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Recognizing Similarities in Automatic Transmissions of Vehicles by Using Time Series Data and Autoencorders AISIN AW CO., LTD
- Format:
- Conference/Event
- Author/Creator:
- Kawakami, Takefumi, author.
- Conference Name:
- WCX SAE World Congress Experience (2019-04-09 : Detroit, Michigan, United States)
- Language:
- English
- Physical Description:
- 1 online resource
- Place of Publication:
- Warrendale, PA SAE International 2019
- Summary:
- AbstractIn recent years, the development time of vehicles has further accelerated, and automation of the development is an urgent task. One example of time wasting tasks is gear-shift calibration. For this purpose, Kawakami and others have studied OK/NG classification of shift quality by using neural networks. However, their classifiers have a problem in versatility over different AT hardwares. In this paper, we develop autoencoders to realize similar/not-similar classification on three AT hardwares of vehicles. These hardwares have different lock-up multi/single-plate clutch structures. Experimental results show that the performance of similar/not-similar classification is high in terms of AUC
- Notes:
- Vendor supplied data
- Publisher Number:
- 2019-01-0343
- Access Restriction:
- Restricted for use by site license
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