Fanuc Corporation

Kazunori Iijima

Kazuhiro Satou

Shunpei Tanaka

Yohei Kamiya

Yuusaku Oho

Satoshi Ikai

Kazuomi Maeda

Hiroyasu Asaoka

Keita Hada

Yusaku Oho

Keitarou Inagaki

Liancheng Hu

This abnormality detection device: causes a motor that drives a drive unit at a plurality of rotational speeds to perform a detection operation based on a command for diagnosing the state of the drive unit, acquires, as information indicating the operating state of the drive unit, a control command for the motor driving the drive unit or a feedback signal from the motor driving the drive unit, during the detection operation; analyzes the control instruction for the motor driving the drive unit or the feedback signal from the motor; determines the state of the drive unit based on the result of the analysis, and notifies, based on the determination result, that the state of the drive unit is different from that in normal time.

Abnormality detection device

A diagnostic apparatus of the invention acquires normal data related to an operating state during normal operation of an industrial machine, stores the normal data, generates a learning model by learning based on the stored normal data, and performs an estimation process for normality or abnormality of an operation of the industrial machine using the learning model. The diagnostic apparatus of the invention further generates verification data including at least one piece of abnormal data based on the stored normal data to verify validity of the learning model on receiving a result of the estimation process using the learning model based on the verification data.

Diagnostic apparatus for generating verification data including at least one piece of abnormal data based on normal data

To provide an abnormality monitoring device capable of reducing the size of a mounted device, enabling high-speed response, and achieving high accuracy in detecting abnormality. The abnormality monitoring device includes: at least one filter that extracts state information pertaining to drive of a mechanism of an industrial machine using a motor, as a signal of at least one frequency band; an integrator that integrates an output of the filter in each frequency band; and an abnormality detection unit that detects abnormality based on an integrated value integrated by the integrator. The state information may be control information of the controller that controls the motor or detection information from at least one detector attached to the mechanism.

Abnormality monitoring device, abnormality monitoring method, and control device

A numerical control system detects a state amount indicating a state of an injection operation of an injection molding machine, generates a characteristic amount that characterizes the state of the injection operation from the state amount, and infers an evaluation value of the state of the injection operation from the characteristic amount. The numerical control system detects an abnormal state on the basis of the evaluation value, generates or updates a learning model by machine learning that uses the characteristic amount, and stores the learning model in correlation with a combination of conditions of the injection operation.

Numerical control system

A thermal displacement compensation system detects a state quantity indicating a state of a machine, infers a thermal displacement compensation amount of the machine from the detected state quantity, and performs a thermal displacement compensation of the machine based on the inferred thermal displacement compensation amount of the machine. The thermal displacement compensation system generates a learning model by machine learning that uses a feature quantity, and stores the generated learning model in association with a combination of specified conditions of individual difference of the machine.

Thermal displacement compensation system

The data management device capable of calculating an evaluation index based on the sensor data includes: a sensor data acquisition unit that acquires the sensor data from one or more sensors installed in an industrial machine; an evaluation index calculation unit that calculates the evaluation index with use of the sensor data; a sensor data storage unit that saves the sensor data; and a sensor data deletion unit that deletes the sensor data when a total volume of the sensor data in the sensor data storage unit exceeds an upper limit. The sensor data deletion unit determines saving priority of the sensor data based on a degree of change in the evaluation index and deletes the sensor data in accordance with the saving priority.

Data management device, data management program, and data management method

A controller of a motor that drives a driven body includes: an inertia estimating unit that estimates inertia on the basis of feedback information (torque and current) of the motor; a computing unit that computes an acceleration or deceleration time constant of the motor from the estimation inertia estimated by the inertia estimating unit; a storage unit that stores an inertia difference which is a difference between the estimation inertia and at least one known actual inertia and a time constant difference which is a difference between an actual acceleration or deceleration time constant corresponding to the actual inertia and an acceleration or deceleration time constant calculated on the basis of the estimation inertia; and a correction unit that corrects the acceleration or deceleration time constant calculated by the computing unit using the inertia difference and the time constant difference stored in the storage unit.

Motor controller

A numerical control system detects a state amount indicating an operation state of a machine tool, creates a characteristic amount that characterizes the state of a machining operation from the detected state amount, infers an evaluation value of the operation state of the machine tool from the characteristic amount, and detects an abnormality in the operation state of the machine tool on the basis of the inferred evaluation value. The numerical control system generates and updates a learning model by machine learning that uses the characteristic amount, and stores the learning model in correlation with a combination of conditions of the machining operation of the machine tool.

Numerical control system that detects an abnormality in an operation state

A numerical control system detects a state amount indicating a state of machining operation of a machine tool, creates a characteristic amount that characterizes the state of machining operation from the detected state amount, infers an evaluation value of the state of machining operation from the characteristic amount, and detects an abnormality in the state of machining operation on the basis of the inferred evaluation value. The numerical control system generates and updates a learning model by machine learning that uses the characteristic amount, and stores the learning model in correlation with a combination of conditions of the machining operation of the machine tool.

A controller of a motor includes: an acceleration/deceleration time constant storing unit that stores an acceleration/deceleration time constant; a position command creating unit that creates a position command value based on the acceleration/deceleration time constant; a position detection unit that detects a rotation position of the motor; a speed command creating unit that creates a speed command for the motor on the basis of the position command value and a position detection value detected by the position detection unit; an ideal response computing unit that computes an ideal response from the position command value; and a response comparing unit that compares the ideal response with an actual response detected by the position detection unit. The response comparing unit changes the acceleration/deceleration time constant stored in the acceleration/deceleration time constant storing unit when it is determined that the ideal response does not match the actual response.

Motor controller that uses an acceleration/deceleration time constant of the motor

To provide a transmission control system that can efficiently utilize communication bandwidth upon transmitting measurement data of machines. A transmission control system includes: a numerical control unit that controls operating of machines and acquires operating information; an A/C conversion unit that acquires behavior information measured by way of a sensor provided to the machine; a priority determination unit that determines priority of transmission in accordance with a condition set in advance, based on types and combinations of the operating information and the behavior information; and a bandwidth control unit that controls allocation of communication bandwidth for transmitting the operating information and the behavior information, based on a usage condition of communication bandwidth and the priority.

Transmission control system

A motor control device capable of promptly positioning a driven object at a target position, while suppressing backlash. The motor control device includes an operation command generation section for generating a first operation command and a second operation command for first and second motors to move the driven object; a preload command generation section for generating a first preload command which is added to the first operation command and a second preload command which is added to the second operation command in order that drive axes of the first motor and the second motor provide the driven object forces in opposite directions; and a preload command adjustment section for adjusting the first preload command and the second preload command in order that an absolute value of the above forces is decreased when an operation amount exceeds a predetermined threshold value.

Motor control device and motor control method

A controller is provided with a repeated control unit configured to calculate a position compensation value, based on a position command for each control period of a motor, a position deviation, which is the difference between the position command and a position of the motor, and a parameter for repeated control, and a machine learning device configured to predict the position compensation value calculated by the repeated control unit, and the machine learning device constructs a learning model so as to minimize an objective function based on the position command, the position deviation, and the position compensation value.

Controller and machine learning device

A controller can switch a control system of a motor to a diagnostic operation mode in addition to a normal operation mode. Abnormality of the motor can be detected by taking advantage of the appearance of a clear difference between a feedback value detected when the motor is normal and a feedback value detected when the motor is abnormal if the control system is switched to the diagnostic mode.

Controller

A controller of a motor that drives a driven body, the controller includes: a command generating unit that generates a movement command for the motor; an inertia estimating unit that acquires feedback information of the motor and estimates an inertia on the basis of a predetermined estimation equation; a difference computing unit that computes a change in the inertia changed with machining based on the movement command of the command generating unit; and a comparing unit that compares a difference between the estimation results before and after the machining of the driven body estimated by the inertia estimating unit and the change in the inertia computed by the difference computing unit. the estimation equation of the inertia estimating unit is corrected on the basis of a comparison result of the comparing unit so that the difference between the estimation results matches a computation result obtained by the difference computing unit.

Growing community of inventors

Yamanashi, Japan

Kazunori Iijima