SOMによる電動工具振動検査のための手腕系振動パターン識別

抄録

In this paper, we propose a pattern classification method of spectra of vibration data in a wrist by a motor-operated electric tool (MOET) using Self-Organizing Feature Map (SOM). We collect 27 data to evaluate the vibration patterns in a wrist for three kinds of MOETs. We compute spectrra of those vibration data and input them to a SOM network to find the spectral patterns. Based on the relations among vibration spectral patterns of MOETs under no load and load conditions, we show that the performance under load conditions can be evaluated by those of unloaded ones.