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    DC electrical circuit protection apparatus and ARC detection method
    1.
    发明授权
    DC electrical circuit protection apparatus and ARC detection method 有权

    公开(公告)号：US11277000B2

    公开(公告)日：2022-03-15

    申请号：US16304398

    申请日：2017-03-24

    申请人： Mitsubishi Electric Corporation

    发明人： Makoto Kanemaru ,  Mitsugi Mori ,  Mitsuru Tsukima

    IPC分类号： H02H3/38 ,  G01R31/08 ,  G01R31/12 ,  H02H1/00 ,  H02H3/10 ,  H02H3/16 ,  H02H3/07 ,  H02H3/02 ,  H02H3/00 ,  H02H3/06

    摘要： In a DC feed system configured by a plurality of DC electrical circuits being combined, when an arc fault occurs, it is difficult to identify a DC electrical circuit in which an arc has occurred. For this reason, a DC electrical circuit protection apparatus includes: a plurality of DC electrical circuits, each of which has a current sensor provided in at least one of a positive or a negative electrical path and has arc noise absorbing mechanism on the upstream side of the current sensor; and an arc detection device which compares respective arc noise signal strengths of the DC electrical circuits from current signals detected by the current sensors of the DC electrical circuits, and based on the signal strengths, identifies a circuit in which an arc has occurred, wherein a DC electrical circuit in which an arc has occurred is identified.

    Abnormality diagnosis device, abnormality diagnosis method, and abnormality diagnosis system
    2.
    发明授权
    Abnormality diagnosis device, abnormality diagnosis method, and abnormality diagnosis system 有权

    公开(公告)号：US11953555B2

    公开(公告)日：2024-04-09

    申请号：US16644168

    申请日：2017-10-24

    申请人： Mitsubishi Electric Corporation

    发明人： Makoto Kanemaru ,  Takuya Ohkubo ,  Sota Sano ,  Akira Satake ,  Satoru Terashima

    IPC分类号： G01R31/34 ,  H02H7/08 ,  H02P29/024

    CPC分类号： G01R31/343 ,  H02H7/08 ,  H02P29/027

    摘要： An abnormality diagnosis device includes: a data acquirer to acquire a current waveform and a driving frequency of an electric motor; a storage which stores a combination of a current value of the current waveform and the driving frequency at an identical time by the data acquirer; a data determiner to determine whether or not a current value of the current waveform and the driving frequency as a diagnosis target at an identical time by the data acquisition match the combination stored in the storage; an analyzer to perform frequency analysis for the current waveform determined to be matched by the data determiner, to extract sideband waves, and calculate a spectrum intensity of the sideband waves; and an abnormality diagnosis processor to make a diagnosis that abnormality has occurred, when the spectrum intensity of the sideband waves is equal to or greater than a threshold.

    Abnormality diagnosis device and abnormality diagnosis method
    4.
    发明授权
    Abnormality diagnosis device and abnormality diagnosis method 有权

    公开(公告)号：US11527987B2

    公开(公告)日：2022-12-13

    申请号：US17291278

    申请日：2018-12-27

    申请人： Mitsubishi Electric Corporation

    发明人： Hiroshi Inoue ,  Makoto Kanemaru ,  Junji Hori ,  Tomoaki Takewa ,  Takuma Sasai

    IPC分类号： H02P29/028 ,  H02P29/40

    摘要： Provided is an abnormality diagnosis device including: a physical quantity measurement processor configured to acquire, as time-series data, a physical quantity of an electric motor or a load; a feature parameter calculation processor configured to calculate feature parameters; a correlation function creation processor configured to create a correlation function for two or more feature parameters, and calculate a correlation coefficient corresponding to a measurement result of the physical quantity that changes depending on an abnormality occurrence state; a database configured to store in advance reference data in which a remaining time until a failure is caused and the correlation coefficient are associated with each other; and a diagnosis processor configured to extract from the reference data the remaining time corresponding to the correlation coefficient, and identify the remaining time until the electric motor or the load causes a failure or a part that has caused a failure.

    Method for estimating bearing fault severity for induction motors
    5.
    发明授权
    Method for estimating bearing fault severity for induction motors 有权

    公开(公告)号：US11099101B2

    公开(公告)日：2021-08-24

    申请号：US16515564

    申请日：2019-07-18

    申请人： Mitsubishi Electric Research Laboratories, Inc. ,  Mitsubishi Electric Corporation

    发明人： Bingnan Wang ,  Shen Zhang ,  Makoto Kanemaru ,  Chungwei Lin ,  Dehong Liu ,  Koon Hoo Teo

    IPC分类号： G01M13/04 ,  G01R31/34 ,  H02H7/08

    摘要： A system for estimating a severity of a bearing fault in an induction motor, uses a set of filters and a set of quantitative models designed for a set of fault frequencies. The system, upon receiving the measurements of the stator current, extracts the first fault current from the stator current using the first filter, determine the first mutual inductance variation from the first fault current using the first quantitative model, and classify the first mutual inductance variation with the fault severity classifier to determine the severity of a first type of fault in the induction motor. Similarly, the system classifies a second type of fault using the second filter and the second quantitative model. The system outputs one or combination of the severity of the first type of fault in the induction motor and the severity of the second type of fault in the induction motor.

    Method for Estimating Bearing Fault Severity for Induction Motors
    6.
    发明申请
    Method for Estimating Bearing Fault Severity for Induction Motors 审中-公开

    公开(公告)号：US20200348207A1

    公开(公告)日：2020-11-05

    申请号：US16515564

    申请日：2019-07-18

    申请人： Mitsubishi Electric Research Laboratories, Inc. ,  Mitsubishi Electric Corporation

    发明人： Bingnan Wang ,  Shen Zhang ,  Makoto Kanemaru ,  Chungwei Lin ,  Dehong Liu ,  Koon Hoo Teo

    IPC分类号： G01M13/04

    摘要： A system for estimating a severity of a bearing fault in an induction motor, uses a set of filters and a set of quantitative models designed for a set of fault frequencies. The system, upon receiving the measurements of the stator current, extracts the first fault current from the stator current using the first filter, determine the first mutual inductance variation from the first fault current using the first quantitative model, and classify the first mutual inductance variation with the fault severity classifier to determine the severity of a first type of fault in the induction motor. Similarly, the system classifies a second type of fault using the second filter and the second quantitative model. The system outputs one or combination of the severity of the first type of fault in the induction motor and the severity of the second type of fault in the induction motor.