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Article
Publication date: 29 February 2024

Heng Liu, Yonghua Lu, Haibo Yang, Lihua Zhou and Qiang Feng

In the context of fixed-wing aircraft wing assembly, there is a need for a rapid and precise measurement technique to determine the center distance between two double-hole…

Abstract

Purpose

In the context of fixed-wing aircraft wing assembly, there is a need for a rapid and precise measurement technique to determine the center distance between two double-hole components. This paper aims to propose an optical-based spatial point distance measurement technique using the spatial triangulation method. The purpose of this paper is to design a specialized measurement system, specifically a spherically mounted retroreflector nest (SMR nest), equipped with two laser displacement sensors and a rotary encoder as the core to achieve accurate distance measurements between the double holes.

Design/methodology/approach

To develop an efficient and accurate measurement system, the paper uses a combination of laser displacement sensors and a rotary encoder within the SMR nest. The system is designed, implemented and tested to meet the requirements of precise distance measurement. Software and hardware components have been developed and integrated for validation.

Findings

The optical-based distance measurement system achieves high precision at 0.04 mm and repeatability at 0.02 mm within a range of 412.084 mm to 1,590.591 mm. These results validate its suitability for efficient assembly processes, eliminating repetitive errors in aircraft wing assembly.

Originality/value

This paper proposes an optical-based spatial point distance measurement technique, as well as a unique design of a SMR nest and the introduction of two novel calibration techniques, all of which are validated by the developed software and hardware platform.

Details

Sensor Review, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0260-2288

Keywords

Article
Publication date: 8 September 2022

Johnny Kwok Wai Wong, Mojtaba Maghrebi, Alireza Ahmadian Fard Fini, Mohammad Amin Alizadeh Golestani, Mahdi Ahmadnia and Michael Er

Images taken from construction site interiors often suffer from low illumination and poor natural colors, which restrict their application for high-level site management purposes…

Abstract

Purpose

Images taken from construction site interiors often suffer from low illumination and poor natural colors, which restrict their application for high-level site management purposes. The state-of-the-art low-light image enhancement method provides promising image enhancement results. However, they generally require a longer execution time to complete the enhancement. This study aims to develop a refined image enhancement approach to improve execution efficiency and performance accuracy.

Design/methodology/approach

To develop the refined illumination enhancement algorithm named enhanced illumination quality (EIQ), a quadratic expression was first added to the initial illumination map. Subsequently, an adjusted weight matrix was added to improve the smoothness of the illumination map. A coordinated descent optimization algorithm was then applied to minimize the processing time. Gamma correction was also applied to further enhance the illumination map. Finally, a frame comparing and averaging method was used to identify interior site progress.

Findings

The proposed refined approach took around 4.36–4.52 s to achieve the expected results while outperforming the current low-light image enhancement method. EIQ demonstrated a lower lightness-order error and provided higher object resolution in enhanced images. EIQ also has a higher structural similarity index and peak-signal-to-noise ratio, which indicated better image reconstruction performance.

Originality/value

The proposed approach provides an alternative to shorten the execution time, improve equalization of the illumination map and provide a better image reconstruction. The approach could be applied to low-light video enhancement tasks and other dark or poor jobsite images for object detection processes.

Details

Construction Innovation , vol. 24 no. 2
Type: Research Article
ISSN: 1471-4175

Keywords

Article
Publication date: 29 March 2024

Pingyang Zheng, Shaohua Han, Dingqi Xue, Ling Fu and Bifeng Jiang

Because of the advantages of high deposition efficiency and low manufacturing cost compared with other additive technologies, robotic wire arc additive manufacturing (WAAM…

Abstract

Purpose

Because of the advantages of high deposition efficiency and low manufacturing cost compared with other additive technologies, robotic wire arc additive manufacturing (WAAM) technology has been widely applied for fabricating medium- to large-scale metallic components. The additive manufacturing (AM) method is a relatively complex process, which involves the workpiece modeling, conversion of the model file, slicing, path planning and so on. Then the structure is formed by the accumulated weld bead. However, the poor forming accuracy of WAAM usually leads to severe dimensional deviation between the as-built and the predesigned structures. This paper aims to propose a visual sensing technology and deep learning–assisted WAAM method for fabricating metallic structure, to simplify the complex WAAM process and improve the forming accuracy.

Design/methodology/approach

Instead of slicing of the workpiece modeling and generating all the welding torch paths in advance of the fabricating process, this method is carried out by adding the feature point regression branch into the Yolov5 algorithm, to detect the feature point from the images of the as-built structure. The coordinates of the feature points of each deposition layer can be calculated automatically. Then the welding torch trajectory for the next deposition layer is generated based on the position of feature point.

Findings

The mean average precision score of modified YOLOv5 detector is 99.5%. Two types of overhanging structures have been fabricated by the proposed method. The center contour error between the actual and theoretical is 0.56 and 0.27 mm in width direction, and 0.43 and 0.23 mm in height direction, respectively.

Originality/value

The fabrication of circular overhanging structures without using the complicate slicing strategy, turning table or other extra support verified the possibility of the robotic WAAM system with deep learning technology.

Details

Rapid Prototyping Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1355-2546

Keywords

Open Access
Article
Publication date: 20 March 2024

Guijian Xiao, Tangming Zhang, Yi He, Zihan Zheng and Jingzhe Wang

The purpose of this review is to comprehensively consider the material properties and processing of additive titanium alloy and provide a new perspective for the robotic grinding…

Abstract

Purpose

The purpose of this review is to comprehensively consider the material properties and processing of additive titanium alloy and provide a new perspective for the robotic grinding and polishing of additive titanium alloy blades to ensure the surface integrity and machining accuracy of the blades.

Design/methodology/approach

At present, robot grinding and polishing are mainstream processing methods in blade automatic processing. This review systematically summarizes the processing characteristics and processing methods of additive manufacturing (AM) titanium alloy blades. On the one hand, the unique manufacturing process and thermal effect of AM have created the unique processing characteristics of additive titanium alloy blades. On the other hand, the robot grinding and polishing process needs to incorporate the material removal model into the traditional processing flow according to the processing characteristics of the additive titanium alloy.

Findings

Robot belt grinding can solve the processing problem of additive titanium alloy blades. The complex surface of the blade generates a robot grinding trajectory through trajectory planning. The trajectory planning of the robot profoundly affects the machining accuracy and surface quality of the blade. Subsequent research is needed to solve the problems of high machining accuracy of blade profiles, complex surface material removal models and uneven distribution of blade machining allowance. In the process parameters of the robot, the grinding parameters, trajectory planning and error compensation affect the surface quality of the blade through the material removal method, grinding force and grinding temperature. The machining accuracy of the blade surface is affected by robot vibration and stiffness.

Originality/value

This review systematically summarizes the processing characteristics and processing methods of aviation titanium alloy blades manufactured by AM. Combined with the material properties of additive titanium alloy, it provides a new idea for robot grinding and polishing of aviation titanium alloy blades manufactured by AM.

Details

Journal of Intelligent Manufacturing and Special Equipment, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2633-6596

Keywords

Article
Publication date: 28 September 2023

Vicente-Segundo Ruiz-Jacinto, Karina-Silvana Gutiérrez-Valverde, Abrahan-Pablo Aslla-Quispe, José-Manuel Burga-Falla, Aldo Alarcón-Sucasaca and Yersi-Luis Huamán-Romaní

This paper aims to present the novel stacked machine learning approach (SMLA) to estimate low-cycle fatigue (LCF) life of SAC305 solder across structural parts. Using the finite…

Abstract

Purpose

This paper aims to present the novel stacked machine learning approach (SMLA) to estimate low-cycle fatigue (LCF) life of SAC305 solder across structural parts. Using the finite element simulation (FEM) and continuous damage mechanics (CDM) model, a fatigue life database is built. The stacked machine learning (ML) model's iterative optimization during training enables precise fatigue predictions (2.41% root mean square error [RMSE], R2 = 0.975) for diverse structural components. Outliers are found in regression analysis, indicating potential overestimation for thickness transition specimens with extended lifetimes and underestimation for open-hole specimens. Correlations between fatigue life, stress factors, nominal stress and temperature are unveiled, enriching comprehension of LCF, thus enhancing solder behavior predictions.

Design/methodology/approach

This paper introduces stacked ML as a novel approach for estimating LCF life of SAC305 solder in various structural parts. It builds a fatigue life database using FEM and CDM model. The stacked ML model iteratively optimizes its structure, yielding accurate fatigue predictions (2.41% RMSE, R2 = 0.975). Outliers are observed: overestimation for thickness transition specimens and underestimation for open-hole ones. Correlations between fatigue life, stress factors, nominal stress and temperature enhance predictions, deepening understanding of solder behavior.

Findings

The findings of this paper highlight the successful application of the SMLA in accurately estimating the LCF life of SAC305 solder across diverse structural components. The stacked ML model, trained iteratively, demonstrates its effectiveness by producing precise fatigue lifetime predictions with a RMSE of 2.41% and an “R2” value of 0.975. The study also identifies distinct outlier behaviors associated with different structural parts: overestimations for thickness transition specimens with extended fatigue lifetimes and underestimations for open-hole specimens. The research further establishes correlations between fatigue life, stress concentration factors, nominal stress and temperature, enriching the understanding of solder behavior prediction.

Originality/value

The authors confirm the originality of this paper.

Details

Soldering & Surface Mount Technology, vol. 36 no. 2
Type: Research Article
ISSN: 0954-0911

Keywords

Article
Publication date: 4 April 2023

Rodoula H. Tsiotsou, Leonidas Hatzithomas and Martin Wetzels

This research aims to investigate the role of consumer resistance (CR), display advertising context, appeal and type of exposure for the successful launch of a brand into a new…

Abstract

Purpose

This research aims to investigate the role of consumer resistance (CR), display advertising context, appeal and type of exposure for the successful launch of a brand into a new market.

Design/methodology/approach

To accomplish this goal, two experiments manipulated the digital context of advertising (congruent vs. incongruent), the advertising appeal (emotional vs. informative) and the type of exposure (incidental vs. forced) using an energy drink brand. In Study 1, data were collected from 80 participants using eye-tracking and an online questionnaire. In Study 2, a total of 138 participants visited a website with the targeted display ad and responded to an online questionnaire.

Findings

Overall, the results of two studies show that the relationship between CR and display advertising effectiveness is moderated by the advertising context and advertising appeal in incidental exposure, whereas only the advertising context moderates this relationship in forced exposure when launching a brand into a new market. Moreover, the study illustrates the importance of collecting subjective and objective data in advancing the knowledge and understanding of interactive marketing communications such as display advertising.

Originality/value

The study is a novel attempt within the well-established realm of interactive marketing and, specifically, of digital advertising to examine the persuasive effects of display ad features such as the context, appeal and exposure on display ad effectiveness, considering consumers' predispositions such as resistance to change.

Details

Journal of Research in Interactive Marketing, vol. 18 no. 2
Type: Research Article
ISSN: 2040-7122

Keywords

Open Access
Article
Publication date: 27 April 2022

Elina Ilén, Farid Elsehrawy, Elina Palovuori and Janne Halme

Solar cells could make textile-based wearable systems energy independent without the need for battery replacement or recharging; however, their laundry resistance, which is…

2560

Abstract

Purpose

Solar cells could make textile-based wearable systems energy independent without the need for battery replacement or recharging; however, their laundry resistance, which is prerequisite for the product acceptance of e-textiles, has been rarely examined. This paper aims to report a systematic study of the laundry durability of solar cells embedded in textiles.

Design/methodology/approach

This research included small commercial monocrystalline silicon solar cells which were encapsulated with functional synthetic textile materials using an industrially relevant textile lamination process and found them to reliably endure laundry washing (ISO 6330:2012). The energy harvesting capability of eight textile laminated solar cells was measured after 10–50 cycles of laundry at 40 °C and compared with light transmittance spectroscopy and visual inspection.

Findings

Five of the eight textile solar cell samples fully maintained their efficiency over the 50 laundry cycles, whereas the other three showed a 20%–27% decrease. The cells did not cause any visual damage to the fabric. The result indicates that the textile encapsulated solar cell module provides sufficient protection for the solar cells against water, washing agents and mechanical stress to endure repetitive domestic laundry.

Research limitations/implications

This study used rigid monocrystalline silicon solar cells. Flexible amorphous silicon cells were excluded because of low durability in preliminary tests. Other types of solar cells were not tested.

Originality/value

A review of literature reveals the tendency of researchers to avoid standardized textile washing resistance testing. This study removes the most critical obstacle of textile integrated solar energy harvesting, the washing resistance.

Details

Research Journal of Textile and Apparel, vol. 28 no. 1
Type: Research Article
ISSN: 1560-6074

Keywords

Article
Publication date: 2 February 2024

Bushi Chen, Xunyu Zhong, Han Xie, Pengfei Peng, Huosheng Hu, Xungao Zhong and Qiang Liu

Autonomous mobile robots (AMRs) play a crucial role in industrial and service fields. The paper aims to build a LiDAR-based simultaneous localization and mapping (SLAM) system…

Abstract

Purpose

Autonomous mobile robots (AMRs) play a crucial role in industrial and service fields. The paper aims to build a LiDAR-based simultaneous localization and mapping (SLAM) system used by AMRs to overcome challenges in dynamic and changing environments.

Design/methodology/approach

This research introduces SLAM-RAMU, a lifelong SLAM system that addresses these challenges by providing precise and consistent relocalization and autonomous map updating (RAMU). During the mapping process, local odometry is obtained using iterative error state Kalman filtering, while back-end loop detection and global pose graph optimization are used for accurate trajectory correction. In addition, a fast point cloud segmentation module is incorporated to robustly distinguish between floor, walls and roof in the environment. The segmented point clouds are then used to generate a 2.5D grid map, with particular emphasis on floor detection to filter the prior map and eliminate dynamic artifacts. In the positioning process, an initial pose alignment method is designed, which combines 2D branch-and-bound search with 3D iterative closest point registration. This method ensures high accuracy even in scenes with similar characteristics. Subsequently, scan-to-map registration is performed using the segmented point cloud on the prior map. The system also includes a map updating module that takes into account historical point cloud segmentation results. It selectively incorporates or excludes new point cloud data to ensure consistent reflection of the real environment in the map.

Findings

The performance of the SLAM-RAMU system was evaluated in real-world environments and compared against state-of-the-art (SOTA) methods. The results demonstrate that SLAM-RAMU achieves higher mapping quality and relocalization accuracy and exhibits robustness against dynamic obstacles and environmental changes.

Originality/value

Compared to other SOTA methods in simulation and real environments, SLAM-RAMU showed higher mapping quality, faster initial aligning speed and higher repeated localization accuracy.

Details

Industrial Robot: the international journal of robotics research and application, vol. 51 no. 2
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 20 March 2024

Ziming Zhou, Fengnian Zhao and David Hung

Higher energy conversion efficiency of internal combustion engine can be achieved with optimal control of unsteady in-cylinder flow fields inside a direct-injection (DI) engine…

Abstract

Purpose

Higher energy conversion efficiency of internal combustion engine can be achieved with optimal control of unsteady in-cylinder flow fields inside a direct-injection (DI) engine. However, it remains a daunting task to predict the nonlinear and transient in-cylinder flow motion because they are highly complex which change both in space and time. Recently, machine learning methods have demonstrated great promises to infer relatively simple temporal flow field development. This paper aims to feature a physics-guided machine learning approach to realize high accuracy and generalization prediction for complex swirl-induced flow field motions.

Design/methodology/approach

To achieve high-fidelity time-series prediction of unsteady engine flow fields, this work features an automated machine learning framework with the following objectives: (1) The spatiotemporal physical constraint of the flow field structure is transferred to machine learning structure. (2) The ML inputs and targets are efficiently designed that ensure high model convergence with limited sets of experiments. (3) The prediction results are optimized by ensemble learning mechanism within the automated machine learning framework.

Findings

The proposed data-driven framework is proven effective in different time periods and different extent of unsteadiness of the flow dynamics, and the predicted flow fields are highly similar to the target field under various complex flow patterns. Among the described framework designs, the utilization of spatial flow field structure is the featured improvement to the time-series flow field prediction process.

Originality/value

The proposed flow field prediction framework could be generalized to different crank angle periods, cycles and swirl ratio conditions, which could greatly promote real-time flow control and reduce experiments on in-cylinder flow field measurement and diagnostics.

Details

International Journal of Numerical Methods for Heat & Fluid Flow, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0961-5539

Keywords

Article
Publication date: 2 January 2024

Xiangdi Yue, Yihuan Zhang, Jiawei Chen, Junxin Chen, Xuanyi Zhou and Miaolei He

In recent decades, the field of robotic mapping has witnessed widespread research and development in light detection and ranging (LiDAR)-based simultaneous localization and…

Abstract

Purpose

In recent decades, the field of robotic mapping has witnessed widespread research and development in light detection and ranging (LiDAR)-based simultaneous localization and mapping (SLAM) techniques. This paper aims to provide a significant reference for researchers and engineers in robotic mapping.

Design/methodology/approach

This paper focused on the research state of LiDAR-based SLAM for robotic mapping as well as a literature survey from the perspective of various LiDAR types and configurations.

Findings

This paper conducted a comprehensive literature review of the LiDAR-based SLAM system based on three distinct LiDAR forms and configurations. The authors concluded that multi-robot collaborative mapping and multi-source fusion SLAM systems based on 3D LiDAR with deep learning will be new trends in the future.

Originality/value

To the best of the authors’ knowledge, this is the first thorough survey of robotic mapping from the perspective of various LiDAR types and configurations. It can serve as a theoretical and practical guide for the advancement of academic and industrial robot mapping.

Details

Industrial Robot: the international journal of robotics research and application, vol. 51 no. 2
Type: Research Article
ISSN: 0143-991X

Keywords

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