Abstract: A machine learning apparatus determines a control parameter of an active vibration isolation apparatus on which an industrial machine is mounted. The industrial machine includes a movable part, a drive source that drives the movable part, and a drive source control section that controls the drive source to position the movable part at a command position. The machine learning apparatus includes: an acquiring section that acquires, as teacher data, a positional deviation, which is a difference between the command position and an actual position of the movable part; a storage section that stores a learning model that outputs the control parameter corresponding to a state quantity concerning the industrial machine; and a learning section that updates the learning model using the teacher data.

Abstract: In a controller and a machine learning device capable of suppressing an influence of an abnormal value based on noise, etc., the machine learning device included in the controller includes a state observation unit for acquiring input data including at least one of internal data and external data of the manufacturing machine controlled by the controller, an input safety circuit for detecting an abnormality in the input data and outputting safe input data, a machine learning unit for executing learning of a learning model and inference using the learning model based on the safe input data and outputting inference data as an inference result, an output safety circuit for detecting an abnormality in the inference data and outputting safe inference data, and an output unit for outputting output data based on the safe inference data.

Abstract: 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.

Abstract: A machine learning system that optimizes coefficients of at least one filter provided in a servo control device that controls a motor includes: an initial setting unit that sets initial values of the coefficients of the filter so as to attenuate at least one specific frequency component; a frequency characteristic calculation unit that calculates at least one of an input/output gain and an input/output phase delay of the servo control device based on an input signal and an output signal of the servo control device, of which the frequencies change; and a filter characteristic removing unit that removes filter characteristics of an initial filter in which the initial values are set to the filter from at least one of the input/output gain and the input/output phase delay obtained based on the input signal and the output signal obtained using the initial filter at the start of machine learning.

Abstract: A parameter setting device sets parameters for driving a machine in which a numerical controller is incorporated. The parameter setting device uses a machine configuration file in which information is described pertaining to the configuration of the machine. Furthermore, the parameter setting device is equipped with a parameter generating unit for generating parameters based on the machine configuration file, and a parameter setting unit for setting the generated parameters in the numerical controller.

Abstract: A machine learning apparatus determines a control parameter of an active vibration isolation apparatus on which an industrial machine is mounted. The industrial machine includes a movable part, a drive source that drives the movable part, and a drive source control section that controls the drive source to position the movable part at a command position. The machine learning apparatus includes: an acquiring section that acquires, as teacher data, a positional deviation, which is a difference between the command position and an actual position of the movable part; a storage section that stores a learning model that outputs the control parameter corresponding to a state quantity concerning the industrial machine; and a learning section that updates the learning model using the teacher data.

Abstract: A machine learning system that optimizes coefficients of at least one filter provided in a servo control device that controls a motor includes: an initial setting unit that sets initial values of the coefficients of the filter so as to attenuate at least one specific frequency component; a frequency characteristic calculation unit that calculates at least one of an input/output gain and an input/output phase delay of the servo control device based on an input signal and an output signal of the servo control device, of which the frequencies change; and a filter characteristic removing unit that removes filter characteristics of an initial filter in which the initial values are set to the filter from at least one of the input/output gain and the input/output phase delay obtained based on the input signal and the output signal obtained using the initial filter at the start of machine learning.

Abstract: A controller that performs, for one or more axes of a machine, position control by taking friction into consideration includes a data acquisition unit acquiring at least a position command and a position feedback and a compensation torque estimation unit estimating coefficients of a friction model used when the position control is performed, on the basis of a position deviation which is a difference between the position command and the position feedback.

Abstract: A parameter setting device sets parameters for driving a machine in which a numerical controller is incorporated. The parameter setting device uses a machine configuration file in which information is described pertaining to the configuration of the machine. Furthermore, the parameter setting device is equipped with a parameter generating unit for generating parameters based on the machine configuration file, and a parameter setting unit for setting the generated parameters in the numerical controller.

Abstract: A parameter setting device sets parameters for driving a machine in which a numerical controller is incorporated. The parameter setting device uses a machine configuration file in which information is described pertaining to the configuration of the machine. Furthermore, the parameter setting device is equipped with a parameter generating unit for generating parameters based on the machine configuration file, and a parameter setting unit for setting the generated parameters in the numerical controller.

Abstract: In a controller and a machine learning device capable of suppressing an influence of an abnormal value based on noise, etc., the machine learning device included in the controller includes a state observation unit for acquiring input data including at least one of internal data and external data of the manufacturing machine controlled by the controller, an input safety circuit for detecting an abnormality in the input data and outputting safe input data, a machine learning unit for executing learning of a learning model and inference using the learning model based on the safe input data and outputting inference data as an inference result, an output safety circuit for detecting an abnormality in the inference data and outputting safe inference data, and an output unit for outputting output data based on the safe inference data.

Abstract: A machining machine system includes: a machining machine; a numerical control device which generates a command for driving an axis of the machining machine; an interior information acquisition unit which acquires interior information of the numerical control device; a tentative determination unit which determines acceptance/rejection of a workpiece as machined by the machining machine based on a comparison result between the interior information and a threshold value; a final determination unit which determines acceptance/rejection of workpieces which are targets of an accuracy inspection which include at least a workpiece as determined to be accepted/rejected by the tentative determination unit based on a measurement result with respect to an accuracy of the workpiece; and a threshold value update unit which updates the threshold value used for determination processing by the tentative determination unit based on determination results by the tentative determination unit and the final determination unit.

Abstract: 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.

Abstract: A controller predicting a workpiece processing result by a processing machine includes a machine learning device learning a relationship between a change in state quantity indicating a processing state and a processing result. The machine learning device includes a state observation unit observing time-series data of the state quantity including at least one of a state of the processing machine and a state of a surrounding environment as a state variable indicating a current state of the environment, a determination data acquisition unit acquiring determination data indicating the processing result, and a learning unit learning the change in state quantity indicating the processing state and the processing result in association with each other by using the state variable and the determination data.

Abstract: A parameter setting device sets parameters for driving a machine in which a numerical controller is incorporated. The parameter setting device uses a machine configuration file in which information is described pertaining to the configuration of the machine. Furthermore, the parameter setting device is equipped with a parameter generating unit for generating parameters based on the machine configuration file, and a parameter setting unit for setting the generated parameters in the numerical controller.

Abstract: A machining machine system includes: a machining machine; a numerical control device which generates a command for driving an axis of the machining machine; an interior information acquisition unit which acquires interior information of the numerical control device; a tentative determination unit which determines acceptance/rejection of a workpiece as machined by the machining machine based on a comparison result between the interior information and a threshold value; a final determination unit which determines acceptance/rejection of workpieces which are targets of an accuracy inspection which include at least a workpiece as determined to be accepted/rejected by the tentative determination unit based on a measurement result with respect to an accuracy of the workpiece; and a threshold value update unit which updates the threshold value used for determination processing by the tentative determination unit based on determination results by the tentative determination unit and the final determination unit.

Abstract: A preload torque value generating unit (22m) generates a preload torque value (Tpm) as a function of the acceleration (am) of a main motor (6m), the preload torque value (Tpm) being a torque value that is appended in advance to a torque command value (Tm) so that the direction of force applied to the main motor (6m) and the direction of force applied to a sub motor (6s) will become opposite to each other. A preload torque value generating unit (22s) generates a preload torque value (Tps) as a function of the acceleration (as) of the sub motor (6s), the preload torque value (Tps) being a torque value that is appended in advance to a torque command value (Ts) so that the direction of force applied to the main motor (6m) and the direction of force applied to the sub motor (6s) will become opposite to each other.

Abstract: In a motor controller according to the present invention, a speed control unit 24m includes an integrator calculating an integrated value Sm of a speed error ?m-?m? between a speed command value ?m and a rotation speed ?m? and generates a torque command value Tm based on ?m-?m?, a predetermined value, a proportional gain and an integration gain. A speed control unit 24s includes an integrator calculating an integrated value Ss of a speed error ?s-?s? between a speed command value ?s and a rotation speed ?s? and generates a torque command value Ts based on ?s-?s?, the predetermined value, a proportional gain and an integration gain. An integrated value selecting unit 28 selects any one of Sm and Ss as the predetermined value, depending on a drive status of a main motor 6m and a sub motor 6s.

Abstract: A motor control system comprises a plurality of control apparatuses and a host control apparatus, wherein each of the control apparatuses include a position control unit controlling position based on a position command and commanded speed from the host control apparatus, a speed control unit controlling speed based on a speed command from the position control unit, a current control unit controlling current based on a current command from the speed control unit, and a current amplifier which amplifies motor driving current based on a voltage command from the current control unit, and wherein the current control unit includes a voltage saturation processing unit which determines whether the voltage command has exceeded supply voltage of the current amplifier, and which outputs the result of the determination, and a voltage saturation notifying unit which notifies the host control apparatus of the result of the determination made by the voltage saturation processing unit.

Abstract: A servo control system capable of using an angle-based synchronization learning control, even when a reference position is not given, while maintaining the advantage of the angle-based synchronization method. The servo control system has X-, y- and z-axes servo controllers, each configured to control x-, y- and z-axes servomotors, respectively. Each of x- and y-axes servo controllers has a reference signal generating part configured to generate a reference signal which monotonically increases or varies in one direction, based on the position command of each axis transmitted from a higher-level controller.