基于OpenCV的低能耗植物工厂照明系统设计与试验

doi:10.3969/j.issn.1004-1524.2022.03.23

浙江农业学报 ›› 2022, Vol. 34 ›› Issue (3): 626-635.DOI: 10.3969/j.issn.1004-1524.2022.03.23

基于OpenCV的低能耗植物工厂照明系统设计与试验

林孝腾(), 孙茜, 郑书河()

福建农林大学机电工程学院,福建福州 350100

收稿日期:2021-04-15 出版日期:2022-03-25 发布日期:2022-03-30
通讯作者: 郑书河
作者简介:*郑书河,E-mail: zshld1998@163.com
林孝腾(1995—),男,浙江温州人,硕士研究生,主要从事植物工厂光调控技术研究。E-mail: linxiaoteng66@163.com
基金资助:
福建省自然科学基金(2017J01423)

Design and experiment of energy-saving lighting system for plant factory based on OpenCV

LIN Xiaoteng(), SUN Qian, ZHENG Shuhe()

College of Mechanical and Electrical Engineering, Fujian Agriculture and Forestry University, Fuzhou 350100, China

Received:2021-04-15 Online:2022-03-25 Published:2022-03-30
Contact: ZHENG Shuhe

摘要/Abstract

摘要：

为解决植物工厂照明系统能耗大的问题,设计了基于OpenCV的低能耗植物工厂照明系统,通过对LED光源进行二次光学设计,将发散的LED光线聚集成圆形光斑对植物进行补光,减少植物未栽种区域的光能浪费。同时,对照明系统的机械结构与控制系统进行设计,基于树莓派上的OpenCV设计图像识别算法,实现光斑大小随植物生长的动态变化,提高系统的自动化程度。以奶油生菜为供试品种,以普通照明系统为对照进行栽种试验。结果表明:设计的照明系统较普通照明系统的能耗降低了55.8%,电能利用效率提高了72.7%,可见设计的照明系统具有较好的节能效果与较高的电能利用率。

关键词: 照明系统, 图像识别, 节能

Abstract:

In order to solve the problem of high energy consumption of light system in the plant factory, the energy-saving lighting system was designed based on OpenCV vision library. In the proposed system, the light source was optically redesigned to make the divergent LED light into a circular spot. Thus, it could provide sufficient light for plants with a smaller power, and reduce energy consumption in the areas without plant. The mechanical structure and control system were also designed. The image recognition algorithm was designed to identify dynamic change of the spot size with the growth of plant based on the OpenCV vision library of Raspberry Pi, which could improve the automation of this system. A test on the effect of the proposed system was carried out with butter lettuce as the plant material, and the ordinary lighting system as the control. The results showed that the energy consumption of the proposed system was reduced by 55.8%, and its power utilization efficiency was increased by 72.7%. In general, the proposed system had energy-saving effect and realized higher power utilization efficiency.

Key words: lighting system, image recognition, energy-saving

中图分类号:

S626
TP391.4

林孝腾, 孙茜, 郑书河. 基于OpenCV的低能耗植物工厂照明系统设计与试验[J]. 浙江农业学报, 2022, 34(3): 626-635.

LIN Xiaoteng, SUN Qian, ZHENG Shuhe. Design and experiment of energy-saving lighting system for plant factory based on OpenCV[J]. Acta Agriculturae Zhejiangensis, 2022, 34(3): 626-635.

图/表 13

图1 照明装置结构图 1,LED光源;2,直线轴承;3,滚珠丝杠滑块;4,透镜板;5,凸透镜;6,可伸缩聚光筒;7,顶板。

Fig.1 Light device structure 1, LED source; 2, Linear bearing; 3, Slider of ball screw; 4, Lens plate; 5, Convex lens; 6, Retractable condenser; 7, Roof.

图2 低能耗植物工厂照明系统实际工作场景照片

Fig.2 Photos of actual working scene of energy-saving lighting system

图3 控制系统整体结构 LCD,液晶显示;PPFD,光量子通量密度;DC,直流电。

Fig.3 Overall structure of control system LCD, Liquid crystal display; PPFD, Photosynthetic photon flux density; DC, Direct current.

图4 图像预处理流程

Fig.4 Flow chart of image preprocessing

图5 灰度化后的图像示例

Fig.5 Demonstration of gray scaled image

图6 Gamma校正前(左)、后(右)的图像示意

Fig.6 Demonstration of images before (left) and after (right) Gamma correction

图7 Gamma校正前(a)、后(b)的图像直方图

Fig.7 Image histogram before (a) and after (b) Gamma correction

图8 剔除误差前(左)、后(右)最小外接圆与外接矩形绘制图像示意

Fig.8 Demonstration of the smallest circumscribed circle and rectangle image before (left) and after (right) removing errors

图9 当植物体积超出光斑时的原图像(左)和处理后图像(右)示意

Fig.9 Demonstration of original image (left) and processed image (right) when plant does not fit spot image

图10 当相邻光斑重叠时的原图像(左)和处理后图像(右)示意

Fig.10 Demonstration of original image (left) and processed image (right) when adjacent spots overlap

图11 聚类分析流程图

Fig.11 Process of clustering analysis

图12 组内光斑与植物体积关系的判别流程

Fig.12 Flow chart of judgment of relationship between spot and plant in group

表1 不同处理下照明系统的电能消耗

Table 1 Power consumption of light system under different treatments kW·h

处理 Treatment	第1~6天 Day 1 to 6	第7~12天 Day 7 to 12	第13~18天 Day13 to 18	合计 Total
试验组Test group	1.372	1.884	2.715	5.971
对照组Control group	3.315	4.127	6.081	13.523

参考文献 21

[1]	刘文科, 刘义飞. 人工光植物工厂技术装备与产业发展的战略思考[J]. 中国农业科技导报, 2018, 20(9): 32-39.
	LIU W K, LIU Y F. Developmental strategies for technology & equipment and industry of plant factory with artificial lighting[J]. Journal of Agricultural Science and Technology, 2018, 20(9): 32-39. (in Chinese with English abstract)
[2]	SAENGTHARATIP S, JOSHI J, ZHANG G, et al. Optimal light wavelength for a novel cultivation system with a supplemental upward lighting in plant factory with artificial lighting[J]. Environment Control in Biology, 2021, 59(1): 21-27. DOI URL
[3]	孙洪助, 王虹, 沈建华, 等. 不同比例红蓝光对生菜种子萌发及幼苗生长的影响[J]. 浙江农业学报, 2014, 26(3): 603-608.
	SUN H Z, WANG H, SHEN J H, et al. Effects of different proportions of red and blue light on seed germination and seedling growth of lettuce[J]. Acta Agriculturae Zhejiangensis, 2014, 26(3): 603-608. (in Chinese with English abstract)
[4]	MORIMOTO T, TORII T, HASHIMOTO Y. Optimal control of physiological processes of plants in a green plant factory[J]. Control Engineering Practice, 1995, 3(4): 505-511. DOI URL
[5]	刘霓红, 蒋先平, 程俊峰, 等. 国外有机设施园艺现状及对中国设施农业可持续发展的启示[J]. 农业工程学报, 2018, 34(15): 1-9.
	LIU N H, JIANG X P, CHENG J F, et al. Current situation of foreign organic greenhouse horticulture and its inspiration for sustainable development of Chinese protected agriculture[J]. Transactions of the Chinese Society of Agricultural Engineering, 2018, 34(15): 1-9. (in Chinese with English abstract)
[6]	刘文科, 杨其长. LED植物光质生物学与植物工厂发展[J]. 科技导报, 2014, 32(10): 25-28.
	LIU W K, YANG Q C. Development status of plant photobiology with LED monochromatic light and plant factory[J]. Science & Technology Review, 2014, 32(10): 25-28. (in Chinese with English abstract)
[7]	刘庆鑫, 方慧, 李宗耕, 等. 自然光植物工厂多层立体栽培补光对生菜产量和品质的影响[J]. 中国农业大学学报, 2019, 24(1): 92-99.
	LIU Q X, FANG H, LI Z G, et al. Effects of increased stereo multi-layer artificial light in natural light plant factory on yield and quality of lettuce[J]. Journal of China Agricultural University, 2019, 24(1): 92-99. (in Chinese with English abstract)
[8]	HENDRAWAN Y, RIZA D F A, MURASE H. Applications of intelligent machine vision in plant factory[J]. IFAC Proceedings Volumes, 2014, 47(3): 8122-8127. DOI URL
[9]	张海辉, 杨青, 胡瑾, 等. 可控LED亮度的植物自适应精准补光系统[J]. 农业工程学报, 2011, 27(9): 153-158.
	ZHANG H H, YANG Q, HU J, et al. Self-adaptive and precise supplementary lighting system for plant with controllable LED intensity[J]. Transactions of the Chinese Society of Agricultural Engineering, 2011, 27(9): 153-158. (in Chinese with English abstract)
[10]	KIM H S, LIM J H. Energy saving of plant cultivation system using LED control system based on ultrasonic sensor[J]. Informatics in Control, Automation and Robotics, 2011, 132: 615-623.
[11]	符民, 文尚胜, 钟惠婷, 等. 基于Taguchi方法的LED植物光源优化设计[J]. 发光学报, 2017, 38(7): 953-959.
	FU M, WEN S S, ZHONG H T, et al. Optimum design of LED plant light source based on Taguchi method[J]. Chinese Journal of Luminescence, 2017, 38(7): 953-959. (in Chinese with English abstract) DOI URL
[12]	LI K, LI Z P, YANG Q C. Improving light distribution by zoom lens for electricity savings in a plant factory with light-emitting diodes[J]. Frontiers in Plant Science, 2016, 7: 92.
[13]	张立国, 李晓松, 肖磊, 等. 基于单目视觉的四旋翼飞行器目标跟踪算法研究[J]. 计量学报, 2018, 39(3): 342-347.
	ZHANG L G, LI X S, XIAO L, et al. Research on target tracking algorithm of the quadrotor aircraft based on monocular vision[J]. Acta Metrologica Sinica, 2018, 39(3): 342-347. (in Chinese with English abstract)
[14]	李伟斌, 马洪林, 易贤, 等. 基于色彩空间变换的彩色图像分割方法[J]. 计算机工程与应用, 2019, 55(9): 162-167.
	LI W B, MA H L, YI X, et al. Segmentation method for color image based on transformed color space[J]. Computer Engineering and Applications, 2019, 55(9): 162-167. (in Chinese with English abstract)
[15]	闫建伟, 苏小东, 赵源, 等. 基于图像特征的小麦胚芽鞘识别[J]. 浙江农业学报, 2019, 31(2): 326-332.
	YAN J W, SU X D, ZHAO Y, et al. Wheat germ sheath recognition based on image features[J]. Acta Agriculturae Zhejiangensis, 2019, 31(2): 326-332. (in Chinese with English abstract)
[16]	LIU Y, JIANG Z S, HUANG H Z, et al. A TEO-based modified Laplacian of Gaussian filter to detect faults in rolling element bearing for variable rotational speed machine[J]. IET Science, Measurement & Technology, 2021, 15(2): 193-203.
[17]	李健, 刘孔宇, 任宪盛, 等. 基于自适应阈值的Canny算法在MRI边缘检测中的应用[J]. 吉林大学学报(工学版), 2021, 51(2): 712-719.
	LI J, LIU K Y, REN X S, et al. Application of Canny algorithm based on adaptive threshold in MR image edge detection[J]. Journal of Jilin University (Engineering and Technology Edition), 2021, 51(2): 712-719. (in Chinese with English abstract)
[18]	尹超, 郭晓金, 田肖, 等. 结构纹理分离的对比度和细节增强[J]. 计算机应用研究, 2018, 35(12): 3832-3835.
	YIN C, GUO X J, TIAN X, et al. Contrast and detail enhancement based on structure and texture[J]. Application Research of Computers, 2018, 35(12): 3832-3835. (in Chinese with English abstract)
[19]	李颀, 胡艺聪, 武付闯. 基于图像处理的育苗箱环境控制系统[J]. 浙江农业学报, 2017, 29(11): 1912-1919.
	LI Q, HU Y C, WU F C. Environment control system of seedling box based on image processing[J]. Acta Agriculturae Zhejiangensis, 2017, 29(11): 1912-1919. (in Chinese with English abstract)
[20]	王君, 杨其长, 仝宇欣. 红蓝光下光强对生菜电能、光能利用效率及品质的影响[J]. 中国农业大学学报, 2016, 21(8): 59-66.
	WANG J, YANG Q C, TONG Y X. Effects on electric-energy and light use efficiency and quality for lettuce under different light intensities supplied with red light and blue light[J]. Journal of China Agricultural University, 2016, 21(8): 59-66. (in Chinese with English abstract)
[21]	季方, 甘佩典, 刘男, 等. LED光质和日累积光照量对番茄种苗生长及能量利用效率的影响[J]. 农业工程学报, 2020, 36(22): 231-238.
	JI F, GAN P D, LIU N, et al. Effects of LED spectrum and daily light integral on growth and energy use efficiency of tomato seedlings[J]. Transactions of the Chinese Society of Agricultural Engineering, 2020, 36(22): 231-238. (in Chinese with English abstract)

基于OpenCV的低能耗植物工厂照明系统设计与试验

Design and experiment of energy-saving lighting system for plant factory based on OpenCV

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

图/表 13

参考文献 21

相关文章 3

编辑推荐

Metrics

本文评价

[1]	秦宽, 梁小龙, 曹成茂, 方梁菲, 吴正敏, 葛俊. 茶园节能型开沟刀设计与试验[J]. 浙江农业学报, 2021, 33(7): 1320-1328.
[2]	刘志, 贺正, 苗芳芳, 贾彪. 基于无人机的水肥一体化玉米出苗率估算方法与试验[J]. 浙江农业学报, 2019, 31(6): 977-985.
[3]	王彦翔, 张艳, 杨成娅, 孟庆龙, 尚静. 基于深度学习的农作物病害图像识别技术进展[J]. 浙江农业学报, 2019, 31(4): 669-676.