Article
Automation & Control Systems
Rakiba Rayhana, Hongguang Yun, Zheng Liu, Xiangjie Kong
Summary: This article proposes an automated defect-detection framework CSA-MaskC-RCNN that can automatically detect and classify defects in water pipelines. The trained model outperforms the state-of-the-art model with a mean average precision of 86.89%. Integrating this automatic defect-detection system can save time and cost for the human operator and aid them in making timely decisions for pipe repair/rehabilitation.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2023)
Article
Computer Science, Interdisciplinary Applications
Shashi Bhushan Jha, Radu F. Babiceanu
Summary: The computer vision domain has been transformed by deep learning algorithms and data science in recent years. Defect detection is crucial in high-tech industries like aerospace manufacturing and is widely conducted with automated industrial quality control systems. There are various methods for defect inspection, including manual inspection, traditional computer vision, and modern computer vision inspection. CNN algorithms have gained popularity in solving complex machine vision problems with the availability of big datasets and powerful hardware. Deep learning-based methods are categorized into dense networks and sparse networks based on their network connections. Learning types include supervised learning for defect classification and segmentation, and unsupervised learning models which can overcome challenges like image labeling and pixel annotation. Pixel-level based segmentation techniques are considered state-of-the-art for automatic optical inspection. However, both supervised and unsupervised models face challenges in model training and achieving expected detection accuracy. Open challenges include algorithmic, application, and data processing challenges. The demand for automated optical inspection is expected to grow in industry practice and academic research by addressing these challenges.
COMPUTERS IN INDUSTRY
(2023)
Article
Computer Science, Artificial Intelligence
Yi Liu, Changsheng Zhang, Xingjun Dong
Summary: In recent years, deep learning methods have been widely used in various industrial scenarios, promoting industrial intelligence. Real-time surface defect inspection of industrial products is one of the research focuses in industry. Surface defect inspection methods based on deep learning show great advantages and make it possible to detect defects in real time with high accuracy.
ARTIFICIAL INTELLIGENCE REVIEW
(2023)
Article
Chemistry, Analytical
Qiaodi Wen, Ziqi Luo, Ruitao Chen, Yifan Yang, Guofa Li
Summary: Two deep learning methods based on Faster R-CNN, Exact R-CNN and CME-CNN, are proposed in this study. Exact R-CNN improves target detection accuracy by incorporating advanced techniques, while CME-CNN enhances performance by generating insulator mask images for defect detection using Exact R-CNN.
Article
Engineering, Civil
Xiaocai Zhang, Xiuju Fu, Zhe Xiao, Haiyan Xu, Zheng Qin
Summary: This paper discusses the impact of growing maritime IoT data and traffic volume on driving artificial intelligence studies, particularly focusing on vessel trajectory prediction. It provides an overview of existing approaches, including state-of-the-art deep learning, and outlines future research directions in this field.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Chemistry, Multidisciplinary
Yujie Huang, Jing Yang, Degang Zhao, Yuheng Zhang, Zongshun Liu, Feng Liang, Ping Chen
Summary: The dark leakage current of AlxGa1-xN Schottky barrier detectors with different Al contents was investigated. It was found that the dark leakage current increased with increasing Al content. XRD and SIMS results showed no significant difference in dislocation density and carbon impurity concentration among the samples, indicating that they were not the main reason for the difference in dark leakage current. However, positron annihilation results revealed an increase in vacancy defect concentration with increasing Al content, which was consistent with the increase in dark leakage current. This discovery is important for accurately controlling the performance of AlxGa1-xN detectors.
Review
Construction & Building Technology
Yongding Tian, Chao Chen, Kwesi Sagoe-Crentsil, Jian Zhang, Wenhui Duan
Summary: This review provides an overview of the current robotic systems used in structural health monitoring (SHM) of bridges, and explores the development trends of multimodal robots and soft robotics. It highlights the potential of integrating various Nondestructive Evaluation (NDE) tools with robotic systems for performing multiple inspection tasks, and emphasizes the advantages of lightweight and adaptable soft robots in special/space-confined environments.
AUTOMATION IN CONSTRUCTION
(2022)
Article
Computer Science, Artificial Intelligence
Reza Eyvazpour, Maryam Shoaran, Ghader Karimian
Summary: This paper reviews the implementation and performance of SLAM algorithms on various platforms. It discusses that the primary option for implementing SLAM algorithms on hardware platforms is using hardware-software co-design approaches, and combining a hardware accelerator and a software approach can improve the speed and performance of the implementation.
ARTIFICIAL INTELLIGENCE REVIEW
(2023)
Review
Chemistry, Analytical
Yanfen Li, Hanxiang Wang, L. Minh Dang, Hyoung-Kyu Song, Hyeonjoon Moon
Summary: This article provides a systematic survey of sewer defect inspection algorithms and research trends, discussing the latest developments and explaining the datasets and evaluation metrics used. Furthermore, it reports the performance of state-of-the-art methods in terms of processing accuracy and speed.
Review
Engineering, Marine
Bosen Lin, Xinghui Dong
Summary: This paper reviews the background knowledge of hull inspection and categorizes different inspection approaches. In addition to manual inspection methods, the study also investigates automatic data processing methods and automated platforms. This research is important for researchers and industry professionals to gain an overall understanding of hull inspection and identify potential directions for future development.
Article
Computer Science, Information Systems
Yijing Guo, Yixin Zeng, Fengqiang Gao, Yi Qiu, Xuqiang Zhou, Linwei Zhong, Choujun Zhan
Summary: This paper proposes an improved algorithm based on YOLOV4-CSP for bamboo surface defect detection. The introduction of asymmetric convolution and attention mechanism enhances the detection performance of specific industrial defects. Experimental results demonstrate the outstanding performance of the algorithm in general and hard-to-detect categories.
Article
Chemistry, Multidisciplinary
Kastor Felsner, Klaus Schlachter, Sebastian Zambal
Summary: The proposed method involves calculating sub-paths, streamlines, and ray tracing to plan a complete inspection path for ultrasonic inspection. Experiment results show that using ray tracing can achieve shorter paths while maintaining coverage.
APPLIED SCIENCES-BASEL
(2021)
Article
Automation & Control Systems
Xiaoqing Zheng, Song Zheng, Yaguang Kong, Jie Chen
Summary: This paper presents the latest advances in surface defect inspection using deep learning, focusing on industrial products in semiconductor, steel, and fabric manufacturing processes. The research provides literature reviews, traditional surface defect inspection algorithms, and applications of deep learning-based inspection algorithms.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2021)
Article
Computer Science, Information Systems
Ling Yang, Bo Dang, Zhiping Ren, Changzan Liu, Jingxin Dang, Yang Zhao, Baixin An, Ruirong Dang
Summary: This study focuses on the inspection of wellbore casings in oil and gas production. A uniform circular array (UCA) and a multichannel data acquisition circuit were developed to address the problem of detecting asymmetry defects. The results of simulations and field experiments demonstrate the effectiveness of the proposed method.
Review
Engineering, Manufacturing
Sijun Ryu, Jeeho Won, Hobyeung Chae, Hwa Soo Kim, Taewon Seo
Summary: This paper introduces the evaluation method and performance indexes of mobile robots, including fluctuation performance, tip-over stability, and terrainability indexes. By these indexes, users can understand the performance of the robot and achieve goals in the right way.
INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING
(2023)
Article
Engineering, Electrical & Electronic
Francisco Bonnin-Pascual, Alberto Ortiz
IEEE SENSORS JOURNAL
(2016)
Article
Engineering, Marine
Francisco Bonnin-Pascual, Alberto Ortiz
Article
Surgery
Jaime Bonnin-Pascual, Cristina Alvarez-Segurado, Marina Jimenez-Segovia, Alessandro Bianchi, Francisco Bonnin-Pascual, Francesc Xavier Molina-Romero, Francesc Xavier Gonzalez-Argente
Article
Computer Science, Interdisciplinary Applications
Francisco Bonnin-Pascual, Alberto Ortiz, Emilio Garcia-Fidalgo, Joan P. Company-Corcoles
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2019)
Article
Chemistry, Analytical
Francisco Bonnin-Pascual, Alberto Ortiz
Article
Environmental Sciences
Francisco Bonnin-Pascual, Emilio Garcia-Fidalgo, Joan P. Company-Corcoles, Alberto Ortiz
Summary: This paper explores the use of aerial robots for visual inspections, focusing on vessel cargo holds for safer, cost-efficient, and intensive inspections. Equipped with sensor suite and control software, the multirotor-type platform provides imagery and enhanced functionalities to support the operator during flight. Through the supervised autonomy (SA) paradigm and extensive use of behavior-based high-level control, the system has been evaluated and proven effective for visual inspections in both laboratory and real environments aboard different vessels.
Article
Computer Science, Interdisciplinary Applications
Kai Yao, Alberto Ortiz, Francisco Bonnin-Pascual
Summary: In this paper, a new bounding boxes-based regression solution is proposed for recognizing generic targets in arbitrary orientations. The solution utilizes a two-stage method and a multi-scale approach, and it is evaluated on datasets from two industry-related case studies, demonstrating competitive performance levels in different scenarios.
COMPUTERS IN INDUSTRY
(2022)
Article
Automation & Control Systems
Emilio Garcia-Fidalgo, Joan P. Company-Corcoles, Francisco Bonnin-Pascual, Alberto Ortiz
Summary: This paper proposes a novel LiDAR-only ODOmetry and Mapping approach LiODOM for pose estimation and map-building by minimizing a loss function derived from a set of weighted point-to-line correspondences. It emphasizes on map representation and introduces a data structure combined with a hashing scheme for fast access to any section of the map.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2022)
Article
Computer Science, Information Systems
Kai Yao, Alberto Ortiz, Francisco Bonnin-Pascual
Summary: The study discusses the challenges of annotating images for vision algorithms based on deep learning. It proposes a weakly-supervised semantic segmentation approach utilizing a novel loss function to counteract the effects of weak annotations. The performance of the approach is evaluated on different industry-related case studies, demonstrating the capability of achieving competitive results with weak annotations.
Proceedings Paper
Automation & Control Systems
Emilio Garcia-Fidalgo, Francisco Bonnin-Pascual, Joan P. Company-Corcoles, Alberto Ortiz
2020 25TH IEEE INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGIES AND FACTORY AUTOMATION (ETFA)
(2020)
Proceedings Paper
Automation & Control Systems
Kai Yao, Alberto Ortiz, Francisco Bonnin-Pascual
2019 24TH IEEE INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGIES AND FACTORY AUTOMATION (ETFA)
(2019)
Proceedings Paper
Automation & Control Systems
Francisco Bonnin-Pascual, Alberto Ortiz
2019 24TH IEEE INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGIES AND FACTORY AUTOMATION (ETFA)
(2019)
Proceedings Paper
Computer Science, Artificial Intelligence
Francisco Bonnin-Pascual, Alberto Ortiz
RECENT ADVANCES IN ARTIFICIAL INTELLIGENCE RESEARCH AND DEVELOPMENT
(2017)
Proceedings Paper
Automation & Control Systems
Alberto Ortiz, Francisco Bonnin-Pascual, Emilio Garcia-Fidalgo, Joan P. Company
ROBOT 2015: SECOND IBERIAN ROBOTICS CONFERENCE: ADVANCES IN ROBOTICS, VOL 2
(2016)
Article
Engineering, Marine
Alba Ricondo, Laura Cagigal, Beatriz Perez-Diaz, Fernando J. Mendez
Summary: This research presents a site-specific metamodel based on the SWASH numerical model simulations, which can predict coastal hydrodynamic variables in a fast and efficient manner. The metamodel uses downscaled and dimensionality reduced synthetic database to accurately reproduce wave setup, wave heights associated with different frequency bands, and wave runup. This method has great potential in coastal risk assessments, early warning systems, and climate change projections.
Article
Engineering, Marine
Xiao Yu, Wangjun Ren, Bukui Zhou, Li Chen, Xiangyun Xu, Genmao Ren
Summary: This study investigated and compared the compression responses and energy absorption capacities of coral sand and silica sand at a strain rate of approximately 1000 s-1. The results showed that coral sand had significantly higher energy absorption capacity than silica sand due to its higher compressibility. The study findings suggest that using poorly graded coral sand can improve its energy absorption capacity.
Article
Engineering, Marine
Jingxi Zhang, Junmin Mou, Linying Chen, Pengfei Chen, Mengxia Li
Summary: This paper proposes a cooperative control scheme for ship formation tracking based on Model Predictive Control. A predictive observer is designed to estimate the current motion states of the leader ship using delayed motion information. Comparative simulations demonstrate the effectiveness and robustness of the proposed controller.
Article
Engineering, Marine
Yu Yao, Danni Zhong, Qijia Shi, Ji Wu, Jiangxia Li
Summary: This study proposes a 2DH numerical model based on Boussinesq equations to investigate the impact of dredging reef-flat sand on wave characteristics and wave-driven current. The model is verified through wave flume experiments and wave basin experiments, and the influences of incident wave conditions and pit morphological features on wave characteristics are examined.
Article
Engineering, Marine
Jayanta Shounda, Krishnendu Barman, Koustuv Debnath
Summary: This study investigates the double-average turbulence characteristics of combined wave-current flow over a rough bed with different spacing arrangements. The results show that a spacing ratio of p/r=4 offers the highest resistance to the flow, and the double-average Reynolds stress decreases throughout the flow depth. The advection of momentum-flux of normal stress shows an increase at the outer layer and a decrease near the bed region after wave imposition. Maximum turbulence kinetic energy production and diffusion occur at different layers. The turbulence structure is strongly anisotropic at the bottom region and near the outer layer, with a decrease in anisotropy observed with an increase in roughness spacing.
Article
Engineering, Marine
Meng Zhang, Lianghui Sun, Yaoguo Xie
Summary: The research proposes a method for online identification of wave bending and torsional moment in hull structures. For structures without large openings, the method optimizes sensor positions and establishes a mathematical model to improve accuracy. For structures with large openings, a joint dual-section monitoring method is proposed to simultaneously identify bending and torsional moments in multiple key cross sections.
Article
Engineering, Marine
Longming Chen, Shutao Li, Yeqing Chen, Dong Guo, Wanli Wei, Qiushi Yan
Summary: This study investigated the dynamic response characteristics and damage modes of pile wharves subjected to underwater explosions. The results showed that the main damaged components of the pile wharf were the piles, and inclined piles had a higher probability of moderate or more significant damage compared to vertical piles. The study also suggested that replacing inclined piles with alternative optimized structures benefits the blast resistance of pile wharves.
Article
Engineering, Marine
I. -C Kim, G. Ducrozet, V. Leroy, F. Bonnefoy, Y. Perignon, S. Bourguignon
Summary: Previous research focused on the accuracy and efficiency of short-term wave fields in specific prediction zones, while we developed algorithms for continuous wave prediction based on the practical prediction zone and discussed important time factors and strategies to reduce computational costs.
Article
Engineering, Marine
Hang Xie, Xianglin Dai, Fang Liu, Xinyu Liu
Summary: This study investigates the load characteristics of a three-dimensional stern model with pitch angle through a drop test, and reveals complex characteristics of pressure distribution near the stern shaft. The study also shows that the vibration characteristics of the load are influenced by the drop height and pitch angle, with the drop height having a greater effect on the high-frequency components.
Article
Engineering, Marine
Hangyuan Zhang, Wanli Yang, Dewen Liu, Xiaokun Geng, Wangyu Dai, Yuzhi Zhang
Summary: The deep-water bridge is more vulnerable to earthquake damage than the bridge standing in air. The larger blocking ratio has a significant impact on the added mass coefficient, which requires further comprehensive study. The generation mechanism of block effect is analyzed using numerical simulation software ANSYS Fluent. The results show that the recirculation zone with focus reduces the pressure on the back surface of the cylinder, resulting in the peak value of in-line force not occurring synchronously with the peak value of acceleration. The change in position and intensity of the recirculation zone with focus, as well as the change in water flow around the cylinder surface, are identified as the generation mechanism of the block effect, which has a 10% influence on the hydrodynamic force. The changing rule of the added mass coefficient with blocking ratio is discussed in detail, and a modification approach to the current added mass coefficient calculation method is suggested. Physical experiments are conducted to validate the modification approach, and the results show that it is accurate and can be used in further study and real practice.
Article
Engineering, Marine
Golnesa Karimi-Zindashti, Ozgur Kurc
Summary: This study examines the performance of an in-house code utilizing a deterministic vortex method on the rotation of circular and square cylinders. The results show that rotational motion reduces drag forces, suppresses fluctuating forces, and increases lift forces. The code accurately predicts vortex shedding suppression and identifies the emergence of near-field wakes in the flow over rotating square cylinders.
Article
Engineering, Marine
George Dafermos, George Zaraphonitis
Summary: The survivability of damaged ships is of great importance and the regulatory framework is constantly updated. The introduction of the probabilistic damage stability framework has rationalized the assessment procedure. Flooding simulation tools can be used to investigate the dynamic response of damaged ships.
Article
Engineering, Marine
Xuyue Chen, Xu Du, Chengkai Weng, Jin Yang, Deli Gao, Dongyu Su, Gan Wang
Summary: This paper proposes a real-time drilling parameters optimization method for offshore large-scale cluster extended reach drilling based on intelligent optimization algorithm and machine learning. By establishing a ROP model with long short-term memory neurons, and combining genetic algorithm, differential evolution algorithm, and particle swarm algorithm, the method achieves real-time optimization of drilling parameters and significantly improves the ROP.
Article
Engineering, Marine
Sung-Jae Kim, Chungkuk Jin, MooHyun Kim
Summary: This study investigates the dynamic behavior of a moored submerged floating tunnel (SFT) under tsunami-like waves through numerical simulations and sensitivity tests. The results show that design parameters significantly affect the dynamics of the SFT system and mooring tensions, with shorter-duration and higher-elevation tsunamis having a greater impact.
Article
Engineering, Marine
G. Clarindo, C. Guedes Soares
Summary: Environmental contours are constructed using the Inverse-First Order Reliability Method based on return periods. The paper proposes the use of the Burr distribution to model the marginal distribution of long-term significant wave heights. The newly implemented scheme results in different environmental contours compared to the reference approach.