{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T10:09:47Z","timestamp":1777457387310,"version":"3.51.4"},"reference-count":34,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2023,9,24]],"date-time":"2023-09-24T00:00:00Z","timestamp":1695513600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Japan Science and Technology Agency (JST) Adaptable and Seamless Technology Transfer Program through Target-driven R&amp;D (A-step)","award":["JPMJTM19AU"],"award-info":[{"award-number":["JPMJTM19AU"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The minor copper (Cu) particles among major aluminum (Al) particles have been detected by means of an integration of a generative adversarial network and electrical impedance tomography (GAN-EIT) for a wet-type gravity vibration separator (WGS). This study solves the problem of blurred EIT reconstructed images by proposing a GAN-EIT integration system for Cu detection in WGS. GAN-EIT produces two types of images of various Cu positions among major Al particles, which are (1) the photo-based GAN-EIT images, where blurred EIT reconstructed images are enhanced by GAN based on a full set of photo images, and (2) the simulation-based GAN-EIT images. The proposed metal particle detection by GAN-EIT is applied in experiments under static conditions to investigate the performance of the metal detection method under single-layer conditions with the variation of the position of Cu particles. As a quantitative result, the images of detected Cu by GAN-EIT \u03c8\u033fGAN in different positions have higher accuracy as compared to \u03c3*EIT. In the region of interest (ROI) covered by the developed linear sensor, GAN-EIT successfully reduces the Cu detection error of conventional EIT by 40% while maintaining a minimum signal-to-noise ratio (SNR) of 60 [dB]. In conclusion, GAN-EIT is capable of improving the detailed features of the reconstructed images to visualize the detected Cu effectively.<\/jats:p>","DOI":"10.3390\/s23198062","type":"journal-article","created":{"date-parts":[[2023,9,24]],"date-time":"2023-09-24T10:48:31Z","timestamp":1695552511000},"page":"8062","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Metal Particle Detection by Integration of a Generative Adversarial Network and Electrical Impedance Tomography (GAN-EIT) for a Wet-Type Gravity Vibration Separator"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6015-9422","authenticated-orcid":false,"given":"Kiagus Aufa","family":"Ibrahim","sequence":"first","affiliation":[{"name":"Department of Mechanical Engineering, Division of Fundamental Engineering, Graduate School of Engineering, Chiba University, Chiba 263-8522, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0509-841X","authenticated-orcid":false,"given":"Prima Asmara","family":"Sejati","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Division of Fundamental Engineering, Graduate School of Engineering, Chiba University, Chiba 263-8522, Japan"},{"name":"Department of Electrical Engineering and Informatics, Vocational College, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Panji Nursetia","family":"Darma","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Division of Fundamental Engineering, Graduate School of Engineering, Chiba University, Chiba 263-8522, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Akira","family":"Nakane","sequence":"additional","affiliation":[{"name":"Sanritsu Machine Industry Co., Ltd., Chiba 263-0002, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Masahiro","family":"Takei","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Division of Fundamental Engineering, Graduate School of Engineering, Chiba University, Chiba 263-8522, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,9,24]]},"reference":[{"key":"ref_1","unstructured":"Green, A.S. 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