本文所要探討的是拍撲翼的結構強度，在分析過程中，先利用現有的材料去自製一個拍撲翼，而利用拍翅的機構以及實驗的儀器，測量出拍撲翼在拍動時，所得到的應變值。在拍撲翼的翼面所受到的壓力分佈，則是以二元二次的分佈函數去模擬，在本文則是利用反向問題的概念，先使用有限元素軟體ANSYS去建立與自製的拍撲翼相同的模型，再給予數組的分佈力函數進行求解得到應變值，將所得到的資料訓練出一個類神經網路，得到應變值與分佈力函數之關係。此時，即可將實驗測得的應變值，輸入至類神經網路反算得到對映的分佈力函數。

　　The strength analysis of flapping wings is discussed in this thesis. In analysis process, we make the model of the flapping wing by carbon fiber first and measure the strains when it is flapping by some helpful instruments. The distributed pressure function on the flapping wing is using the two-variables quadratic function. Hence, we employ the concept of inverse analysis and construct the same model of our flapping wing by commercial finite element software ANSYS to obtain the strains when the distributed pressure function is given. By using these data obtained by ANSYS, the relations between strains and the coefficients of the distributed pressure function can be trained by using the neural networks. Therefore, the experimental strains can now be inputted to the neural networks we trained to obtain the corresponding distributed pressure function.

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