樹脂歯車のかみ合い振動データと歯元き裂進展の画像の収集

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  • Acquisition of meshing vibration data and image pictures of crack propagation at tooth root of plastic gears

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<p>The purpose of this study is to generate training data for failure detection by Neural Network, which estimates extent of damage from vibration data of meshing plastic gear pairs. Generally, measurement of meshing vibration with accelerometers installed on a gear system is not difficult. Therefore, one can automatically acquire vibration data under operation and obtain a large amount of vibration data. However, it is not easy to obtain a large amount of evaluation data of the damage extent. Evaluation of the damage extent is possible if the operation has stopped. It means that the procedure of this data acquisition requires additional work, and there is a need for acquiring data of the damage extent, automatically. This research addresses this need by developing an automatic data acquisition system of the meshing vibration and the extent of damage. In the developed system, an accelerometer installed on the housing of bearings is used for acquisition of vibration data, and a high-speed camera observes cracks occurring at the root of the target tooth. The measurement condition was discussed, and the effectiveness of the system was confirmed through experiments. Additionally, a damage index of the crack at the root was proposed, and the computed index was used as labels for training data. Finally, the measured meshing vibration data was visualized for generating training data of Convolutional Neural Network.</p>

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