臺灣博碩士論文加值系統

本研究是利用碰擊試驗的方式，對水果進行破壞性果肉碰擊損傷及非破壞性成熟度分級檢測，首先利用一改製的單擺式衝擊試驗機進行平板（曲率半徑無限大）衝錘探頭碰擊蘋果，改變不同的動量及儲藏溫度，由力量-時間波形圖得到碰擊時的最大撞擊力Fp及撞擊接觸時間tc，碰擊後量測蘋果的損傷深度及損傷體積，並計算蘋果損傷的吸收能量；接著使用保麗龍網、發泡棉及瓦楞紙三種常見的緩衝包裝材料，探討其緩衝效果以作為水果選擇緩衝包裝材料的參考依據；進一步探討不同曲率半徑的衝錘探頭，在不同的動量及儲藏溫度下對蘋果碰擊損傷的影響。其次自行設計組裝一套番石榴自由落體碰擊檢測裝置和一套鋼珠自由掉落碰擊檢測裝置，對番石榴進行成熟度檢測，藉由碰擊試驗得到力量-時間波形圖，選擇有顯著性的碰擊參數，使用鑑別分析及類神經網路分析來判別番石榴成熟度分級的準確率。
實驗分析結果顯示，使用平板衝錘探頭進行碰擊試驗對蘋果所造成的碰擊損傷可得以下結論，在無緩衝材料下，當動量越大時，最大碰擊力Fp就越高，蘋果損傷深度及損傷體積也隨之增大，且蘋果吸收能量E2隨之增加；在有發泡棉、保麗龍網和瓦楞紙緩衝材料下，以發泡棉作為緩衝材料時，蘋果吸收能量最高，緩衝材料吸收能量最低，緩衝效果較其他兩緩衝材料差。在4℃冷藏下，使用瓦楞紙做為緩衝材料時緩衝效果最好，在三種動量都找不到碰擊損傷；而在室溫下，在動量10°時，使用保麗龍網當緩衝材料時有較佳的緩衝效果。最大碰擊力Fp隨著衝錘探頭曲率半徑的增加而提高，而碰擊接觸時間tc隨著衝錘探頭曲率半徑的增大而減少，曲率半徑R32衝錘探頭的損傷體積比曲率半徑R24和R40衝錘探頭大，應是R32的曲率半徑和蘋果的半徑相近緣故。
在番石榴自由落體檢測番石榴成熟度試驗中，取採摘後時間第一、三、五、七天的前兩個彈跳回波資料做分析，以彈性常數Ki作為分級指標，使用三個分類顯著參數，進行鑑別分析後其分級準確率為77.4%。；以採摘後時間作為分級指標時，使用五個分類顯著參數，進行鑑別分析後其分級準確率為84.21%。取採摘後時間第一、三、五天的前三個彈跳回波資料做分析，以彈性常數Ki作為分級指標時，使用四個分類顯著指標，進行鑑別分析後其分級準確率為72.69%。；以採摘後時間作為分級指標時，使用五個分類顯著參數，進行鑑別分析後其分級準確率為93.76%。
在番石榴鋼珠彈跳檢測番石榴成熟度的試驗中，以彈性常數Ki作為分級指標時，使用四個分類顯著指標，進行類神經網路分級，當訓練1500次後其分級準確率為74.51%；訓練2000次後其分級準確率為75.49%。以採摘後時間第一、三、五天作為分級指標時，使用四個分類顯著指標，進行類神經網路分級，訓練1500次後其分級準確率為69.23%；訓練2000次後其分級準確率為74.34%。由壓縮試驗結果可驗證輕微碰擊檢測番石榴成熟度分級是一種非破壞性的實驗。

A manner of impact test was used in this study, the volume of bruise damage was estimated in destructive test and grade the maturity of fruits in non-destructive test. First of all, the apples were impacted by a restructured simple pendulum device with plate hammer (infinite of curvature radius). The impact test for apple was conduct for different the rise angle and storage temperature. The peak force Fp and the contact time tc from the force-time waveform graph could be obtained, the depth and volume of bruise damage would be measured and absorbed energy of the apple bruise damage would be also calculated. Three kinds of packing cushion, styrofoam net, cotton and corrugated paper were used to investigate the effect of cushion. The result could be used as a basis of the selection of packing cushion for fruit. The effect of pendulum hammer with different curvature radius was explored further in different angles and temperatures. Furthermore, self-design a fruit a drop freely device and a steel ball drop freely device were estimated maturity classification for the guava. According to Step Regression Analysis, the significantly different of parameters from force-time waveform graph of the impact experiment were selected. The maturity classification of guava was determined by the Discriminate Analysis and Artificial Neural Network.
The results from the impact experiment showed that the impact bruise of apple used plate pendulum hammer can get the conclusions as following. With the non-cushion material, when the rise angle was raised increase, the peak force would be more increase. Not only the bruise damage depth and bruise volume of apple increased, but also the absorbed energy of apple bruises damage volume increased. However, the impact time was not significantly different at room temperature, but the impact time was significantly different between 10° and 20° angle at 4 ℃ temperature. For three kinds of packing cushion material, there was the largest absorbed energy of apple and lowest absorbed energy of the cushion material for the cotton, the buffer effect of the cotton was poor than the other cushion material. It was not found any damage for the corrugated paper used in anyone rise angle and have the best buffer effect at 4 ℃ temperature, but there was better buffer effect for the styrofoam net used in 10° rise angle at room temperature. With the curvature radius of pendulum hammer increasesd, the peak force Fp increase and contact time tc decreased. The bruise damage volume of apple show that the R32 of curvature radius pendulum probe was higher than the R24 and the R40 of curvature radius, it is the reason that the R32 of curvature radius is similar with that of the apple.
In the guava drop freely experiment of maturity classification, the data of former two rebound waves in the 1st 、3rd、5th and 7th of the postharvest time were obtained. The elasticity constant Ki was used as a classification index, three significantly different parameters were selected to conduct the discriminate analysis. The accuracy of maturity classification was 77.4 %. When the post-harvest time was used as a classification index, five significantly different parameters were selected to conduct the discriminate analysis. The accuracy of maturity classification was 84.21%. The data of former three rebound waves in the 1st、3rd and 5th of the postharvest time were obtained. The elasticity constant Ki was used as a classification index, four significantly different parameters were selected to conduct the discriminate analysis. The accuracy of maturity classification was 72.6 %. When the post-harvest time was used as a classification index, five significantly different parameters were selected to conduct the discriminate analysis. The accuracy of maturity classification was 93.76 %.
In the experiment of the steel ball drop freely to estimate maturity of the guava, The elasticity constant Ki was used as a classification index, four significantly different parameters were selected to conduct the artificial neural network. The accuracy of maturity classification was 74.51 % when artificial neural network was trained 1500 times and 75.49 % when artificial neural network was trained 2000 times. While the post-harvest time , 1st、3rd and 5th times, were used as a classification index, , four significantly different parameters were selected to conduct the artificial neural network. The accuracy of maturity classification was 69.23 % when artificial neural network was trained 1500 times and 74.34 % when artificial neural network was trained 2000 times. It could be approved a non-destructive detection for slight impact test from the compression test of guava.

摘 要 I
ABSTRACT III
目錄 V
表目錄 X
圖目錄 XIII
附錄目錄 XVI
符號說明 XIX
第一章 前言 1
1-1研究背景 1
1-2研究動機 3
1-3研究目的 4
第二章 文獻探討 5
2-1蘋果碰擊試驗 5
2-2水果成熟度 11
第三章 實驗原理 15
3-1碰擊理論 15
3-1-1蘋果碰擊試驗-碰擊裝置原理 15
3-1-2蘋果碰擊試驗-時域圖分析 20
3-1-3番石榴成熟度試驗-輕微碰擊裝置原理 22
3-1-4番石榴成熟度試驗-時域圖分析 25
3-2 類神經網路 32
3-3阿基米德原理 33
3-4堅實度(Firmness)量測 33
3-5 濕基含水率Mc(Moisture Content) 34
3-6 資料分析 35
3-6-1變異數分析 35
3-6-2 Scheffe 多重比較檢定 37
3-6-3 集群分析 38
3-6-4鑑別分析 39
第四章 實驗材料與設備與方法 41
4-1測試材料 41
4-2儀器設備 43
4-2-1 基本物理性質測量儀器及設備 43
4-2-2 力量感測擷取設備 46
4-2-3 蘋果碰擊試驗設備 48
4-2-4 番石榴自由落體碰擊試驗設備 51
4-2-5 番石榴鋼珠掉落碰擊試驗設備 52
4-3分析軟體 53
4-3-1 μ-MUSYCS-SPARTAN V2.0版軟體 53
4-3-2碰擊訊分析軟體FAMOS 4.0 53
4-3-3 物性分析軟體Texture Expert 54
4-3-4 SAS分析軟體 55
4-4 實驗方法 56
4-4-1蘋果碰擊損傷試驗 56
4-4-2番石榴成熟度輕微碰擊試驗 64
第五章 結果與討論 69
5-1 蘋果破壞性碰擊檢測試驗 69
5-1-1蘋果基本物性 69
5-1-2緩衝材料基本物性 72
5-1-3蘋果碰擊損傷和緩衝材料緩衝效果之比較 73
5-1-3-1 不同動量時各種緩衝材料之最大碰擊力Fp 73
5-1-3-2 不同動量時各種緩衝材料之碰擊接觸時間tc 75
5-1-3-3 不同動量時各種緩衝材料之損傷深度 77
5-1-3-4 不同動量時各種緩衝材料之損傷體積Λ 78
5-1-3-5 不同動量時各種緩衝材料之蘋果吸收能量E2 82
5-1-3-6 不同動量時各種緩衝材料之緩衝材料吸收能量E3 84
5-1-4不同曲率半徑衝錘探頭碰擊接觸情形下蘋果碰擊損傷之比較 88
5-1-4-1 不同動量時各種曲率半徑衝錘探頭之最大碰擊力Fp 88
5-1-4-2 不同動量時各種曲率半徑衝錘探頭之碰擊接觸時間tc 89
5-1-4-3 不同動量時各種曲率半徑衝錘探頭之損傷深度 91
5-1-4-4 不同動量時各種曲率半徑衝錘探頭之損傷體積Λ 93
5-1-4-5 不同動量時各種曲率半徑衝錘探頭之蘋果吸收能量E2 95
5-2番石榴非破壞性碰擊檢測成熟度試驗 98
5-2-1番石榴基本物性 98
5-2-2番石榴自由落體碰擊試驗 100
5-2-2-1 二個彈跳回波分析 100
5-2-2-2 三個彈跳回波分析 105
5-2-2-3 恢復係數比較 109
5-2-2-4 番石榴壓縮試驗 110
5-2-3番石榴鋼珠彈跳碰擊試驗 111
5-2-3-1 鋼珠自由落體碰擊力量 119
第六章 結論與建議 120
6-1 結論 120
6-2 未來展望與建議 122
參考文獻 123

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