A monitoring method of artificial intelligence video recognition belt piled coal

A technology of video recognition and artificial intelligence, applied in the direction of conveyor objects, conveyor control devices, transportation and packaging, etc., can solve time-consuming, labor-intensive, safety and stability issues, reduce time-sensitive operations and ensure operational safety Effect

Active Publication Date: 2021-04-23
JINGYING SHUZHI TECH HLDG CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0013] In order to overcome the defects of time-consuming, labor-intensive and weak safety and stability of the prior art, the present invention provides a monitoring method for coal-belt piles by artificial intelligence video recognition which saves time and labor and can monitor the coal piles in real time.

Method used

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  • A monitoring method of artificial intelligence video recognition belt piled coal
  • A monitoring method of artificial intelligence video recognition belt piled coal
  • A monitoring method of artificial intelligence video recognition belt piled coal

Examples

Experimental program
Comparison scheme
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Embodiment 1

[0031] Such as Figures 1 to 4 As shown, the monitoring method of the artificial intelligence video recognition belt pile of coal of the present embodiment comprises the following steps: first set up a cordon 4 between the belt coal chute and the transfer point and the belt 2, and then pass the mining high-definition explosion-proof camera 1 in real time The video of the warning line is collected, and the high-definition explosion-proof camera 1 for mine transmits the video of the warning line to the server in real time through the network. The server analyzes the video of the warning line through the artificial intelligence video recognition model. If the target is covered by the amount of coal accumulation, the detection result is that the coal accumulation is caused by the occlusion, and the belt 2 is determined to be piled with coal.

[0032] Preferably, the warning line 4 is set at 1 / 3 between the belt coal chute and the transfer point and the belt 2 .

[0033] Further, ...

Embodiment 2

[0040] The monitoring method of the artificial intelligence video recognition belt pile of coal of the present embodiment comprises the following steps: first set up a warning line 4 between the belt coal chute and the transfer point and the belt 2, and then collect the warning line in real time through the mine-used high-definition explosion-proof camera 1 Video, mining high-definition explosion-proof camera 1 transmits the video of the warning line to the server in real time through the network, and the server analyzes the video of the warning line through the artificial intelligence video recognition model. If the target is met, if the detection result is the occlusion caused by the coal accumulation, it is determined that the belt 2 is piled with coal. If the detection result is not the occlusion caused by the coal accumulation, it is not judged as the belt 2 pile of coal.

[0041] Preferably, the warning line 4 is set at 1 / 3 between the belt coal chute and the transfer poi...

Embodiment 3

[0049] The monitoring method of the artificial intelligence video recognition belt pile of coal of the present embodiment comprises the following steps: first set up a warning line 4 at 1 / 3 between the belt chute and the transfer point and the belt 2, and then pass through the mine high-definition explosion-proof camera 1 The video of the warning line is collected in real time, and the high-definition explosion-proof camera 1 for mine transmits the video of the warning line to the server in real time through the network. The server analyzes the video of the warning line through the artificial intelligence video recognition model. When the warning line 4 is blocked, it detects whether it is a coal pile 3 If the coal accumulation blocks the target, the detection result is that the coal accumulation is caused by the coal accumulation, and the belt 2 pile of coal is determined. If the detection result is not caused by the coal accumulation, the coal accumulation is not judged as the...

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Abstract

The invention discloses an artificial intelligence video recognition monitoring method for belt piled coal, comprising the following steps: firstly setting a warning line between the belt coal chute and the transfer point and the belt, and then collecting the video of the warning line in real time through a mine-used high-definition explosion-proof camera , the mining high-definition explosion-proof camera transmits the video of the warning line to the server in real time through the network. The server analyzes the video of the warning line through the artificial intelligence video recognition model. When the warning line is blocked, it detects whether the target is blocked by the accumulation of coal. The occlusion caused by the amount of coal accumulation is determined to be a belt pile of coal, and the detection result is not the occlusion caused by the amount of coal accumulation, which is not determined to be a belt pile of coal. The invention aims to use artificial intelligence technology to solve the problem of belt running detection, timely discover and alarm the belt coal pile phenomenon during the belt running process, and is applicable to various belt transportation scenarios, reducing manual timing correction operations on existing detection sensors, and at the same time reducing Waste of manpower and time.

Description

technical field [0001] The invention belongs to the field of belt transportation monitoring, in particular to an artificial intelligence video recognition monitoring method for belt piled coal. Background technique [0002] Coal conveying belt conveyor is the main device for transporting materials in coal mines. During the long-term operation of belt conveying, belt coal piles are frequent failures. Belt piles of coal cause system failures to stop and affect production efficiency; Belt fire and other potential safety hazards; when the belt is heavily piled with coal, the material will be jammed and blocked, which will easily cause the belt to tear. Between the reloading point and the belt at the front of the coal chute, the belt is torn when it is squeezed; as well as the reprinting point, the coal scatter outside the coal hole, etc. are not conducive to safe production, which brings great hidden dangers to safe production. . [0003] At present, coal pile detection mostly...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): B65G43/08
CPCB65G43/08B65G2203/041
Inventor 吴喆峰曹凌基朱晓宁
Owner JINGYING SHUZHI TECH HLDG CO LTD
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