Abstract

This study concerns a method for evaluating the structural anomaly of F type support information board from acceleration measurements. Acceleration of the top of supports columns were measure about three years. The evaluation f structural anomaly is performed by the autoencoder method.In the method training of the autoencoder is conducted from the normal conditions, and diagnosis of the structural is conducted by estimation error from the data neural network. The diagnoses are performed to the information board at two sites.Data of site B,which has unstable boundary,has high fluctuation to the natural frequency and constant fluctuation to the average of the natural frequency.Data of site A has stable natural frequency.Additionally site B shows a large change in condition after the typhoon passed, and the autoencoder was able to show a significant change in error value. At site A, the values were stable, and although there were temporary fluctuations, the results were not problematic in the long term. Therefore, the method of structural variation detection using the autoencoder is a practical method.

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