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基于比重和圖像的核桃內部品質無損檢測與分選
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國家自然科學基金項目(52075003、61379080)和山西省回國留學人員科研教研項目(HGKY2019065)


Internal Quality Nondestructive Detection and Sorting Principle of Walnut Based on Density and Digital Image
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    摘要:

    針對核桃內部品質不易檢測、市場上帶殼核桃中劣質核桃比例較高的問題,闡述了根據比重判斷核桃內部品質的原理,提出核桃無損檢測與分選方案。將攝像工具所采集的核桃圖像進行處理、擬合,并估算核桃體積;由稱量平臺獲取核桃質量并換算成重量;根據核桃的比重使不同核桃落入不同容器中,或根據核桃沖擊力與核桃體積的比值,即比重等效參數對核桃進行檢測與分選。在核桃下落到平面時,核桃中分面與平面的夾角相對穩(wěn)定在60°左右,利用這一特點設置正面、側面圖像采集工具,可較準確地獲取核桃的輪廓,從而提高分選精度。該方法可間接檢測核桃內部品質,對核桃殼仁、工作環(huán)境、操作人員均無不良影響。

    Abstract:

    Because the internal quality of walnuts is not easy to detect and a certain proportion of shelled walnuts in supermarkets are of poor quality, the principle of judging the internal quality of walnut according to the density was discussed, and the method and equipment of walnut sorting were studied. The principle of sorting walnuts was as follows: firstly, the walnut image collected by the camera was processed to estimate the volume of walnut;the weight of walnut was obtained;the gas pipe was selected according to the density of walnut to output gas;as a result, different walnuts fell into different containers. Walnut can also be detected and sorted according to density equivalent parameters. Secondly, when the walnut fell to the platform, the angle between its split plane and the platform was always about 60°. With this feature, the front and side cameras can be set in the correct orientation to obtain the contours of walnut, calculate the density of walnut and improve the sorting accuracy. In conclusion, this technology can indirectly detect the internal quality of walnut and promote intelligent and advanced detection. The sorting scheme had no adverse effect on walnut, working environment and operators. With the decrease of camera price, the decline of image processing cost and the improvement of computer operation speed, the cost of walnut sorter would be greatly reduced. The food processing plant would be able to arrange multiple work stations and multiple sorters at the same time, so as to meet the requirements of production efficiency when large quantities of walnut were sorted. Compared with the existing methods, the proposed method can realize nondestructive detection and had high academic value.

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于大國,趙明,SHI Yijun,陳俐華,曹成茂,王俊元.基于比重和圖像的核桃內部品質無損檢測與分選[J].農業(yè)機械學報,2021,52(7):373-378,357. YU Daguo, ZHAO Ming, SHI Yijun, CHEN Lihua, CAO Chengmao, WANG Junyuan. Internal Quality Nondestructive Detection and Sorting Principle of Walnut Based on Density and Digital Image[J]. Transactions of the Chinese Society for Agricultural Machinery,2021,52(7):373-378,357.

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  • 收稿日期:2021-01-28
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  • 在線發(fā)布日期: 2021-07-10
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