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Bridges

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场景介绍需求分析方案亮点核心产品典型案例

场景介绍

Bridges are critical nodes in the transportation backbone network and play a significant role in the development of transportation systems. During their service life, they can suffer from structural damage and functional degradation due to environmental factors such as erosion, material aging, and other causes.

The Ruhr IoT Bridges Sensing System utilizes intelligent sensing, communication, networking, and computing technologies. By implementing real-time monitoring of environmental and structural parameters in bridges, the system facilitates a comprehensive analysis and intelligent evaluation of the the safety conditions of bridges.

需求分析

Structural instability

Due to environmental degradation, traffic loads, wind, earthquakes, and human factors, bridge structures can suffer varying degrees of damage and deterioration. In extreme cases, this may lead to catastrophic events.

Overloading

Overloading increases the fatigue stress range of bridges, aggravates structural damage, and can lead to catastrophic failure when reaching a certain level.

Maintenance Management

Maintenance management relies primarily on regular manual inspections, with relatively long intervals between consecutive inspections.

方案亮点

Real-time Security Situation Awareness

Real-time Security Situation Awareness involves continuously monitoring the displacement, deformation, and vibration of structural stress conditions, as well as environmental factors such as wind and rain, to timely assess the safety conditions of bridges.
Early Warning System For Abnormal States

By conducting real-time analysis on the monitoring data of the bridge, the system will assess the bridge's health condition, and upon detecting any abnormalities, send notifications to relevant person.
Maintenance Guidance

Based on the assessment results, provide guidance to assist bridge managers in developing more efficient plans for maintenance .
Anomaly Data Traceability

By building the system, once special or abnormal situations occur, it is possible to trace back through the closed-loop management of data and processes to identify incident causes and reinforce responsibilities.