Design formulas for vibration control of sagged cables using passive MR dampers

Yuanfeng Duan,Yi-Qing Ni,Hongmei Zhang,Billie F. Jr. Spencer,Jan-Ming Ko,Shenghao Dong 국제구조공학회 2019 Smart Structures and Systems, An International Jou Vol.23 No.6

In this paper, a method for analyzing the damping performance of stay cables incorporating magnetorheological (MR) dampers in the passive control mode is developed taking into account the cable sag and inclination, the damper coefficient, stiffness and mass, and the stiffness of damper support. Both numerical and asymptotic solutions are obtained from complex modal analysis. With the asymptotic solution, analytical formulas that evaluate the equivalent damping ratio of the sagged cable-damper system in consideration of all the above parameters are derived. The main thrust of the present study is to develop an general design formula and a universal curve for the optimal design of MR dampers for adjustable passive control of sagged cables. Two sag-affecting coefficients are derived to reflect the effects of cable sag on the maximum attainable damping ratio and the optimal damper coefficient. For the cable configurations commonly used in cable-stayed bridges, the sag-affecting coefficients are directly expressed in terms of the sag-extensibility parameter to facilitate the control design. A case study on adjustable passive vibration control of the longest cable (536 m) on Stonecutters Bridge is carried out to demonstrate the influence of the sag for the damper design, and to figure out the necessity of adjustability of damper coefficients for achieving maximum damping ratio for different vibration modes.

Anomaly detection of isolating switch based on single shot multibox detector and improved frame differencing

Yuanfeng Duan,Qi Zhu,Hongmei Zhang,Wei Wei,Chung Bang Yun 국제구조공학회 2021 Smart Structures and Systems, An International Jou Vol.28 No.6

High-voltage isolating switches play a paramount role in ensuring the safety of power supply systems. However, their exposure to outdoor environmental conditions may cause serious physical defects, which may result in great risk to power supply systems and society. Image processing-based methods have been used for anomaly detection. However, their accuracy is affected by numerous uncertainties due to manually extracted features, which makes the anomaly detection of isolating switches still challenging. In this paper, a vision-based anomaly detection method for isolating switches, which uses the rotational angle of the switch system for more accurate and direct anomaly detection with the help of deep learning (DL) and image processing methods (Single Shot Multibox Detector (SSD), improved frame differencing method, and Hough transform), is proposed. The SSD is a deep learning method for object classification and localization. In addition, an improved frame differencing method is introduced for better feature extraction and a hough transform method is adopted for rotational angle calculation. A number of experiments are conducted for anomaly detection of single and multiple switches using video frames. The results of the experiments demonstrate that the SSD outperforms the You-Only-Look-Once network. The effectiveness and robustness of the proposed method have been proven under various conditions, such as different illumination and camera locations using 96 videos from the experiments.

Design formulas for vibration control of taut cables using passive MR dampers

Yuanfeng Duan,Yi-Qing Ni,Hongmei Zhang,Billie. F., Jr. Spencer,Jan-Ming Ko,Yi Fang 국제구조공학회 2019 Smart Structures and Systems, An International Jou Vol.23 No.6

Using magnetorheological (MR) dampers in multiswitch open-loop control mode has been shown to be cost-effective for cable vibration mitigation. In this paper, a method for analyzing the damping performance of taut cables incorporating MR dampers in open-loop control mode is developed considering the effects of damping coefficient, damper stiffness, damper mass, and stiffness of the damper support. Making use of a three-element model of MR dampers and complex modal analysis, both numerical and asymptotic solutions are obtained. An analytical expression is obtained from the asymptotic solution to evaluate the equivalent damping ratio of the cable-damper system in the open-loop control mode. The individual and combined effects of the damping coefficient, damper stiffness, damper mass and stiffness of damper support on vibration control effectiveness are investigated in detail. The main thrust of the present study is to derive a general formula explicitly relating the normalized system damping ratio and the normalized damper parameters in consideration of all concerned effects, which can be easily used for the design of MR dampers to achieve optimal open-loop vibration control of taut cables.

CNN-based damage identification method of tied-arch bridge using spatial-spectral information

Yuanfeng Duan,Qianyi Chen,Hongmei Zhang,Chung Bang Yun,Sikai Wu,Qi Zhu 국제구조공학회 2019 Smart Structures and Systems, An International Jou Vol.23 No.5

In the structural health monitoring field, damage detection has been commonly carried out based on the structural model and the engineering features related to the model. However, the extracted features are often subjected to various errors, which makes the pattern recognition for damage detection still challenging. In this study, an automated damage identification method is presented for hanger cables in a tied-arch bridge using a convolutional neural network (CNN). Raw measurement data for Fourier amplitude spectra (FAS) of acceleration responses are used without a complex data pre-processing for modal identification. A CNN is a kind of deep neural network that typically consists of convolution, pooling, and fully-connected layers. A numerical simulation study was performed for multiple damage detection in the hangers using ambient wind vibration data on the bridge deck. The results show that the current CNN using FAS data performs better under various damage states than the CNN using time-history data and the traditional neural network using FAS. Robustness of the present CNN has been proven under various observational noise levels and wind speeds.

Ultrasonic guided wave approach incorporating SAFE for detecting wire breakage in bridge cable

Zhang, Pengfei,Tang, Zhifeng,Duan, Yuanfeng,Yun, Chung Bang,Lv, Fuzai 국제구조공학회 2018 Smart Structures and Systems, An International Jou Vol.22 No.4

Ultrasonic guided waves have attracted increasing attention for non-destructive testing (NDT) and structural health monitoring (SHM) of bridge cables. They offer advantages like single measurement, wide coverage of acoustical field, and long-range propagation capability. To design defect detection systems, it is essential to understand how guided waves propagate in cables and how to select the optimal excitation frequency and mode. However, certain cable characteristics such as multiple wires, anchorage, and polyethylene (PE) sheath increase the complexity in analyzing the guided wave propagation. In this study, guided wave modes for multi-wire bridge cables are identified by using a semi-analytical finite element (SAFE) technique to obtain relevant dispersion curves. Numerical results indicated that the number of guided wave modes increases, the length of the flat region with a low frequency of L(0,1) mode becomes shorter, and the cutoff frequency for high order longitudinal wave modes becomes lower, as the number of steel wires in a cable increases. These findings were used in design of transducers for defect detection and selection of the optimal wave mode and frequency for subsequent experiments. A magnetostrictive transducer system was used to excite and detect the guided waves. The applicability of the proposed approach for detecting and locating wire breakages was demonstrated for a cable with 37 wires. The present ultrasonic guided wave method has been found to be very responsive to the number of brokenwires and is thus capable of detecting defects with varying sizes.

Ultrasonic guided wave approach incorporating SAFE for detecting wire breakage in bridge cable

Pengfei Zhang,Zhifeng Tang,Yuanfeng Duan,Chung Bang Yun,Fuzai Lv 국제구조공학회 2018 Smart Structures and Systems, An International Jou Vol.22 No.4

Ultrasonic guided waves have attracted increasing attention for non-destructive testing (NDT) and structural health monitoring (SHM) of bridge cables. They offer advantages like single measurement, wide coverage of acoustical field, and long-range propagation capability. To design defect detection systems, it is essential to understand how guided waves propagate in cables and how to select the optimal excitation frequency and mode. However, certain cable characteristics such as multiple wires, anchorage, and polyethylene (PE) sheath increase the complexity in analyzing the guided wave propagation. In this study, guided wave modes for multi-wire bridge cables are identified by using a semi-analytical finite element (SAFE) technique to obtain relevant dispersion curves. Numerical results indicated that the number of guided wave modes increases, the length of the flat region with a low frequency of L(0,1) mode becomes shorter, and the cutoff frequency for high order longitudinal wave modes becomes lower, as the number of steel wires in a cable increases. These findings were used in design of transducers for defect detection and selection of the optimal wave mode and frequency for subsequent experiments. A magnetostrictive transducer system was used to excite and detect the guided waves. The applicability of the proposed approach for detecting and locating wire breakages was demonstrated for a cable with 37 wires. The present ultrasonic guided wave method has been found to be very responsive to the number of broken wires and is thus capable of detecting defects with varying sizes.

Vector mechanics-based simulation of large deformation behavior in RC shear walls using planar four-node elements

Hongmei Zhang,Yufei Shan,Yuanfeng Duan,Chung Bang Yun,Song Liu 국제구조공학회 2020 Structural Engineering and Mechanics, An Int'l Jou Vol.74 No.1

For the large deformation of shear walls under vertical and horizontal loads, there are difficulties in obtaining accurate simulation results using the response analysis method, even with fine mesh elements. Furthermore, concrete material nonlinearity, stiffness degradation, concrete cracking and crushing, and steel bar damage may occur during the large deformation of reinforced concrete (RC) shear walls. Matrix operations that are involved in nonlinear analysis using the traditional finite-element method (FEM) may also result in flaws, and may thus lead to serious errors. To solve these problems, a planar four-node element was developed based on vector mechanics. Owing to particle-based formulation along the path element, the method does not require repeated constructions of a global stiffness matrix for the nonlinear behavior of the structure. The nonlinear concrete constitutive model and bilinear steel material model are integrated with the developed element, to ensure that large deformation and damage behavior can be addressed. For verification, simulation analyses were performed to obtain experimental results on an RC shear wall subjected to a monotonically increasing lateral load with a constant vertical load. To appropriately evaluate the parameters, investigations were conducted on the loading speed, meshing dimension, and the damping factor, because vector mechanics is based on the equation of motion. The static problem was then verified to obtain a stable solution by employing a balanced equation of motion. Using the parameters obtained, the simulated pushover response, including the bearing capacity, deformation ability, curvature development, and energy dissipation, were found to be in accordance with the experimental observation. This study demonstrated the potential of the developed planar element for simulating the entire process of large deformation and damage behavior in RC shear walls.

Development of a full-scale magnetorheological damper model for open-loop cable vibration control

Ru Zhang,Yi-Qing Ni,Yuanfeng Duan,Jan-Ming Ko 국제구조공학회 2019 Smart Structures and Systems, An International Jou Vol.23 No.6

Modeling of magnetorheological (MR) dampers for cable vibration control to facilitate the design of even more effective and economical systems is still a challenging task. In this study, a parameter-adaptive three-element model is first established for a full-scale MR damper based on laboratory tests. The parameters of the model are represented by a set of empirical formulae in terms of displacement amplitude, voltage input, and excitation frequency. The model is then incorporated into the governing equation of cable-damper system for investigation of open-loop vibration control of stay cables in a cable-stayed bridge. The concept of optimal voltage/current input achieving the maximum damping for the system is put forward and verified. Multi-mode suboptimal and Single-mode optimal open-loop control method is then developed. Important conclusions are drawn on application issues and unique characteristics of open-loop cable vibration control using MR dampers.

An active learning method with difficulty learning mechanism for crack detection

Zhicheng Zhang,Jiangpeng Shu,Jun Li,Jiawei Zhang,Weijian Zhao,Yuanfeng Duan 국제구조공학회 2022 Smart Structures and Systems, An International Jou Vol.29 No.1

Crack detection is essential for inspection of existing structures and crack segmentation based on deep learning is asignificant solution. However, datasets are usually one of the key issues. When building a new dataset for deep learning, laborious and time-consuming annotation of a large number of crack images is an obstacle. The aim of this study is to develop an approach that can automatically select a small portion of the most informative crack images from a large pool in order to annotate them, not to label all crack images. An active learning method with difficulty learning mechanism for crack segmentation tasks is proposed. Experiments are carried out on a crack image dataset of a steel box girder, which contains 500 images of 320 × 320 size for training, 100 for validation, and 190 for testing. In active learning experiments, the 500 images for training are acted as unlabeled image. The acquisition function in our method is compared with traditional acquisition functions, i.e., Query-By-Committee (QBC), Entropy, and Core-set. Further, comparisons are made on four common segmentation networks: U-Net, DeepLabV3, Feature Pyramid Network (FPN), and PSPNet. The results show that when training occurs with 200 (40%) of the most informative crack images that are selected by our method, the four segmentation networks can achieve 92%-95% of the obtained performance when training takes place with 500 (100%) crack images. The acquisition function in our method shows more accurate measurements of informativeness for unlabeled crack images compared to the four traditional acquisition functions at most active learning stages. Our method can select the most informative images for annotation from many unlabeled crack images automatically and accurately. Additionally, the dataset built after selecting 40% of all crack images can support crack segmentation networks that perform more than 92% when all the images are used.