scholarly journals Design and Experimental Evaluation of an Aerial Solution for Visual Inspection of Tunnel-like Infrastructures

2022 ◽  
Vol 14 (1) ◽  
pp. 195
Author(s):  
Bianca Bendris ◽  
Julián Cayero Becerra
Keyword(s):  
Visual Inspection ◽  
Surface Coverage ◽  
State Of The Art ◽  
Visual Examination ◽  
Railway Tunnel ◽  
Trajectory Length ◽  
Planning Algorithm ◽  
Inspection And Maintenance ◽  
Path Planning Algorithm

Current railway tunnel inspections rely on expert operators performing a visual examination of the entire infrastructure and manually annotating encountered defects. Automatizing the inspection and maintenance task of such critical and aging infrastructures has the potential to decrease the associated costs and risks. Contributing to this aim, the present work describes an aerial robotic solution designed to perform autonomous inspections of tunnel-like infrastructures. The proposed robotic system is equipped with visual and thermal sensors and uses an inspection-driven path planning algorithm to generate a path that maximizes the quality of the gathered data in terms of photogrammetry goals while optimizing the surface coverage and the total trajectory length. The performance of the planning algorithm is demonstrated in simulation against state-of-the-art methods and a wall-following inspection trajectory. Results of a real inspection test conducted in a railway tunnel are also presented, validating the whole system operation.

scholarly journals Automatic Boundary Extraction for Photovoltaic Plants Using the Deep Learning U-Net Model

2021 ◽  
Vol 11 (14) ◽  
pp. 6524
Author(s):  
Andrés Pérez-González ◽  
Álvaro Jaramillo-Duque ◽  
Juan Bernardo Cano-Quintero
Keyword(s):  
Research Work ◽  
Solar Photovoltaic ◽  
Boundary Extraction ◽  
Pv Systems ◽  
Periodic Maintenance ◽  
Planning Algorithm ◽  
Extraction Processes ◽  
Inspection And Maintenance ◽  
Photovoltaic Plants ◽  
Path Planning Algorithm

Nowadays, the world is in a transition towards renewable energy solar being one of the most promising sources used today. However, Solar Photovoltaic (PV) systems present great challenges for their proper performance such as dirt and environmental conditions that may reduce the output energy of the PV plants. For this reason, inspection and periodic maintenance are essential to extend useful life. The use of unmanned aerial vehicles (UAV) for inspection and maintenance of PV plants favor a timely diagnosis. UAV path planning algorithm over a PV facility is required to better perform this task. Therefore, it is necessary to explore how to extract the boundary of PV facilities with some techniques. This research work focuses on an automatic boundary extraction method of PV plants from imagery using a deep neural network model with a U-net structure. The results obtained were evaluated by comparing them with other reported works. Additionally, to achieve the boundary extraction processes, the standard metrics Intersection over Union (IoU) and the Dice Coefficient (DC) were considered to make a better conclusion among all methods. The experimental results evaluated on the Amir dataset show that the proposed approach can significantly improve the boundary and segmentation performance in the test stage up to 90.42% and 91.42% as calculated by IoU and DC metrics, respectively. Furthermore, the training period was faster. Consequently, it is envisaged that the proposed U-Net model will be an advantage in remote sensing image segmentation.

Non-Nominal Path Planning of Assembly Processes

2005 ◽  
Author(s):  
Johan S. Carlson ◽  
Rikard So¨derberg ◽  
Robert Bohlin ◽  
Lars Lindkvist ◽  
Tomas Hermansson
Keyword(s):  
Path Planning ◽  
Automotive Industry ◽  
Planning Process ◽  
State Of The Art ◽  
Cost Effective ◽  
Worst Case ◽  
Positioning Systems ◽  
Planning Algorithm ◽  
On Line ◽  
Path Planning Algorithm

One important aspect in the assembly process design is to assure that there exist a collision-free assembly path for each part and subassembly. In order to reduce the need of physical verification the automotive industry use digital mock-up tool with collision checking for this kind of geometrical assembly analysis. To manually verify assembly feasibility in a digital mock-up tool can be hard and time consuming. Therefore, the recent development of efficient and effective automatic path planning algorithm and tools are highly motivated. However, in real production, all equipment, parts and subassemblies are inflicted by geometrical variation, often resulting in conflicts and on-line adjustments of off-line generated assembly paths. To avoid problems with on-line adjustments, state-of-the-art tools for path-planning can handle tolerances by a general clearance for all geometry. This is a worst-case strategy, not taking account for how part and assembly variation propagates through the positioning systems of the assembly resulting in geometry areas of both high and low degree of variation. Since, this latter approach results in unnecessary design changes or in too tight tolerances we have developed a new algorithm and working procedure enabling and supporting a more cost effective non-nominal path planning process for assembly operations. The basic idea of the paper is to combine state of the art technology within variation simulation and automatic path planning. By integrating variation and tolerance simulation results into the path planning algorithm we can allow the assembly path going closer to areas of low variation, while avoiding areas of high variation. The benefits of the proposed approach are illustrated on an industrial case from the automotive industry.

scholarly journals Robot Navigation Based on Human Trajectory Prediction and Multiple Travel Modes

2018 ◽  
Vol 8 (11) ◽  
pp. 2205 ◽  
Author(s):  
Zhixian Chen ◽  
Chao Song ◽  
Yuanyuan Yang ◽  
Baoliang Zhao ◽  
Ying Hu ◽  
...  
Keyword(s):  
State Of The Art ◽  
Robot Navigation ◽  
Dynamic Environments ◽  
Mobile Robot Navigation ◽  
Challenging Problem ◽  
Trajectory Prediction ◽  
Planning Algorithm ◽  
Public Datasets ◽  
Path Planning Algorithm ◽  
Navigation Strategies

For a mobile robot, navigation skills that are safe, efficient, and socially compliant in crowded, dynamic environments are essential. This is a particularly challenging problem as it requires the robot to accurately predict pedestrians’ movements, analyse developing traffic situations, and plan its own path or trajectory accordingly. Previous approaches still exhibit low accuracy for pedestrian trajectory prediction, and they are prone to generate infeasible trajectories under complex crowded conditions. In this paper, we develop an improved socially conscious model to learn and predict a pedestrian’s future trajectory. To generate more efficient and safer trajectories in a changing crowed space, an online path planning algorithm considering pedestrians’ predicted movements and the feasibility of the candidate trajectories is proposed. Then, multiple traffic states are defined to guide the robot finding the optimal navigation strategies under changing traffic situations in a crowded area. We have demonstrated the performance of our approach outperforms state-of-the-art approaches with public datasets, in low-density and simulated medium-density crowded scenarios.

Non-Destructive Evaluation of Composite Pipes and Tanks: Development of Inspection Strategies

2004 ◽  
Author(s):  
Harald Thon ◽  
Bjo̸rn Melve
Keyword(s):  
Ultrasonic Testing ◽  
Visual Inspection ◽  
Practical Experience ◽  
Radiographic Examination ◽  
Visual Examination ◽  
The Public ◽  
Research Programmes ◽  
Composite Pipes ◽  
Non Destructive

The document describes practical experience gained from several research programmes and the use of GRP products both offshore and onshore. An OLF document was compiled during 1990’s and the visual inspection part of the document was used in the ISO 14692, part 4 [12] with requirements and defect criteria. Additional parts on ultrasonic and radiographic examination have been included in the Norwegian standard Norsok M-622 [1]. However, we would like to publish the full version of this document and make it available in the public domain. Some of the methods described is well developed, while others still would require research efforts to make the techniques practical useful. For practical use, the visual examination with failure description, acceptance criteria and corrective actions are most developed. Further, radiography has been useful in several projects in assessing the quality of adhesive joints. The ultrasonic testing is expected to become better to use as the equipments and methods are developing. Every reasonable effort has been made to ensure that this publication is based on the author’s best knowledge. However, no responsibility of any kind for any injury, delay, loss or damage can be accepted for parties using information given herein.

scholarly journals An Efficient and Adaptable Path Planning Algorithm for Automated Fiber Placement Based on Meshing and Multi Guidelines

Materials ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4209
Author(s):  
Hong Xiao ◽  
Wei Han ◽  
Wenbin Tang ◽  
Yugang Duan
Keyword(s):  
Path Planning ◽  
Accuracy Analysis ◽  
Fiber Placement ◽  
Surface Meshing ◽  
Automated Fiber Placement ◽  
Planning Algorithm ◽  
Selection For ◽  
Update Strategy ◽  
Path Planning Algorithm

Path planning algorithms for automated fiber placement are used to determine the directions of the fiber paths and the start and end positions on the mold surfaces. The quality of the fiber paths determines largely the efficiency and quality of the automated fiber placement process. The presented work investigated an efficient path planning algorithm based on surface meshing. In addition, an update method of the datum direction vector via a guide-line update strategy was proposed to make the path planning algorithm applicable for complex surfaces. Finally, accuracy analysis was performed on the proposed algorithm and it can be adopted as the reference for the triangulation parameter selection for the path planning algorithm.

scholarly journals Voronoi-Visibility Roadmap-based Path Planning Algorithm for Unmanned Surface Vehicles

2019 ◽  
Vol 72 (04) ◽  
pp. 850-874 ◽  
Author(s):  
Hanlin Niu ◽  
Al Savvaris ◽  
Antonios Tsourdos ◽  
Ze Ji
Keyword(s):  
Path Planning ◽  
Voronoi Diagram ◽  
Shortest Path ◽  
Performance Comparison ◽  
Computational Time ◽  
Planning Problem ◽  
Planning Algorithm ◽  
Quantitative Results ◽  
Path Planning Algorithm

In this paper, a novel Voronoi-Visibility (VV) path planning algorithm, which integrates the merits of a Voronoi diagram and a Visibility graph, is proposed for solving the Unmanned Surface Vehicle (USV) path planning problem. The VM (Voronoi shortest path refined by Minimising the number of waypoints) algorithm was applied for performance comparison. The VV and VM algorithms were compared in ten Singapore Strait missions and five Croatian missions. To test the computational time, a high-resolution, large spatial dataset was used. It was demonstrated that the proposed algorithm not only improved the quality of the Voronoi shortest path but also maintained the computational efficiency of the Voronoi diagram in dealing with different geographical scenarios, while also keeping the USV at a configurable clearance distance c from coastlines. Quantitative results were generated by comparing the Voronoi, VM and VV algorithms in 2,000 randomly generated missions using the Singapore dataset.

Data science in economics: comprehensive review of advanced machine learning and deep learning methods

2020 ◽  
Author(s):  
Saeed Nosratabadi ◽  
Amir Mosavi ◽  
Puhong Duan ◽  
Pedram Ghamisi ◽  
Ferdinand Filip ◽  
...  
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Data Science ◽  
State Of The Art ◽  
Science Methods ◽  
Learning Models ◽  
Diverse Range ◽  
Hybrid Machine ◽  
Economics Research

This paper provides a state-of-the-art investigation of advances in data science in emerging economic applications. The analysis was performed on novel data science methods in four individual classes of deep learning models, hybrid deep learning models, hybrid machine learning, and ensemble models. Application domains include a wide and diverse range of economics research from the stock market, marketing, and e-commerce to corporate banking and cryptocurrency. Prisma method, a systematic literature review methodology, was used to ensure the quality of the survey. The findings reveal that the trends follow the advancement of hybrid models, which, based on the accuracy metric, outperform other learning algorithms. It is further expected that the trends will converge toward the advancements of sophisticated hybrid deep learning models.

Counterfeit Parts Recognition and Detection for Failure Analysts

2010 ◽  
Author(s):  
Katherine V. Whittington
Keyword(s):  
Thermal Cycle ◽  
Visual Inspection ◽  
Acoustic Microscopy ◽  
Scanning Acoustic Microscopy ◽  
3D Measurement ◽  
X Ray ◽  
Wide Range ◽  
Electronic Parts ◽  
Testing Awareness

Abstract The electronics supply chain is being increasingly infiltrated by non-authentic, counterfeit electronic parts, whose use poses a great risk to the integrity and quality of critical hardware. There is a wide range of counterfeit parts such as leads and body molds. The failure analyst has many tools that can be used to investigate counterfeit parts. The key is to follow an investigative path that makes sense for each scenario. External visual inspection is called for whenever the source of supply is questionable. Other methods include use of solvents, 3D measurement, X-ray fluorescence, C-mode scanning acoustic microscopy, thermal cycle testing, burn-in technique, and electrical testing. Awareness, vigilance, and effective investigations are the best defense against the threat of counterfeit parts.

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