Detection of Abnormal Operation Noise Using CHLAC of Sound Spectrograph and Continuous DP Matching

DOI Web Site Web Site 12 References
  • Hattori Koosuke
    Graduate School of Engineering, Nagoya Institute of Technology
  • Ohmi Taishi
    Graduate School of Engineering, Nagoya Institute of Technology
  • Taguchi Ryo
    Graduate School of Engineering, Nagoya Institute of Technology
  • Umezaki Taizo
    Graduate School of Engineering, Nagoya Institute of Technology

Bibliographic Information

Other Title
  • CHLACと連続DPマッチングを用いた機械駆動異音の自動検出
  • CHLAC ト レンゾク DP マッチング オ モチイタ キカイ クドウイオン ノ ジドウ ケンシュツ

Search this article

Abstract

It is a general way that the industrial product is tested by individual inspector. If the product involves sound factors, each inspector will evaluate the test product to sort out a strange engine noise from the natural sound. However, it is hard to cover the consistency in evaluation criteria due to the personal equation referred to the idea that every individual had an inherent bias, plus a physical and mental conditions can be a negative effect on his/her evaluation criteria. It would be ideal if the criteria would not be affected by anyone, anywhere, circumstances; accordingly the quality of products must be equated. In this paper, we propose a noise detection method based on Cubic Higher-order Local Auto-Correlation (CHLAC) scheme and DP Matching provided by Cepstrum Analysis to extract the correct solution. This technique is practically used for detecting any human abnormal movements out of a monitored video clip and identifying individual persons by voice. The study results are shown to be highly effective in our proposed method.

Journal

References(12)*help

See more

Keywords

Details 詳細情報について

Report a problem

Back to top