Affiliation:
1. SOKEN, INC.
2. TOYOTA MOTOR CORPORATION
Abstract
<div class="section abstract"><div class="htmlview paragraph">Recently, it has become possible to dynamically observe the internal oil behavior using a medical X-ray computed tomography (CT) system, which can capture internal images without disassembling the object being evaluated. The problem in applying the CT method to lubrication analysis is the artifact, like noise, which occurs during dynamic observation. In this paper, we developed a method to reduce this artifact with machine learning by generating artifacts through simulation and using them as supervised data.</div></div>
Publisher
Society of Automotive Engineers of Japan
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