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Applied Sciences
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Vibration Control and Monitoring of Machine Tools
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Vibration Control and Monitoring of Machine Tools

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Acoustics and Vibrations".

Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 6963

Special Issue Editor

Dr. Yutaka Nakano

E-Mail Website
Guest Editor
School of Engineering, Tokyo Institute of Technology, 2-12-1, O-okayama, Meguro-ku, Tokyo 152-8552, Japan
Interests: self-excited vibration; friction vibration; chatter vibration; brake squeal; dynamic absorber
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, although there is a need for further development of high-precision and high-efficiency machining technology to achieve thin-walled or complex shape machine parts, the vibration generated during the machining process has become a bottleneck in achieving them. For example, chatter vibration reduces machining quality and significantly restricts productivity. Therefore, the industry continues to seek chatter suppression or avoidance technology. In the last decade, there have been many advances regarding vibration control and monitoring technologies for chatter vibration. The main topic of the present Special Issue is to provide recent achievements in vibration control techniques and vibration monitoring technologies during the machining process.

Your contribution is welcome and much appreciated as an author or a reviewer.

Dr. Yutaka Nakano
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. Applied Sciences is an international peer-reviewed open access semimonthly 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

  • machine tool vibration
  • chatter vibration
  • vibration control
  • damping
  • vibration monitoring
  • measurement and signal processing

Published Papers (2 papers)

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Research

23 pages, 47007 KiB  
Article
Experimental Study on Application of Tuned Mass Dampers for Chatter in Turning of a Thin-Walled Cylinder
by Yutaka Nakano, Tsubasa Kishi and Hiroki Takahara
Appl. Sci. 2021, 11(24), 12070; https://doi.org/10.3390/app112412070 - 17 Dec 2021
Cited by 11 | Viewed by 2438
Abstract
Chatter is more likely to occur during the turning process of a thin-walled cylindrical workpiece owing to the low rigidity of such workpieces. Chatter causes intensive vibration, deterioration of the surface finish accuracy, tool damage, and tool wear. Tuned mass dampers (TMD) are [...] Read more.
Chatter is more likely to occur during the turning process of a thin-walled cylindrical workpiece owing to the low rigidity of such workpieces. Chatter causes intensive vibration, deterioration of the surface finish accuracy, tool damage, and tool wear. Tuned mass dampers (TMD) are usually applied as a passive damping technique to induce a large damping effect using a small mass. This study experimentally investigated the effect of the mounting arrangement and tuning parameters of the TMDs on the production of chatter during the turning process of a thin-walled cylinder, wherein multiple TMDs with extremely small mass ratios were attached to the rotating workpiece. The results of the cutting tests performed by varying the circumferential and axial mounting positions of the TMDs exhibited different characteristics of the chatter suppression effect. Conclusively, the TMDs could suppress the chatter generated by the vibration mode with circumferential nodes if they were mounted on the workpiece to avoid the coincidence of the circumferential arrangement with the pitch of the vibration nodes, regardless of the extremely small mass of the TMDs. Full article
(This article belongs to the Special Issue Vibration Control and Monitoring of Machine Tools)
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23 pages, 7563 KiB  
Article
RUL Prediction of Rolling Bearings Based on a DCAE and CNN
by Chenyang Wang, Wanlu Jiang, Xukang Yang and Shuqing Zhang
Appl. Sci. 2021, 11(23), 11516; https://doi.org/10.3390/app112311516 - 5 Dec 2021
Cited by 32 | Viewed by 3264
Abstract
Predicting the remaining useful life (RUL) of mechanical equipment can improve production efficiency while effectively reducing the life cycle cost and failure rate. This paper proposes a method for predicting the remaining service life of equipment through a combination of a deep convolutional [...] Read more.
Predicting the remaining useful life (RUL) of mechanical equipment can improve production efficiency while effectively reducing the life cycle cost and failure rate. This paper proposes a method for predicting the remaining service life of equipment through a combination of a deep convolutional autoencoder (DCAE) and a convolutional neural network (CNN). For rolling bearings, a health indicator (HI) could be built by combining DCAE and self-organizing map (SOM) networks, performing more advanced characterization against the original vibration data and modeling the degradation state of the rolling bearings. The HI serves as the label of the original vibration data, and the original data with such label is input into the prediction model of the RUL based on a one-dimensional convolutional neural network (1D-CNN). The model was trained for predicting the RUL of a rolling bearing. The bearing degradation dataset was evaluated to verify the method’s effectiveness. The results demonstrate that the constructed HI can characterize the bearing degradation state effectively and that the method of predicting the RUL can accurately predict the bearing degradation trend. Full article
(This article belongs to the Special Issue Vibration Control and Monitoring of Machine Tools)
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