On-line detection method for internal shriveling defects of walnut

Abstract

The invention discloses an on-line detection method for internal shriveled defects of walnuts. An industrial CCD camera is used to obtain images of walnuts under dynamic conditions, and binary processing is performed to obtain the projected area. The weight information of the walnut under the dynamic condition is obtained by combining the acceleration sensor; then the walnut weight prediction model obtained by the regression analysis of the projected area and weight of the walnut is used to calculate the predicted weight of the walnut, and calculate its relationship with the real quality of the walnut The relative error between them, using the relative error as the discriminant threshold to judge whether the detected walnut is shriveled walnut, and crack the shell to verify the discriminative accuracy; then perform regression analysis on different discriminant thresholds and their corresponding discriminative accuracy; finally use the golden section Search the fitting function between the discrimination threshold and the discrimination accuracy to find the best discrimination threshold. If the relative error of the detected walnut weight is greater than this threshold, it will be judged as shriveled walnut. If the relative error of the detected walnut weight is less than or equal to This threshold is used to identify normal walnuts; this method can realize the non-destructive detection of shriveled walnuts only by using the image projection area of ​​walnuts and walnut weight information. The speed and accuracy are suitable for large-scale production in factories, and can be used for online detection of internal shriveled defects of various nuts such as walnuts.

Description

technical field [0001] The invention relates to a method for detecting internal quality of nuts, in particular to an on-line detection method for internal shriveled defects of walnuts. Background technique [0002] Walnut shriveling defect is a common quality problem of intact walnuts in the market, which seriously affects the quality and sales price of commercial walnuts. The main causes of walnut shriveling defects under natural conditions are: the limitation of walnut growth environment conditions, such as low soil nutrients and water shortage; diseases and insect pests during the growth of walnuts, etc. Therefore, the walnut shriveling defect inevitably exists in the whole walnut products sold in the market. At the same time, walnut shriveled defect is different from other defects, it belongs to internal quality problem, shriveled walnut and normal walnut are indistinguishable in appearance. Under natural observation conditions, the appearance of the two is basically t...

AI Technical Summary

Problems solved by technology

Although near-infrared spectroscopy and terahertz spectroscopy are sensitive to moisture and can detect moisture inside walnuts and living pests, etc., there is little water in deteriorating thin-skinned walnuts such as shriveled and empty shells, so near-infrared spectroscopy and terahertz spectroscopy cannot detect Effective detection of deteriorating thin-skinned walnuts such as shriveled and empty shells

Moreover, the cost of the above technical equipment is high, the amount of information and data is large, and the real-time performance is poor, most of which are difficult to meet the requirements of online production

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