（2018年4月～2019年3月の期間で集計）＊順位の変動は2018年1月～2018年12月の期間との比較

ディーゼル機関におけるエタノールおよびブタノール混合軽油の燃焼比較

山本 昌平, 坂口 大作, 植木 弘信, 石田 正弘

日本機械学会論文集Ｂ編　（2013）　DOI:10.1299/kikaib.79.380

機械学習を用いたしゅう動面状態監視システムに関する研究

橋本 優花, 本田 知己, 持田 裕介, 杉山 和彦, 中村 由美子, 高東 智佳子

日本機械学会論文集　（2018）　DOI:10.1299/transjsme.18-00275

Machine equipment usually comprises many mechanical elements that can fail because of functional deterioration and friction. For tribo-elements like plane bearings, it is extremely important to diagnose the abnormal conditions and prevent such parts from breakdown caused by wear. However, diagnosing tribo-elements requires expensive diagnostic equipment and expertise. This study aims to propose a cost- and time- effective system that detect the signs of breakdown during equipment operation by using machine learning to identify abnormalities. We conducted wear tests in contaminated oil and used multiple sensors to collect data regarding the friction force, the electrical contact resistance, the acoustic emission (AE) signal, and vibration. An appropriate learning sample was selected using k-fold cross-validation. The electrical contact resistance was found to contribute relatively little to the detection of abnormalities, whereas the friction coefficient contributed greatly. Furthermore, the AE signal and the vibration detected local changes on the sliding surface. Consequently, we found that machine learning can judge whether monitoring data are normal or abnormal.

熱電対による表面温度測定の誤差解析

中村 元

日本機械学会論文集　（2018）　DOI:10.1299/transjsme.18-00216

In surface temperature measurement by thermocouple, measurement error was quantitatively investigated when the temperature measuring junction was adhered to the surface and a part of the lead wire was placed on the isothermal surface. First, heat paths of a thermocouple were modeled by thermal-resistance-network. Unknown parameters related to the contact between the thermocouple and the surface were estimated based on the measured data. The error ratio calculated by the thermal-resistance-network model agreed well to the experimental data both quantitatively and qualitatively, which indicates the validity of this model. Then, an analytic solution was derived with only main heat paths of the thermal-resistance-network. As a result, it was confirmed that even with only main heat paths, a reasonable error-ratio corresponding to the measurement can be obtained. Using the analytic solution, the error-ratio was calculated against various parameters, such as type and diameter of metal wire, gap between the junction and the surface, thermal conductivity of adhesive, lead-length placed on the isothermal surface, and so forth. Based on the analytic results, the effective method was presented to reduce the measurement error.