電気学会論文誌D(産業応用部門誌)
Online ISSN : 1348-8163
Print ISSN : 0913-6339
ISSN-L : 0913-6339
139 巻 , 2 号
選択された号の論文の28件中1~28を表示しています
特集:ドローンとロボット組み込み/サスティナブルシステム
特集論文
論文
  • 近藤 稔
    2019 年 139 巻 2 号 p. 199-205
    発行日: 2019/02/01
    公開日: 2019/02/01
    ジャーナル 認証あり

    The authors are developing a condition monitoring system using vibration analysis and machine learning for the purpose of monitoring the condition of railway vehicle equipment. In railway vehicles, vibrations change due to long-term state change, so long-term data should be used for learning. In this case, it is not practical to use all data, so it is necessary to use only some part of the data, which is called prototype data. Therefore, a prototype selection method based on the neighborhood method is proposed in this paper. As a result of applying the proposed method to the vibration data during the abnormal simulation test, the expected effect was confirmed.

  • 山村 明義, 富井 規雄
    2019 年 139 巻 2 号 p. 206-214
    発行日: 2019/02/01
    公開日: 2019/02/01
    ジャーナル 認証あり

    One of the problems in urban railway lines in the Tokyo area is that minor delays occur quite often during morning rush hours. To prevent these minor delays from occurring, railway companies are attempting to employ various types of countermeasures. However, these countermeasures may be extremely expensive to implement and thus, it is critical to quantitatively evaluate the effectiveness of these countermeasures. To this end, train traffic simulations are used. In this paper, we introduce a novel simulation approach that uses historical train traffic records. In addition, we introduce a concept to determine the arrival times of trains by using primarily the running times whereas in existing research the arrival times were determined from the headway time. We determine a rule to estimate the running times from the interval of trains at the previous station. We validated our simulator by comparing the simulation results with actual train traffic data.

  • 竹内 活徳, 松下 真琴
    2019 年 139 巻 2 号 p. 215-224
    発行日: 2019/02/01
    公開日: 2019/02/01
    ジャーナル 認証あり

    This paper describes the torque and power factor characteristics of SynRMs (synchronous reluctance motors) considering their magnetic energy and co-energy properties. Since the inductance of SynRM varies drastically due to the magnetic saturation effect, it is not easy for us to understand their characteristics, MTPA (maximum torque per ampere) points, and maximum power factor points, quantitatively applying the frame based on equivalent circuit models. In this study, we focused on the fact that the model constructed by the magnetic energy and co-energy gives more simple expressions to the torque and power factor compared to the equivalent circuit model. A SynRM that consists of a stator, same as a benchmark model (D-model) provided by IEEJ, and a rotor with 3 layer flux-barrier was simulated by the electromagnetic field analysis, and its magnetic energy and co-energy were calculated. As a result, three states (I, II and III) were defined depending on degrees of the magnetic saturation level. Then, the output torque per square ampere becomes maximum on a boundary region between state II and III. Further, the current phase of the MTPA point moves to the leading phase side with increasing the current magnitude on state III and the phase of the maximum power factor point is larger than that of the MTPA point. It was clarified that the model constructed by the magnetic energy and co-energy are suitable for discussions on the SynRM characteristics taking account of the magnetic saturation.

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