For Libraries For Publication Open Access Downloads About Us Contact Us
Paper Titles
Spatial Data Mining Based on Campus GIS
p.641
A Visualization Interface Programming
p.646
Study of Shaped Charge Jet Penetration into Concrete Target
p.650
Study on the Effect of Different Rear Windscreen Angles on Aerodynamic Characteristic of the Automobile
p.654
An Intelligent Control System of Candy Production Process
p.658
Process Optimization of Candy Production Based on Data Mining
p.662
Research on New Green Camouflage Pigments
p.666
Research on Solution and Key Technologies of Network DNC for CNC Workshop
p.670
UDDI Based Support System for Collaborative Product Development
p.675

An Intelligent Control System of Candy Production Process

Article Preview

Abstract:

Candy production processes involve many process variables. Operators often find it difficult to effectively monitor the process data, analyze current states, detect and diagnose process anomalies, and take appropriate actions to control the processes. The objective of this work is to develop an intelligent control system of candy production process to improve final candy quality and to increase production efficiency with good human-machine interfaces. The study is conducted by using virtual instrument, multi-sensor data fusion and fuzzy control technology to online detect and control typical parameters. Experiment results show that this system can reach requirements of processing accuracy and real-time property and is highly cost-efficient and practical.

You might also be interested in these eBooks
Advanced Research on Material Engineering, Chemistry, Bioinformatics View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 282-283)

Pages:

658-661

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.282-283.658

Citation:

Cite this paper

Online since:

July 2011

Authors:

Jia Liang Zhang, Bei Zhi Li, Jian Guo Yang, Han Yan Chen

Keywords:

Candy Production, Data Fusion, Intelligent Control, Virtual Instrument (VI)

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

© 2011 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

References

[1] G.A. Oliveira, M.R.C. Nogueira, C.Z. Brusamarello, M.L. Corazza and F.C. Corazza: Journal of Food Engineering, Vol. 89 (2008), p.251.

DOI: 10.1016/j.jfoodeng.2007.12.019

Google Scholar

[2] J.A. Wilson and L.F.M. Zorzetto: Computers and Chemical Engineering, Vol. 21 (1997), p.951.

Google Scholar

[3] V. Uraikul, C.W. Chan and P. Tontiwachwuthikul: Engineering Applications on Artificial Intelligence, Vol. 20 (2007), p.115.

Google Scholar

[4] R. Sharmin, U. Sundararaj, S. Shah, L.V. Griend and Y. Sun: Chemical Engineering Science, Vol. 60 (2006), p.6372.

Google Scholar

[5] A. Johnston, L. Candy and E. Edmonds: Design Studies, Vol. 29(2008), p.556.

Google Scholar

[6] A.H. Taner, J.E. Briqnell: Sensors and Actuators, A: Physical, Vol. 61(1997), p.427.

Google Scholar

[7] Y. Huang, Y. Lan, W.C. Hoffmann and R.E. Lacey: J. Bionic Engineering, Vol. 4(2007), p.53.

Google Scholar

[8] L. Lianzhong and M. Zaheeruddin: Building Services Engineering Research and Technology, Vol. 28(2007), p.35.

Google Scholar

© 2025 Trans Tech Publications Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. For open access content, terms of the Creative Commons licensing CC-BY are applied.
Scientific.Net is a registered trademark of Trans Tech Publications Ltd.