A Novel Material Identification Method Based on Material Surface Static Electricity Discharge

Abstract

In this paper, a novel material identification method based on material surface static electricity discharge is introduced. The induced charge model between charged material and a metal electrode is established at first. The process of accelerated discharge of material surface charge through metal electrode is studied. Then the electrostatic signal acquisition system with a special structure is designed. Five typical materials, aluminium, glass, paper, wood and polytetrafluoroethylene (PTFE) are measured. The attenuation speed of material electrostatic signal is represented by feature values which consist of the discharge factor and signal peak variance. Then the k nearest neighbor classification algorithm is used to identify and classify the five kinds of materials. The results show that average recognition accuracy rate of the five materials is 83 %. This method could be used in the materials identification.