Online detecting method for wizened defects of insides of walnuts

Abstract

The invention discloses an online detecting method for wizened defects of insides of walnuts. The online detecting method comprises the following steps: acquiring an image of a walnut under a dynamic condition by using an industrial CCD camera, carrying out binarization processing on the image to obtain a projection area of the walnut, and meanwhile acquiring weight information of the walnut under the dynamic condition by using a weighing sensor and a digital acceleration sensor; carrying out regression analysis on the projection area and the weight of the walnut to obtain a walnut weight prediction model, and calculating by using the walnut weight prediction model to obtain predicted weight of the walnut, and calculating relative error between the predicted weight of the walnut and the real weight of the walnut, judging whether the detected walnut is a wizened walnut or not by using the relative error as a judgment threshold value, and breaking the hull to verify judgment accuracy; carrying out regression analysis on different judgment threshold values and judgment accuracies corresponding to the judgment threshold values; and finally, searching a fitting function between the judgment threshold values and the judgment accuracies by using a golden section method, finding out the optimal judgment threshold value, if the relative error of the weight of the detected walnut is greater than the threshold value, determining that the walnut is the wizened walnut, and if the relative error of the weight of the detected walnut is smaller than or equal to the threshold value, determining that the walnut is an abnormal walnut. Nondestructive detection of wizened walnuts can be realized by the projection area of the images of the walnuts and the weight information of the walnuts only, and the method is simple. Compared with the prior art, the online detecting method has the advantages that detecting cost is greatly reduced, detecting speed and accuracy are improved, and the online detecting method is suitable for factory large-scale production, and can be used for online detection of wizened defects of the insides of various nuts such as the 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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