Abstract

In the process of using a long-span converter station steel structure, engineering disasters can easily occur. Structural monitoring is an important method to reduce hoisting risk. In previous engineering cases, the structural monitoring of long-span converter station steel structure hoisting is rare. Thus, no relevant hoisting experience can be referenced. Traditional monitoring methods have a small scope of application, making it difficult to coordinate monitoring and construction control. In the monitoring process, many problems arise, such as complicated installation processes, large-scale data processing, and large-scale installation errors. With a real-time structural monitoring system, the mechanical changes in the long-span converter station steel structure during the hoisting process can be monitored in real-time in order to achieve real-time warning of engineering disasters, timely identification of engineering issues, and allow for rapid decision-making, thus avoiding the occurrence of engineering disasters. Based on this concept, automatic monitoring and manual measurement of the mechanical changes in the longest long-span converter station steel structure in the world is carried out, and the monitoring results were compared with the corresponding numerical simulation results in order to develop a real-time structural monitoring system for the whole long-span converter station steel structure’s multi-point lifting process. This approach collects the monitoring data and outputs the deflection, stress, strain, wind force, and temperature of the long-span converter station steel structure in real-time, enabling real-time monitoring to ensure the safety of the lifting process. This research offers a new method and basis for the structural monitoring of the multi-point hoisting of a long-span converter station steel structure.

Highlights

  • The longer the span of a converter station steel structure, the more serious the bending deformation, and the higher the risk of fracture or collapse

  • Numerical Calculation Model for Multi-Point Hoisting of a Long-Span Converter Station

  • Through the real-time structural monitoring system, the monitoring and calculation data can be unified for real-time analysis, and the mechanical changes in the long-span converter station steel structure during the hoisting process can be monitored in real-time to achieve the real-time warning of engineering disasters, timely identification of engineering issues, and rapid decision-making, avoiding the occurrence of engineering disasters

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Summary

Introduction

The longer the span of a converter station steel structure, the more serious the bending deformation, and the higher the risk of fracture or collapse. In terms of analysis and control, some scholars have developed monitoring systems to process monitoring data in order to analyze and control the construction process of long-span converter station steel structures [6,7]. To explore more accurate monitoring methods, Hu et al [10] designed a long-span converter station steel structure axial force monitoring system based on a vibration sensor. Established a long-span converter station steel structure monitoring system based on a pure circuit and analyzed and controlled the construction of a long-span structure by real-time analysis and processing of electrical signals. To solve the above problems, the deflection, stress, strain, wind force, and temperature change of the longest long-span converter station steel structure in the world were monitored by automatic monitoring and manual measurement and compared with numerical simulation results. Combined with the monitoring results, a real-time structural monitoring system for the multi-point hoisting of a long-span converter station steel structure is developed, ensuring the smooth hoisting process of a long-span converter station steel structure and verifying the reliability of the monitoring system

Project Overview
Multi-Point
Principle
Real-Time
Results
17. Deflection along the center line of the
Monitoring System Results
Analysis
Evaluation Parameters
Conclusions
Full Text
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