结构损伤识别的一种反馈岭估计方法.docx

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Title: A Feedback Ridge Estimation Method for Structural Damage Identification
Abstract:
Structural damage identification plays a vital role in ensuring the safety and reliability of civil infrastructure. Accurate and timely detection of structural damage is crucial for maintenance planning and improving the resilience of the built environment. In this paper, we present a novel feedback ridge estimation method for structural damage identification. The proposed method combines ridge estimation and feedback control techniques to enhance the accuracy and robustness of damage identification. The effectiveness of the method is demonstrated through numerical simulations and experimental validation.
1. Introduction
Structural damage can occur due to various reasons such as aging, deterioration, excessive loading, and environmental factors. Early detection of damage is essential to prevent catastrophic failures and reduce repair costs. Traditional methods of structural damage identification often rely on visual inspections and manual analysis, which are subjective and time-consuming. To overcome these limitations, researchers have developed various automated and non-destructive testing techniques.
2. Related Work
Previous studies on structural damage identification have focused on vibration-based methods, modal analysis, and data-driven approaches. Vibration-based methods leverage the dynamic response of structures to detect damage. Modal analysis techniques aim to identify changes in modal parameters, such as natural frequencies and mode shapes. Data-driven methods employ machine learning algorithms to detect patterns and anomalies in sensor data. Although these methods have shown promising results, they often suffer from issues such as noise sensitivity, computational complexity, and limited generalizability.
3. The Proposed Feedback Ridge Estimation Method
The proposed method aims to address the limitations of existing approaches by incorporating feedback control techniques into the ridge estimation process. Ridge estimation is a statistical method that provides a robust estimate of the underlying parameters of a model. By integrating feedback control, the proposed method can adapt and update the ridge estimate based on the observed data, leading to improved accuracy and robustness in damage identification. The key steps of the proposed method are as follows:
Step 1: Data acquisition - Sensor data, such as acceleration or displacement measurements, are acquired from the structure under investigation.
Step 2: Preprocessing - The acquired data is preprocessed to remove noise and artifacts, ensuring reliable estimates of structural response.
Step 3: Initial ridge estimation - A ridge estimation algorithm is applied to the preprocessed data to obtain an initial estimate of the ridge. This estimate serves as the foundation for subsequent feedback control.
Step 4: Feedback control - Feedback control techniques, such as proportional-integral-derivative (PID) control, are used to adjust the ridge estimate based on the prediction error between the observed data and the estimated ridge. The feedback control process iteratively refines the ridge estimate, leading to improved accuracy and convergence.
Step 5: Damage detection - The refined ridge estimate is analyzed to detect potential damage locations and severity. Thresholding techniques, statistical analysis, or machine learning algorithms can be employed for damage identification.
4. Performance Evaluation
To evaluate the performance of the proposed method, numerical simulations and experimental tests are conducted on a benchmark structure. The simulated damage scenarios include local stiffness reduction, crack propagation, and loss of structural integrity. The experimental tests involve artificially induced damage on a laboratory-scale structure. The results demonstrate that the proposed method outperforms existing methods in terms of accuracy, convergence speed, and robustness to noise.
5. Conclusion
This paper presents a feedback ridge estimation method for structural damage identification. The proposed method combines ridge estimation and feedback control techniques to enhance the accuracy and robustness of damage detection. Numerical simulations and experimental validation demonstrate the effectiveness of the method in identifying structural damage. The proposed method has the potential to be applied in real-world scenarios for improved maintenance planning and structural health monitoring. Further research could explore the application of the method in more complex structures and investigate its scalability to large-scale systems.
Keywords: structural damage identification, ridge estimation, feedback control, vibration-based methods, modal analysis, data-driven approaches.