APPLICATION OF ACOUSTIC ANALYSIS IN CONTROL SYSTEMS OF ROBOTIC MACHINE TOOLS
DOI:
https://doi.org/10.15588/1607-3274-2018-2-6Keywords:
acoustic diagnostics, robotic machine tool, neural networks, reference model.Abstract
Relevance. The problem of controlling complex technological machines such as machines with mechanisms based on kinematics withparallel structure is given consideration in the article in order to improve accuracy of positioning of actuators, to ensure their dynamic
adjustment and optimization of trajectories of displacement of operating elements of the equipment (cutting tools, assembling or controlling
instruments). The object of the study is the model of the operating area of a mobile robotic machine tool.
Objective. The goal of the work is to create a concept for controlling a mobile robotic machine tool applying acoustic control on the
basis of a reference model based on deep neural networks.
Method. A method of identification and control of a mobile robotic machine tool using spectral description of absorption of acoustic
wave with further processing of obtained information is offered. This method allows determining accuracy of positioning of actuators, as
well as conducting dynamic adjustment and optimization of trajectories of displacement of operating elements of the equipment. A method
of acoustic analysis for precision machining on machine tools with parallel kinematics has been developed.
Results. A neural network reference model has been constructed, which allows to diagnose current characteristics of the state of objects
in different conditions, namely mechanism’s configuration, mechanism’s geometric parameters while running motor-spindle, dynamics of
displacement of mechanism’s nodes of the experimental stand with variable velocities and load on the drive, as well as temperature changes of the object. The developed neural network models also were tested for adequacy.
Conclusions. The experiments on the study of the dependency between the parameters of the spectrum of the acoustic signal with a
given discreteness disturbed by excitatory effect in the form of “white noise” confirmed efficiency of this approach. Prospects for further
research may consist in creation of methods for optimal control of complex technological machines to improve accuracy of positioning
of actuators and to improve their dynamic settings.
References
Kovalevskyy S. V., Kovalevska O. S. Acoustic Monitoring with
Neural Network Analysis, American Journal of Neural Networks
and Applications, 2015, Vol. 1, No. 2, pp. 39–42. DOI: 10.11648/j.ajnna.20150102.12
Tyurin Yu. N., Pogrebnjak A. D. Electric heating using a liquid electrode, Surface and Coatings Technology, 2001, pp. 293–299.
Hohmann M., Brooks G., Spiegelhauer C. Production methods and applications for high-quaIity metaI powders and sprayformed products. Produktionsmethoden und Anwendungen fur qualitativ hochwertige Metallpulver und spruhkompaktierte Halbzeuge. Stahl
und Eisen, 2005, 258 р.
Yasa E., Kruth J. Application of laser re-melting on Selective laser melting parts. Catholic University of Leuven, Dept. of Mech. Eng, Heverlee, Belgium. Advances in Production Engineering, Management, 6, 2011, pp. 259–270.
David Bourella L., Joseph Beaman J., Jr. a, Ming C. Leub and W. David Rosenc. A Brief History of Additive. Manufacturing and the 2009 Roadmap for Additive Manufacturing: Looking Back and Looking Ahead. RapidTech, 2009, 328 p.
Dutta В. еt. al. Additive Manufacturing by Direct Metal Deposition, Advanced materials & processes, May, 2011, pp. 33–36.
Fngelo H. C. Subramanian R. Powder Metalurge: Science,
technology and application. New Dehli, 2009, 128 р.
Kruglov I. A., Mishulina O. A. Neural networks modeling of
multivariable vector functions in ill-posed approximation
problems, Journal of Computer and System Sciences
International, 2013, Vol. 52, No. 4, pp. 503–518.
Kovalevskiy S. V., Kovalevskaya E. S., Nagieva A. I. Akusticheskiy kontrol razmerov i pokazateley sherohovatosti poverhnostey detaley s primeneniem neyrosetevyih modeley, NeyrositovI tehnologiyi ta yih zastosuvannya : zbirnik prats mizhnarodnoyi naukovoyi konferentsiyi. Kramatorsk, DDMA, 2014, pp. 24–35.
Kovalevskiy S. V., Kovalevskaya E. S., Tulupov V. I. Razvitie metodov akusticheskoy diagnostiki v mashinostroenii:
monografIya. Kramatorsk, DGMA, 2014, 91 p.
Vadutov O. S. Matematicheskie osnovyi obrabotki signalov.
Praktikum: uchebnoe posobie; Tomskiy politehnicheskiy
universitet. 3-e izd., ispr. i dop. Tomsk, Izd-vo Tomskogo
politehnicheskogo universiteta, 2014, 102 p.
Eroshenko AndrIy Mihaylovich Akusticheskaya diagnostika
staticheskih i dinamicheskih svoystv mehanizmov s parallelnoy
kinematikoy, Kompleksne zabezpechennya yakostI
tehnologIchnih protsesIv ta sistem (KZYaTPS – 2017): materIali tez dopovIdey VII mizhnarodnoYi naukovo-praktichnoyi konferentsiyi (m. Chernigiv, 24–27 kvit. 2017 r.) : u 2-h t. ChernIgIvskiy natsIonalniy tehnologIchniy unIversitet [ta in.]; vidp. za vip.: [ta in.]. Chernigiv, ChNTU, 2017, Vol. 1, pp. 59–60.
Osipov L. A. Obrabotka signalov na tsifrovyih protsessorah.
Lineyno-approksimiruyuschiy metod. Moscow, Goryachaya
liniya-Telekom, 2001, 114 p.
Selivanov S. G., Guzairov M. B. Sistemotehnika innovatsionnoy podgotovki proizvodstva v mashinostroenii. Moscow, Mashinostroenie, 2012, 568 p.
Smirnov V. A. Kinetostaticheskoe modelirovanie
energoeffektivnogo upravleniya oborudovaniem s parallelnoy
kinematikoy, Vestnik YuUrGU. Seriya «Mashinostroenie», 2010,
Vyp. 16, No. 29, pp. 65–71
Hristoforov A. V. Metodyi analiza spektra signala. Uchebnometodicheskoe posobie k spetsialnomu laboratornomu praktikumu dlya studentov starshih kursov i magistrantov kafedr radiofizicheskogo napravleniya. Kazan 2004, 21 p.
Zhuk A. Ya., Malyishev G. P., Zhelyabina N. K., Klevtsov O. M. Tehnicheskaya diagnostika. Kontrol i prognozirovanie:
monografiya. Zaporozhye, Izdatelstvo Zaporozhskoy
gosudarstvennoy inzhenernoy akademii, 2008, 500 p.
Kovalevs’kyy S. V., Kovalevs’ka O. S., Korzhov Ye. O., Koshevoy A. O.; za zah. red. d.t.n., prof. S. V. Kovalevs’koho Diahnostyka tekhnolohichnykh system i vyrobiv mashynobuduvannya (z vykorystannyam neyromerezhevoho pidkhodu) : monohrafiya. Kramators’k, DDMA, 2016, 186 p.
Downloads
How to Cite
Issue
Section
License
Copyright (c) 2018 О. S. Kovalevska, S. V. Kovalevskyy
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Creative Commons Licensing Notifications in the Copyright Notices
The journal allows the authors to hold the copyright without restrictions and to retain publishing rights without restrictions.
The journal allows readers to read, download, copy, distribute, print, search, or link to the full texts of its articles.
The journal allows to reuse and remixing of its content, in accordance with a Creative Commons license СС BY -SA.
Authors who publish with this journal agree to the following terms:
-
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License CC BY-SA that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
-
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
-
Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
