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Artificial intelligence-based crane risk data identification method

A technology of data identification and artificial intelligence, applied in the field of risk data identification, can solve problems such as easy falling, pin falling off, arm folding, etc., and achieve the effect of reducing workload, preventing dangerous accidents, and improving detection efficiency

Active Publication Date: 2021-12-03
丹华海洋工程装备(南通)有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] There are many safety hazards in the use of cranes, so they need to be inspected frequently. However, once the equipment is built, it generally needs to be operated in a high-altitude environment for a long time, so it is difficult to achieve manual inspection.
Especially the cotter pin of the tower crane, if it is not open or the opening is not enough, it will easily fall off during use, causing the pin shaft without the cotter pin to fall off by itself during use, which will eventually cause major damage to the folding arm. Accidents, so it is necessary to identify crane risk data through artificial intelligence

Method used

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  • Artificial intelligence-based crane risk data identification method
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  • Artificial intelligence-based crane risk data identification method

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Embodiment Construction

[0012] In order to allow those skilled in the art to better understand the present invention, the present invention will be described below in conjunction with the embodiments and accompanying drawings.

[0013] In order to realize the contents of the present invention, the present invention designs a method for identifying crane risk data based on artificial intelligence, including the following steps:

[0014] step : Use UAV to automatically obtain real-time images of the cotter pin area of ​​the tower crane, and identify and segment the device where the cotter pin is located.

[0015] Since the working environment of the tower crane is high altitude, the drone is used in the present invention to collect the target image with an RGB camera. At the same time, in order to save human resources, in the present invention, the UAV is used to adaptively acquire target images.

[0016] Firstly, the 3D model of the tower crane to be detected is obtained according to the prior data...

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Abstract

An artificial intelligence-based crane risk data identification method of the present invention comprises the following steps: step: using a UAV to automatically obtain a real-time image of the cotter pin area of ​​the tower crane, and identifying and segmenting the device where the cotter pin is located; step: continuing according to the segmented image Analyze and identify the cotter pin and nut groove, and obtain the image features of each part; step: construct the evaluation index feature value reflecting the risk of the cotter pin, and evaluate the risk degree of the cotter pin of the current crane; step: detect the obtained cotter pin risk degree Whether the evaluation value is greater than the threshold judges whether to carry out early warning operation, thereby avoiding the occurrence of dangerous accidents. The invention realizes the self-adaptive detection and intelligent evaluation of the safety risk of the cotter pin of the tower crane in the high-altitude environment, and can effectively prevent the occurrence of dangerous accidents through early warning.

Description

technical field [0001] This application relates to the technical field of risk data identification, in particular to an artificial intelligence-based crane risk data identification method. Background technique [0002] There are many potential safety hazards in the use of cranes, so they need to be inspected frequently. However, once the equipment is built, it generally needs to be operated in a high-altitude environment for a long time, so it is difficult to achieve manual inspection. Especially the cotter pin of the tower crane, if it is not open or the opening is not enough, it will easily fall off during use, causing the pin shaft without the cotter pin to fall off by itself during use, which will eventually cause major damage to the folding arm. Accidents, so it is very necessary to identify crane risk data through artificial intelligence. Contents of the invention [0003] In view of the above problems, the present invention proposes a method for identifying crane r...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/34
Inventor 王根德
Owner 丹华海洋工程装备(南通)有限公司