書誌事項
- タイトル別名
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- Non-Destructive Inspection of Adhesive Imperfection in CBN Grinding Wheel
- CBN セグメント トイシ ノ セッチャク フリョウ ノ ヒハカイ ケンサ
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抄録
An automatic system of ultrasonic inspection with a multi-layered neural network software to adhesive surface defects between CBN segment chips and a disk periphery has been developed to serve the guarantee of the quality of the grinding wheel. The network was used to contrive the accuracy improvement of the inspection. The waveforms reflected from the adhesive location of either prescribed artificially exfoliated defect or non-defect were investigated in detail to distinct the characteristics of the waveform. The network learned preferentially with both defect and non-defect waveforms, and also the improvement of the network learning compensated the amplitude of the wave near the edges was implemented. The inspection was performed to the grinding wheel with being unknown defects by using the learned network. Inspection results supported that the inspection system contributes the decision of the adhesive integrity of the CBN grinding wheel.
収録刊行物
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- 日本機械学会論文集A編
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日本機械学会論文集A編 69 (687), 1635-1640, 2003
一般社団法人 日本機械学会
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キーワード
詳細情報 詳細情報について
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- CRID
- 1390282679456203776
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- NII論文ID
- 110002370493
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- NII書誌ID
- AN0018742X
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- ISSN
- 18848338
- 03875008
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- NDL書誌ID
- 6776853
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可