The disclosure provides a milling system and method under different lubrication conditions. The system uses a tool to mill the workpiece, a force measuring system to measure the milling force, a tool change system to replace the tools, a tool storage to store the tools. It can store the tools, provide the lubricating oil to the milling surface, select different tools according to different processing conditions, select the best angle differences of the unequal spiral angle tools according to different conditions comprising dry cutting, casting-type lubrication, minimal quantities of lubrication or minimal quantities of nanofluid lubrication, and/or choose the optimal tool according to different cutting parameters in order to obtain the minimum milling force.

The method of the present invention includes: an integrity information collection step of collecting a current amount; a first inferiority information collection step of collecting a current amount; a setting step of setting an integrity reference value and an inferiority reference value on the basis of the information collected; an extraction step of collecting a current amount in real time, and extracting a measurement value from the collected information; a detection step of detecting an integrity index value of the machine tool by comparing the measurement value extracted with the integrity reference value and the inferiority reference value set in the setting step; and an outputting step of outputting the integrity index value detected.

The method of the present invention includes: an integrity information collection step of collecting a current amount for each of an inflow period, a constant period, and an outflow period; a first inferiority information collection step of collecting a current amount for each of the periods; a setting step of setting a warning value and a critical value in each of the periods based on the information collected; an extraction step of collecting a current amount, which is consumed when a workpiece is machined by the machine tool in real time, for each of the periods; a detection step of detecting an integrity index value of the machine tool by detecting the number of times that the current amount of the periods collected exceeds the warning value and the critical value in each of the periods; and an outputting step of outputting the integrity index value detected.

A processing system that successively processes a plurality of workpieces includes: a tool that processes each of the workpieces; a motor that rotates the tool or each of the workpieces; a control unit that controls the motor; and a measurement unit that obtains an electrical quantity of the motor, where the control unit includes a first control unit that controls a rotational speed of the motor based on a first difference between a first electrical quantity and a second electrical quantity, the first electrical quantity is an electrical quantity obtained by the measurement unit at a specific processed portion of a first workpiece currently being processed, the second electrical quantity is an electrical quantity obtained by the measurement unit during processing of a portion of a second workpiece corresponding to the specific processed portion, and the second workpiece is a workpiece that was processed prior to the first workpiece.

The present invention concerns a method and a system for detecting malfunctions in an apparatus and/or defects in a workpiece processed by said apparatus. The method provides for acquiring a sound signal emitted by an apparatus during an operation cycle of the same, then comparing the sound signal with a plurality of audio tracks stored in a memory area for determining a malfunction of the apparatus and/or a defectiveness of the workpiece processed by the apparatus based on the result of said comparison. The operation cycle is subdivided into a plurality of work phases and during the acquisition of the sound signal a work phase of said plurality of work phases is identified. Each audio track of the plurality of stored audio tracks comprises an audio component relating to acquired sound signals, and additional information data comprising at least one identifier of the work phase executed by the apparatus during the acquisition of the sound signals of the audio component. The plurality of audio tracks used for the comparison with the sound signal is a group of audio tracks of the plurality of audio tracks whose identifier of the work phase of the apparatus corresponds to the identified work phase. The identification data of the audio tracks additionally comprise at least one identifier of a plurality of components activated during the phase to which the audio component refers, and it is further provided for a) identifying a plurality of components activated during the identified work phase, b) on the basis of the plurality of activated components, identifying a set of comparison phases among the plurality of phases of the operation cycle, and c) identifying as defective at least one component between the plurality of components activated during the work phase and/or the workpiece, on the basis of the audio tracks relating to the set of comparison phases identified and/or on the basis of sound signals acquired during the identified comparison phases.

An abnormality detection apparatus for working tools configured to be used in a machining process performed by a machine tool, the abnormality detection apparatus includes a storage portion which previously stores correlations between features of a plurality of operating portions relation to the machining process performed by the machine tool, and a tool condition of each of a plurality of working tool types, and a tool condition determining portion which determines the tool condition of the working tools based on the correlations.

A sensor (10) for inspecting a tool (28) of a machine tool (24) is provided that has a radio frequency transmitter (12) for generating a radio frequency signal, a radio frequency receiver (14) for generating a received signal from a received radio frequency signal, a coupling unit (16) to couple a radio frequency signal into the tool (28) and to decouple it from the tool (28), and a control and evaluation unit (20) to determine a time of flight of a radio frequency signal transmitted from the radio frequency transmitter (12) and received again by the radio frequency receiver (14) with reference to the received signal of the radio frequency receiver (14).

A sensor module for a tool holder for a cutting tool, such that when the sensor module is arranged to the tool holder having a cutting tool connected thereto, an axial portion of the cutting tool is positionable in a predefined rest position with respect to the sensor module. The sensor module includes at least one position sensor, wherein, when the sensor module is arranged to the tool holder having a cutting tool connected thereto, the position sensor is located radially spaced from the axial portion of the cutting tool for measuring deflection of the cutting tool with respect to the rest position. The disclosure further relates to a tool holder, a cutting tool, a cutting assembly, and a method for measuring deflection of a cutting tool.

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.

An anomaly detection device includes: an initial-stage detection information acquisition unit that acquires detection information at an initial stage in a series of a machining step performed using one tool; a map-function identification unit that identifies a mapping function for mapping the detection information at the initial stage, on reference detection information; a wear-progress-stage detection information acquisition unit that acquires detection information at a wear progress stage that follows the initial stage in the series of the machining step; a map-function application unit that applies the mapping function to the detection information at the wear progress stage; an anomaly-degree calculation unit that calculates an anomaly degree indicating a degree of difference, from the reference detection information, of the detection information at the wear progress stage to which the mapping function is applied; and an anomaly detecting unit that detects an abnormality of the tool based on determination as to whether the anomaly degree exceeds an anomaly determination threshold value determined in advance.