検索結果 - 岡山大学学術成果リポジトリ

JaLCDOI	10.18926/14146
フルテキストURL	Mem_Fac_Eng_39_1_21.pdf
著者	鳥越崇史\| 小西正躬\| 今井純\| 西竜志\|
抄録	In this paper, neuro based intelligent diagnosis methods for electro-mechanical control system are proposed. A self organizing map neural network (SOM) is used to classify measured data of the target system as a qualitative diagnostic method. Besides of the above procedure, it is expected to attain more efficient maintenance by a quantitative estimation of failure. For the purpose, new method is proposed using a hierarchical neural network (HNN). In the method, classified results by SOM are processed for the quantitative diagnosis. Hierarchical neural network can identify inner structure of the relations between failure causes and its results that enables a quantitative diagnosis.
出版物タイトル	Memoirs of the Faculty of Engineering, Okayama University
発行日	2005-01
巻	39巻
号	1号
開始ページ	21
終了ページ	27
ISSN	0475-0071
言語	英語
論文のバージョン	publisher
NAID	120002308342

JaLCDOI	10.18926/14136
フルテキストURL	Mem_Fac_Eng_39_1_16.pdf
著者	内田哲也\| 石丸早苗\| 島村薫\| 宇治章人\| 松尾俊彦\| 大月洋\|
抄録	PE film was treated with fuming nitric acid at 80℃ for 20 min, resulting in introduction of COOH moieties on the film surface. The COOH’s were reacted with ethylenediamine, whose amino groups were used for linking with (2-[4-(dibutylamino)phenyl]ethenyl)-3-carboxy-methylbenzo-thiazolium, photoelectric dye (NK-5962), which absorbs visible light and converts the photon energy to electric potentials. The dye molecules were immobilized on the PE film surface and they were able to stimulate chick retinal tissues on incidence of visible light. These facts hopefully lead to development of an artificial retinal prosthesis.
出版物タイトル	Memoirs of the Faculty of Engineering, Okayama University
発行日	2005-01
巻	39巻
号	1号
開始ページ	16
終了ページ	20
ISSN	0475-0071
言語	英語
論文のバージョン	publisher
NAID	120002308066

JaLCDOI	10.18926/14098
フルテキストURL	Mem_Fac_Eng_OU_40_1_16.pdf
著者	阿部快洋\| 小西正躬\| 西竜志\| 今井純\|
抄録	In this study, auto tuning of PID control gains in hot strip looper controller is made based on RNN model. Neuro emulator is employed to model the characteristics of looper dynamics. Combining neuro emulator and RNN model, auto tuning system of PID control gains is constructed. As the inputs to RNN, plural evaluation functions which reflect individual preference of human experts. Further, Self learning mechamism is embeded to RNN model which enables adaptation to the change in rolling chracteristics. Through numerical experiments, the effect of the proposed method is ascertained.
出版物タイトル	Memoirs of the Faculty of Engineering, Okayama University
発行日	2006-01
巻	40巻
号	1号
開始ページ	16
終了ページ	22
ISSN	0475-0071
言語	英語
論文のバージョン	publisher
NAID	120002308615