Copper particle has been detected among dominant aluminum particles by in-situ resistance background implemented in conductance-path recognition algorithm (iRB-CPR). The iRB 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 iRB. 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 iRB-CPR successfully suppress the resistance deviation ratio in the simulation 〖〈r〉〗^sim 93.8% and experiment 〖〈r〉〗^exp 73.9%. Moreover, the Cu detection by iRB-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.
