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An audio-video fusion detection method for power room monitoring

A detection method, audio and video technology, applied in the detection field, can solve problems such as difficult audio and video data detection work, power enterprise losses, and inaccurate detection of abnormal events

Active Publication Date: 2019-06-28
STATE GRID CORP OF CHINA +2
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  • Claims
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AI Technical Summary

Problems solved by technology

Due to the large scale of audio and video data and human fatigue, it is difficult for monitoring personnel to reliably complete the detection of audio and video data for a long time; Early warning measures will cause huge losses to power companies
In view of the noisy environment of the power room, the occurrence of abnormal events cannot be accurately detected

Method used

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  • An audio-video fusion detection method for power room monitoring
  • An audio-video fusion detection method for power room monitoring
  • An audio-video fusion detection method for power room monitoring

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Embodiment Construction

[0027] like figure 1 As shown, the present invention includes the steps of extracting the video feature vector of the monitoring area, extracting the audio feature vector of the monitoring area and carrying out fusion processing of the video feature vector and the audio feature vector; its specific detection steps are as follows:

[0028] Step A: feature extraction of video data, divided into three steps of A1, A2 and A3;

[0029] Step A1, for the monitoring area video, select the indicator area to be monitored in the video, and use the following noise filtering algorithm formula to change the color of each pixel in the indicator image non-linearly, and obtain the indicator image after noise filtering ;

[0030]

[0031] Among them, Ir, Ig, and Ib are the red, green, and blue channels of the original image respectively, J is the single-channel image output at the corresponding position, and λ is the adjustment parameter.

[0032] Step A2, according to step A1, obtain the...

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Abstract

The invention discloses an audio and video integration detection method orienting electric power machine room monitoring. The concrete detection steps of the detection method are divided into four steps: feature extraction of audio and video data is performed; an audio abnormal event is detected by adopting the mel-frequency cepstral coefficient as for audios of monitoring areas; feature selection is performed with 1.8 seconds acting as a unit; and the obtained video feature vectors and audio feature vectors are compared. The beneficial effects of the detection method are that safety event detection can be automatically performed in the electric power machine room key areas, and the whole process is automatically completed without too much human interaction; and occurrence of the abnormal event can be accurately detected as for the condition of noisy environment of the electronic power machine room.

Description

technical field [0001] The invention relates to a detection method, in particular to an audio and video fusion detection method oriented to the monitoring of an electric machine room. Background technique [0002] As a pillar energy source for national economic development, electric power is very important for its safety and security. At present, in order to ensure the safety of property within the power company, my country's power companies usually install audio and video monitoring equipment at different locations in the power supply room to detect possible abnormal events. However, most of the current audio and video surveillance systems have a single function, which simply collects audio and video information and transmits the data to the central control room, but there is no real-time and effective abnormal event detection method for these data. After an abnormal event occurs, monitoring personnel usually need to spend a lot of time playing back audio and video histori...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/00G06Q50/06G06K9/00G10L25/24G10L25/51
Inventor 袁慧徐明星王会洪李新德彭祥礼董亮
Owner STATE GRID CORP OF CHINA
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