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基于計算機(jī)視覺與敲擊振動融合技術(shù)檢測鴨蛋殼強(qiáng)度
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Duck Egg’s Shell Intensity Model Based on Fusion of Computer Vision and Impact Excitation
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    通過對敲擊振動特征頻率矩陣變異系數(shù)和測定有裂紋蛋殼強(qiáng)度的探索性分析,獲得鴨蛋殼強(qiáng)度特征頻率的分離閾值λ=0.02。通過傳感器數(shù)據(jù)關(guān)聯(lián),確定了進(jìn)入模型的特征變量。采用后向消去法進(jìn)行多元線性回歸建立了無裂紋鴨蛋殼強(qiáng)度預(yù)測模型,結(jié)合蛋殼強(qiáng)度分離閾值得出基于特征層多傳感器融合鴨蛋殼強(qiáng)度的系統(tǒng)模型。驗(yàn)證性試驗(yàn)表明該模型有較好適應(yīng)性,對于各種顏色、形態(tài)鴨蛋的蛋殼強(qiáng)度都有較好的預(yù)測效果,誤差均值小于3.1%,誤差標(biāo)準(zhǔn)差為

    Abstract:

    0.003。Computer vision analysis and impact excitation frequency analysis were used to construct the duck egg’s intensity model. By the analysis in the CV (coefficient of variation) of the duck egg’s impact excitation frequency and the analysis of the crack egg’s intensity, the threshold value (λ=0.02) which can be applied to distinguish the duck egg intensity at the level of 1MPa (confidence at the level of 95%) was obtained. Then the characteristic variables were entered into the model. The backward elimination procedure was used to perform multi-dimensional linear regression in order to establish the forecast model of the non-crack duck eggs’ shell intensity. Combined with the threshold value which had been obtained, the system model of duck egg’s shell intensity based on the multi-sensor fusion can be obtained. The confirmation experiment indicates that the model had good adaptability on duckeggs with different color and mass, the model shows high accuracy (the mean of forecast error is 3.1%) as well as good stability (the standard deviation of forecast error is 0.003). 

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劉鵬,屠康,潘磊慶.基于計算機(jī)視覺與敲擊振動融合技術(shù)檢測鴨蛋殼強(qiáng)度[J].農(nóng)業(yè)機(jī)械學(xué)報,2009,40(8):175-180. Duck Egg’s Shell Intensity Model Based on Fusion of Computer Vision and Impact Excitation[J]. Transactions of the Chinese Society for Agricultural Machinery,2009,40(8):175-180.

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