To enhance the accuracy and efficiency of bridge damage identification,a novel data-driven damage identification method was proposed.First,convolutional autoencoder(CAE)was used to extract key features from the accele...To enhance the accuracy and efficiency of bridge damage identification,a novel data-driven damage identification method was proposed.First,convolutional autoencoder(CAE)was used to extract key features from the acceleration signal of the bridge structure through data reconstruction.The extreme gradient boosting tree(XGBoost)was then used to perform analysis on the feature data to achieve damage detection with high accuracy and high performance.The proposed method was applied in a numerical simulation study on a three-span continuous girder and further validated experimentally on a scaled model of a cable-stayed bridge.The numerical simulation results show that the identification errors remain within 2.9%for six single-damage cases and within 3.1%for four double-damage cases.The experimental validation results demonstrate that when the tension in a single cable of the cable-stayed bridge decreases by 20%,the method accurately identifies damage at different cable locations using only sensors installed on the main girder,achieving identification accuracies above 95.8%in all cases.The proposed method shows high identification accuracy and generalization ability across various damage scenarios.展开更多
This paper intends to identify the modal parameters of an offshore platform under ambient excitation, and to compare the identified results with theoretical solutions. Using ambient sources of excitation to determine ...This paper intends to identify the modal parameters of an offshore platform under ambient excitation, and to compare the identified results with theoretical solutions. Using ambient sources of excitation to determine the modal characteristics of large civil engineering structures is desirable for several reasons. The forced vibration testing of such structures generally requires a large amount of specialized equipment and makes the tests quite expensive. Also, an automated health monitoring system for a large civil structure will most likely use ambient excitation. The Eigensystem Realization Algorithm (ERA) is applied in conjunctied acceleration information. Finally, offshore platform numerical model gets output response data under ambient excitation. Simulated data from numerical model of an offshore platform under ambient excitation is used for the identification of the system. According to the comparison results, the proposed method is shown to be effective for modal parameter identification under ambient excitation.展开更多
基金The National Natural Science Foundation of China(No.52361165658,52378318,52078459).
文摘To enhance the accuracy and efficiency of bridge damage identification,a novel data-driven damage identification method was proposed.First,convolutional autoencoder(CAE)was used to extract key features from the acceleration signal of the bridge structure through data reconstruction.The extreme gradient boosting tree(XGBoost)was then used to perform analysis on the feature data to achieve damage detection with high accuracy and high performance.The proposed method was applied in a numerical simulation study on a three-span continuous girder and further validated experimentally on a scaled model of a cable-stayed bridge.The numerical simulation results show that the identification errors remain within 2.9%for six single-damage cases and within 3.1%for four double-damage cases.The experimental validation results demonstrate that when the tension in a single cable of the cable-stayed bridge decreases by 20%,the method accurately identifies damage at different cable locations using only sensors installed on the main girder,achieving identification accuracies above 95.8%in all cases.The proposed method shows high identification accuracy and generalization ability across various damage scenarios.
文摘This paper intends to identify the modal parameters of an offshore platform under ambient excitation, and to compare the identified results with theoretical solutions. Using ambient sources of excitation to determine the modal characteristics of large civil engineering structures is desirable for several reasons. The forced vibration testing of such structures generally requires a large amount of specialized equipment and makes the tests quite expensive. Also, an automated health monitoring system for a large civil structure will most likely use ambient excitation. The Eigensystem Realization Algorithm (ERA) is applied in conjunctied acceleration information. Finally, offshore platform numerical model gets output response data under ambient excitation. Simulated data from numerical model of an offshore platform under ambient excitation is used for the identification of the system. According to the comparison results, the proposed method is shown to be effective for modal parameter identification under ambient excitation.
