Motor control device
    6.
    发明授权

    公开(公告)号:US09929687B2

    公开(公告)日:2018-03-27

    申请号:US15315044

    申请日:2015-10-08

    Inventor: Hiroko Yoneshima

    Abstract: A motor control device includes: a motor; an inverter; and a control device. The control device includes: a detection device detecting a rotational position and a revolution speed of the motor; a positioning control device for a rotor; a deceleration device for the motor; and a determination device for the revolution speed of the motor. When the revolution speed is higher than or equal to the first predetermined revolution speed, the motor control device starts controlling the motor to rotate at the target speed, according to the rotational position, without executing the positioning control. When the revolution speed is lower than the first predetermined revolution speed and higher than or equal to the second predetermined revolution speed, the deceleration device decelerates the motor. When the revolution speed is lower than the second predetermined revolution speed, the positioning control device starts executing the positioning control.

    DEVICE HEALTH ESTIMATION BY COMBINING CONTEXTUAL INFORMATION WITH SENSOR DATA

    公开(公告)号:US20170167993A1

    公开(公告)日:2017-06-15

    申请号:US14969984

    申请日:2015-12-15

    CPC classification number: G01N25/72 G05B13/00 G05B23/024

    Abstract: A method and system for detecting fault in a machine. During operation, the system obtains control signals and corresponding sensor data that indicates a condition of the machine. The system determines consistent time intervals for each of the control signals. During a consistent time interval the standard deviation of a respective control signal is less than a respective predetermined threshold. The system aggregates the consistent time intervals to determine aggregate consistent intervals. The system then maps the aggregate consistent intervals to the sensor data to determine time interval segments for the sensor data. The system may generate features based on the sensor data. Each respective feature is generated from a time interval segment of the sensor data. The system trains a classifier using the features, and applies the classifier to additional sensor data indicating a condition of the machine over a period of time to detect a machine fault.

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