A method for estimating pipe removal depth in concrete pouring based on artificial intelligence video analysis

A technology of video analysis and artificial intelligence, applied in the field of construction engineering, can solve the problems of loose management, less action, and uneven quality of side station supervisors, so as to improve human efficiency, avoid potential risks, and facilitate retrieval and backtracking Effect

Active Publication Date: 2022-01-28
广东创成建设监理咨询有限公司
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Under the existing manual on-site supervision and management mode, its shortcomings are more obvious. The specific developments are as follows: the quality of side station supervision and management has the following high-risk problems: the quality of side station supervisors is uneven, and it is impossible to fully grasp the side station supervision. The key points of the side station can easily lead to the loss of control of the side station process; the supervisors have great discretion, and the lack of image data support for the side station process and side station management results can easily lead to the supervision accepting benefits and relaxing management; during the side station supervision process, due to the side station The supervisors lack restraint, and it often happens that only the side stations do nothing or do little; the supervision records of the side stations are not serious and have no traceability; during the side station process, there are safety and quality hazards or violations of mandatory standards for engineering construction. Behavior, stay in rectification suggestions or verbal notification, do not track and close the rectification situation

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A method for estimating pipe removal depth in concrete pouring based on artificial intelligence video analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0030] Below, in conjunction with accompanying drawing and specific embodiment, the invention is further described:

[0031] A method for estimating pipe removal depth in concrete pouring based on artificial intelligence video analysis, the method comprising:

[0032] a1. Use the deep learning method CoViAR-Mobile-V3 algorithm to segment and judge the real-time uploaded video stream, analyze the event type of the time window video, segment the video segment, and analyze the tube installation before pouring and the tube pull out during pouring Valid video segments for subsequent analysis;

[0033] a2. Based on the CoViAR-resnet algorithm, aiming at the installation of conduits before pouring, analyze and identify the behavior process of installing a single conduit, and count the number of all conduits installed by counting the number of installed conduits. The total length of conduit installation is approximately equal to the depth of the hole diameter In fact, combined with k...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention provides a method for estimating the depth of extubation in concrete pouring based on artificial intelligence video analysis. By analyzing the collected video data, during the installation process of the conduit, the behavior process of installing a single conduit is analyzed, and the number of all conduits installed is counted. Combined with the hole depth parameter, estimate the length of a single catheter; during the pouring process, analyze the behavior process of a single extubation, analyze the number of extubated sections in a single extubation behavior, and combine the estimated length of a single pipe to estimate the extracted catheter length. Using the pouring volume and hole diameter information, calculate the depth of the current concrete, combined with the above analysis, calculate the remaining conduit length in the current concrete, estimate whether the extubation is compliant, and whether risk warning is required. The present invention adopts the intelligent side station supervision of the whole process, which avoids the potential risks caused by the human factors of the supervisors. Online real-time risk early warning requires only a small number of supervision experts to remotely analyze and judge the risks of the system early warning, so that the side station supervision and management personnel Efficiency is improved.

Description

technical field [0001] The invention relates to the technical field of construction engineering, in particular to a method for estimating the pipe removal depth in concrete pouring based on artificial intelligence video analysis. Background technique [0002] Concrete pouring quality management is an important part of the supervision work at the side station of the construction site. The pouring method often adopts the conduit method underwater concrete pouring method. During the pouring process of this method, the supervision of the depth of pipe removal is one of the core supervision items in the quality management of concrete pouring. . The reason why it needs to be supervised and managed is that when the underwater conduit is poured, the conduit is assembled in sections at the beginning until the conduit goes deep into the empty bottom of the pouring. After a certain amount of concrete is poured, the part of the conduit buried in the concrete is too deep. As a result, t...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Patents(China)
IPC IPC(8): G08B21/18G06N3/04G06N3/08
CPCG08B21/18G06N3/08G06N3/045
Inventor 张永炘李永忠高来先吴国爱李佳祺黄伟文贾云博邓先亮何东城
Owner 广东创成建设监理咨询有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products