Abstract: The present invention addresses the problem of, when an abnormality has occurred in one detector, switching to feedback control based on a detector in which an abnormality has not occurred. This motor control device 100 is provided with a first abnormality detection unit 115 that detects an abnormality in a separate detector 154 as the detector or a feedback cable 1541 thereof, a second abnormality detection unit 116 that detects an abnormality in an encoder 151 of a motor as the detector or a feedback cable 1511 thereof, and a switching unit 111 that switches from full-closed control to semi-closed control, or to control using only the separate detector. When either of the first abnormality detection unit 115 or the second abnormality detection unit 116 has detected an abnormality, the switching unit 111 switches to control using only any detector in which an abnormality has not occurred.

Abstract: An object is to make it possible to acquire a parameter or a first physical quantity that has been learned and an evaluation function value and thereby check the progress or the result of machine learning. An output device includes: an information acquisition unit which acquires, from a machine learning device that performs machine learning on a servo control device for controlling a servo motor driving the axis of a machine tool, a robot or an industrial machine, a parameter or a first physical quantity of a constituent element of the servo control device that is being machine learned or has been machine learned and an evaluation function value; and an output unit which outputs information indicating a relationship between the acquired parameter, the first physical quantity or a second physical quantity determined from the parameter and the evaluation function value.

Abstract: Provided is a control device capable of automatically determining whether or not an inertia estimation function needs to be activated. The control device 10 is for an electric motor and comprises: a first inertia estimation unit 11 that estimates whether or not there has been a change in the inertia of an object to be driven, on the basis of at least one among first information pertaining to an operation program or operation settings for a device comprising the electric motor, second information obtained from a detection device for detecting the shape of the object to be driven by the electric motor, and third information indicating the operation state of the electric motor; and a second inertia estimation unit 12 that estimates the inertia of the object to be driven if the first inertia estimation unit 11 has estimated that there has been a change in the inertia of the object to be driven.

Abstract: The present invention addresses the problem of providing a display device with which it is possible to display a location in a machining path at which a step occurs that is large enough to affect machining precision without actual machining, and to be able to accurately and at low cost predict the occurrence of the step in the machining path. The problem can be resolved with a display device with which: time-series data is acquired for the position of a driven body or an electric motor on each axis of a machine tool; machining paths are calculated based on the acquired time-series data for the position of the driven body or electric motor on each axis; based on the calculation result for the machining paths, a height reference plane is set for each machining path; the heights from the reference planes of adjacent machining paths are compared; and the locations on the machining paths in which height differences occur that are greater than or equal to a set threshold value are displayed.

Abstract: Regarding a backlash amount measurement system provided in the servo control device of the drive motor of machine tools and industrial machines, a technical problem is to accurately measure the backlash amount at the time of inversion of a drive shaft by means of a backlash amount measurement system having a simpler configuration with a small number of detectors. The above technical problem can be solved by a backlash amount measuring unit equipped with an inversion detection unit which detects the start of inversion of the shaft, an arrival detection unit which detects that the backlash end has been reached from the start of inversion, and a time/distance measurement unit which measures the time from when the inversion detection unit detects the start of inversion until the arrival detection unit detects that the backlash end has been reached, or the movement distance.

Abstract: This display device comprises a determination unit and a display unit 18. The determination unit monitors the trajectory difference between an actual trajectory and a trajectory in a machining program for a spindle, and: determines, with regard to a site at which the trajectory difference is small and the actual speed of the spindle is small relative to the maximum value setting for a command speed, whether accuracy can be maintained even if the command speed is increased; and/or determines, with regard to a site at which the trajectory difference is small and the actual acceleration of the spindle is small relative to the maximum value setting for a command acceleration, whether accuracy can be maintained even if the command acceleration is increased. The display unit 18 displays the site in a highlighted manner.

Abstract: A control device includes a feedback acquisition section that acquires a feedback value from an industrial machine driven by an operation of an electric motor, a correction section that corrects a command for operating the electric motor, based on the feedback value, a filter section that performs, on the feedback value to be supplied to the correction section, filtering for reducing a value in a frequency band predetermined, a driving state determination section that determines whether or not a driving state of the industrial machine is changed, and a filter switching section that switches the frequency band of the filtering to be performed by the filter section from a first frequency band to a second frequency band, when the driving state is determined to be changed.

Abstract: The invention provides a servomotor controller that makes it possible to reduce compensation delay even when a dead band is provided. The servomotor controller includes a motion acquiring unit that acquires a motion of the servomotor, an acceleration amount acquiring unit that acquires an acceleration amount of the servomotor, a compensating unit that compensates a motion of the servomotor, and a compensation start determining unit that determines a start of the compensation by the compensating unit responsive to the motion of the servomotor, wherein the compensation start determining unit has a dead band unit that sets a dead band range which is a range of a predetermined value relative to the motion of the servomotor, and the dead band unit changes the dead band range based on the acceleration amount acquired by the acceleration amount acquiring unit.

Abstract: The present disclosure is intended to enable a user to grasp a state of load on an arithmetic processing unit (100, 200) so that the user can stop an excessive function of the arithmetic processing unit (100, 200), or can transfer part of arithmetic processes to another arithmetic processing unit (100, 200) with a small load. Included are the arithmetic processing unit (100, 200) that executes a plurality of processes related to servo control processing; and an observation unit (300) that determines at least one of point-of-time information about start of each of the processes executed by the arithmetic processing unit or point-of-time information about end of each of the processes executed by the arithmetic processing unit; and an output unit (400) that calculates information about usage of the arithmetic processing unit based on the point-of-time information determined by the observation unit, and outputs the calculated information.

Abstract: A machine learning device which performs machine learning to optimize at least one of a coefficient of a filter and a feedback gain, the machine learning device comprising: a state information acquiring unit which acquires state information including the at least one of the coefficient and the feedback gain and including input/output gain and input/output phase delay of a servo control device; an action information output unit which outputs action information including adjustment information for the at least one of the coefficient and the feedback gain; a reward output unit which obtains and outputs a reward on the basis of whether a Nyquist plot calculated from the input/output gain and the input/output phase delay passes through the inside of a closed curve; and a value function updating unit which updates a value function on the basis of the value of the reward, the state information, and the action information.

Abstract: Various factors may cause an error between the shape of a workpiece machined by an industrial machine and the target shape of the workpiece. An image analysis device includes a first image generating section that generates first image data indicating a first distribution of locations on a workpiece of an error between a shape of the workpiece machined by an industrial machine and a pre-prepared target shape of the workpiece; a second image generating section that generates second image data indicating a second distribution of locations on the workpiece of an error between a command transmitted to the industrial machine for machining the workpiece and feedback from the industrial machine corresponding to the command; and a correlation acquisition section that obtains a correlation between the first distribution and the second distribution, based on the first image data and the second image data.

Abstract: A plurality of evaluation functions and a machine learning result of each of the evaluation functions are output so that a relation between the evaluation function and the learning result can be ascertained. An output device includes: an output unit that outputs a plurality of evaluation functions used by a machine learning device that performs machine learning of parameters of components of a servo control device that controls a servo motor that drives an axis of a machine tool, a robot, or an industrial machine and a machine learning result of each of the evaluation functions; and an information acquisition unit that acquires the machine learning result from at least one of the servo control device and the machine learning device.

Abstract: Provided is a control device capable of automatically determining whether or not an inertia estimation function needs to be activated. The control device 10 is for an electric motor and comprises: a first inertia estimation unit 11 that estimates whether or not there has been a change in the inertia of an object to be driven, on the basis of at least one among first information pertaining to an operation program or operation settings for a device comprising the electric motor, second information obtained from a detection device for detecting the shape of the object to be driven by the electric motor, and third information indicating the operation state of the electric motor; and a second inertia estimation unit 12 that estimates the inertia of the object to be driven if the first inertia estimation unit 11 has estimated that there has been a change in the inertia of the object to be driven.

Abstract: To provide a servo controller for an industrial machine allowing construction of a system achieving more excellent power efficiency than a conventional system. A servo controller includes: a driving motor that drives an industrial machine; a load detecting unit that detects a load on the driving motor or the amount of power consumed by the driving motor; a buffer motor that feeds regenerative power to the driving motor on the basis of a result of the detection by the load detecting unit; and a base speed setting unit for recovering the buffer motor to a second base speed set to be lower than a constant first base speed preset for the buffer motor and applied before the regenerative power is fed to the driving motor after the buffer motor is decelerated from the first base speed and the regenerative power is fed to the driving motor.

Abstract: A control apparatus of a machine tool includes: a slide position control unit configured to control a slide according to operation patterns; a pressure command generation unit configured to generate a pressure command for a die cushion according to the operation patterns; a pressure detection unit configured to detect an actual pressure of the die cushion; a die cushion speed control unit configured to control the die cushion, based on an error between the pressure command and the actual pressure; and a command reach determination unit configured to determine whether or not the error is greater than a pressure threshold, wherein the slide position control unit sets, based on a result of the determination by the command reach determination unit, a waiting period between the operation pattern at the time of the determination and the next operation pattern, wherein the slide is kept at its position during the waiting period.

Abstract: A motor control device includes an acceleration detecting section configured to detect an acceleration of a control object, and an acceleration control section configured to control an acceleration of a motor driving the control object based on the detected acceleration, in which the acceleration control section includes a vibration component extraction filter configured to extract a vibration component generated between the motor and the control object, and the vibration component extraction filter changes a filter characteristic frequency according to at least one of a position and a mass of the control object.

Abstract: A motor controller includes: a command unit which outputs a command value for controlling a motor that drives a driven unit; a motor control unit which controls the motor based on the command value; a compensation filter which compensates for the command value; and a preprocessing unit which is provided in a stage preceding the compensation filter, the compensation filter has a frequency region in which a gain is greater than 1 and the preprocessing unit executes, when a variation in the command value before being compensated for with the compensation filter is equal to or less than a predetermined value, preprocessing in which a past command value is used as a current command value.

Abstract: Setting of parameters that determine filter characteristics is facilitated. A machine learning device performs machine learning of optimizing coefficients of at least one filter provided in a servo control device that controls rotation of a motor. The filter is a filter for attenuating a specific frequency component. The coefficients of the filter are optimized on the basis of measurement information of a measurement device that measures at least one of an input/output gain and an input/output phase delay of the servo control device on the basis of an input signal of which the frequency changes and an output signal of the servo control device.

Abstract: An object is to read the information of a feature shape included in a machining program so as to calculate a control command suitable for machining processing on the feature shape. A numerical controller (300) includes: a feature detection unit (302) which detects the feature of a machined shape from a machining program that commands the movement of a tool or a workpiece; an inward-turning amount calculation unit (303) which calculates, based on a servo parameter of a servo controller (400) that drives the tool or the workpiece, the feature of the machined shape detected from the machining program and a machining requirement that specifies a machining condition, a relation formula that determines the inward-turning amount of a machining path with respect to a program path; and a feedrate determination unit (304) which determines a feedrate that is optimized with the relation formula.

Abstract: A machine learning device that searches for a first parameter of a component of a servo control device that controls a servo motor includes: a solution detection unit that acquires a set of evaluation function values used during machine learning or after machine learning, plots the set of evaluation function values in a search range of the first parameter or a second parameter used for searching for the first parameter, and detects whether a search solution is at an edge of the search range or is in a predetermined range from the edge; and a range changing unit that changes the search range to a new search range of the first parameter or the second parameter based on the estimation made on evaluation function values of an evaluation function expression when the search solution is at the edge of the search range or is in the predetermined range.