AE法によるTiNセラミックス皮膜の熱衝撃疲労に対する損傷評価

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It is widely used in the industry field, because the ceramics coating materials have many excellent features. However, that clear criterions for evaluation on the character of films have not been determined is made to lower the reliability of the materials. It is necessary to quantitatively grasp the damage conditions and growth in order to determine the criterions. In this study, the technique that quantitatively evaluates the damage conditions of the films with AE method and image processing technique, when the thermal shock was repeatedly given to the film by YAG laser, is proposed. Concretely, the detected AE signals by a laser irradiation are divided into heating and cooling process, and the features of AE signals in the individual process are extracted. And, the features of damage conditions in the irradiation area are quantitatively extracted by the image processing. The detected AE signals in heating process correspond with the image data on the damage before a laser irradiation. Therefore, the neural network for estimating the damage before an irradiation learned the relationship between the signals and the image data. On the other side, the detected AE signals in cooling process correspond with the image data on the damage growth after an irradiation. Therefore, the network for estimating the damage growth after an irradiation learned the relationship between the signals and the image data. From the output of the two networks, it was possible to evaluate the conditions and the growth of the thermal shock damage. The effectiveness of the constructed network became clear by the comparison with the experimental results.
一般社団法人日本機械学会の論文
2002-09-25

AE法によるTiNセラミックス皮膜の熱衝撃疲労に対する損傷評価

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