Results 241 to 250 of about 6,071,763 (407)
Tool Wear Prediction in Machining of Aluminum Matrix Composites with the Use of Machine Learning Models. [PDF]
Materials (Basel)Hamrol A +3 more
europepmc +1 more source
Local-feature and global-dependency based tool wear prediction using deep learning. [PDF]
Sci Rep, 2022 Yang C, Zhou J, Li E, Wang M, Jin T.
europepmc +1 more source
Advanced Functional Materials, EarlyView.Molecular engineering of a nonconjugated radical polymer enables a significant enhancement of the glass transition temperature. The amorphous nature and tunability of the polymer, arising from its nonconjugated backbone, facilitates the fabrication of organic memristive devices with an exceptionally high yield (>95%), as well as substantial ...
Daeun Kim +14 more
wiley +1 more source
Intelligent tool wear prediction based on deep learning PSD-CVT model. [PDF]
Sci RepSi S, Mu D, Si Z.
europepmc +1 more source
Micro-Milling Tool Wear Monitoring via Nonlinear Cutting Force Model. [PDF]
Micromachines (Basel), 2022 Liu T, Wang Q, Wang W.
europepmc +1 more source
Wear and MnS Layer Adhesion in Uncoated Cutting Tools When Dry and Wet Turning Free-Cutting Steels [PDF]
, 2019 Daniel Krähmer +5 more
openalex +1 more source
Measurement of tool wear using a non-contact method, using a laser measuring system
, 2021 Bartłomiej Grzegorzewski +1 more
openalex +1 more source
Two‐Dimensional Materials as a Multiproperty Sensing Platform
Advanced Functional Materials, EarlyView.Various sensing modalities enabled and/or enhanced by two‐dimensional (2D) materials are reviewed. The domains considered for sensing include: 1) optoelectronics, 2) quantum defects, 3) scanning probe microscopy, 4) nanomechanics, and 5) bio‐ and chemosensing.
Dipankar Jana +11 more
wiley +1 more source
Research on Tool Wear Monitoring Technology Based on Variational Mode Decomposition and Back Propagation Neural Network Model. [PDF]
Sensors (Basel)Wang K, Wang A, Wu L.
europepmc +1 more source