Fanuc Corporation

Chao Zhi

Takuya Maeda

Kazuhiro Satou

Yohei Kamiya

Keita Hada

Takeshi Sumi

Ryutaro Ishikawa

A collision position estimation device allowing extraction of data related to a torque of a section related to collision of a cushion member includes a machine learning device. The machine learning device includes a state observation unit for observing axis movement data indicating information related to movement of the axis and motor torque data indicating data related to torque of a motor driving the axis as a state variable representing a current state of an environment, a label data acquisition unit for acquiring collision position data indicating the position of the axis during collision of the cushion member as label data, and a learning unit for associating and learning the information related to movement of the axis and the data related to the torque of the motor driving the axis with the position of the axis during collision of the cushion member using the state variable and the label data.

Collision position estimation device and machine learning device

A three-phase reactor according to an embodiment includes a first plate iron core and a second plate iron core disposed oppositely to each other; a plurality of cylindrical iron cores disposed between the first plate iron core and the second plate iron core orthogonally to the first plate iron core and the second plate iron core, the iron cores being disposed rotationally symmetrically with respect to an axis equidistant from central axes of the iron cores, as a rotation axis; and a plurality of coils each wound on each of the iron cores.

Three-phase reactor

A three-phase transformer according to an embodiment includes a first plate iron core and a second plate iron core disposed opposite each other; a plurality of columnar iron cores disposed between the first plate iron core and the second plate iron core so as to be connected to the first plate iron core or the second plate iron core, the number of the columnar iron cores being an integer multiple of 3, the columnar iron cores being disposed rotation-symmetrically with respect to an axis equidistant from central axes of the columnar iron cores; and coils including a plurality of primary coils and a plurality of secondary coils, the number of the primary coils being an integer multiple of 3, the number of the secondary coils being an integer multiple of 3, the primary coils and the secondary coils being wound on the individual columnar iron cores.

Three-phase transformer

A motor includes a rotor including a shaft and a rotor body, a bearing fitted to the shaft and rotatably holding the shaft, a bearing holder arranged on the opposite side to the rotor body so as to hold the bearing, a movement regulation member arranged closer to the rotor body than the bearing and separated to regulate movement of the bearing toward the rotor body, a first engagement part provided at the rotor body to be adjacent to the movement regulation member, a first engagement target part provided at the movement regulation member to be adjacent to the rotor body to be able to be engaged with the first engagement target part, a second engagement part provided at the movement regulation member, a second engagement target part provided at the bearing holder, and a coupling member that couples the bearing holder and the movement regulation member.

Motor and method of manufacturing motor

A machine learning apparatus that learns a condition associated with a predicted life of a motor includes: a state observation unit that observes a state variable composed from at least one of output data of a sensor that detects an operation state of the motor and data relating to presence or absence of a failure in the motor; an actual life data acquisition unit that acquires data relating to an actual life of the motor; and a learning unit that learns the condition associated with the predicted life of the motor in accordance with a training data set created based on a combination of the state variable and the actual life.

Machine learning apparatus and method for learning predicted life of motor, life prediction apparatus and motor system including machine learning apparatus

Growing community of inventors

Yamanashi, Japan

Chao Zhi