基于模式分类的喷嘴料液雾滴速度测量研究

doi:10.16180/j.cnki.issn1007-7820.2019.08.007

Abstract

Abstract:

In order to measure the change of velocity after the spray of liquid droplets in the process of tobacco leaf feeding, it provided effective data for the evaluation of the uniformity of tobacco feed. In this experiment, the image of the sprayed droplets were collected from the axial direction of the nozzle, and the collected images were pre-processed and image segmentation. Classifying the segmented droplets by pattern classification, and calculating the velocity of each type of droplet according to the measurement method of high-speed camera imaging. The results shown that the accuracy of the data calculated by the model classification was 95.65%, and the calculated speed error was 4.6%. Both data were within the specified range. The experiment used a high-speed camera to acquire images, and the droplet velocity was calculated by software. Compared with the earlier experimental scheme, reduced measurement equipment prices for low-cost measurements. The measurement method of the pattern classification had higher accuracy, which could provide reliable analysis for subsequent feeding uniformity analysis. The data was more efficient and at the same time played the foundation for the intelligence of data measurement.

Key words: droplet velocity, image preprocessing, image segmentation, pattern classification, low-cost, intelligentialize

CLC Number:

TP391.41

SUN Tengfei,JIANG Honghai. Research on Speed Measurement of Nozzle Material Liquid Droplet Based on Pattern Classification[J].Electronic Science and Technology, 2019, 32(8): 33-37.

Figures/Tables 8

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References 19

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区域	A	B	D
传统统计	6.359 2	4.921 3	3.560 1
模式分类	6.104 8	4.704 7	3.396 3

Research on Speed Measurement of Nozzle Material Liquid Droplet Based on Pattern Classification

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Figures/Tables 8

References 19

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实验批次		1		2		3
分类方式		传统统计	模式分类	传统统计	模式分类	传统统计	模式分类
A 区	1	50	50	61	59	46	43
	2	21	19	15	18	17	16
	3	8	9	5	4	6	7
B 区	4	68	70	87	88	64	65
	5	32	31	24	24	30	32
	6	18	20	13	10	18	16
D 区	7	16	16	25	24	10	11
	8	57	58	36	35	35	34
	9	87	90	90	94	64	60

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