Vortex-Induced Vibration Detection in Long-Span Suspension Bridges
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for real-time identification and monitoring of vortex-induced vibrations (VIV) in long-span bridges are inaccurate and unable to detect the occurrence and end moments of VIV events, relying on manual visual judgment or batch spectrum analysis that is not suitable for online real-time monitoring.
Innovation Solution
A real-time online monitoring method using recursive Hilbert transform processing of bridge acceleration signals, involving high-pass filtering, displacement integration, and conversion of signals into complex plane vectors to intuitively identify VIV through circular image features, allowing for real-time detection and early warning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual visual judgment or batch spectrum analysis is used to identify VIV, then the identification process is simple to implement, but the measurement precision and real-time capability are insufficient
Solution Approach 1:
The patent applies dynamic adaptive filtering by adjusting the Q-factor of the resonant filter based on the instantaneous frequency estimation. This allows the filter to dynamically track the VIV frequency while rejecting non-resonant components, achieving high measurement precision without requiring complex fixed-filter designs. The dynamic adaptation enables real-time tracking of VIV events with varying frequencies.
Solution Approach 2:
The patent replaces manual visual judgment and batch spectrum analysis with an automated signal processing system based on resonant filtering and Hilbert transform. This substitution of mechanical/manual processes with electronic signal processing algorithms enables both high measurement precision and real-time operation, eliminating the trade-off between accuracy and automation.
2Productivity
If batch spectrum analysis is performed on monitoring data, then the analysis can be conducted with simple processing, but real-time online judgment cannot be achieved
Solution Approach 1:
The patent implements preliminary action by continuously maintaining a resonant filter tuned to the current estimated VIV frequency, ready to immediately capture and analyze vibration signals when VIV occurs. This pre-positioned filtering capability eliminates the need for batch processing delays, enabling real-time detection and immediate identification of VIV events as they happen.
Solution Approach 2:
The patent ensures continuous useful action through the ongoing execution of frequency tracking and resonant filtering operations. The system continuously estimates instantaneous frequency, adjusts filter parameters, and processes signals in real-time without interruption or batch delays. This continuous operation enables immediate detection and analysis of VIV events, achieving both high productivity and minimal time loss.
3Measurement precision
If the monitoring system uses complex signal processing algorithms, then the measurement precision improves, but the ease of operation and computational requirements increase
Solution Approach 1:
The patent implements self-service through automatic frequency tracking and adaptive filter tuning. The system autonomously estimates the instantaneous VIV frequency, adjusts the resonant filter Q-factor and center frequency without manual intervention, and automatically identifies VIV events. This self-adjusting capability maintains high measurement precision while simplifying operation, as the system performs complex signal processing automatically without requiring operator expertise or manual configuration.
Data Source
AI summary
The invention discloses a real-time online monitoring, perception, and early warning method for vortex-induced vibration of suspension bridges. Based on the fast Fourier transform FFT of the bridge acceleration monitoring signal, The first-order nature frequency of the bridge can be obtained by reading the horizontal coordinate corresponding to the first-order energy peak of the spectrum and determine the high-pass filter cut-off frequency. The low-frequency noise is eliminated by the filter in order to calculate the displacement of the bridge by the recursive acceleration integration method; Taking the integrated displacement data as the real part and its Hilbert transform as the imaginary part, the analytic signal is plotted and evaluated in the complex plane to achieve the perception and early warning of VIVs. The advantages of the invention are real-time, high precision, accuracy and intuition, online real-time VIV perception and measurement of bridge vibration parameters during VIV can be realized.