Highway tunnel fire smoke dynamic detection method

A technology for dynamic detection and road tunnels, which is applied in neural learning methods, image data processing, image enhancement, etc., can solve the problems of high false negative rate and false negative rate, untimely acquisition of tunnel fire disaster information, slow fire accident detection rate, etc. question

Active Publication Date: 2021-10-22
CHINA MERCHANTS CHONGQING COMM RES & DESIGN INST
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Problems solved by technology

The traditional road tunnel fire accident detection rate is slow, and the rate of missed and false alarms is high, which not only leads to the untimely acquisition of tunnel fire disaster information, which is not conducive to on-site decision-making and rescue, but also detects the life safety of firefighters. Fire smoke dynamic detection

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  • Highway tunnel fire smoke dynamic detection method
  • Highway tunnel fire smoke dynamic detection method
  • Highway tunnel fire smoke dynamic detection method

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Embodiment Construction

[0069] Embodiments of the present invention are described below through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematically illustrating the basic idea of ​​the present invention, and the following embodiments and the features in the embodiments can be combined with each other under the condition of no conflict.

[0070] Wherein, the accompanying drawings are for illustrative purposes only, and represent only schematic diagrams, rather than physical drawings, and should not be const...

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Abstract

The invention relates to a highway tunnel fire smoke dynamic detection method, and belongs to the technical field of highway tunnels. The method comprises the following steps: S1, extracting a motion area; S2, segmenting a suspected smoke region; S3, feature analysis and extraction; and S4, fire smoke detection. According to the method, suspected smog area segmentation is carried out in a YUV color space through a color filtering rule based on a motion area extracted by a Gaussian mixture model, then color and texture features of smog in the suspected smog area are mainly researched, a color moment of the smog is calculated, a uniform local binary pattern (ULBP) and a gray level co-occurrence matrix (GLCM) of the smog are extracted to carry out feature fusion, a machine learning classifier is used for model training to distinguish smoke and non-smoke, smoke recognition is completed, and an optimal algorithm is selected according to an analysis result.

Description

technical field [0001] The invention belongs to the technical field of road tunnels and relates to a dynamic detection method for fire smoke in road tunnels. Background technique [0002] Under the special environment of closed road tunnels, fire has become the biggest threat to the safety of road tunnel operations. The traditional road tunnel fire accident detection rate is slow, and the rate of missed and false alarms is high, which not only leads to the untimely acquisition of tunnel fire disaster information, which is not conducive to on-site decision-making and rescue, but also detects the life safety of firefighters. Fire smoke dynamic detection. Based on the high-definition camera in the tunnel, the artificial intelligence algorithm is used to dynamically obtain the fire smoke in the tunnel, obtain the diffusion range and position of the fire smoke in the tunnel in real time, and make reasonable decision-making for fire accident rescue, which has important engineerin...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/38G06K9/46G06K9/62G06N3/04G06N3/08G06T7/11G06T7/136G06T7/194G06T7/246
CPCG06N3/04G06N3/084G06T7/248G06T7/11G06T7/136G06T7/194G06T2207/10016G06T2207/10024G06T2207/20081G06T2207/20084G06T2207/30232G06F18/241
Inventor 丁浩刘帅杨孟胡学兵李文峰陈建忠曹鹏陈俊涛
Owner CHINA MERCHANTS CHONGQING COMM RES & DESIGN INST
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