特集 「移動体におけるAI応用・異常検知関連技術」
転がり軸受の損傷診断における深層学習の適用
2023 年 31 巻 1 号 p. 30-33
詳細
2023 年 31 巻 1 号 p. 30-33
This paper presents a diagnostic method for rolling bearings using deep learning instead of conventional rule-based diagnostic methods which requires human and time costs. However, deep learning has two major problems. One is difficulty in acquiring large amount of data under the operation with damaged rolling bearings for training, and the other is difficulty in interpreting the diagnostic results. As a solution to these problems, this paper introduces transfer learning and a method to visualize the input data points contributing to the diagnostic results.
