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Noise analysis method in transformer substation

A method of analysis, technology of substations

Inactive Publication Date: 2019-10-15
STATE GRID XINJIANG ELECTRIC POWER CO URUMQI ELECTRIC POWER SUPPLY CO +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to provide a noise analysis method in a substation, which solves the problem that the inspection robot in the existing substation has missed judgments and misjudgments when judging equipment failures, resulting in inaccurate inspection results

Method used

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  • Noise analysis method in transformer substation
  • Noise analysis method in transformer substation
  • Noise analysis method in transformer substation

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Embodiment 1

[0056] A noise analysis method in a substation provided by a preferred embodiment of the present invention, such as figure 1 shown, including the following steps:

[0057] Step 1: collect the sound of the device, perform preprocessing, and obtain a sound segment signal that can accurately represent the sound information and meet the system standards, and the preprocessing includes sequentially performing pre-emphasis, frame-by-frame windowing, and endpoint detection;

[0058] Step 1.1: Collect the sound sequences of different devices by carrying a microphone array;

[0059] Step 1.2: Since the sound collection will be affected by various aspects, and the high-frequency part will drop sharply in the dB range, so the first-order data filter is used to pre-emphasize the sound signal collected in step 1.1, and the The frequency spectrum of the falling part in the sound signal is improved, thereby maintaining the flatness of the signal frequency spectrum, ensuring that the frequen...

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Abstract

The invention discloses a noise analysis method in a transformer substation and belongs to the technical field of transformer substation equipment. The method comprises the following steps of: firstly, acquiring equipment sound, and preprocessing to obtain a sound segment signal capable of accurately representing sound information; carrying out MFCC characteristic parameter extraction on the soundsegment signal; then, carrying out deep learning is carried out on MFCC characteristic parameters, and constructing a model based on a convolutional neural network; after the model is trained and tested, outputting an identification result; finally, judging whether abnormal noise is sent out by the equipment or not according to the identification result. In this way, whether the equipment has a fault or not is illustrated. According to the invention, the problem of inaccurate inspection result caused by missed judgment and misjudgment when the inspection robot in the existing transformer substation judges the equipment fault is solved.

Description

technical field [0001] The invention belongs to the technical field of substation equipment and relates to a noise analysis method in a substation. Background technique [0002] With the widespread application of inspection robots in substations, robot inspections can complete some inspection tasks that cannot be done manually, so more and more manual inspections are replaced by robot inspections, and more intelligent inspection robots Functions are also being slowly developed. [0003] The failure of equipment may be reflected in the appearance or the noise emitted. However, in the process of robot inspection, in the face of some equipment failures, it may not be possible to obtain the equipment failure from the appearance or training data. Information, if you only judge whether the equipment is faulty from the operating status of the equipment, when the equipment has failed but is still running, it may be wrongly judged that the equipment is working normally, which is not...

Claims

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Application Information

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IPC IPC(8): G10L21/0208G10L15/02G10L15/04G10L25/24G10L25/30G10L25/45
CPCG10L15/02G10L15/04G10L21/0208G10L25/24G10L25/30G10L25/45
Inventor 赵建平常喜强邢占礼刘新宇王学民赛涛王志远王秀龙周喜宾徐海奇于文海王陆陆夏治艾则孜江·加帕尔陈超马弘历李京芳夏瑞鹏原春亮王帅王鑫高峰陈疆
Owner STATE GRID XINJIANG ELECTRIC POWER CO URUMQI ELECTRIC POWER SUPPLY CO
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