抄録
This paper proposes a method of inverse analysis for identification of an impact load using selected strain data. Taking the dynamic behavior of structure under the impact load is comparatively easy if many sensors and high precision measuring devices are available. On the other hand, if the dynamic behavior can be identified by a few strain data with lower accuracy, the method has advantages to measuring cost and efficiency. In our proposed inverse analysis, the fuzzy clustering is used for selecting and picking up the strain data containing error for the neural network learning. As a result, it is shown that the proposed method using fuzzy clustering has an advantage on the inverse analysis for some margin of error.
