoring, operational reliability, and timely early warning of abnormal link data. At present, the information integrated network management system of the provincial company has found that the abnormal data of optical fiber links is difficult to be accurately and timely found and early warning. [0003] In actual work, optical fiber network links often have faults due to exc...

Claims

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Application Information

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IPC IPC(8): H04B10/079G06N3/04
CPCH04B10/0793G06N3/045
Inventor 张楷涵陈功伯周晓东林烨婷陈少钦张良嵩
Owner STATE GRID FUJIAN ELECTRIC POWER CO LTD
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