旋转干燥机在减少烟丝过度干燥中的智能控制

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applied
sciences
Article
Intelligent Control in the Application of a Rotary Dryer for
Reduction in the Over-Drying of Cut Tobacco
Shunpeng Pang
1,†
, Junhua Jia
1
, Xiangqian Ding
1,
*, Shusong Yu
1
and Yang Liu
2

 
Citation: Pang, S.; Jia, J.; Ding, X.;
Yu, S.; Liu, Y. Intelligent Control in
the Application of a Rotary Dryer for
Reduction in the Over-Drying of Cut
Tobacco. Appl. Sci. 2021, 11, 8205.
https://doi.org/10.3390/
app11178205
Academic Editor: Paolo Renna
Received: 12 July 2021
Accepted: 31 August 2021
Published: 3 September 2021
Publishers Note: MDPI stays neutral
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Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
1
College of Information Science and Engineering, Ocean University of China, Qingdao 266100, China;
pangshunpeng@gmail.com (S.P.); jiajunhua@stu.ouc.edu.cn (J.J.); yushusong@ouc.edu.cn (S.Y.)
2
Qingdao New Star Software Consulting Co., Ltd., Qingdao 266100, China; liuyangdaqu@gmail.com
* Correspondence: dingxiangqianouc@gmail.com
Current address: College of Information Science and Engineering, OUC Laoshan Campus, Ocean University
of China, No. 238 Songling Road, Qingdao 266100, China.
Abstract:
The drying process is fundamental for cut tobacco processing. However, there are some
problems related to the drying process such as overheating, or inconsistent control of moisture
content. This paper shows how an intelligent controller is designed for an industrial rotary drying
system. This controller is applied to a tobacco production unit to reduce overdried cut tobacco and
improve the overall unit performance. The proposed control system aims to keep the content of
moisture at the dryer outlet as close as possible to the optimal value and improve the homogeneity of
the product without any operator intervention. The study shows that, if a reduction of humidity in
the cut tobacco drying process is achieved using AI, the quality of the final product improves. In
particular, if compared to regulatory control, the proposed method constantly monitors and adjusts
the moisture content level in order to reduce the amount of overdried product. The findings of this
paper indicate that the suggested process can save at least 222.2 kg of cut tobacco for each batch in
the first stage of the drying process.
Keywords: cut tobacco drying; rotary dryer; intelligent controller
1. Introduction
It is well-known that rotary dryers are the main dehydration equipment used for
many different types of processing such as food industry [
1
], agriculture [
2
], and tobacco
production [
3
]. The rotary dryers can remove water from the material through heat
exchange, the greatest advantage of rotary dryers is that they can process more material in
a more efficient way than other kinds of dryers [
4
]. Usually, the wet material is dried by
hot air pumped into the rotating drum of the dryer [
5
]. At the same time, the drum needs
to keep rotating all the time to increase the contact area between the wet material and the
hot air.
However, traditional dryers usually operate at low thermal efficiency, because of the
inconsistent control of temperature originating from the human factor or overheating [
6
].
For example, during regular operation, incorrect or delayed correction of temperature in
process points can lead to significant variations of the outlet moisture content, resulting in
a decline of the product quality.
At present, the application of automation control technology to the industrial rotary
dryer is a highly effective way to improve operation, safety, and efficiency. The core
implementation of automation control technology is the fuzzy control strategy, which has
been already used in various industrial applications [
7
]. Tsourveloudis and Kiralakis [
8
]
have designed a system with two controllers, a fuzzy controller (FC) and a neuro-fuzzy
controller (NFC), for an industrial rotary dryer applied to olive stones. The FC was based on
some operators’ experience and knowledge. The NFC, on the other hand, was constructed
by applying the adaptive neuro-fuzzy inference system to the data collected from an
Appl. Sci. 2021, 11, 8205. https://doi.org/10.3390/app11178205 https://www.mdpi.com/journal/applsci
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