Copper particle detection method by in-situ resistance background implemented in conductance-path recognition algorithm (iRB-CPR) among dominant aluminum particles. (April 2022)

• Record Type: Journal Article
• Authors: Sejati, Prima Asmara; Baidillah, Marlin Ramadhan; Prayitno, Yosephus Ardean Kurnianto; Ibrahim, Kiagus Aufa; Kawashima, Daisuke; Takei, Masahiro
• Is Part Of: Measurement. Volume 193(2022)
• Publication Date: 2022-04
• Subjects: Electrical resistance measurement -- Conducting path -- Non-ferrous metal particles -- Decision tree algorithm; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2022.110983
• Languages: English
• ISSNs: 0263-2241

Abstract

Highlights: In-situ electrical resistance background measurement. Particle conductance-path recognition by decision tree algorithm. Particle volume fraction and particle arrangement prediction. Resistance measurement normalization based-on resistance background database. Copper particle detection method among dominant aluminum particles as a part of metal particle separation. Abstract: Copper particle has been detected among dominant aluminum particles by in-situ resistance background implemented in conductance-path recognition algorithm ( i RB-CPR). The i RB is a particle volume fraction prediction from a resistance background database measured by shifted-four-wire measurement (SRM) in various particle arrangements. The CPR is adopted from a decision tree algorithm to predict the particle conductance path by comparing the real-condition resistances classified by i RB. The selected resistance background is used as a denominator to normalize the resistance measurement by SRM under unknown particle arrangement in the real condition. Finally, Cu is detected by comparing the normalized resistances with the normalized spatial-mean resistance. The i RB-CPR successfully suppress the resistance deviation ratio in the simulation 〈 r 〉 s i m 93.8% and experiment 〈 r 〉 e x p 73.9%. Moreover, the Cu detection by i RB-CPR satisfies give a low error E S = 6.11% at S = 180 under α = 10%. This research opens a new detection modality as a part of non-ferrous metal particles recovery.