Abstract
In order to improve the detection efficiency of egg quality on-line detection mechanism, and reduce eggshell breakage rate in the detection because of mechanical vibration generated, the modal analysis of the detection mechanism key components of the double circular arc cylinder and frame was carried out, by using the finite element analysis software ANSYS, and then it was tested by experiment. The results showed that the vibration frequency of the detection mechanism, lower than 971.28 Hz, could not cause vibration of double circular drum group, and this helped to reduced the eggshell breakage rate. Moreover, the frame frequency was found relatively low and easy to cause vibration, so the vibration reduction design of the detection mechanism was mainly based on the frame. It was a reliable and rapid method to analyze the vibration characteristics of mechanism by using the modal analysis of finite element software ANSYS, and this laid the foundation for the vibration analysis and optimum design of other components of the detection mechanism.
Publication Date
8-28-2017
First Page
76
Last Page
78,84
DOI
10.13652/j.issn.1003-5788.2017.08.017
Recommended Citation
Shuanqiao, WANG and Zhihong, YU
(2017)
"Study on eggshell breakage rate of egg detection mechanism based on FEM,"
Food and Machinery: Vol. 33:
Iss.
8, Article 17.
DOI: 10.13652/j.issn.1003-5788.2017.08.017
Available at:
https://www.ifoodmm.cn/journal/vol33/iss8/17
References
[1] 司伟达, 韩兆鹏, 刘旭明. 鲜禽蛋分级和质量控制技术研究现状[J]. 中国家禽, 2013, 35(8): 44-48.
[2] 姜松, 漆虹, 王国江, 等. 禽蛋基本特性参数分析与试验[J]. 农业机械学报, 2012, 43(4): 137-141.
[3] 孙力, 蔡健荣, 林颢, 等. 基于声学特性的禽蛋裂纹实时在线检测系统[J]. 农业机械学报, 2011, 42(5): 183-186.
[4] 张超, 卢伟, 丁天华. 禽蛋品质无损检测的研究现状及其展望[J]. 食品工业科技, 2015, 36(18): 381-384.
[5] 介邓飞, 王晓婧, 魏萱. 基于近红外光谱禽蛋新鲜度无损检测模型研究[J]. 食品与机械, 2016, 32(8): 115-118.
[6] 吴佳, 汤全武, 史崇升, 等. 马铃薯品质无损检测技术研究进展[J]. 食品与机械, 2014, 30(3): 257-260.
[7] 王栓巧. 基于机器视觉的种蛋品质检测系统研究[D]. 呼和浩特: 内蒙古农业大学, 2009: 9.
[8] 余坚勇, 郝利民, 钱平, 等. 基于有限元分析的浅盘食品包装容器设计[J]. 食品与机械, 2011, 27(2): 94-97.
[9] 李硕, 肖书浩, 刘静. 基于逆向工程和ANSYS的鸡蛋蛋壳受力分析[J]. 机械制造, 2015, 53(10): 25-28.
[10] 丁天华, 卢伟, 张超, 等. 基于MUSIC功率谱和CPNN的鸡蛋散黄无损检测方法[J]. 南京农业大学学报, 2015, 38(6): 1 009-1 015.