Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/3837
Title: Data science approaches to diagnostics of metal stress-strain state using semiconductor sensor suitable for system design
Authors: Balitskii, O.
Kolesnikow, W.
Owsyannikow, A.
Lizunow, S.
Eliasz, J.
Keywords: diagnostics
system design
semiconductor sensor
Issue Date: 2018
Abstract: Article describes the data science approaches to diagnostics of metal stressstrain state using semiconductor sensor suitable for system design. It has been described the elongation curves (on permanent loading 370-450 MPa) in time of St3 (kp, sp) specimens in initial state, after treatment in He and H2 with pressure 35 MPa and temperature 623 К during 10 hours as well as a curves of the average signal of semiconductor sensors that controls this process and spectral sensitivity of the semiconductor sensors of the visible range depending on the time of the exposure of the samples.
Description: Data science approaches to diagnostics of metal stress-strain state using semiconductor sensor suitable for system design / O. Balitskii and other // Badania Nieniszczące i Diagnostyka (Non-destructive testing and diagnostics). – 2018. – Vol. 4. – P. 38-41.
URI: http://hdl.handle.net/123456789/3837
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