A novel intelligent control system for flue-curing barns based on real-time image features

被引：18

作者：

Wu, Juan ^{[1
,2
]}

Yang, Simon X. ^{[3
]}

Tian, Fengchun ^{[1
]}

机构：

[1] Chongqing Univ, Coll Commun Engn, Chongqing 400044, Peoples R China

[2] Chongqing Coll Elect Engn, Chongqing 401331, Peoples R China

[3] Univ Guelph, Sch Engn, Adv Robot & Intelligent Syst ARIS Lab, Guelph, ON N1G 2W1, Canada

来源：

BIOSYSTEMS ENGINEERING | 2014年 / 123卷

关键词：

Intelligent control; Image features; Image processing; Neural networks; FARM ODOR; FEATURE-EXTRACTION; TOBACCO-LEAVES; CURED TOBACCO; COLOR; CLASSIFICATION; COMPONENT; TEXTURE;

D O I：

10.1016/j.biosystemseng.2014.05.008

中图分类号：

S2 [农业工程];

学科分类号：

0828 ;

摘要：

Most intensive tobacco curing systems are manually operated requiring the curers to frequently observe the status of tobacco leaves and in order to achieve the desired temperature and relative humidity, curers adjust the setpoint values of dry and wet bulb temperatures and the time to change to the next setpoints. Control is therefore subjective and it is difficult to maintain consistent high quality curing. A novel intelligent control system based on the real-time image processing of the tobacco leaves images to monitor the status of the tobacco leaves was developed. A neural network based approach was designed to identify the setpoints for the dry and wet bulb temperatures, and the time to change to the next setpoints. Inputs were 12 extracted image features obtained from an image processing algorithm and the measured dry and wet bulb temperatures in the barn. Without any manual intervention by curers, the developed intelligent control system achieved real-time monitoring and management of the curing process. The effectiveness of the developed intelligent control system was demonstrated by simulation and experiment. (C) 2014 IAgrE. Published by Elsevier Ltd. All rights reserved.

引用

页码：77 / 90

页数：14

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