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Machines
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Machine Science and Research in HUST: Celebrating the 70th Anniversary...
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Machine Science and Research in HUST: Celebrating the 70th Anniversary of Huazhong University of Science and Technology

A special issue of Machines (ISSN 2075-1702).

Deadline for manuscript submissions: closed (30 September 2023) | Viewed by 2877

Special Issue Editor

Prof. Dr. Qibai Huang

E-Mail Website
Guest Editor
School of Mechanical Science & Engineering, Huazhong University of Science and Technology, Wuhan, China
Interests: Mechanical system dynamics; vibration and noise control; intelligent materials and structures; vehicle engineering; mechanical design; special vehicle and intelligent equipment

Special Issue Information

Dear Colleagues,

To celebrate the 70th anniversary of the School of Mechanical Science and Engineering of Huazhong University of Science and Technology, we plan to launch this anniversary Special Issue on the latest status of intelligent design and manufacturing of electromechanical systems, aiming at intelligent design, and novel findings on the dynamics of electromechanical systems, vibration and noise control, fault diagnosis, intelligent manufacturing equipment/theories, and robotic technology.

Therefore, this Special Issue will commit to bringing together original papers, which reveal the state-of-the-art in the field of intelligent design and manufacturing and to promote the development of intelligent design, manufacturing, and control. Papers containing theoretical innovation and practical experimental results are particularly encouraged.

Prof. Dr. Qibai Huang
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Machines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • intelligent design
  • intelligent materials and structures
  • topological optimization
  • dynamics of machinery
  • vibration and noise control
  • machine diagnosis and prediction
  • intelligent manufacturing
  • advanced control theory
  • advanced manufacturing equipment
  • mechanical systems
  • robotics
  • systems and control engineering

Published Papers (2 papers)

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Research

19 pages, 8906 KiB  
Article
Numerical Investigation of Background Noise in a Circulating Water Tunnel
by Zhangkai Huang, Meixia Chen, Ting Wang, Huachang Cui and Wenkai Dong
Machines 2023, 11(8), 839; https://doi.org/10.3390/machines11080839 - 18 Aug 2023
Viewed by 789
Abstract
The presence of excessive background noise in hydrodynamic noise experiments conducted in circulating water tunnels can significantly impact the accuracy and reliability of experimental test results. To address this issue, it is crucial to evaluate and optimize the background noise during the design [...] Read more.
The presence of excessive background noise in hydrodynamic noise experiments conducted in circulating water tunnels can significantly impact the accuracy and reliability of experimental test results. To address this issue, it is crucial to evaluate and optimize the background noise during the design stage. In this research, acoustic field model and fluid–solid coupling numerical calculation model of circulating water tunnels are established. Utilizing the finite element method, we analyze the flow noise and flow-excited noise resulting from wall pressure pulses in the circulating water tunnel. Furthermore, we conduct a noise contribution analysis and explore strategies for structural vibration noise control. The results demonstrate that both flow noise and flow-excited noise decrease with increasing frequency, with flow-excited noise being the primary component of the tunnel’s background noise. The presence of resonant peaks significantly contributes to the elevated flow-excited noise levels. Moreover, enhancing structural stiffness and damping proves less effective in suppressing low-frequency peaks. Additionally, employing sound measurement pods suspended from the side of the test section for noise measurement exhibits a high error rate at low frequencies. This research provides insights into optimizing background noise in water tunnels, thereby informing future enhancements in tunnel design. Full article
(This article belongs to the Special Issue Machine Science and Research in HUST: Celebrating the 70th Anniversary of Huazhong University of Science and Technology)
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20 pages, 8966 KiB  
Article
Line-Structured Light Fillet Weld Positioning Method to Overcome Weld Instability Due to High Specular Reflection
by Jun Wang, Xuwei Zhang, Jiaen Liu, Yuanyuan Shi and Yizhe Huang
Machines 2023, 11(1), 38; https://doi.org/10.3390/machines11010038 - 29 Dec 2022
Cited by 1 | Viewed by 1741
Abstract
Fillet welds of highly reflective materials are common in industrial production. It is a great challenge to accurately locate the fillet welds of highly reflective materials. Therefore, this paper proposes a fillet weld identification and location method that can overcome the negative effects [...] Read more.
Fillet welds of highly reflective materials are common in industrial production. It is a great challenge to accurately locate the fillet welds of highly reflective materials. Therefore, this paper proposes a fillet weld identification and location method that can overcome the negative effects of high reflectivity. The proposed method is based on improving the semantic segmentation performance of the DeeplabV3+ network for structural light and reflective noise, and, with MobilnetV2, replaces the main trunk network to improve the detection efficiency of the model. To solve the problem of the irregular and discontinuous shapes of the structural light skeleton extracted by traditional methods, an improved closing operation using dilation in a combined Zhang-suen algorithm was proposed for structural light skeleton extraction. Then, a three-dimensional reconstruction as a mathematical model of the system was established to obtain the coordinates of the weld feature points and the welding-torch angle. Finally, many experiments on highly reflective stainless steel fillet welds were carried out. The experimental results show that the average detection errors of the system in the Y-axis and Z-axis are 0.3347 mm and 0.3135 mm, respectively, and the average detection error of the welding torch angle is 0.1836° in the test of a stainless steel irregular fillet weld. The method is robust, universal, and accurate for highly reflective irregular fillet welds. Full article
(This article belongs to the Special Issue Machine Science and Research in HUST: Celebrating the 70th Anniversary of Huazhong University of Science and Technology)
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