Application of Sensing Measurement in Machining
A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Machines Testing and Maintenance".
Deadline for manuscript submissions: 30 November 2024 | Viewed by 1017
Special Issue Editors
Interests: monitoring and control of machines; mechatronic systems
Special Issues, Collections and Topics in MDPI journals
Interests: system monitoring; sensor technology; CNC machining; thermophysics of grinding; contactless measurement
Special Issue Information
Dear Colleagues,
The question of whether it is possible to make machines capable of sensation persists. Many researchers have been trying to achieve this for years, but machining processes are complex and therefore it is not easy to engineer “feeling machines”. Sensors are the primary equipment used by modern enterprises to diagnose the health of systems and the state a process is in. The expectation is that sensors should connect human and computer-controlled machine tools. Sensor features make it possible to capture changes in mechanical systems and provide the necessary information for decision making in both traditional and unmanned technologies. Of course, every industry has a desire to develop and use efficient systems that can prevent downtime and extend tool life in machining applications. In this way, it is possible to increase process productivity and ensure efficient resource use.
Although signal acquisition is an important part of sensor application, signal analysis and processing are equally important to the goals of better recognizing the situation during machining. Signal processing extracts and selects useful features to better understand the relationship between the sensor signal and process behavior.
In this case, areas of study are monitoring technological system state parameters and process output parameters based on sensing measurements; tool condition monitoring; tool health monitoring; determination of remaining useful lifetime; condition-based maintenance system; prognostic health management; ‘smart’ tools; sensor fusion in machining; and methods for processing initial sensor signals.
This Special Issue seeks original research papers focusing on advances in all facets of online/offline machining diagnostics and monitoring based on sensors measurements.
We welcome papers that offer new research approaches, methodologies, sights and scientific directions in the abovementioned topics. We hope that this Special Issue will be useful and informative to seasoned scientists, inexperienced scientist and practitioners.
Prof. Dr. Ján Piteľ
Guest Editor
Dr. Natalia Lishchenko
Guest Editor Assistant
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
- advanced machining
- sensor monitoring
- sensors
- process monitoring
- signal processing
- sensing measurement
- diagnostics
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