Article
Construction & Building Technology
Khoa Nguyen, Ngoc Van Bach Pham, Thao T. B. Dao
Summary: This paper presents a method for detecting damage of bridge cables using a climbing robot. It is able to detect cracks and local reductions in diameter by analyzing the wavelet transform of the robot's displacement.
ADVANCES IN STRUCTURAL ENGINEERING
(2022)
Article
Engineering, Civil
Fei Wang, Zhong-da Lv, Min-jie Gu, Qin-kai Chen, Zhuo Zhao, Jun Luo
Summary: The study investigated the impact of axial forces generated by self-anchored suspension cable-stayed bridges on the main beam, as well as the stability of orthotropic steel box girders. Through model tests and axial compression tests, the stability and ultimate bearing capacity of the box girder structure were evaluated, leading to the conclusion that the model should be designed at a scale of 1:4.
THIN-WALLED STRUCTURES
(2021)
Article
Computer Science, Interdisciplinary Applications
Keunyoung Jang, Yun-Kyu An, Byunghyun Kim, Soojin Cho
Summary: This article introduces a deep learning-based automated crack evaluation technique using a ring-type climbing robot for high-rise bridge piers, achieving a precision of 90.92%. The technique utilizes various image processing algorithms to quantify cracks and automatically establish a digital crack map.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
(2021)
Review
Engineering, Multidisciplinary
Lixiao Zhang, Guoyang Qiu, Zhishou Chen
Summary: Cables are crucial components in cable-stayed bridges, and monitoring their tension is essential for ensuring bridge safety. This paper examines both traditional and innovative methods for monitoring cable force, including recent advancements in intelligent monitoring techniques. The conclusion provides insight for the future development of cable-stayed bridges.
Article
Chemistry, Multidisciplinary
Jaegyun Park, Jaeyong Yoon, Chulho Park, Jungwhee Lee
Summary: As the demand and construction of cable-stayed bridges have increased, research on the safety of cable-stayed bridges in the event of natural disasters such as fires and explosions is actively being conducted. This study evaluates the usability of the cable-stayed bridge in the event of cable damage and assesses its seismic performance and the impact of the damage through numerical analysis.
APPLIED SCIENCES-BASEL
(2023)
Article
Robotics
Zhenliang Zheng, Wenchao Zhang, Xueqi Fu, Sarsenbek Hazken, Xiaoli Hu, Huaping Chen, Jianwen Luo, Ning Ding
Summary: CCRbot-IV is a climbing robot designed for bridge cable-inspection tasks, with the capability to cross various obstacles and carry heavy loads. It utilizes a quad-ducted propeller and a gripping mechanism for locomotion and anchoring, achieving obstacle-free operation.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Construction & Building Technology
Yanxiao Yang, Mubiao Su, Heng Liu
Summary: In the study, the effects of ambient temperature change, stiffness degradation of the main beam, and cable damage on the deflection of the main girder in a single-tower cable-stayed bridge under self-weight were investigated. The results showed that the deflection difference of the girder had obvious characteristics before and after cable damage, with a twisted distribution curve and increasing peak value. The deterioration of the girder's performance made the deflection more sensitive to cable damage. Ambient temperature change had a significant influence on the girder's deflection, but no obvious influence on the deflection difference before and after cable damage.
Article
Engineering, Civil
Hourui Duan, Hongbo Liu, Yue Sun, Hongshuai Gao
Summary: Based on the analysis of the engineering background of the cable-stayed bridge without backstays in Jinzhou Bridge, it is found that the current cable force fails to satisfy the actual requirements. Finite element models are established and modified to analyze the internal force states of the beam and tower, and determine the reasonable internal force state and corresponding cable forces.
JOURNAL OF CIVIL STRUCTURAL HEALTH MONITORING
(2023)
Article
Construction & Building Technology
Xiaoling Liu, Xiyan Yi, Bing Wang, Ying Liu
Summary: A novel method for assessing grouped cable forces using deflection data is proposed in this article, which includes establishing a simplified equation between cable forces and girder deflection, determining the threshold value of cable force change rate, and developing a condition assessment method for grouped cable forces. A case study of a real bridge validates the proposed theoretical equation and shows a decrease in the assessment scores of grouped cables over six years, reflecting the development of other component defects.
Article
Engineering, Civil
Wen-ming Zhang, Jie Chen, Gen-min Tian, Xiao-fan Lu
Summary: This paper proposes an analytical algorithm to solve the full-bridge response of a hybrid cable-stayed suspension bridge under a horizontal transverse live load. The bridge is divided into several components and mechanical models and response calculation theories are built for each component. The feasibility and effectiveness of the analytical method are verified by comparing the results with those from the finite element model.
Article
Construction & Building Technology
Tzu-Hsuan Lin, Alan Putranto, Pin -Hang Chen, Yun-Zhen Teng, Li Chen
Summary: We have developed a High Mobility Inchworm Climbing Robot (HMICRobot) capable of traversing obstacles and conducting internal inspections in steel box girder bridges. Compared to existing robots, the HMICRobot has superior climbing and obstacle-crossing capabilities due to its hybrid power design, unique footpad electromagnetic control, and central core module with large wheels. With exceptional locomotion abilities, such as vertical and horizontal climbing, flipping, and obstacle-crossing, the HMICRobot is a promising solution for complex inspection and maintenance tasks in steel box girders. In the field of inspection robots, the HMICRobot represents a significant advancement, particularly for internal inspections of steel box girder bridges.
AUTOMATION IN CONSTRUCTION
(2023)
Article
Engineering, Mechanical
Houjun Kang, Xiaoyang Su, Zihao Pi
Summary: The study explores the dynamic characteristics of a multi-cable-stayed shallow-arch model of a cable-stayed bridge under internal resonance, finding that support stiffness can reduce response amplitudes by absorbing energy to some extent.
NONLINEAR DYNAMICS
(2022)
Article
Robotics
Liang Yang, Bing Li, Jinglun Feng, Guoyong Yang, Yong Chang, Biao Jiang, Jizhong Xiao
Summary: This paper introduces a wall-climbing robot for metric concrete inspection that can detect and measure surface flaws and generate defect-highlighted 3D models. The robot has good operational performance and can work under low illuminated and texture-less environments. Additionally, the paper provides a publicly accessible concrete structure dataset.
JOURNAL OF FIELD ROBOTICS
(2023)
Article
Engineering, Civil
Mohammad E. Omran, Abbas H. Karani
Summary: This paper studies the performance of isolated cable-stayed bridges in case of cable loss conditions, focusing on the Bill Emerson Cable-Stayed Bridge with Roll-N-Cage (RNC) isolators. The results show that the RNC isolator with an activated buffer mechanism can effectively reduce the permanent displacement under seismic loads and provide structural stability.
Article
Engineering, Civil
Noel Soto, Clara Cid, Aitor Baldomir, Santiago Hernandez
Summary: This paper presents a methodology to optimize the cable system in cable-stayed bridges by considering the accidental breakage of one cable. A multi-model optimization strategy is proposed, and design constraints are established on both the intact and damaged models. Impact loads are applied in the damaged models to account for the dynamic effect of cable breakage. The objective is to minimize the steel volume by varying cable anchor positions, number of cables, cross-sectional areas, and prestressing forces. The approach is applied to the Queensferry Crossing Bridge, resulting in a different layout with increased cables and smaller areas, while minimizing the penalty in steel volume.
ENGINEERING STRUCTURES
(2023)
Article
Instruments & Instrumentation
Fengyu Xu, Jiang Quansheng, Yuxuan Lu, Guoping Jiang
Summary: Soft climbing robots have great potential in unstructured environments by imitating motion of creatures, and a pneumatic soft climbing robot with stiffness gradient was designed. The research focused on analyzing visco-mechanical properties at the contact surface and deformation characteristics of cavities, and calculated the optimal number of cavities in an actuator required for climbing. Through simulation and 3D printing, a prototype soft climbing robot was prepared for climbing experiments, providing a new method for monitoring complex unstructured environments.
SMART MATERIALS AND STRUCTURES
(2021)
Review
Engineering, Mechanical
Junjun Zhu, Quansheng Jiang, Yehu Shen, Chenhui Qian, Fengyu Xu, Qixin Zhu
Summary: With the development of intelligent manufacturing and automation, the requirements for mechanical fault diagnosis are increasing. The current fault signals are mostly time series, and recurrent neural networks have achieved promising results in this field. This study reviews the latest RNN methods and introduces the applications of RNN and combined neural networks including RNN.
JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY
(2022)
Article
Engineering, Multidisciplinary
Chunran Huo, Quansheng Jiang, Yehu Shen, Chenhui Qian, Qingkui Zhang
Summary: A modified ADC-CNN model and improved LATL training method were proposed for fault diagnosis of rolling bearings. Experimental results showed that the proposed method significantly outperformed the traditional 1D-CNN model on the PU dataset.
Article
Engineering, Multidisciplinary
Chenhui Qian, Quansheng Jiang, Yehu Shen, Chunran Huo, Qingkui Zhang
Summary: In this paper, a feature transfer learning model based on improved DenseNet and joint distribution adaptation (FT-IDJ) is proposed for rolling bearing fault diagnosis. The experimental results showed that FT-IDJ has higher classification accuracy and can effectively identify various common faults of rolling bearings.
MEASUREMENT SCIENCE AND TECHNOLOGY
(2022)
Article
Computer Science, Artificial Intelligence
Chenhui Qian, Junjun Zhu, Yehu Shen, Quansheng Jiang, Qingkui Zhang
Summary: Mechanical intelligent fault diagnosis is a crucial method for accurately identifying the health status of mechanical equipment. With the rise of big data era, deep network models and deep transfer learning algorithms have been utilized to enhance data processing and fault classification capabilities. This paper summarizes recent advancements and discusses the challenges and trends in using deep transfer learning for intelligent fault diagnosis.
NEURAL PROCESSING LETTERS
(2022)
Article
Engineering, Multidisciplinary
Weiyang Xu, Yehu Shen, Quansheng Jiang, Qixin Zhu, Fengyu Xu
Summary: This study proposes a method for extracting weak fault features from rolling bearing vibration signals using improved singular spectrum decomposition (SSD) and a singular-value energy autocorrelation coefficient spectrum (SVEACS). Experimental results demonstrate that the proposed method can effectively extract features and accurately diagnose faults in rolling bearings under strong noise.
MEASUREMENT SCIENCE AND TECHNOLOGY
(2022)
Article
Engineering, Mechanical
Jiahao Chen, Yehu Shen, Qixin Zhu, Quansheng Jiang, Ou Xie, Jing Miao
Summary: This paper investigates the impact of motion blur on feature matching in vSLAM systems and proposes a local residual motion blur discrimination network for efficient detection of motion blur images. By combining the motion blur recognition results with the vSLAM system, the performance of the system can be effectively improved. Experimental results show that the proposed algorithm significantly enhances the stability and accuracy of the vSLAM system.
JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY
(2022)
Article
Computer Science, Artificial Intelligence
Weiyang Xu, Quansheng Jiang, Yehu Shen, Fengyu Xu, Qixin Zhu
Summary: In this study, a method for predicting the remaining useful life (RUL) of rolling bearings is proposed, which combines Convolutional Autoencoder (CAE) networks and a status degradation model. The method accurately predicts the RUL of bearings and evaluates the degree of degradation.
APPLIED SOFT COMPUTING
(2022)
Article
Engineering, Multidisciplinary
Xing Li, Yehu Shen, Jinbin Lu, Quansheng Jiang, Ou Xie, Yong Yang, Qixin Zhu
Summary: This paper presents DyStSLAM, a visual SLAM system with a stereo configuration that efficiently identifies moving objects and accomplishes dynamic data association. By extracting feature points, estimating the disparity map, and performing instance segmentation simultaneously, the system combines the motion confidence estimation and pose estimation of static objects to construct a sparse point cloud map including both static background and dynamic objects.
MEASUREMENT SCIENCE AND TECHNOLOGY
(2023)
Article
Engineering, Multidisciplinary
Ming Ma, Quansheng Jiang, Haochen Wang, Yehu Shen, Fengyu Xu
Summary: This article introduces a novel bionic pneumatic gripper inspired by spider legs, which has the advantages of simplicity and adaptability in structure. The gripping power is usually limited due to the low modulus of soft materials, so a design with symmetrical fingers, pneumatic actuated joints, rigid links, and pneumatic soft pads is proposed to increase the gripping force. The compressibility and elasticity of the soft joint and pad enable the gripper to handle fragile objects without damage. The prototype is manufactured and evaluated for gripping force, flexibility, and adaptability with promising results.
JOURNAL OF BIONIC ENGINEERING
(2023)
Article
Automation & Control Systems
Chunran Huo, Quansheng Jiang, Yehu Shen, Qixin Zhu, Qingkui Zhang
Summary: Deep transfer learning is used to solve the problem of unsupervised intelligent fault diagnosis of rolling bearings. However, when the data distribution between two domains is different, the existing deep transfer learning models are not enough to complete the target domain data learning. An enhanced transfer learning method based on the linear superposition network is proposed for rolling bearing fault diagnosis. Experimental results show improved bearing fault diagnostic precision compared to traditional feature-based transfer learning methods.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Engineering, Mechanical
Qin Yao, Mengchuang Zhang, Quansheng Jiang, Shangjun Ma
Summary: This paper establishes a preliminary mathematical model considering uncertain factors for the PRSM and introduces the quasi-Monte Carlo method to improve solving efficiency. The parameter sensitivities of uncertain factors to load distribution and contact characteristics are comprehensively ranked, and the computational cost for constructing the ALK model is decreased by selecting sensitive variables. The ALK-QMC method is combined to explore the main factors affecting the structural reliability of PRSM and optimize it using the NSGA-II-Downhill algorithm, which is verified by the finite element method.
PROBABILISTIC ENGINEERING MECHANICS
(2023)
Article
Engineering, Electrical & Electronic
Weiyang Xu, Quansheng Jiang, Yehu Shen, Qixin Zhu, Fengyu Xu
Summary: In this study, a method for predicting the remaining useful life (RUL) based on data feature distribution and spatial attention residual network (SARN) is proposed. The method segments multisensor data using distribution feature difference analysis to highlight degradation characteristics. By combining the proposed SARN with a spatial attention mechanism and residual network, more extensive and complementary features can be extracted, improving the accuracy of RUL prediction.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Engineering, Mechanical
Quansheng Jiang, Kai Cai, Fengyu Xu
Summary: Path planning is essential for the operation of bending robots. This paper proposes an obstacle-avoidance path-planning method for a 5 DOF bending robot based on an improved artificial potential field. The method uses a connecting-rod coordinate system and incorporates a rapidly exploring random tree algorithm to overcome the local minimum problem and enhance path smoothness. Simulation and experiments demonstrate the effectiveness of the proposed method in planning optimal paths for bending robot operations.
MECHANICAL SCIENCES
(2023)
Article
Construction & Building Technology
Jia Liang, Qipeng Zhang, Xingyu Gu
Summary: A lightweight PCSNet-based segmentation model is developed to address the issues of insufficient performance in feature extraction and boundary loss information. The introduction of generalized Dice loss improves prediction performance, and the visualization of class activation mapping enhances model interpretability.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Gilsu Jeong, Minhyuk Jung, Seongeun Park, Moonseo Park, Changbum Ryan Ahn
Summary: This study introduces a contextual audio-visual approach to recognize multi-equipment activities in tunnel construction sites, improving monitoring effectiveness. Tested against real-world operation data, the model achieved remarkable results, emphasizing the potential of contextual multimodal models in enhancing operational efficiency in complex construction sites.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Jin Wang, Zhigao Zeng, Pradip Kumar Sharma, Osama Alfarraj, Amr Tolba, Jianming Zhang, Lei Wang
Summary: This study presents a dual-path network for pavement crack segmentation, combining Convolutional Neural Network (CNN) and transformer. A lightweight CNN encoder is used for local feature extraction, while a novel transformer encoder integrates high-low frequency attention mechanism and efficient feedforward network for global feature extraction. Additionally, a complementary fusion module is introduced to aggregate intermediate features extracted from both encoders. Evaluation on three datasets confirms the superior performance of the proposed network.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Pierre Gilibert, Romain Mesnil, Olivier Baverel
Summary: This paper introduces a flexible method for crafting 2D assemblies adaptable to various geometric assumptions in the realm of sustainable construction. By utilizing digital fabrication technologies and optimization approaches, precise control over demountable buildings can be achieved, improving mechanical performance and sustainability.
AUTOMATION IN CONSTRUCTION
(2024)
Review
Construction & Building Technology
Jorge Loy-Benitez, Myung Kyu Song, Yo-Hyun Choi, Je-Kyum Lee, Sean Seungwon Lee
Summary: This paper discusses the advancement of tunnel boring machines (TBM) through the application of artificial intelligence. It highlights the significance of AI-based management subsystems for automatic TBM operations and presents recent contributions in this field. The paper evaluates modeling, monitoring, and control subsystems and suggests research paths for integrating existing management subsystems into TBM automation.
AUTOMATION IN CONSTRUCTION
(2024)
Review
Construction & Building Technology
Alireza Shamshiri, Kyeong Rok Ryu, June Young Park
Summary: This paper reviews the application of text mining and natural language processing in the construction field, highlighting the need for automation and minimizing manual tasks. The study identifies potential research opportunities in strengthening overlooked construction aspects, coupling diverse data formats, and leveraging pre-trained language models and reinforcement learning.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Zhengyi Chen, Hao Wang, Keyu Chen, Changhao Song, Xiao Zhang, Boyu Wang, Jack C. P. Cheng
Summary: This study proposes an improved coverage path planning system that leverages building information modeling and robotic configurations to optimize coverage performance in indoor environments. Experimental validation shows the effectiveness and applicability of the system. Future research will focus on further enhancing coverage ratio and optimizing computation time.
AUTOMATION IN CONSTRUCTION
(2024)
Review
Construction & Building Technology
Yonglin Fu, Junjie Chen, Weisheng Lu
Summary: This study presents a review of human-robot collaboration (HRC) in modular construction manufacturing (MCM), focusing on tasks, human roles, and interaction levels. The review found that HRC solutions are applicable to various MCM tasks, with a primary focus on timber component production. It also revealed the diverse collaborative roles humans can play and the varying levels of interaction with robots.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Qiong Liu, Shengbo Cheng, Chang Sun, Kailun Chen, Wengui Li, Vivian W. Y. Tam
Summary: This paper presents an approach to enhance the path-following capability of concrete printing by integrating steel cables into the printed mortar strips, and validates the feasibility and effectiveness of this approach through experiments.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Honghu Chu, Lu Deng, Huaqing Yuan, Lizhi Long, Jingjing Guo
Summary: The study proposes a method called Cascade CATransUNet for high-resolution crack image segmentation. This method combines the coordinate attention mechanism and self-cascaded design to accurately segment cracks. Through a customized feature extraction architecture and an optimized boundary loss function, the proposed method achieves impressive segmentation performance on HR images and demonstrates its practicality in UAV crack detection tasks.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Daniel Lamas, Andres Justo, Mario Soilan, Belen Riveiro
Summary: This paper introduces a new method for creating synthetic point clouds of truss bridges and demonstrates the effectiveness of a deep learning approach for semantic and instance segmentation of these point clouds. The proposed methodology has significant implications for the development of automated inspection and monitoring systems for truss bridges.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Kahyun Jeon, Ghang Lee, Seongmin Yang, Yonghan Kim, Seungah Suh
Summary: This study proposes two enhanced unsupervised text classification methods for domain-specific non-English text. The results of the tests show that these methods achieve excellent performance on Korean building defect complaints, outperforming state-of-the-art zero-shot and few-shot text classification methods, with minimal data preparation effort and computing resources.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Yoonhwa Jung, Julia Hockenmaier, Mani Golparvar-Fard
Summary: This study introduces a transformer-based natural language processing model, UNIfORMATBRIDGE, that automatically labels activities in a project schedule with Uniformat classification. Experimental results show that the model performs well in matching unstructured schedule data to Uniformat classifications. Additionally, the study highlights the importance of this method in developing new techniques.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
De-Graft Joe Opoku, Srinath Perera, Robert Osei-Kyei, Maria Rashidi, Keivan Bamdad, Tosin Famakinwa
Summary: This paper introduces a digital twin technology combining Building Information Modelling and the Internet of Things for the construction industry, aiming to optimize building conditions. The technology is implemented in a university library, successfully achieving real-time data capture and visual representation of internal conditions.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Zaolin Pan, Yantao Yu
Summary: The construction industry faces safety and workforce shortages globally, and worker-robot collaboration is seen as a solution. However, robots face challenges in recognizing worker intentions in construction. This study tackles these challenges by proposing a fusion method and investigating the best granularity for recognizing worker intentions. The results show that the proposed method can recognize multi-granular worker intentions effectively, contributing to seamless worker-robot collaboration in construction.
AUTOMATION IN CONSTRUCTION
(2024)
