A Noise Separation Method Based on Unsupervised Mode for Working Conditions of Power Transformers

A power transformer and noise separation technology, applied in instruments, speech analysis, measurement of ultrasonic/sonic/infrasonic waves, etc., can solve the problem of separating noise characteristics, etc.

Active Publication Date: 2021-10-26
ANHUI NANRUI JIYUAN POWER GRID TECH CO LTD +1
View PDF13 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to solve the defect in the prior art that it is difficult to separate the noise characteristics from the voiceprint signal of the power transformer, and to provide a method for separating the noise of the power transformer working condition based on an unsupervised method to solve the above problems

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A Noise Separation Method Based on Unsupervised Mode for Working Conditions of Power Transformers
  • A Noise Separation Method Based on Unsupervised Mode for Working Conditions of Power Transformers
  • A Noise Separation Method Based on Unsupervised Mode for Working Conditions of Power Transformers

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0057] In order to have a further understanding and understanding of the structural features of the present invention and the achieved effects, the preferred embodiments and accompanying drawings are used for a detailed description, as follows:

[0058] Such as figure 1 As shown, a kind of power transformer working condition noise separation method based on the unsupervised mode of the present invention, comprises the following steps:

[0059] The first step is to collect the voiceprint data of the power transformer: the audio of the power transformer is collected on the spot through the voiceprint collection sensor.

[0060] The second step is the preprocessing of the voiceprint data: the collected transformer voiceprint is denoised by using segmentation, framing, and audio windowing preprocessing methods. The specific steps are as follows:

[0061] (1) Carry out segmentation operation on the collected transformer audio s(t). In order to make the input transformer audio al...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention relates to an unsupervised method for separating working condition noise of a power transformer, which solves the defect that it is difficult to separate the noise from the voiceprint signal of the power transformer compared with the prior art. The invention comprises the following steps: collection of voiceprint data of power transformers; preprocessing of voiceprint data; compression of transformer voiceprints; separation of transformer working condition noise. In the present invention, through the collected transformer audio, after denoising processing, the frequency compression method and frequency features are used to extract the transformer voiceprint features and effectively fuse them; for the sound of the transformer working condition, the sound emitted by the stable working condition and the unstable transient noise For the additive superposition problem, an algorithm based on the angle similarity between eigenvectors is proposed, which realizes the separation and detection of voiceprint superposition, separates the noise characteristics of transformer working conditions, and lays the foundation for the judgment and detection of transformer working conditions.

Description

technical field [0001] The invention relates to the technical field of power equipment, in particular to an unsupervised mode-based noise separation method for working conditions of power transformers. Background technique [0002] Due to the influence of latent fault factors such as internal discharge, overheating, winding deformation, loose mechanical parts and equipment insulation aging of large power transformers (reactors), serious faults will occur during the operation of power transformers (reactors) over time. The traditional manual judgment method is to judge the type and location of the fault by listening to the operating sound of the equipment with the human ear. This type of method has certain limitations, ambiguity, subjectivity and lack of persistence. The specific performance is that different technicians may have inconsistent judgment standards for transformer faults, and some subtle acoustic signals cannot be judged, which requires the accumulation of certai...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Patents(China)
IPC IPC(8): G10L21/0272G10L21/0208G01H17/00
CPCG01H17/00G10L21/0208G10L21/0272
Inventor 张可杨可军黄文礼王成龙
Owner ANHUI NANRUI JIYUAN POWER GRID TECH CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap