Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Melih C. Yesilli"'
Publikováno v:
Volume 2: Manufacturing Processes; Manufacturing Systems.
Surface texture influences wear and tribological properties of manufactured parts, and it plays a critical role in end-user products. Therefore, quantifying the order or structure of a manufactured surface provides important information on the qualit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fec0e10c0b3bc726c781812a42fbebe5
https://doi.org/10.1115/msec2022-86659
https://doi.org/10.1115/msec2022-86659
Surface roughness and texture are critical to the functional performance of engineering components. The ability to analyze roughness and texture effectively and efficiently is much needed to ensure surface quality in many surface generation processes
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::170dd094c164189806bf327678d86e8c
http://arxiv.org/abs/2204.05968
http://arxiv.org/abs/2204.05968
Publikováno v:
CIRP Journal of Manufacturing Science and Technology. 28:118-135
The increasing availability of sensor data at machine tools makes automatic chatter detection algorithms a trending topic in metal cutting. Two prominent and advanced methods for feature extraction via signal decomposition are Wavelet Packet Transfor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9cea3a9054b538d3a29ec7f3dec9770e
https://doi.org/10.1016/j.cirpj.2019.11.003
https://doi.org/10.1016/j.cirpj.2019.11.003
Autor:
Melih C. Yesilli, Firas A. Khasawneh
Publikováno v:
2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA).
Surface roughness plays an important role in analyzing engineering surfaces. It quantifies the surface topography and can be used to determine whether the resulting surface finish is acceptable or not. Nevertheless, while several existing tools and s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::26b2a71e32da0106f4f9cd11c5ae8af7
https://doi.org/10.1109/icmla52953.2021.00219
https://doi.org/10.1109/icmla52953.2021.00219
Autor:
Firas A. Khasawneh, Melih C. Yesilli
There has been an increasing interest in leveraging machine learning tools for chatter prediction and diagnosis in discrete manufacturing processes. Some of the most common features for studying chatter include traditional signal processing tools suc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6fb68d9f0c77ef565dc4ad8a3ad287f4
Publikováno v:
ICMLA
Chatter detection has become a prominent subject of interest due to its effect on cutting tool life, surface finish and spindle of machine tool. Most of the existing methods in chatter detection literature are based on signal processing and signal de
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ad0cc1da615b9d4ada717d013f85ae5f
https://doi.org/10.1109/icmla.2019.00200
https://doi.org/10.1109/icmla.2019.00200
Publikováno v:
Volume 8: 31st Conference on Mechanical Vibration and Noise.
Enhancements in manufacturing technologies, especially 3D-printing, have enabled the production of intricate micro-scale, elastic meta-structures. This study explores the broadband vibration absorption characteristics of these structures for three di
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3f84cd8170f3bca8a5ee257ef2459f8f
https://doi.org/10.1115/detc2019-97673
https://doi.org/10.1115/detc2019-97673
Machining processes are most accurately described using complex dynamical systems that include nonlinearities, time delays, and stochastic effects. Due to the nature of these models as well as the practical challenges which include time-varying param
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f8c0ba746aceef674384b35ead3f08d5
http://arxiv.org/abs/1905.08671
http://arxiv.org/abs/1905.08671
Chatter detection from sensor signals has been an active field of research. While some success has been reported using several featurization tools and machine learning algorithms, existing methods have several drawbacks such as manual preprocessing a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3a37f726744bea297cfa82311ae89a82