A monitoring device of a main spindle rotation speed in a machine tool displays a variation state of the rotation speed by a rotation speed variation unit using a display unit in the machine tool. The monitoring device includes a drawing unit, a variation position display unit, and a reduction effect index display unit. The drawing unit is configured to display a variation diagram that illustrates a relationship between a variation amplitude and a variation cycle of the rotation speed. The reduction effect index display unit is configured to display a reduction effect index on the variation diagram. The reduction effect index represents a reduction effect of chatter vibration. The reduction effect index is calculated based on a speed ratio that is a ratio of a rotation speed of one rotation before to a rotation speed at an identical rotation position of the main spindle at any given timing.

A machine tool includes: a display; a tool configured to machine a workpiece; a spindle configured to rotate the tool or the workpiece; a sensor configured to detect a vibration frequency of the spindle or the tool; and a processor configured to control the machine tool. The processor is configured to: detect a chatter vibration in the spindle or the tool based on the vibration frequency; based on a frequency of the chatter vibration, a rotation speed of the spindle, and the number of cutting edges of the tool, calculate an order corresponding to the number of vibrations of the tool during a period of time until a current rotation angle of a first cutting edge of the tool reaches a current rotation angle of a second cutting edge of the tool; and present order information on the display, the order information indicating a magnitude of the calculated order.

Example implementations described herein are directed to systems and methods for extracting signal in the presence of noise for industrial IoT systems. Through the example implementations described herein, the high-frequency band signal of the sensor output can be maintained despite data compression, while also retaining information regarding the condition of the machine. Example implementations can also generate compressed data pairs to synchronized downsampled envelopes and spectrum data.

A machine tool includes a tool and a workpiece machined by the tool, and sensors configured to detect a position of the tool and/or the tool holder holding the tool in a spatially and time resolved manner A method for offline and/or online identification of a state of the machine tool includes: a) detecting or providing positions p.sub.i of the tool and/or of the tool holder at a series of points in time i, i=1 . . . n; b) determining for the series of points in time i a series of position changes Δm.sub.i according to the formula Δm.sub.i=p.sub.i/p.sub.i-1 and a series of speed changes Δv.sub.i according to the formula Δv.sub.i=v.sub.i/v.sub.i-1 with

[00001]$v_i=\frac{P_i-P_{i-1}}{t_i-t_{i-1}}$

and formula

[00002]$v_{i-1}=\frac{P_{i-1}-P_{i-2}}{t_{i-1}-t_{i-2}};$

c) identifying the state of the tool, the tool holder, the machine tool and/or the workpiece machined in the machine tool based on the position changes Δm.sub.i and the speed changes Δv.sub.i.

A machine tool includes: a spindle unit for rotatably supporting a spindle; a moving mechanism for moving the spindle unit; a motor for driving the moving mechanism; a motor control unit for controlling the motor; and an estimation unit for estimating that abnormal vibration is likely to have occurred in the spindle when the amplitude of a signal indicating the driving state of the motor falls out of a predetermined allowable range.

The invention provides a data augmentation method based on generative adversarial networks in tool condition monitoring. Firstly, the sensor acquisition system is used to obtain the vibration signal and noise signal during the cutting process of the tool; second, the noise data subject to the prior distribution is input to the generator to generate data, and the generated data and the collected real sample data are input to the discriminator for identification, the confrontation training between the generator and the discriminator until the training is completed; then, use the trained generator to generate sample data, and determine whether the generated sample data and the actual tool state sample data are similar in distribution; finally, combined with the accuracy of the deep learning network model to predict the state of the tool to verify the availability of the generated data.

A machine tool includes: a main spindle that holds a work piece; a tool holding unit that holds a tool for processing the work piece; a detection unit that detects vibration generated during processing of the work piece; and a processor that controls machining of the work piece performed by the tool, in which the processor compares a detected value detected by the detection unit with a predefined threshold value, interrupts the machining by releasing contact between the work piece and the tool at time of generation of chatter vibration or when there is a sign of the generation of the chatter vibration in which the detected value exceeds the threshold value, and analyzes the chatter vibration while the machining is being interrupted on basis of the detected value detected by the detection unit before the interruption.

A monitoring device of a main spindle rotation speed in a machine tool displays a variation state of the rotation speed by a rotation speed variation unit using a display unit in the machine tool. The monitoring device includes a variation value setting unit, a drawing unit, a first display unit, and a settable range calculating unit. The settable range calculating unit is configured to calculate a settable range of a variation amplitude and a variation cycle based on a calculation formula. The calculation formula includes the variation cycle, a difference between a first rotation speed and a second rotation speed at mutually different timings among the rotation speeds varied relative to a reference rotation speed, an inertia of a rotating body, a rated output of a motor that drives a main spindle, and a usage proportion to the rated output of the motor.

A monitoring device of a main spindle rotation speed in a machine tool displays a variation state of the rotation speed by a rotation speed variation unit using a display unit in the machine tool. The monitoring device includes a drawing unit, a variation position display unit, and a reduction effect index display unit. The drawing unit is configured to display a variation diagram that illustrates a relationship between a variation amplitude and a variation cycle of the rotation speed. The reduction effect index display unit is configured to display a reduction effect index on the variation diagram. The reduction effect index represents a reduction effect of chatter vibration. The reduction effect index is calculated based on a speed ratio that is a ratio of a rotation speed of one rotation before to a rotation speed at an identical rotation position of the main spindle at any given timing.

A rotation controller controls a rotation mechanism for rotation of a spindle. A movement controller causes, while the spindle is rotating, a feed mechanism to bring a cutting tool into contact with a workpiece to cause the cutting tool to cut the workpiece. The rotation controller controls a spindle rotation speed so as to accelerate or decelerate the rotation of the spindle, and the movement controller brings the cutting tool into contact with the workpiece after the rotation controller starts the rotation of the spindle, and separates the cutting tool from the workpiece while the spindle rotation speed is put under the acceleration control or deceleration control exercised by the rotation controller.