Proceedings of the 2005 IEEE Midnight-Summer Workshop on Soft Computing in Industrial Applications, 2005. SMCia/05.最新文献_第3页

Reconfigurable multi-stage neural networks in monitoring industrial machines 可重构多级神经网络在工业机械监控中的应用

Proceedings of the 2005 IEEE Midnight-Summer Workshop on Soft Computing in Industrial Applications, 2005. SMCia/05. Pub Date : 2005-06-28 DOI: 10.1109/SMCIA.2005.1466963

H. Marzi

引用次数: 2

Comparisons of logistic regression and artificial neural network on power distribution systems fault cause identification 逻辑回归与人工神经网络在配电系统故障原因识别中的比较

Proceedings of the 2005 IEEE Midnight-Summer Workshop on Soft Computing in Industrial Applications, 2005. SMCia/05. Pub Date : 2005-06-28 DOI: 10.1109/SMCIA.2005.1466960

L. Xu, M. Chow, X.Z. Gao

引用次数: 26

Image processing approach to features extraction in classification of control chart patterns 控制图模式分类中特征提取的图像处理方法

Proceedings of the 2005 IEEE Midnight-Summer Workshop on Soft Computing in Industrial Applications, 2005. SMCia/05. Pub Date : 2005-06-28 DOI: 10.1109/SMCIA.2005.1466953

K. Lavangnananda, Apivadee Piyatumrong

{"title":"Image processing approach to features extraction in classification of control chart patterns","authors":"K. Lavangnananda, Apivadee Piyatumrong","doi":"10.1109/SMCIA.2005.1466953","DOIUrl":"https://doi.org/10.1109/SMCIA.2005.1466953","url":null,"abstract":"Control chart patterns can be used to determine behavior of system. They are vital in process control as they are used in detecting the abnormalities which may occur. Accurate identification of these charts is necessary to the efficiency and reduction of system troubleshooting time. The accuracy of the classification depends largely on how noisy the signals in these charts are. If their noise ratio is very high, this suggests that reliable classification is almost impossible. One of the major difficulties lies in differentiation between increasing and decreasing patterns especially where gradients of inclination and declination are small. This paper describes an improvement in identifying highly noisy control chart patterns by utilizing features extraction in classification using neural networks in previous works. Features, which were founded useful for the classification, are mean, standard deviation, skewness, and kurtosis. The improvement can be summarized into two factors, the introduction of two more useful features, slope and Pearson correlation coefficient, and the additional transformation derived from the original signal. This work yields better performance than previous works which used the same data set by increasing the overall accuracy from 83.30% to 90.47%.","PeriodicalId":283950,"journal":{"name":"Proceedings of the 2005 IEEE Midnight-Summer Workshop on Soft Computing in Industrial Applications, 2005. SMCia/05.","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123342838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 15

An intelligent control scheme with self-updating for industrial processes 一种具有自更新功能的工业过程智能控制方案

Proceedings of the 2005 IEEE Midnight-Summer Workshop on Soft Computing in Industrial Applications, 2005. SMCia/05. Pub Date : 2005-06-28 DOI: 10.1109/SMCIA.2005.1466952

Limin Liu, Ping Yan, Yunxiu Wang, Q. Liu

引用次数: 8

Fuzzy logic based sensitivity assessment for winding deformation detection 基于模糊逻辑的卷绕变形检测灵敏度评价

Proceedings of the 2005 IEEE Midnight-Summer Workshop on Soft Computing in Industrial Applications, 2005. SMCia/05. Pub Date : 2005-06-28 DOI: 10.1109/SMCIA.2005.1466942

S. Santhi, V. Jayashankar

引用次数: 1

A predictive thickness control structure and decision about the better control parameter for the cold rolling process through sensitivity factors via neural networks 利用神经网络建立了冷轧过程厚度预测控制结构，并通过灵敏度因子确定了较好的控制参数

Proceedings of the 2005 IEEE Midnight-Summer Workshop on Soft Computing in Industrial Applications, 2005. SMCia/05. Pub Date : 2005-06-28 DOI: 10.1109/SMCIA.2005.1466941

L. E. Zarate

{"title":"A predictive thickness control structure and decision about the better control parameter for the cold rolling process through sensitivity factors via neural networks","authors":"L. E. Zarate","doi":"10.1109/SMCIA.2005.1466941","DOIUrl":"https://doi.org/10.1109/SMCIA.2005.1466941","url":null,"abstract":"The single stand rolling mill governing equation is a non-linear function on several parameters (entry thickness, front and back tensions, yield stress and friction coefficient among others). Any alteration in one of them will cause alterations on the rolling load and, consequently, on the outgoing thickness. This paper presents a method to determinate the appropriate adjustment for thickness control considering three possible control parameters: roll gap, front and back tensions. The method uses a predictive model based in the sensitivity equation of the process where the sensitivity factors are obtained by differentiating a neural network previously trained. The method considers as the best control action the one that demands the smallest adjustment. By otherwise, one of the capital issues in the controller design for rolling systems is the difficulty to measure the final thickness without time delays. The time delay is a consequence of the locations of the outgoing sensors that are always placed some distance away from the roll gap. The proposed control system calculates the necessary adjustment based on a predictive model for the output thickness. This model permits to overcome the time delay that exists in such processes. The new structure can eliminate the thickness sensor, usually based on an X-ray detector. Simulation results show the feasibility of the proposed technique.","PeriodicalId":283950,"journal":{"name":"Proceedings of the 2005 IEEE Midnight-Summer Workshop on Soft Computing in Industrial Applications, 2005. SMCia/05.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132754223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Tuning of PID controller using gain/phase margin and immune algorithm 利用增益/相位裕度和免疫算法对PID控制器进行整定

Proceedings of the 2005 IEEE Midnight-Summer Workshop on Soft Computing in Industrial Applications, 2005. SMCia/05. Pub Date : 2005-06-28 DOI: 10.1109/SMCIA.2005.1466950

Dong Hwa Kim

引用次数: 17

Implementation of real time color gamut mapping using neural network 利用神经网络实现实时色域映射

Proceedings of the 2005 IEEE Midnight-Summer Workshop on Soft Computing in Industrial Applications, 2005. SMCia/05. Pub Date : 2005-06-28 DOI: 10.1109/SMCIA.2005.1466962

Hak-Sung Lee, Dongil Han

引用次数: 4

Fire protection system for cargo trains using fuzzy logic 基于模糊逻辑的货运列车消防系统

Proceedings of the 2005 IEEE Midnight-Summer Workshop on Soft Computing in Industrial Applications, 2005. SMCia/05. Pub Date : 2005-06-28 DOI: 10.1109/SMCIA.2005.1466944

H. Elsayed, H. Amer, R. Daoud, D.W. Ramzy, M. Ghobrial

引用次数: 4

Tuning of PID controller for dead time process using immune based multiobjective 基于免疫多目标的死时间过程PID控制器整定

Proceedings of the 2005 IEEE Midnight-Summer Workshop on Soft Computing in Industrial Applications, 2005. SMCia/05. Pub Date : 2005-06-28 DOI: 10.1109/SMCIA.2005.1466949

Dong Hwa Kim, Won-Pyo Hong

引用次数: 5