Application of Grey Model in Intelligent-Control of Micro-Hole Abrasive Flow Machining

In this paper, a control system based on the prediction of processing flow in Abrasive flow machining is designed. In this system,flow is predicted by an improved GM(1,1) model in conformation of background value. Combined with fuzzy control system, it can adapt the pressure to meet the processing requirement automatically. Experiments proved that the improved GM(1,1) model can predict the processing flow accuratly, and the fuzzy control system based on grey prediction can improve the machining accuracy of micro-hole AFM effectively.

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Experimental Study of Titanium Alloy Micro-Holes by EDM Fuzzy Control System

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.188.195 ◽

2011 ◽

Vol 188 ◽

pp. 195-198

Author(s):

Yu Kui Wang ◽

X.S. Geng ◽

Zhen Long Wang ◽

D.B. Shan

Keyword(s):

Titanium Alloy ◽

Control System ◽

Fuzzy Control ◽

Pulse Interval ◽

Control Parameters ◽

Fuzzy Control System ◽

System A ◽

Suitable Parameter ◽

Micro Holes ◽

Micro Hole

Aiming at machining deep micro-holes in titanium alloy, an experimental approach for EDM adopted a fuzzy control system was introduced. The fuzzy control system based on statistics of discharge states, that pulse interval and jumping height as control parameters, was self-developed. The suitable parameter for the deep micro-hole EDM process can be handily adjusted and modified in visual MATLAB fuzzy editor. A lot of experiments for titanium alloy micro-hole machining were performed on the EDM machine tool adopting the fuzzy control system. A titanium alloy deep micro-hole with 80μm in diameter and 15 in the ratio of depth-diameter is obtained. The process and results of experiments show that the process stability and efficiency be improved; due to the fuzzy control system and its suitable control parameters are applied.

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A simulated annealing approach to switching grey prediction fuzzy control system design

International Journal of Systems Science ◽

10.1080/00207729808929556 ◽

1998 ◽

Vol 29 (6) ◽

pp. 637-642 ◽

Cited By ~ 15

Author(s):

CHING-CHANG WONG ◽

CHIA-CHONG CHEN

Keyword(s):

Simulated Annealing ◽

Control System ◽

Fuzzy Control ◽

System Design ◽

Control System Design ◽

Grey Prediction ◽

Fuzzy Control System

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Study on the Control System of Grinding the Nozzle of Twin Flapper-Nozzle Valve

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.644-650.62 ◽

2014 ◽

Vol 644-650 ◽

pp. 62-66

Author(s):

Shu Zhen Yang ◽

Rui Qian ◽

Yu Jie Bai

Keyword(s):

Control System ◽

Intelligent Control ◽

Fine Tuning ◽

Machining Accuracy ◽

Control Technology ◽

Working Pressure ◽

Abrasive Flow Machining ◽

Intelligent Control System ◽

High Level ◽

Very High

In this paper, neural network and grey fuzzy control technology are applied in Abrasive Flow Machining (AFM) to grind the mico-hole in th nozzle of the twin flapper-nozzle valve. An intelligent control system with fine tuning working pressure is established that can predict the process parameters automatically before machining and forcast the flow to adjust the working pressure in machining.The result of experiment indicates that this system has high level of intelligent and can get very high machining accuracy.

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A on-line rule tuning grey prediction fuzzy control system design

Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290) ◽

10.1109/ijcnn.2002.1007685 ◽

2003 ◽

Author(s):

Hsuan-Ming Feng ◽

Ching-Chang Wong

Keyword(s):

Control System ◽

Fuzzy Control ◽

System Design ◽

Control System Design ◽

Grey Prediction ◽

Fuzzy Control System ◽

On Line

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Using Fuzzy Control for Feed Rate Scheduling of Computer Numerical Control Machine Tools

Applied Sciences ◽

10.3390/app11104701 ◽

2021 ◽

Vol 11 (10) ◽

pp. 4701

Author(s):

Cheng-Jian Lin ◽

Chun-Hui Lin ◽

Shyh-Hau Wang

Keyword(s):

Control System ◽

Fuzzy Control ◽

Feed Rate ◽

Three Dimensional ◽

Numerical Control ◽

Machining Accuracy ◽

Fuzzy Control System ◽

Industrial Processing ◽

Curvature Variation ◽

Rate Scheduling

In industrial processing, workpiece quality and processing time have recently become important issues. To improve the machining accuracy and reduce the cutting time, the cutting feed rate will have a significant impact. Therefore, how to plan a dynamic cutting feed rate is very important. In this study, a fuzzy control system for feed rate scheduling based on the curvature and curvature variation is proposed. The proposed system is implemented in actual cutting, and to verify the data an optical three-dimensional scanner is used to measure the cutting trajectory of the workpiece. Experimental results prove that the proposed fuzzy control system for dynamic cutting feed rate scheduling increases the cutting accuracy by 41.8% under the same cutting time; moreover, it decreases the cutting time by 50.8% under approximately the same cutting accuracy.

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Using Fuzzy Control for Feedrate Scheduling of Computer Numerical Control Machine Tools

10.21203/rs.3.rs-203034/v1 ◽

2021 ◽

Author(s):

Cheng-Jian Lin ◽

Chun-Hui Lin ◽

Shyh-Hau Wang

Keyword(s):

Control System ◽

Fuzzy Control ◽

Machine Tools ◽

Three Dimensional ◽

Numerical Control ◽

Machining Accuracy ◽

Fuzzy Control System ◽

Industrial Processing ◽

Curvature Variation ◽

Feedrate Scheduling

Abstract In industrial processing, workpiece quality and processing time have become important issues lately. Fortunately, dynamic cutting feedrate scheduling has been proposed to improve machining accuracy and decrease cutting time. Studies have shown that the curvature and cutting feedrate significantly influence the machining accuracy. Therefore, the present study proposes a fuzzy control system for feedrate scheduling based on the curvature and curvature variation. The proposed system is implemented in actual cutting, and an optical three-dimensional scanner is performed as a verification to measure the cutting trajectory of the workpiece. Experimental results prove that the proposed fuzzy control system for dynamic cutting feedrate scheduling increases the cutting accuracy by 43% under the same cutting time; moreover, it decreases the cutting time by 49% under the same cutting accuracy.

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