Automated visual inspection of CMS HGCAL silicon sensor surface using an ensemble of a deep convolutional autoencoder and classifier

Autor: Grönroos, Sonja, Pierini, Maurizio, Chernyavskaya, Nadezda

More than a thousand 8" silicon sensors will be visually inspected to look for anomalies on their surface during the quality control preceding assembly into the High-Granularity Calorimeter for the CMS experiment at CERN. A deep learning-based algori

Externí odkaz: http://arxiv.org/abs/2303.15319

Machine learning and multimethod-NDE for estimating neutron-induced embrittlement

Autor: Rinta-aho, Jari, Grönroos, Sonja

Publikováno v: Rinta-aho, J & Grönroos, S 2021, Machine learning and multimethod-NDE for estimating neutron-induced embrittlement . in European NDE Symposium for NPP : Event booklet . NOMAD project, pp. 16, European Symposium on NDE for NPP, Saarbruchen, Germany, 4/05/21 . < https://nomad-horizon2020.eu/events/european-symposium-on-non-destructive-evaluation-for-npp/_speakers/NOMAD_eventbooklet_0305_final.pdf >

In this study, 157 irradiated and non-irradiated Charpy specimens[1] manufactured from six different steel alloys used in the reactorpressure vessels (18MND5-W, 22NiMoCr37, A508-B, 15Kh2NMFA,HSST03 and A508-Cl2) were measured. The measurements includ

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=355e65625b88::eca1251441d3ee32e3f598544dd514b1
https://cris.vtt.fi/ws/files/65176539/NOMAD_European_NDE.pdf