Monitoring method for identifying belt coal piling through artificial intelligent video

A technology of video recognition and artificial intelligence, applied in the direction of conveyor control devices, conveyors, conveyor objects, etc., can solve time-consuming and labor-intensive security and stability issues

Active Publication Date: 2019-07-26
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

Method used

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  • Monitoring method for identifying belt coal piling through artificial intelligent video
  • Monitoring method for identifying belt coal piling through artificial intelligent video
  • Monitoring method for identifying belt coal piling through artificial intelligent video

Examples

Experimental program
Comparison scheme
Effect test

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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PUM

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Abstract

The invention discloses a monitoring method for identifying belt coal piling through an artificial intelligent video. The monitoring method comprises the following steps: arranging a warning line among a belt coal drop and a transferring point, and a belt; then acquiring a warning line video in real time through a mineral high-definition and explosion-proof camera; transmitting the warning line video to a server in real time by the mineral high-definition and explosion-proof camera through a network; analyzing the warning line video by the server through an artificial intelligent video identification model; when the warning line is shielded, detecting whether a target is shielded by coal piling or not; determining the belt coal piling when a detection result is that the shielding is causedby the coal piling; and judging that the belt coal piling is not caused when the detection result is that the shielding is not caused by the coal piling. The monitoring method disclosed by the invention aims at solving the problem of belt operation detection by utilizing an artificial intelligent technology; a belt coal piling phenomenon in a belt operation process is found and alarmed in time; the monitoring method is applicable to various belt conveying scenes and fixed-time correction operation of manpower on an existing detection sensor is reduced; and meanwhile, wastes of manpower and time are reduced.

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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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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