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KAI MING SHOU SYSTEM

Issuing time:2023-10-10 14:23

Introduction of “KMS” Intelligent nspection System of Pipeline

“KMS”intelligent inspection system of pipeline incorporates features of data visualization, integrated patrol management, and intelligent risk warning. It includes the development of locomotive-linked intelligent pipeline inspection equipment, an intelligent inspection and warning platform, and a handheld terminal app. It enables intelligent identification and early warning ofvarious conditions along the pipeline, such as construction vehicles,third-party construction activities, encroachments, suspicious individuals, oiland gas leaks, and natural disasters. The system can achieve automated assessment of pipeline conditions, intelligent warnings, leak point navigation, remote operation and maintenance, and diverse report generation.


Components of the “KMS" System:

       Unmanned Aerial Vehicle(UAV)/Vehicle-based Inspection Equipment (Data Collection)

       Multi-source Data Processing and Analysis System (Data Processing)

       Handheld Terminal App (On-siteDisposal)

       Intelligent Inspectionand Warning Platform (Backend Management)



Inspection Plan for Oil and Gas Facility Daily Inspection and Comprehensive Nighttime Management of Facilities

UAVs equipped with laser methane detectors and refrigeration-based infrared thermalimaging gimbals are used to monitor and detect VOC gas leaks and emissions within the facility. Additionally, high-definition zoom cameras are deployed to conduct detailed inspections of key valves, instruments, and bolts. The backend AI-based intelligent recognition module automatically identifies and alerts potential safety hazards.


3D Digital Construction

UAVs carry high-precision aerial survey cameras that utilize oblique photography andclose-range photogrammetry techniques to create highly accurate 3D models ofthe facility. These models are integrated with current management systems, implementing digital information management and coordination of physical assets.



    


    

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