Digital Twin–Based Structural Health Management System Products and Engineering Services
To enhance structural risk management and control measures during the operation and maintenance of jacket platforms,Simultaneously meet the requirements for digitalization of engineering projects. For jacket platforms, conduct monitoring and develop digital twin models, leveraging digitalization during the construction phase to establish a foundational digital model. Utilize structural digital twins to monitor the operational status of engineering facilities, thereby supporting safety risk management and full lifecycle integrity management for deepwater jacket platform structures.
The structural health management system developed based on digital twin technology not only integrates various types of advanced sensing devices,In addition, a corresponding advanced software system has been developed to provide users with comprehensive structural health monitoring and management, offering broad market prospects.
Through maritime and land communication,Real-time display of the current status of monitoring sensors and devices on the platform.
Completion and O&M information for the twin digital twin catheter rack can be realized.Tracking and management of data during the construction phase;
The integrated database stores all structured data and unstructured documents related to the jacket structure.Facilitates unified management, search, interaction, and application.
By employing a combined inversion algorithm that integrates monitoring data with simulation databases, the digital twin can demonstrate a certain degree of timeliness withinCorresponds to the stress field under actual environmental conditions;
Support operations and maintenance management through expert decision-making, enabling twin-basedDevelopment of refined assessment and testing plans.
Through long-term data accumulation and feedback-driven design,Quantitative comparison of redundancy or conservatism.
Core Algorithms for Digital Twins
A first-level digital twin establishes a computationally realistic model for large-scale simulations, thereby forming a foundational database.
The secondary digital twin is generated by refining the base database using monitoring data to create an application database for early warning and simulation.
A Level-3 digital twin is an intelligent model continuously trained using big data and deep-learning techniques, built upon the accumulated big-data foundation of a Level-2 digital twin.
Contact Information
Address: Company Headquarters:Building A, Overseas Students’ Entrepreneurship Park, No. 1 Huoju Road, High-tech Industrial Park, Dalian
Experiment–Manufacturing Base: Tangli Industrial Park, Hongqi Subdistrict, Ganjingzi District, Dalian City
Telephone: Corporate Headquarters: 0411-84660668
Experiment-Manufacturing Base: 0411-82646110
Email: info@kingmile.com
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