基于振动声纹协同感知的桥梁伸缩缝状态监测方法、装置及系统
By collecting vibration and acoustic signals of bridge expansion joints using a distributed sensor array, a temporal co-evolution field is constructed and mapped to a physical force transmission path network. This solves the problems of low efficiency and large error in existing bridge expansion joint monitoring methods, and achieves accurate damage identification and reliable condition assessment.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- 中铁科学研究院集团有限公司
- Filing Date
- 2026-01-28
- Publication Date
- 2026-07-17
AI Technical Summary
Existing methods for monitoring the condition of bridge expansion joints are inefficient, make it difficult to accurately identify minor faults, and result in large amounts of data redundancy and high system energy consumption due to continuous sensor monitoring. They also cannot effectively distinguish between actual structural damage and environmental interference signals.
By synchronously collecting vibration and acoustic signals through distributed sensor arrays, a set of original monitoring data with timestamp alignment is generated. Spatiotemporal correlation modeling is performed to construct a time-series co-evolution field, causal lag modes are separated, and mapped to the physical force transmission path network to generate a hidden damage topology map, thereby quantitatively assessing the overall performance level and local damage degree of bridge expansion joints.
This has improved the accuracy and reliability of damage identification, reduced subjective intervention errors, enhanced the adaptability and robustness of the monitoring system, and improved monitoring efficiency and stability in complex environments.
Smart Images
Figure CN121637110B_ABST