WO2021164137A1 - 数控机床刀具状态监测及控制系统与方法 - Google Patents

数控机床刀具状态监测及控制系统与方法 Download PDF

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Publication number
WO2021164137A1
WO2021164137A1 PCT/CN2020/089260 CN2020089260W WO2021164137A1 WO 2021164137 A1 WO2021164137 A1 WO 2021164137A1 CN 2020089260 W CN2020089260 W CN 2020089260W WO 2021164137 A1 WO2021164137 A1 WO 2021164137A1
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WO
WIPO (PCT)
Prior art keywords
tool
machine
state
monitoring
abnormal
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Application number
PCT/CN2020/089260
Other languages
English (en)
French (fr)
Inventor
李长河
尹硕
罗亮
吉卫喜
万斌辉
李昊罡
曹华军
卢秉恒
唐立志
张彦彬
徐杰
罗慧明
徐海州
杨敏
洪华平
高腾
侯亚丽
马五星
陈帅
Original Assignee
青岛理工大学
江南大学
宁波三韩合金材料有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Publication date
Application filed by 青岛理工大学, 江南大学, 宁波三韩合金材料有限公司 filed Critical 青岛理工大学
Publication of WO2021164137A1 publication Critical patent/WO2021164137A1/zh
Priority to ZA2021/06684A priority Critical patent/ZA202106684B/en

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Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23Q—DETAILS, COMPONENTS, OR ACCESSORIES FOR MACHINE TOOLS, e.g. ARRANGEMENTS FOR COPYING OR CONTROLLING; MACHINE TOOLS IN GENERAL CHARACTERISED BY THE CONSTRUCTION OF PARTICULAR DETAILS OR COMPONENTS; COMBINATIONS OR ASSOCIATIONS OF METAL-WORKING MACHINES, NOT DIRECTED TO A PARTICULAR RESULT
    • B23Q17/00—Arrangements for observing, indicating or measuring on machine tools
    • B23Q17/09—Arrangements for observing, indicating or measuring on machine tools for indicating or measuring cutting pressure or for determining cutting-tool condition, e.g. cutting ability, load on tool
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/18—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form
    • G05B19/406—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by monitoring or safety
    • G05B19/4065—Monitoring tool breakage, life or condition
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Definitions

  • the invention belongs to the field of state monitoring of numerical control equipment, and particularly relates to a state monitoring and control system and method for cutting tools of numerical control machine tools.
  • Tool damage is the most common type of failure in the machining process of machine tools. Many machine tool manufacturers usually design to add monitoring units during the manufacturing process, including monitoring the state of the tools. However, due to the ever-changing processing and manufacturing processes, the selected tools are also different, so the equipment's own monitoring system has low adaptability and accuracy for tool monitoring.
  • the detection rhythm of the machine vision machine tool in-position detection system in the prior art cannot be autonomous, or the detection time node is set by manual participation, or the automatic detection beat is set based on past experience. In this aspect of automatic detection The degree of intelligence is relatively lacking.
  • the present invention provides a CNC machine tool tool condition monitoring and control system.
  • This system can realize accurate monitoring of the tool condition while greatly reducing the downtime of the tool abnormality diagnosis process and improving the production of the machine tool. efficient.
  • one or more embodiments of the present invention provide the following technical solutions:
  • the state monitoring and control system of CNC machine tools includes: a data acquisition unit and a data analysis and processing unit; the data acquisition unit includes a vibration state detection device and a machine vision acquisition device;
  • the vibration state detection device collects the abnormal vibration signal during the tool processing in real time and transmits it to the data analysis and processing unit;
  • the data analysis and processing unit uses the tool state pre-judgment model to pre-judge the abnormal situation and determine the time point when the tool is abnormal;
  • the machine vision acquisition device completes the acquisition of the tool image and transmits it to the data analysis processing unit after the state pre-judgment and without affecting the continuity of the tool processing, so as to realize the accurate judgment of the abnormal state of the tool.
  • the embodiment of the present disclosure also discloses the control method of the CNC machine tool condition monitoring and control system, including:
  • the tool image acquisition is completed, so as to realize the accurate judgment of the abnormal state of the tool.
  • the tool wear is monitored through machine learning SVM for real-time monitoring, feature extraction of the collected vibration signal, as the input of SVM, tool wear as output, training tool state prediction suitable for the system requirements Judgment model.
  • the original current vibration signal is decomposed into a series of IMFs and the linear superposition of the remaining parts;
  • the principal component analysis method is used to perform principal component analysis on the intrinsic mode functions obtained after EMD decomposition, that is, each order of intrinsic mode functions after EMD decomposition is treated as each group of unrelated vectors, and finally the electric vibration signal after EMD decomposition is obtained. main ingredient.
  • the estimated value of tool wear is obtained by inputting the real-time monitoring signal to the SVM, and the wear threshold is set. When the tool wear is greater than the set threshold, the tool will enter a sharp wear stage.
  • a further technical solution is to use the professional image processing function module in the data processing unit to perform multi-angles using the professional image processing function module in the data processing unit to retrieve the standard tool geometry image and the image collected by machine vision from the database according to the tool parameter information in the current state when the tool is abnormal. Comparing calculations of multi-directional geometric dimensions, it is concluded whether the tool is abnormal and the specific quantification of the abnormal tool state, which mainly refers to the specific value of the tool wear and whether the tool is damaged.
  • the machine tool sends the start work instruction to the machine vision acquisition device at the same time.
  • the machine vision acquisition device quickly transports the CCD camera to the peripheral position of the tool according to the tool position coordinates transmitted inside the machine tool, and then sends the tool image acquisition low-speed intermittent to the machine tool working system.
  • Rotation command the spindle rotates slowly and intermittently.
  • the CCD camera performs fast focusing and completes image acquisition in a short time when the tool is in a static state.
  • the spindle rotates intermittently and the lens captures image frequency and dynamic images.
  • the focus time in the acquisition situation is consistent with the beat.
  • the spindle stop command is issued to the machine tool again to make the system in a non-working state.
  • the machine vision acquisition device includes a magnetic base part, through which the acquisition device is installed and fixed to the working tool table, and the fixed position origin is set on the tool table as a workpiece coordinate system in the machine tool as the entire machine vision
  • the acquisition device is a workpiece coordinate system in the machine tool coordinate system, which is called the zero point coordinate.
  • the external machine vision acquisition device is connected with the machine tool coordinate system, so that the image acquisition device becomes a numerical control processing system Part of
  • the fixed position is the intersection of the circular line of the cylindrical tool post and the X-axis direction to ensure that the Y-axis coordinate point is consistent with the tool coordinate point.
  • the movement of this system can meet the requirements of the movement performance of this system.
  • the image acquisition of the axial direction of the bottom of the tool is realized through the rotation mechanism installed at the connection part of the CCD lens and the tool bar to realize the up and down rotation of the lens along the Y axis.
  • the machine vision acquisition device only collects images at two azimuth angles in the circumferential and axial directions;
  • the guide rods on the X and Y direction axes can achieve any spatial position of the working area.
  • a displacement sensor is arranged inside the end of the two-axis guide rod. The displacement sensor shows that the X and Z axes are in operation.
  • the present disclosure organically combines the machine learning theory with the machine vision detection method.
  • the use of machine learning technology to predict the state of the tool by the mapping relationship between the sensor's one-dimensional signal and the tool state has the advantages of higher accuracy and fast speed.
  • the accuracy of model training based on machine learning theory is difficult to achieve foolproof.
  • the subsequent processing of abnormal tools adds extra workload.
  • a machine vision monitoring module is added.
  • As a direct monitoring method it can effectively ensure the accuracy.
  • the speed of modern image real-time processing technology is difficult to achieve the processing of industrial field production. Speed requirements.
  • the system of the present invention can perform real-time monitoring of machine tool tools during the processing of CNC equipment. When the tool status is abnormal, the machine learning diagnosis model can quickly perform abnormal monitoring and response to the abnormal situation.
  • the machine tool stops and the image vision system completes the tool in a short time. After the image is collected, the tool is changed and the processing is continued to ensure the continuity of processing.
  • the data analysis and processing unit subsequently performs image analysis and processing on the collected tool images, and finally realizes the accurate judgment of the tool status, and at the same time verifies the pre-judgment of the tool status.
  • the various parts of the system of the present invention communicate with each other. During the working process, each unit updates the state in real time according to different states, and the processing process is intelligently controlled in real time through an intelligent control computer.
  • the system of the present disclosure is divided into state pre-judgment and accurate judgment of the tool in the tool state judgment, and the system occupies a short period of equipment normal running time during the working process, which effectively improves the working efficiency of the machine tool.
  • the tool state pre-judgment in the system of the present disclosure is based on the principle of machine learning theory, and the accurate judgment of the tool state is based on image comparison and analysis processing methods.
  • the data acquisition unit of the present disclosure is composed of a smart tool holder with a built-in sensor and a detachable machine vision collection device fixed by a magnetic base on the machine tool.
  • the smart tool holder with a built-in sensor guarantees the precise time point for detecting the abnormality of the tool.
  • the machine vision collection device Through the image acquisition and information comparison of the tool to ensure accurate judgment of the tool status;
  • the smart tool holder of the present disclosure is equipped with permanent magnets, and a deceleration mechanism composed of rotating rolling elements and bearings is installed internally, so that the internal coil mechanism can generate electricity through the electromagnetic induction effect during the machining process, so that the smart tool holder has self-powered Function.
  • the internal integrated sensor is connected to the wireless transmitter, which solves the wiring problem of some lines in the processing area and does not compress the normal working space of the bed;
  • the machine vision device of the present disclosure adopts a CCD camera for image collection.
  • the CCD camera can be transported to the designated detection position of the system through two vertically connected electric telescopic rods to complete image collection. Position coordinates are monitored, so that the CCD space coordinates can be monitored and controlled in real time in the system;
  • the database unit of the present disclosure communicates with other units, so that the data information of each unit in the system can be shared in real time, and it is ensured that the decision-making and control unit can effectively control each unit based on the real-time information;
  • the various hardware devices and software systems in the system of the present disclosure have a high degree of matching with most existing machine tools, and are easy to install, and the machine tool equipment does not need to be modified to a large extent.
  • Figure 1 is a structural diagram of an online tool detection and control system according to an embodiment of the disclosure
  • Figure 2 is an isometric view of the visual inspection device according to an embodiment of the disclosure.
  • Figure 3 (a)- Figure 3 (b) are axonometric views of the magnetic base and the Z-axis electric telescopic rod of the embodiment of the disclosure;
  • Figure 3(c) is a fixed case of a camera data cable retracting device according to an embodiment of the present disclosure
  • Fig. 4(a) is the connecting plate of the displacement sensor and the telescopic rod according to the embodiment of the present disclosure
  • Fig. 4(b) is a cross-sectional view of the connecting plate A-A shown in Fig. 4(a) of the embodiment of the present disclosure
  • Figure 5 (a) is an assembly diagram of an electric telescopic rod, connecting parts and sensors of an embodiment of the disclosure
  • Figure 5(b) is a B-B cross-sectional view of Figure 5(a) of an embodiment of the present disclosure
  • Fig. 5(c) is a partial enlarged view of Fig. 5(a) of an embodiment of the present disclosure
  • Figure 6 (a) is an axonometric view of the connecting member of the telescopic rod according to the embodiment of the disclosure
  • Figure 6(b) is a front view of a telescopic rod connecting member of an embodiment of the disclosure.
  • Fig. 6(c) is a partial enlarged view of Fig. 6(b) ii of the embodiment of the present disclosure
  • Fig. 6(d) is a cross-sectional view of the C-C section of Fig. 6(b) of the embodiment of the present disclosure
  • Figure 7 is a tapered pin of an embodiment of the disclosure.
  • Fig. 8 is an axonometric view of an X-axis electric telescopic rod according to an embodiment of the disclosure
  • Fig. 9(a) is a camera rotating bracket fixing device according to an embodiment of the present disclosure.
  • Fig. 9(b) is a top view of a camera rotating bracket fixing device according to an embodiment of the present disclosure.
  • Figure 9(c) is an assembly diagram of the telescopic rod connecting device, the telescopic rod and the camera rotating bracket fixing device of the embodiment of the disclosure;
  • Fig. 9(d) is a partial enlarged view of Fig. 9(c) iii of the embodiment of the present disclosure
  • Figure 10 (a) is an axonometric view of a camera rotating bracket according to an embodiment of the disclosure
  • Figure 10(b) is an assembly diagram of a camera rotating bracket and a fixing device according to an embodiment of the disclosure
  • Fig. 11 is an exploded view of the camera data cable retracting and releasing device according to the embodiment of the disclosure.
  • Figure 12 (a) is the housing of the camera data cable retracting device according to the embodiment of the disclosure.
  • Figure 12(b) is the lower box body of the roller mounting box of the embodiment of the present disclosure.
  • Figure 12(c) is a top view of the lower box body of the roller mounting box of the embodiment of the disclosure.
  • Figure 12(d) is a D-D cross-sectional view of Figure 12(c) of an embodiment of the disclosure.
  • Figure 13 (a) is an isometric view of the roller mounting box of the embodiment of the disclosure.
  • Figure 13(b) is an isometric view of the upper case of the roller mounting case of the embodiment of the disclosure.
  • Figure 13(c) is an isometric view of the lower box body of the roller mounting box of the embodiment of the disclosure.
  • Figure 13 (d) is a front view of the assembly of the roller mounting box of the embodiment of the present disclosure.
  • Fig. 13(e) is a cross-sectional view of the E-E section of Fig. 13(d) of the embodiment of the present disclosure
  • Figure 13 (f) is a front view of the flange cover of the roller mounting box of the embodiment of the disclosure.
  • Fig. 13(g) is a cross-sectional view of the F-F section of Fig. 13(f) of the embodiment of the present disclosure
  • Figure 14 (a) is a top view of the assembly of the roller unit of the embodiment of the disclosure.
  • Fig. 14(b) is a G-G cross-sectional view of Fig. 14(a) of an embodiment of the present disclosure
  • Figure 15 is an isometric view of the roller drive motor of the embodiment of the disclosure.
  • Figure 16 (a) is the front view of the drive motor connecting plate
  • Fig. 16(b) is a cross-sectional view of the H-H section of Fig. 16(a) of the embodiment of the present disclosure
  • Fig. 16(c) is a partial enlarged view of Fig. 16(a)iv of an embodiment of the present disclosure
  • FIG. 16(d) is a schematic diagram of the connection between the motor and the connecting plate according to the embodiment of the disclosure.
  • Fig. 16(e) is a partial enlarged view of Fig. 16(d) v of the embodiment of the present disclosure
  • Figure 17 (a) is an axonometric view of a smart detection tool holder according to an embodiment of the disclosure
  • Figure 17(b) is an exploded view of the smart detection tool holder according to the embodiment of the disclosure.
  • 18(a) and 18(b) are isometric views of two types of cutter heads with replaceable installation of the smart tool holder according to the embodiment of the present disclosure
  • Figure 19 (a) and Figure 19 (b) are isometric views of two indexable inserts according to the embodiment of the disclosure.
  • Figure 19(c) is an axonometric view of an insert cutting workpiece according to an embodiment of the disclosure.
  • Figure 20 (a) is a structural diagram of the central internal components of the smart tool holder according to an embodiment of the disclosure.
  • Figure 20 (b) is a front view of the middle of a smart tool holder according to an embodiment of the disclosure.
  • Fig. 20(c) is a cross-sectional view of the I-I section of Fig. 20(b) of the embodiment of the present disclosure
  • Figure 20 (d) is a cross-sectional view of the middle of the smart tool holder according to an embodiment of the disclosure
  • Figure 21 (a) is an isometric view of the internal coil of the power generating device according to the embodiment of the disclosure.
  • Figure 21 (b) is a front view of the coil assembly unit of the embodiment of the disclosure.
  • Fig. 21(c) is a cross-sectional view of the J-J section of Fig. 21(b) of the embodiment of the present disclosure
  • Figure 21 (d) is a partial enlarged view of Figure 21 (b) vi of the embodiment of the present disclosure
  • Figure 22 (a) is an isometric view of the vibration sensor unit of the embodiment of the disclosure.
  • Figure 22 (b) is a coil fixed bearing of an embodiment of the present disclosure
  • FIG. 23 is a schematic diagram of the connection of each unit of the system of the embodiment of the disclosure.
  • FIG. 24 is a working flow chart of the machine tool after the initial judgment of the tool abnormality in the embodiment of the disclosure.
  • FIG. 25 is a schematic diagram of the wear of the inserts of the indexable cutter according to the embodiment of the disclosure.
  • FIG. 26 is an isometric view of the tool changing device for numerical control equipment of an embodiment of the disclosure.
  • Fig. 27 is a schematic diagram of a tool initial judgment module of an embodiment of the disclosure.
  • Figure 28 is an axonometric view of a smart tool magazine unit of an embodiment of the disclosure.
  • I data acquisition unit, II, data analysis and processing unit, III, intelligent tool magazine unit, IV, abnormal tool conveying unit, V, display unit, VI, decision-making and control unit, VII, database unit.
  • I-01-Magnetic seat I-02-Z-axis electric telescopic rod, I-03-Z-axis displacement sensor connecting plate, I-04-Z-axis displacement sensor, I-05-roller mounting box, I-06-roller Mounting box fixed shell, I-07- telescopic rod connecting part, I-08-taper pin, I-09-X axis electric telescopic rod, I-10-X axis displacement sensor connecting plate, I-11-X axis displacement sensor , I-12-Camera rotating bracket fixing device, I-13-X-axis telescopic rod end fixed nut, I-14-X-axis telescopic rod end fixed round nut, I-15-washer, I-16-CCD camera , I-17-Camera rotating bracket;
  • I-18-Knife shank fixing part I-19-Reinforced ring fixing bolt, I-20-Knife shank connection reinforcing ring, I-21-Knife handle working part, I-22-Reinforced ring fixing nut, I-23 -Cutterhead installation stop bolts, I-24- Cutterhead installation stop fast, I-25- Machining cutterhead, I-26- Cutterhead installation part.
  • I-051301-Roller box lower shell connection through hole I-050101-Image signal data line hole, I-050102-Roller drive motor power line hole, I-051201-Drive motor connecting plate fixing hole, I-051301-roller Stepped hole in the lower shell of the box, I-052201-threaded hole on the side wall of the upper shell of the roller box, I-052202-through hole for connecting the upper and lower shells, I-050801-fixed threaded hole for the drive motor, I-051201-fixed motor connection on the connecting plate Hole, I-051202-Connecting plate and lower shell connecting through hole;
  • I-2101-Radio frequency device I-2102-Radio frequency device holder, I-2103-Fixed frame assembly bearing, I-2104-Coil upper end support bearing, I-2105-Rotating rolling element upper end support bearing, I-2106- Power module, I-2107-rotating rolling element, I-2108-rotating rolling element lower end support bearing, I-2109-flange cover, I-2115-signal transmitting hole, I-2116-sensor data line hole, I-211001 -Coil winding boss, I-210401-power storage module, I-210402-power rectifier module, I-211002-wire transmission tube, I-2112-central axis transmission line tube, I-2113-vibration sensor, I -2114-vibration sensor fixing clip, I-211401-fixing clip positioning hole, I-211402-data line hole, I-2111-coil fixing bearing, I-211101-fixing clamp positioning threaded hole, I-211102-coil fixing slot , I-211103-sensor fixing hole, I-211104-bearing rolling
  • this embodiment discloses a CNC machine tool state monitoring and control system, including data acquisition unit I, data analysis and processing unit II, VII database unit, VI decision-making and control unit, intelligent tool magazine unit III, display Unit V and abnormal tool conveying unit IV.
  • the system can realize accurate judgment of tool status through data acquisition and data analysis and processing unit.
  • Intelligent tool magazine unit and decision-making and control unit can realize the replacement of new tools in the case of abnormal machine tools and the accurate judgment and classification of abnormal tools and subsequent intelligent processing.
  • Figure 23 is a schematic diagram of the connection of each unit of the system;
  • the data acquisition unit includes a power sensor, a data acquisition card, an industrial CCD camera, and an AD converter, which completes data acquisition and transmits it to the data analysis and processing unit, data analysis and
  • the processing unit includes industrial computers and software processing modules run by industrial computers.
  • Data analysis and processing units communicate with decision-making and control units.
  • Decision-making and control units include industrial computer central processing units and CNC machine tool control systems, decision-making and control units and intelligent tool magazines.
  • the intelligent tool magazine unit includes the arranging tool magazine, the tool changer and the tool magazine intelligent module
  • the auxiliary equipment is the industrial mechanical gripper
  • the intelligent tool magazine unit includes the arranging tool magazine, the tool changer and the tool magazine intelligent module
  • the auxiliary equipment is the industrial mechanical gripper
  • the intelligent tool magazine unit includes the arranging tool magazine, the tool changer and the tool magazine intelligent module
  • the auxiliary equipment is the industrial mechanical gripper
  • the intelligent tool magazine unit includes the decision-making and control unit, the data analysis and processing unit, and the database server
  • the display unit communicates to display the required data.
  • the structure of the data acquisition unit and the connection of the components are as follows:
  • the data acquisition unit I is divided into two parts, including a vibration state detection device and a visual detection device.
  • the main body of the visual detection device is composed of an electric telescopic rod and a pull-rope displacement sensor. It is assembled into a detachable external image visual acquisition device through other auxiliary devices.
  • the realization of the vision detection device is shown in Figure 2.
  • the vision detection device includes a camera, an X-axis displacement sensor I-11, a Z-axis displacement sensor I-04 and a magnetic base I-01;
  • the Z-axis displacement sensor I-04 is fixed on one side of the magnetic base through the Z-axis electric telescopic rod I-02, and the bottom side of the magnetic base is connected to the X-axis electric telescopic rod through the telescopic rod connecting part I-07.
  • the telescopic rod is connected with the X-axis displacement sensor, and the X-axis electric telescopic rod is also connected to the camera rotating bracket fixing device.
  • the camera rotating bracket fixing device I-12 is equipped with a camera rotating bracket, and the camera rotating bracket I-17 is installed with a camera.
  • the magnetic base is installed and fixed to the working tool table.
  • one side of the magnetic base is also installed with a roller mounting box I-05, the roller mounting box is installed in the roller mounting box fixed shell I-06, the telescopic rod connecting part is provided with a tapered pin I-08, the Z-axis displacement sensor and The Z-axis electric telescopic rod is fixed and installed by bolts through the Z-axis displacement sensor connecting plate I-03, and the X-axis displacement sensor and X-axis electric telescopic rod I-09 are fixed and installed by bolts through the X-axis displacement sensor connecting plate I-10.
  • One end of the X-axis electric telescopic rod uses the X-axis telescopic rod end fixing round nut I-13, the X-axis telescopic rod end fixing nut I-14 and the spacer I-15 to be installed on the camera rotating bracket fixing device.
  • the camera uses a CCD camera I-16, and the X-axis displacement sensor and the Z-axis displacement sensor are rope-type displacement sensors.
  • FIG. 3(a) and 3(b) the axonometric drawing of the magnetic base and the Z-axis electric telescopic rod is shown in Figures 3(a) and 3(b).
  • the side wall of the magnetic base I-01 is provided with side wall threads.
  • one end of the rod body of the Z-axis electric telescopic rod is provided with a tapered pin hole I-0204, and the other end of the rod body of the Z-axis electric telescopic rod is a fixed boss, and two sides of the fixed boss are respectively provided
  • Figure 3(c) is a schematic diagram of the structure of the fixed box body of the camera data cable retracting device. Hole I-0603, the upper edge of the other vertical side wall extends horizontally outwards to form a horizontal side wall, and a horizontal side wall connecting through hole I-0601 is opened.
  • Figure 4(a) is a structural diagram of the connecting plate between the displacement sensor and the telescopic rod;
  • Figure 4(b) is a cross-sectional view of the connecting plate A-A shown in Figure 4(a);
  • the X-axis displacement sensor connecting plate and the Z-axis displacement sensor connecting plate have the same structure.
  • the connecting plate through holes I-0301 and stepped holes I-0302 are respectively opened on the plates.
  • there are 4 stepped holes located at In the middle of the connecting plate there are 4 connecting plate through holes, two in a group, which are respectively located on the structure near the two ends of the connecting plate.
  • the main part of the displacement sensor is fixed on the driving device of the electric telescopic rod, and the other end is fixed on the end of the telescopic rod.
  • the CCD camera is connected to the end of the X-axis electric telescopic rod through a rotation controller, which can realize the rotation in the Y-axis direction. With the linear displacement of the X-axis and the Y-axis, the effective collection of tool images can be realized.
  • Figure 5(a) is an assembly drawing of an electric telescopic rod, connecting parts and sensors;
  • Figure 5(b) is a BB cross-sectional view of Figure 5(a);
  • Figure 5(c) is Figure 5(a)i Partial enlarged view;
  • the telescopic rod conical pin hole I-0204 provided in the telescopic rod connecting part I-07 matches the telescopic rod connecting part I-07 tapered pin positioning hole I-0701, and the telescopic rod connecting part I-07 is also provided with a sensor connector fixing thread Hole I-0702 is used to fix the sensor.
  • the lower end of the Z-axis displacement sensor I-04 is the sensor connector I-0401.
  • Figure 6(a) is an axonometric view of the connecting part of the telescopic rod
  • Figure 6(b) is the front view of the connecting part of the telescopic rod
  • Figure 6(c) is a partial enlarged view of Figure 6(b) ii
  • 6(d) is a cross-sectional view of CC section in Fig. 6(b);
  • the side wall of the end base of the telescopic rod connecting part I-07 is provided with an X-axis telescopic rod fixing hole I-0703.
  • Fig. 7 shows a tapered pin structure, and the bottom of the tapered pin is provided with a taper pin removal threaded hole I-0801.
  • Figure 8 is a isometric view of the X-axis electric telescopic rod; one end of the X-axis electric telescopic rod is the telescopic rod connector I-0901, the telescopic rod connector is provided with a fixed keyway I-0902, and the other end of the X-axis electric telescopic rod
  • the base is provided with a connecting threaded hole I-0903.
  • Figure 9(a) is the camera rotating bracket fixing device;
  • Figure 9(b) is the top view of the camera rotating bracket fixing device;
  • Figure 9(c) is the telescopic rod connecting device, the telescopic rod and the camera rotating bracket fixing device assembly drawing;
  • Figure 9( d) is a partial enlarged view of Figure 9(c) iii;
  • the upper supporting structure of the camera rotating bracket fixing device is provided with a camera bracket connecting threaded hole I-1201 for fixing the camera, and the middle supporting structure is provided with a connecting keyway through hole I-1202 for connecting with the fixed keyway of the X-axis electric telescopic rod.
  • the bottom support structure is provided with a threaded hole I-1203 for the sensor connector.
  • Figure 10(a) is a isometric view of the camera rotating bracket
  • Figure 10(b) is an assembly drawing of the camera rotating bracket and fixing device
  • the camera rotating bracket is provided with a camera fixing buckle I-1701 and a camera rotating drive device I-1702
  • the rotating drive device of the camera is provided with a connecting threaded hole I-1703, which is used to cooperate with the connecting threaded hole I-1201 of the camera bracket to realize the connection with the camera rotating bracket fixing device.
  • Figure 11 is an exploded view of the camera data cable retracting device; the camera data cable retracting device includes the main roller box I-0513, and the roller box top plate I-0501 is used on the top plate connecting bolt I-0506 Fix the top plate of the roller box on the main box of the roller, and the main box of the roller is fixed with the connecting bolt I-0514 of the main box of the roller.
  • the motor fixing bolt I-0509 and the gasket I-0510 are fixed on the motor fixing plate I-0512, the lower shell of the roller box I-0517 and the upper shell I-0522 of the roller box are connected with the nut I-0518 through the upper and lower shells of the roller box ,
  • the upper and lower shell connecting bolts I-0523 of the roller box, the hexagonal nut I-0515, and the gasket I-0516 are fixedly connected.
  • Figure 12 (a) is the housing of the camera data cable retractable device;
  • Figure 12 (b) is the lower box of the roller mounting box;
  • Figure 12 (c) is the top view of the lower box of the roller mounting box;
  • Figure 12 (d) is Figure 12 ( c) DD cross-sectional view;
  • the main box of the roller is provided with a through hole I-051301 for the lower shell of the roller box, an image signal data line hole I-050101, a wheel drive motor power line hole I-050102, a drive motor connecting plate fixing hole I-051201, a roller box Stepped hole of lower body shell I-051301.
  • Figure 13(a) is an axonometric view of the roller mounting box
  • Figure 13(b) is an axonometric view of the upper box body of the roller mounting box
  • Figure 13(c) is an axonometric view of the lower box body of the roller mounting box
  • Figure 13(d) The front view of the assembly of the roller mounting box
  • Figure 13(e) is the EE cross-sectional view of Figure 13(d)
  • Figure 13(f) is the front view of the flange cover of the roller mounting box
  • Figure 13(g) is Figure 13(f) FF section cross-sectional view
  • the upper case of the roller mounting box is provided with threaded holes I-052201 on the side wall of the upper shell of the roller case and connection through holes I-052202 for the upper and lower shells.
  • the lower shell of the roller box body is provided with upper and lower shell connecting through holes 1I-051701, flange cover connecting threaded holes I-051702, and the lower shell of the roller box body and the roller main box body connecting through holes I-051703.
  • the upper and lower shell connecting through holes 1I-051701 and the upper and lower shell connecting through holes 2I-052202 are matched with the mounting bolts to realize the roller installation box.
  • Figure 14 (a) is a top view of the assembly of the roller unit;
  • Figure 14 (b) is a G-G cross-sectional view of Figure 14 (a);
  • Figure 15 is the isometric view of the roller drive motor; the motor fixing plate is provided with the connecting plate fixing motor connection hole I-051201, the connecting plate and the lower shell connecting through hole I-051202, and the roller drive stepping motor is installed with the screw hole of the drive motor. On the motor fixing plate.
  • Figure 16 (a) is the front view of the drive motor connecting plate;
  • Figure 16 (b) is the HH cross-sectional view of Figure 16 (a);
  • Figure 16 (c) is the partial enlarged view of Figure 16 (a) iv;
  • Figure 16 (d) ) Is a schematic diagram of the connection between the motor and the connecting plate;
  • Fig. 16(e) is a partial enlarged view of Fig. 16(d)v.
  • Figure 17(a) is an axonometric view of the intelligent detection tool holder;
  • Figure 17(b) is an exploded view of the intelligent detection tool holder;
  • a reinforcing ring at the joint of the shank is arranged between the fixed part of the shank and the working part of the shank.
  • the reinforcing ring I-20 at the joint of the shank is fixed by the reinforcing ring fixing bolt I-19 and the reinforcing ring fixing nut I-22.
  • the handle works
  • a cutter head installation stop bolt I-23 and a cutter head installation stop block I-24 are arranged between part I-21 and the processing cutter head.
  • the processing cutter head I-25 is installed on the cutter head installation part I-26.
  • the disc mounting part is threadedly connected with the working part of the tool holder.
  • Figure 18 (a) is a side milling cutter axonometric view
  • Figure 18 (b) is a plane milling cutter axonometric view
  • Figure 19 (a) is a plane milling indexable insert isometric view
  • Figure 19 ( b) is an axonometric view of a replaceable blade of a grooving tool
  • Figure 19(c) is an axonometric view of the blade cutting workpiece.
  • Figure 20 (a) is a structural diagram of the internal components of the middle part of the smart tool holder
  • Figure 20 (b) is the front view of the middle part of the smart tool holder
  • Figure 20 (c) is a cross-sectional view at II of Figure 20 (b)
  • Figure 20 (d) is A cross-sectional view of the middle of the smart tool holder.
  • a radio frequency device I-2101 Inside the smart tool holder are arranged a radio frequency device I-2101, a radio frequency device holder I-2102, a holder assembly bearing I-2103, a coil upper end support bearing I-2104, a rotating rolling element upper end support bearing I-2105, and a power supply module.
  • I-2106, the rotating rolling element I-2107, the lower end supporting bearing of the rotating rolling element I-2108, the flange cover I-2109, the above components are assembled and installed in the smart tool holder in turn.
  • the handle shell of the smart knife handle is provided with a signal transmitting hole I-2115 and a sensor data line hole I-2116.
  • Figure 21 (a) is a perspective view of the internal coil of the power generating device;
  • Figure 21 (b) is the front view of the coil assembly unit;
  • Figure 21 (c) is the JJ cross-sectional view of Figure 21 (b);
  • Figure 21 (d) is Figure 21 (b) Partial enlarged view at vi.
  • the power generating device includes coil winding boss I-211001;
  • the upper end supporting bearing of the coil is respectively installed with the power storage module I-210401, the power rectifier module I-210402, the wire conveying pipe I-211002, the vibration sensor fixing clamp I-2114, the vibration sensor I-2113, and the reversing bearing I-2111. .
  • Figure 22 (a) Axonometric view of the vibration sensor unit; internal coils of the generator: data line hole I-211402, vibration sensor I-2113, fixing clip positioning hole I-211401, central axis transmission line pipe I-2112; data line hole The I-211402 is held on the same axis through the central axis transmission line tube I-2112, and the bolts are used to fix the vibration sensor through the fixing clamp positioning hole I-211401.
  • Coil fixed bearing; coil assembly unit includes: fixing clamp positioning threaded hole I-211101, coil fixing slot I-211102, sensor fixing hole I-211103, bearing rolling element and bracket I-211104, bearing bottom outer ring I-211105.
  • the fixing clamp positioning thread hole I-211101 and the fixing clamp positioning hole I-211401 tightly fix the sensor on the coil unit by bolts. Install the vibration sensor I-2113 in the sensor fixing hole I-211103 and fix it with adhesive to ensure the effective transmission of tool vibration signals.
  • Figure 26 is an axonometric drawing of the tool changer of the CNC equipment; the tool changer of the CNC equipment includes the fixed tool changer III-06 and the tool changer III-08, the tool changer III-06 and the tool changer III-08 pass The tool change rotation axis III-07 is connected.
  • Figure 28 is an axonometric view of the intelligent tool magazine unit; the intelligent tool magazine unit includes the tool magazine holder III-05, the tool magazine holder III-02 is arranged in the tool magazine holder, and the bottom of the tool magazine holder is the tool magazine changing edge III-03, there is an intelligent tool magazine fixing hole III-01 on the tool magazine fixing frame, and the tool magazine fixing frame is also equipped with a tool magazine tool change drive device III-04.
  • the side wall of the magnetic base I-01 is provided with a side wall threaded hole I-0102, which is matched with the horizontal side wall connecting through hole I-0601 on the fixed shell of the roller mounting box to install the fixing bolt, and the Z-axis electric telescopic rod
  • the upper second threaded blind hole I-0203 is connected with the vertical side wall through the through hole I-0603 to install the fixing bolts.
  • connection method realizes the convenience of disassembly and easy installation. Damaged parts can be replaced, which improves the service life of the device and makes its installation and operation simple.
  • the Z-axis displacement sensor and the electric telescopic rod are fixed and installed by bolts through the Z-axis displacement sensor connecting plate I-03.
  • the ordinary bolts are fixed on the electric telescopic rod through the connecting plate through hole I-0301, and the connecting plate is fixed by passing through the connecting plate step
  • the countersunk screw of hole I-0302 fixes the displacement sensor.
  • the assembly diagram is shown in Figure 5(a) Electric telescopic rod, connecting parts and sensor assembly drawing.
  • the sensor connector I-0401 and the telescopic rod connecting part I-07 are kept on the same axis, so that the connected pull rope is kept perpendicular to the horizontal plane. This installation method ensures the accuracy of the vertical displacement of the measuring camera.
  • connection method of the X-axis pull-rope displacement sensor and the telescopic rod is the same as the above-mentioned method, and the X-axis displacement sensor connector is fixed to the camera rotation bracket fixing device I-12 sensor connector fixing threaded hole in the same connection method At I-1203, make the X-axis sensor's pull rope orientation parallel to the horizontal plane to ensure the accuracy of measuring the horizontal displacement of the camera.
  • the linear movement of the camera in two directions is completed by two electric telescopic rods, and the two telescopic rods are connected by the telescopic rod connecting part I-07, and the Z-axis telescopic rod is connected with the internal threaded hole of the connecting part through the thread at the bottom of the rod.
  • the cross-sectional view of the threaded connection is shown in the cross-sectional view of the BB section in Figure 5(a) in Figure 5(b), and it is locked by the tapered pin I-08 to avoid loosening between the components in the reciprocating linear motion.
  • the X-axis electric telescopic rod is fixed at the threaded hole I-0903 through the X-axis telescopic rod fixing hole I-0703 by bolts, and there are a total of four threaded connections on the front and rear faces to ensure the connection strength.
  • the camera rotation bracket fixing device I-12 is installed circumferentially by installing a flat key, and at the same time, a v washer I-15 and a fixing nut are used. I-13 and round head nut I-14 are used for axial positioning, and the double-nut fastening structure can prevent loosening to a large extent.
  • the camera rotating bracket fixing device connects the camera part and the translation device part.
  • the assembly drawing of the entire X axis and the direct connection components is shown in Figure 9(c) the assembly drawing of the telescopic rod connecting device, the telescopic rod and the camera rotating bracket fixing device.
  • the camera rotating bracket I-17 is fixed on the camera rotating bracket fixing device I-12 by countersunk screws I-1201, as shown in Figure 10(b) as shown in the assembly drawing of the camera rotating bracket and fixing device.
  • Camera bracket rotation device I-1702, built-in stepping motor and control unit drive the camera to rotate around the machine tool Y-axis at a specified angle, and the installation method and component structure can achieve image collection at a specific angle.
  • the camera bracket buckle I-1701 facilitates the disassembly and replacement of the CCD camera, and meets the requirements of the system to replace the camera according to different functions.
  • the scroll wheel part of the vision system mainly meets the dynamic length adjustment of the camera data line and the motor power line during the motion of the telescopic rod.
  • the motion process is described in detail in the design of the camera motion function below. All components are integrated and installed in the roller mounting box I-05.
  • the main structure is a stepping motor I-0508 with a control unit connected to the drive line roller I-0519.
  • the control unit controls the stepping motor to rotate according to the length of the system command line.
  • the wire harness is wound in the roller groove, and the wire harness is retracted through the forward and reverse rotation of the motor.
  • the winding roller I-0519 is installed in the lower shell of the roller box I-0517, and the lower shell passes through its positioning through holes and the box.
  • the stepped hole of the body I-051201 is used for positioning and installation, and the countersunk bolt I-0514, nut I-0515 and washer I-0516 are used for bolt connection.
  • the drive motor is placed on the motor connecting plate, and the motor connecting plate is also connected according to the bolts. It is installed and fixed in the main box of the roller to ensure that the axis of the roller and the main shaft of the motor coincide.
  • the two shafts are connected through the coupling I-0504 and the flat key I-0505, so that the motor can drive the roller to rotate.
  • the roller I-0519 is placed in the roller box.
  • the box is divided into upper and lower parts.
  • a cavity with a specific structure is cast inside to match the bearing sleeve I-0521, deep groove ball bearing I-0521, and end flange cover I-0524 And the specific structure of the cavity to complete the assembly of the roller.
  • the assembled cross-sectional view is shown in Figure 14(b) in Figure 14(a) GG cross-sectional view.
  • the upper and lower shells of the roller box and the flange cover are connected by bolts at specific positions. Encapsulation of the entire structure.
  • the vibration signal collection is completed by the smart tool holder, which has a built-in vibration sensor, and realizes the self-generation of the smart tool holder during processing through a rotating drive mechanism, which is used by the vibration sensor and the top wireless signal transmitter.
  • the main body of the intelligent tool holder is composed of the tool holder fixing part I-18 and the tool holder core working part I-21, the cutter head fixing part I-26.
  • the core working part I-19 of the tool holder is a hollow part, which integrates various working parts inside.
  • the upper and lower ports are threaded holes. Both the upper and lower parts of the tool holder are threaded.
  • the integral connection of the three parts is realized through the threaded connection.
  • the cutter head is used to install various blades. Different cutter heads can be replaced according to different processing processes. As shown in Figure 18, there are two different cutter heads. Different cutter heads can be installed with different types of blades, as shown in Figure 19(a) and Figure 19. (b) As shown in the axonometric drawing of indexable blades, the system can monitor various installed blades.
  • the principle of power generation is the principle of electromagnetic induction.
  • the tool holder rotates at a high speed during the machining process, driving the internal power generating device rolling body I-2107 to follow the rotation, and its follow-up rotation mainly passes through the cylindrical rolling body and works.
  • the friction force of the inner wall of the rolling element I-2107 is shown in Fig. 20(a)
  • the internal component structure diagram of the middle part of the smart knife holder, and the top and bottom are shown in Fig.
  • the front view of the middle part of the smart knife holder The bearing, the rolling element and cage I-211104 of this bearing are shown in the corresponding parts in the front view of the middle part of the smart tool holder in Figure 22(b).
  • the upper and lower support bodies of the rolling element are the inner and outer rings.
  • the lower part is the outer ring.
  • the inner and outer rings can rotate relative to each other under the action of the rolling elements. All bearings in this power generation device use this type of bearing.
  • the rolling element and the bearings at both ends are installed in the hollow part of the working part of the tool holder.
  • the bottom of the rolling element is enclosed in the hollow cavity of the working part through a flange cover.
  • the coil is installed in the rotating rolling element I-2107.
  • the axonometric drawing of the coil is shown in Figure 21.
  • the bottom outer ring of the reduction bearing is in transitional fit with the closed entity.
  • the convex parts have the same shape and can be plug-in installation.
  • the high-speed rotation of the tool holder drives the rotating rolling elements to follow the rotation, and the rotating rolling elements drive the bottom outer ring of the reduction bearing to rotate.
  • the top inner ring also follows the rotation under the action of the rolling element friction.
  • the tool holder rotates at high speed, but the inside The coil rotates at a very slow speed, and the two produce a large slip rate.
  • a permanent magnet is installed inside the hollow of the tool holder, and the coil part is integrated with a closed coil. In this rotating state, the permanent magnet generates a changing magnetic field due to the rotation, so that The closed coil cuts the magnetic induction line and generates current.
  • the current generated by the closed coil is shown in the cross-sectional view of JJ section 21(b) in Figure 21(c).
  • the current transmission part I-211002 is delivered to the current rectifier module I-210402 for rectification and storage
  • the power line is routed through the internal power supply tube to provide power to the vibration sensor and the radio frequency transmitter.
  • the integrated vibration sensor inside the coil is fixed on the deceleration bearing through the fixing frame I-2114 to obtain the vibration signal generated in real time due to the tool change during the machining process.
  • the assembly cross-sectional view of the integrated component inside the coil is shown in Figure 21(c), 21(b)
  • the front view of the coil assembly unit is shown.
  • Each unit communicates through the intelligent module to realize the information exchange, and then realizes the overall control system to prioritize the actions at different stages to ensure the normal operation of the machine tool.
  • the machine vision system is connected with the machine tool servo system, and the servo system accepts the action instructions of the machine vision system and cooperates with the machine vision system to complete image collection After that, disconnect the connection and resume normal processing of the machine tool.
  • it can realize the real-time acquisition of processing parameters by each unit, so that each part can complete the set work according to the processing requirements. If the machining accuracy is input to the system and the tool monitoring unit obtains it in real time, the tool abnormality pre-judgment threshold will be changed in real time to ensure that the tool of the machine tool can always be in a valid state.
  • the core computing part of the system is executed by an external industrial computer, including real-time acquisition of real-time data of each subsystem, analysis, judgment and decision-making, transmission and transmission of commands to each subsystem according to different working conditions, execution of various machine tools at different stages of action and subsystem work Coordination of distribution and so on.
  • the database unit VII is used to store the massive data generated during the intelligent monitoring process.
  • the vibration signal collected during the tool monitoring process and the image signal collected by machine vision are mainly used for the storage of signal data and the transmission with the system.
  • the database in this unit simultaneously completes the design and process parameters of CNC machine tools. In most cases, this data presents a dynamic mode and needs to be stored randomly during the design and manufacturing process.
  • the final functional requirements of this system should also have the relevant manufacturing and enterprise management personnel to be able to query the information of CNC equipment in real time at any time, so this system selects the Web database system based on the C/S structure as
  • the main work carrier of the database unit realizes data input and storage and data output through the communication connection with the entire system, and becomes a transfer station for the operation of each system, which greatly saves the memory load of the industrial computer and provides for the normal and stable operation of the system
  • it can realize the real-time acquisition of device information by relevant personnel through the web client through smart devices such as mobile phones.
  • modern databases already have comprehensive data center processing capabilities, fast performance, and unlimited virtualization capabilities, the database in this system can complete the database functions of this system while taking into account the functional requirements of other systems of CNC equipment. That is, this module has scalability in practical applications.
  • the decision-making and control unit VI is mainly composed of an external industrial computer and an internal control system of numerical control equipment.
  • the internal processor of the professional computer performs the intelligent analysis of the collected data as described above, the decision is made, and then different actions are completed by issuing instructions to the machine tool control system.
  • the intelligent tool magazine unit II is developed based on the ARM microprocessor. Design an automatic tool change system, which can perform automatic tool change actions according to the machine tool change instructions.
  • a disk-shaped tool magazine is used as an example to introduce the function of the tool library.
  • Different types of tools used in the machining process are backed up and installed in the disk-shaped tool library. Two tools of the same type are installed nearby, which is convenient for tool management.
  • the tool selection method adopts any tool selection method, and the required tool is selected according to the requirements of the program command, that is, when the tool is abnormal in the processing process, according to the program tool change command issued by the decision-making unit, the tool library is designated and selected as a spare The tool is changed.
  • the automatic tool change system in the intelligent tool magazine unit has a tool recognition device.
  • the identification of the tool is mainly through the numbering of different tool holders in the tool magazine.
  • the tool holders with different numbers are installed with different types of tools and input into the ARM tool change system before processing.
  • the intelligent tool magazine can be calibrated after identifying the status of the tool according to the data analysis module.
  • the data analysis unit analyzes and finds that the tool is abnormal, the unit performs abnormal calibration of the tool seat number where the tool is located, replaces the tool, and stores the abnormal tool in the library.
  • the image signal data analysis is completed and the accurate state of the tool is obtained, it is transmitted to the intelligent tool magazine unit for information update of the abnormal state.
  • the information is sent to the intelligent tool magazine unit to remove the abnormal calibration of the abnormally calibrated tool.
  • the tool changer of this unit consists of two manipulators with opposite orientations, which complete the tool change between the tool magazine and the worktable through the directional rotation of the rotating shaft by the drive device.
  • Abnormal tool conveying unit IV mainly refers to industrial machinery grippers, such as ABB industrial robots and other equipment. Through the establishment of a communication connection between the industrial robot and the intelligent tool magazine, the mutual transmission and sharing of information is realized, and the auxiliary equipment is guided to complete the set work. The specific work is: After the intelligent tool magazine updates the accurate status of the calibrated abnormal tool, the manipulator classifies and transports the tool to the tool processing area according to the abnormal type of the tool. If the cutting edge of the tool is damaged, the tool is transported to the tool change area; The blade becomes blunt and transports the tool to the tool sharpening area, etc.
  • Figure 24 is a working flow chart of the machine tool after the tool is initially judged abnormal
  • Figure 25 is a schematic diagram of the wear of the interchangeable tool blade
  • Figure 27 is the schematic diagram of the tool initial judgment module; including:
  • the data acquisition unit and the data analysis and processing unit are divided into two subsystems, which are respectively used for pre-judgment and precise judgment of the tool status.
  • the vibration signal during the machining process is detected and used as the signal input for the system tool detection pre-judgment.
  • the vibration sensor is integrated in the smart tool holder, and uses wireless transmission inside the tool holder. This device will not compress the normal working space of the bed, and will not interfere with the direction and angle movement of the working moving parts. It is suitable for use in actual production.
  • the signal collected by the vibration sensor is transmitted to an external industrial computer through the wireless device in real time for data processing, analysis and judgment. Data analysis, processing and judgment are mainly done through related software in industrial computers, such as matlab software for data processing and analysis.
  • the types of tool faults are mainly divided into two types: excessive wear of the blade and tool damage.
  • Tool wear will change the geometry of the tool, the cutting edge will become blunt, and the cutting force will change during the cutting process, which will lead to varying degrees of vibration in the workpiece processing area.
  • the cutting part of the tool is deformed obviously, the cutting force will change sharply in an instant, and the vibration signal will also change sharply.
  • the monitoring of the broken state of the tool can be realized by monitoring the instantaneous change of the vibration signal in real time.
  • the change process of tool wear is a gradual process.
  • flank wear process curve is basically similar to the shape of the bathtub curve. As shown in Figure 25, the wear is divided into three stages, initial wear, normal wear, and sharp wear.
  • the tool state pre-judgment module monitors the amount of tool wear through machine learning SVM for real-time monitoring.
  • SVM is a machine learning algorithm established on the basis of the VC dimension theory of statistical learning theory and the principle of structural risk minimization.
  • the dimension of vector features does not affect the complexity of the algorithm itself, which not only saves time and cost, but also enables the establishment of monitoring models It's easier.
  • the classification of SVM is an algorithm based on the principle of two classifications. It maps the tool wear characteristic training samples to a higher-dimensional space, and establishes an optimal classification hyperplane pair space in this high-dimensional space. Different types of vectors are divided. In this embodiment, the above-mentioned three tool wear vectors are selected and divided into hyperplanes.
  • the classification hyperplane can be used as the corresponding classifier in the aforementioned data analysis and processing unit.
  • This monitoring method is an indirect measurement.
  • Machine learning training is carried out through historical experimental data of tool wear to obtain a machine learning model that meets the needs of the system. In order to avoid the influence of other factors in the machining process on the collected vibration signals, the collected signals are extracted as the input of the SVM, and the tool wear is the output, and the model of the tool state pre-judgment suitable for the requirements of the system is trained. In order to make the final training model more accurate, the signal feature multi-method fusion extraction method is adopted in the feature extraction part to remove noise interference and extract effective information to the greatest extent.
  • the method of combining two signal processing methods of EMD empirical mode decomposition and principal component analysis is used to describe the extraction of signal vibration signal characteristics.
  • EMD is an important part of a new non-stationary signal Hilbert-Huang transform that has emerged in recent years. It is suitable for the analysis of linear and stationary signals as well as the analysis of nonlinear and non-stationary signals.
  • the essence of this method is to identify all the vibration modes contained in the signal through the characteristic time scale. In this process, the characteristic time scale and the definition of IMF have a certain degree of experience and approximation.
  • the EMD method is intuitive, indirect, posterior, and adaptive.
  • the characteristic time scale used in its decomposition is derived from the original signal, that is, the signal comes from the internal spindle of the machine tool and other drive motors.
  • the specific decomposition process of the electric vibration signal that changes with the time scale is as follows:
  • the inherent modal function of each order covers all the information of tool wear during the machining process.
  • Principal component analysis is a statistical method. Transform a group of potentially correlated variables into a group of linearly uncorrelated variables through orthogonal transformation, and the group of variables after conversion is called principal components.
  • the inherent modal functions of each order after EMD decomposition are treated as groups of uncorrelated vectors, and the principal components of the electrical vibration signal after EMD decomposition are finally obtained. Through the calculation of the contribution rate of different components, the first few principal components whose information contribution rate reaches 85% or more are selected as the input of the vector in machine learning.
  • the estimated value of tool wear can be obtained by inputting the real-time monitoring signal to SVM, and the system will automatically set the wear threshold according to the machining accuracy requirements.
  • the tool flank wear VB 0.3mm is the default Threshold value, when the tool VB> 0.3mm, the tool will enter the stage of sharp wear, which will have a greater impact on the machining accuracy.
  • the parameter requirements can be input in the manual interface.
  • the tool status The judgment module automatically adjusts the VB wear threshold according to the parameter requirements to ensure the machining accuracy requirements of the machine tool.
  • the direct tool measurement method used is tool vision image acquisition and subsequent image comparison.
  • the standard geometric size images of all tools in the intelligent tool magazine of CNC machine tools are stored in the system database unit.
  • the data analysis module can retrieve the standard tool geometry image and the image collected by machine vision from the database according to the tool parameter information in the current state.
  • Use the professional image processing function module in the data processing unit to perform multi-angle Comparing and calculating the geometric dimensions of the orientation, it is obtained whether the tool is abnormal and the specific quantification of the abnormal tool state.
  • This system mainly refers to the specific value of the tool wear and whether the tool is damaged. With the classification of tool monitoring status during machining, this module can be expanded.
  • the machine vision acquisition device includes a magnetic base part, through which the acquisition device is installed and fixed to the working tool table.
  • the fixed position origin on the tool table is similar to the coordinate form of the machine tool and it is set as a workpiece coordinate system in the machine tool.
  • the external machine vision acquisition device is connected with the machine tool coordinate system to make the image acquisition device Become a part of CNC machining system.
  • the fixed position is the intersection of the circumferential line of the cylindrical tool post and the X-axis direction to ensure that the Y-axis coordinate point is consistent with the tool coordinate point.
  • the image acquisition of the axial direction of the bottom of the tool is installed through the CCD lens and the connection part of the tool bar.
  • the rotating mechanism realizes the up and down rotation of the lens along the Y axis.
  • the machine vision system only performs image acquisition skills of two azimuth angles in the circumferential and axial directions to meet the requirements of geometrical size comparison in the image processing module.
  • the machine vision system is designed as a whole with a stretchable and compressible working guide rod. When in the working state, the guide rods on the X and Y axis can be used to reach any spatial position of the working area.
  • a linear pull-rope displacement sensor is installed inside the end of the two-axis guide rod.
  • the linear pull-rope displacement sensor obtains the coordinate values of the X-axis and Z-axis at work, and combines the position data of the zero coordinate in the workpiece coordinate system of the machine tool.
  • the coordinates of the lens position in the machine tool are calculated to realize the automatic judgment and adjustment of the position of the vision system during the subsequent image acquisition process.
  • the machine vision system establishes a communication connection with the numerical control system, so that the lens position of the machine vision system can be monitored and controlled in real time by the numerical control system like a tool.
  • the working guide rods are in a contracted state. At this time, the entire system occupies the smallest volume of space, which is not the normal working space of the compressor bed.
  • the work guide rod adopts an electric telescopic rod device to realize the movement in the Z-axis and X-axis directions, and a rope-type displacement sensor is installed on the head of the electric telescopic rod to detect and calculate the coordinates of the camera lens position.
  • the driver drives the internal sliding brush of the sensor to change the displacement, output a linearly changing DC voltage signal, and provide it to the system for the camera lens position coordinate
  • the calculation is stored in the CNC system, and the coordinates are displayed on the display board at the same time.
  • a connecting wire retracting device Since the CCD camera and the system need to be connected, in order to avoid damage to the wire during the expansion and contraction of the rod, a connecting wire retracting device is designed.
  • the principle is to design a grooved roller, and the wire is wound on the roller through the groove.
  • the roller motor According to the system's detection of the telescopic length of the telescopic rod, the roller motor is automatically driven to perform forward and reverse rotation to realize the retracting and unwinding of the wire harness, thereby avoiding the problem of excessive pulling or curling of the data cable during the expansion and contraction process.
  • the prerequisite for the normal operation of the machine vision system is to have a strong auto-focusing ability.
  • this system uses CCD camera to adopt passive auto-focus technology, and auto-focus according to the imaging definition to meet the requirements of image acquisition. Since the realization of the main function of this system is to perform further status confirmation and calculation and quantification of the abnormality of the abnormal tool category judged by the initial monitoring, the initial abnormal state of the tool mainly comes from the cutting edge area of the tool, so the focus window size of the vision system is based on the real-time numerical control system.
  • State parameter data is automatically judged, such as judging the position of the lens work center of the vision system according to the tool setting point coordinates, and checking the parameters of the working tool according to the current tool number transmitted by the CNC system, so that the machine vision system can focus on the focus area according to the current tool's own parameter characteristics
  • the automatic judgment and division of the window and the sampling frequency and other relevant parameters in the image acquisition process make self-determination settings. The above methods are used to ensure the effectiveness and accuracy of the acquired images, and avoid the redundancy or lack of acquired image information.
  • the core of the machine vision system is image acquisition and processing, and the quality of the image itself is extremely critical to the entire system.
  • the illumination light source is the most important factor in determining the image quality of the machine vision system.
  • the target features in the image can be optimally separated from the background information, thereby greatly reducing the difficulty of image processing and improving the stability of the system And reliability.
  • the machine vision system adopts LED light source, and the light source is selected according to engineering requirements such as the geometric characteristics of the machine tool and optical properties to meet the requirements of this machine vision system.
  • the main control system will issue a machine stop command and the tool will rise to a safe position.
  • the machine tool sends a start work instruction to the machine vision system at the same time.
  • the machine vision system is in working state.
  • the CCD camera is quickly transported to the periphery of the tool through the system internal position judgment function module and the control system module.
  • the tool image acquisition low-speed intermittent rotation command is issued to the machine tool working system, the spindle rotates slowly and intermittently, and the CCD camera performs rapid focusing and completes image acquisition in a short time when the spindle rotates intermittently and the tool is in a static state.
  • the intermittent rotation of the spindle is highly matched with the image frequency of the lens and the focusing time in the case of dynamic image acquisition. To avoid excessive speed affecting the quality of the acquired image, and too slow to increase the acquisition process time, which affects the subsequent tool change and processing of the machine tool.
  • the collected image information is sent to the data information processing module, and the spindle stop instruction is issued to the machine tool again, and the system working guide rods are all retracted, so that the system is in a non-working state.
  • the entire machine vision system is developed using an embedded system to realize image data collection, data transmission, component control and communication functions.
  • Embedded system technology includes integrated circuit technology, system structure technology, sensing and detection technology, and real-time operating system, etc. Technology, with the technical support of this system, all the functions described in the above-mentioned machine vision system can be realized.
  • This system communicates with multiple module systems in the entire numerical control equipment, and is connected with the data analysis and processing module to realize further analysis of image information and complete accurate diagnosis of abnormal tool conditions. It communicates with the machine tool control system to complete the coordinated actions of the machine tool during the image acquisition process. Connect with the data storage module to realize data preservation and continuous filling and updating of database content. It is connected with the display module to realize the process monitoring and display in the process of image data acquisition.

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Abstract

一种数控机床刀具状态监测及控制系统与控制方法，实时采集到刀具加工过程中的异常振动信号；利用刀具状态预判断的模型对异常情况进行状态预判断并确定刀具发生异常的时间点；在状态预判断后且在不影响刀具加工的连续性的情况下完成刀具图像的采集，实现对刀具异常状态做出准确判断。该控制系统在刀具状态判断上分为状态预判断及刀具的精确判断，且系统在工作过程中占用短暂的设备正常运行时间，有效提高了机床的工作效率；该系统中刀具状态预判断基于机器学习理论原理，刀具状态的精确判断基于图像比对及分析处理方法。

Description

数控机床刀具状态监测及控制系统与方法 技术领域
本发明属于数控设备状态监测领域，尤其涉及数控机床刀具状态监测及控制系统及方法。
背景技术
本部分的陈述仅仅是提供了与本公开相关的背景技术信息，不必然构成在先技术。
机床作为制造加工行业的基础设备，对其进行状态监测具有重要意义。在数控加工过程，产品质量的保障及加工过程的安全性离不开对数控设备刀具的实时监测，其状态监测是数控设备监测的一个重要组成部分，如果不能对加工过程中刀具突发状况进行实时监测和采取有效的控制措施，则会对加工过程的连续性产生不同程度的影响，对整个制造产业造成不可估量的损失。
通过对相关文献查阅发现，设备刀具在加工过程中发生的非正常损坏，即刀具磨、破损情况的发生，如果得不到及时控制将直接导致所加工零件的损坏及报废，尤其是在刀柄及刀片加工过程中体现尤为明显，如果设备刀具发生异常不能及时检测及采取有效控制措施，可能导致成批量加工的刀柄及刀片不满足工艺要求，无法保证购买者在后续机加工中零件的精度及相关刀具使用寿命，并且在某些特殊加工工序中甚至会对机床设备造成不同程度的损伤。为了避免以上情况的发生，开发一套有效的刀具状态在线监测和控制系统显得尤为重要，通过此系统可以实现对刀具的有效管理，提高刀具的使用寿命，降低生产成本，提高加工效率，进而增加企业的生产效益。
刀具损坏是机床在加工过程中最常见的故障类型，许多机床生产商在制造过程中通常设计添加监测单元，包括对刀具状态的监测。然而由于加工制造工艺的千变万化，所选用刀具也各不相同，故设备自身的监测系统对刀具监测的适应性及准确率较低。
发明人在研究中发现，现有的刀具检测系统存在采用检测切削力作为状态判断的依据，使系统整体的分辨率较低，导致加工过程中切削力变化的因素十分复杂，故此系统容易对刀具状态做出误判，影响机床正常的加工。
还有的刀具检测系统需要在系统中添加不同种类的传感器，开发的系统需要将多个传感器进行融合，降低了系统工作过程的稳定性。同时由于传感器的安装需要贴近刀具及其附近连接件，传感器与系统处理器需要连线进行数据传输，很大程度上干扰机床的正常加工，阻碍了此种刀具状态监测方法在实际生产的应用。
还有的刀具检测方法可以对异常刀具状态进行有效的监测，但是随着企业传统制造向智能制造步伐的持续迈进，对刀具状态监测的精度要求越来越高同时实时性也要满足生产要求，故单独对刀具的异常状态的有效监测已经不再满足企业自动化产线向智能产线转变的技术要求，因此对刀具在线状态监测提出了精度更高，实时性更好的技术要求。
另外由于在实际加工过程中，刀具回转的速度变化范围较大，且存在加工过程中切削润滑方式等因素变化的情况，使现有装置在某些工况下无法起到很好的刀具状态监测功能。
现有技术中的机器视觉的机床刀具在位检测系统的检测节奏不能实现自主化，或者由人工参与进行检测时间节点的设置，或者根据以往历经验设置自动检测节拍，在此方面的自动化检测中智能化程度相对欠缺。
发明内容
为克服上述现有技术的不足，本发明提供了数控机床刀具状态监测及控制系统，该系统能够在实现对刀具状态精确监测的同时，极大压缩刀具异常诊断过程的停机时间，提高机床的生产效率。
为实现上述目的，本发明的一个或多个实施例提供了如下技术方案：
数控机床刀具状态监测及控制系统，包括：数据采集单元及数据分析处理单元；所述数据采集单元包括振动状态检测装置及机器视觉采集装置；
所述振动状态检测装置实时采集到刀具加工过程中的异常振动信号并传输至数据分析处 理单元；
所述数据分析处理单元利用刀具状态预判断的模型对异常情况进行状态预判断并确定刀具发生异常的时间点；
所述机器视觉采集装置在状态预判断后且在不影响刀具加工的连续性的情况下完成刀具图像的采集并传输至数据分析处理单元，实现对刀具异常状态做出准确判断。
本公开的实施例子还公开了数控机床刀具状态监测及控制系统的控制方法，包括：
实时采集到刀具加工过程中的异常振动信号；
利用刀具状态预判断的模型对异常情况进行状态预判断并确定刀具发生异常的时间点；
在状态预判断后且在不影响刀具加工的连续性的情况下完成刀具图像的采集，实现对刀具异常状态做出准确判断。
进一步的技术方案，对刀具进行状态预判断时，针对不同的故障类型分别处理，对于刀具破损，通过实时监测振动信号的瞬时变化情况即可实现对刀具破损状态的监测，对刀具磨损量的监测则通过机器学习SVM进行实时监测。
进一步的技术方案，对刀具磨损量的监测则通过机器学习SVM进行实时监测时，对采集的振动信号进行特征提取，作为SVM的输入，刀具磨损量作为输出，训练适合本系统要求的刀具状态预判断的模型。
进一步的技术方案，以EMD经验模态分解和主成分分析两种信号处理方式结合的方法进行振动信号特征提取：
经过EMD方法分解就将原始电流振动信号分解成一系列IMF以及剩余部分的线性叠加；
采用主成分分析方法对EMD分解后得到的固有模态函数进行主成分分析，即将EMD分解后的各阶固有模态函数作为各组不相关的向量处理，最终得出EMD分解后电振动信号的主成分。
进一步的技术方案，根据实时监测的信号输入到SVM得到刀具磨损的估计值，设置磨损量阈值，当刀具磨损量大于设定阈值后，刀具会进入急剧磨损阶段。
进一步的技术方案，在机床发生刀具异常状态下，根据当前状态下刀具的参数信息从数据库中调取标准刀具几何图像与机器视觉采集的图像运用数据处理单元中专业图像处理功能模块进行多角度，多方位的几何尺寸对比计算，得出刀具是否发生异常及对异常刀具状态的具体量化，主要指刀具磨损量的具体数值及刀具是否发生破损。
进一步的技术方案，机床在加工过程中出现刀具异常状态后，发出机床停转指令，刀具上升至安全位置；
与此同时，机床同时向机器视觉采集装置发出开始工作指令，机器视觉采集装置根据机床内部传输的刀具位置坐标，将CCD相机快速输送至刀具周边位置后，向机床工作系统发出刀具图像采集低速间歇旋转指令，主轴慢速间歇旋转，在主轴旋转间歇过程中刀具处于静止状态下，CCD相机进行快速对焦并在短时间内完成图像采集，此过程，主轴间歇旋转运动与镜头采集图像频率及动态图像采集情况下的对焦时间在节拍上契合，图像信号采集结束后，再次向机床发出主轴停转指令，使系统处于非工作状态。
进一步的技术方案，机器视觉采集装置包括磁座部分，通过磁座部分将采集装置安装固定至工作刀台上，在刀台上将固定位置原点设置为机床中一个工件坐标系，作为整个机器视觉采集装置在机床坐标系中的一个工件坐标系，称其为零点坐标，在此零点坐标的串联下将外置的机器视觉采集装置的与机床坐标系建立连接，使图像采集装置成为数控加工系统中的一部分；
固定位置为圆柱形刀台的圆周线与X轴方向的交点位置，保证其Y轴坐标点与刀具坐标点一致，在后续机器视觉采集装置工作过程中，只进行Z轴和X轴两个方向的运动即可满足此系统的运动性能的要求，对刀具底部轴向方向的图像采集通过CCD镜头与刀杆连接部安装的旋转机构实现镜头沿Y轴线上下旋转。
进一步的技术方案，机器视觉采集装置只进行周向及轴向两个方位角度的图像采集；
在处于工作状态时通过X和Y方向轴上的导杆实现工作区域任意空间位置的到达，在两 轴导杆的末端内部设置有位移传感器，通过位移传感器得出X轴和Z轴在工作时的坐标值，结合零点坐标在机床工件坐标系中位置数据，计算得出镜头位置在机床中的坐标，实现后续图像采集过程中的位置自动判断及调整。
以上一个或多个技术方案存在以下有益效果：
本公开将机器学习理论与机器视觉检测方法进行有机的结合。利用机器学习技术对传感器一维信号与刀具状态的映射关系对刀具进行状态预判断，其具有正确性较高及速度快的优点，然而基于机器学习理论的模型训练准确率难以达到万无一失，这样会对异常刀具的后续处理增加额外工作负担，在此基础上增加机器视觉监测模块，其作为一种直接监测方式，能够有效保证准确率，然而现代图像实时处理技术的速度难以达到工业现场生产的加工速度要求。本发明系统能在数控设备加工过程中对机床刀具进行实时监测，当刀具状态异常发生，机器学习诊断模型能快速对异常情况进行异常监测与响应，机床停机，图像视觉系统在短时间内完成刀具图像的采集后，进行换刀，继续加工，保证加工的连续性。数据分析处理单元后续对采集的刀具图像进行图像分析处理，最终实现刀具状态的精确判断，同时对刀具状态的预判断进行验证。通过两种技术的有效结合，实现了本系统所提出的优益功能。本发明系统各部分之间进行通讯连接，工作过程中根据不同状态各单元都实时进行状态的更新，通过智能控制计算机对加工过程进行实时智能控制。
本公开的系统在刀具状态判断上分为状态预判断及刀具的精确判断，且系统在工作过程中占用短暂的设备正常运行时间，有效提高了机床的工作效率。
本公开的系统中刀具状态预判断基于机器学习理论原理，刀具状态的精确判断基于图像比对及分析处理方法。
本公开的数据采集单元由内置传感器的智能刀柄及由磁座固定在机床上可拆卸的机器视觉采集装置构成，内置传感器的智能刀柄保证检测刀具发生异常的精确时间点，机器视觉采集装置通过对刀具的图像采集及信息比对以保证对刀具状态做出精确判断；
本公开的智能刀柄安装有永久磁体，通过内部设计安装的由旋转滚动体及轴承等组成的减速机构，使内部线圈机构在加工过程中能通过电磁感应效应发电，使智能刀柄具有自供电功能。同时内部集成的传感器连接无线发射装置，解决了加工区域部分线路走线问题，不压缩机床正常工作空间；
本公开的机器视觉装置中采用CCD相机进行图像的采集，通过两个垂直连接的电动伸缩杆可将CCD相机输送至系统指定检测位置完成图像采集，电动伸缩杆上装有位移传感器，可以对CCD相机位置坐标进行监测，使CCD空间坐标能在系统中实时监测与控制；
本公开的数据库单元与其他各单元都进行通讯连接，使本系统中各单元的数据信息能够实时共享，并且保证决策及控制单元根据实时信息对各单元进行有效控制；
本公开的系统中各种硬件装置及软件系统与现有的大多数机床匹配度高，并且安装方便，不需要对机床设备在很大程度上进行改造。
附图说明
构成本发明的一部分的说明书附图用来提供对本发明的进一步理解，本发明的示意性实施例及其说明用于解释本发明，并不构成对本发明的不当限定。
图1为本公开实施例子的刀具在线状态检测及控制系统结构图；
图2为本公开实施例子的视觉检测装置轴测图；
图3(a)-图3(b)为本公开实施例子的磁座与Z轴电动伸缩杆轴测图；
图3(c)为本公开实施例子的相机数据线收放装置固定箱体；
图4(a)为本公开实施例子的位移传感器与伸缩杆连接板；
图4(b)为本公开实施例子的图4(a)所示连接板A-A截面剖视图；
图5(a)为本公开实施例子的电动伸缩杆，连接部件及传感器装配图；
图5(b)为本公开实施例子的图5(a)B-B截面剖视图；
图5(c)为本公开实施例子的图5(a)ⅰ出局部放大图；
图6(a)为本公开实施例子的伸缩杆连接部件轴测图；
图6(b)为本公开实施例子的伸缩杆连接部件主视图；
图6(c)为本公开实施例子的图6(b)ⅱ处局部放大图；
图6(d)为本公开实施例子的图6(b)处C-C截面剖视图；
图7为本公开实施例子的圆锥销；
图8为本公开实施例子的X轴电动伸缩杆轴测图；
图9(a)为本公开实施例子的相机旋转支架固定装置；
图9(b)为本公开实施例子的相机旋转支架固定装置俯视图；
图9(c)为本公开实施例子伸缩杆连接装置，伸缩杆及相机旋转支架固定装置装配图；
图9(d)为本公开实施例子的图9(c)ⅲ处局部放大图；
图10(a)为本公开实施例子的相机旋转支架轴测图；
图10(b)为本公开实施例子的相机旋转支架及固定装置装配图；
图11为本公开实施例子的相机数据线收放装置爆炸图；
图12(a)为本公开实施例子的相机数据线收放装置外壳；
图12(b)为本公开实施例子的滚轮安装箱下箱体；
图12(c)为本公开实施例子的滚轮安装箱下箱体俯视图；
图12(d)为本公开实施例子的图12(c)D-D截面剖视图；
图13(a)为本公开实施例子的滚轮安装箱轴测图；
图13(b)为本公开实施例子的滚轮安装箱上箱体轴测图；
图13(c)为本公开实施例子的滚轮安装箱下箱体轴测图；
图13(d)为本公开实施例子的滚轮安装箱装配主视图；
图13(e)为本公开实施例子的图13(d)处E-E截面剖视图；
图13(f)为本公开实施例子的滚轮安装箱法兰盖主视图；
图13(g)为本公开实施例子的图13(f)处F-F截面剖视图；
图14(a)为本公开实施例子的滚轮单元装配俯视图；
图14(b)为本公开实施例子的图14(a)处G-G截面剖视图；
图15为本公开实施例子的滚轮驱动电机轴测图；
图16(a)为驱动电机连接板主视图；
图16(b)为本公开实施例子的图16(a)处H-H截面剖视图；
图16(c)为本公开实施例子的图16(a)ⅳ处局部放大图；
图16(d)为本公开实施例子的电机与连接板连接示意图；
图16(e)为本公开实施例子的图16(d)ⅴ处局部放大图；
图17(a)为本公开实施例子的智能检测刀柄轴测图；
图17(b)为本公开实施例子的智能检测刀柄爆炸图；
图18(a)与图18(b)为本公开实施例子的智能刀柄可替换安装的两种刀盘轴测图；
图19(a)与图19(b)为本公开实施例子的两种可转位式刀片轴测图；
图19(c)为本公开实施例子的刀片切削工件轴测图；
图20(a)为本公开实施例子的智能刀柄中部内部部件结构图；
图20(b)为本公开实施例子的智能刀柄中部主视图；
图20(c)为本公开实施例子的图20(b)处I-I截面剖视图；
图20(d)为本公开实施例子的智能刀柄中部剖视图
图21(a)为本公开实施例子的发电装置内部线圈轴测图；
图21(b)为本公开实施例子的线圈组装单元主视图；
图21(c)为本公开实施例子的图21(b)处J-J截面剖视图；
图21(d)为本公开实施例子的图21(b)ⅵ处局部放大图；
图22(a)为本公开实施例子的振动传感器单元轴测图；
图22(b)为本公开实施例子线圈固定轴承；
图23为本公开实施例子系统各单元连接示意图；
图24为本公开实施例子初判断刀具异常后机床工作流程图；
图25为本公开实施例子可换位刀具刀片磨损示意图；
图26为本公开实施例子数控设备换刀装置轴测图；
图27为本公开实施例子刀具初判断模块原理图；
图28为本公开实施例子智能刀库单元轴测图；
图中Ⅰ、数据采集单元，Ⅱ、数据分析处理单元，Ⅲ、智能刀库单元，Ⅳ、异常刀具输送单元，Ⅴ、显示单元，Ⅵ、决策及控制单元、Ⅶ、数据库单元。
Ⅰ-01-磁座，Ⅰ-02-Z轴电动伸缩杆，Ⅰ-03-Z轴位移传感器连接板，Ⅰ-04-Z轴位移传感器，Ⅰ-05-滚轮安装箱，Ⅰ-06-滚轮安装箱固定壳，Ⅰ-07-伸缩杆连接部件，Ⅰ-08-圆锥销，Ⅰ-09-X轴电动伸缩杆，Ⅰ-10-X轴位移传感器连接板，Ⅰ-11-X轴位移传感器，Ⅰ-12-相机旋转支架固定装置，Ⅰ-13-X轴伸缩杆端固定螺母，Ⅰ-14-X轴伸缩杆端固定圆头螺母，Ⅰ-15-垫片，Ⅰ-16-CCD相机，Ⅰ-17-相机旋转支架；
Ⅰ-18-刀柄固定部，Ⅰ-19-加强环固定螺栓，Ⅰ-20-刀柄连接处加强环，Ⅰ-21-刀柄工作部，Ⅰ-22-加强环固定螺母，Ⅰ-23-刀盘安装止挡螺栓，Ⅰ-24-刀盘安装止挡快，Ⅰ-25-加工刀盘，Ⅰ-26-刀盘安装部。
Ⅰ-0101-固定凹槽，Ⅰ-0102-侧壁螺纹孔，Ⅰ-0103-磁座旋钮，Ⅰ-0201-固定凸台，Ⅰ-0202-第一螺纹孔，Ⅰ-0203-第二螺纹孔，Ⅰ-0204-圆锥销孔，Ⅰ-0601-水平侧壁连接通孔，Ⅰ-0602-底板连接通孔，Ⅰ-0603-垂直侧壁连接通孔，Ⅰ-0301-连接板通孔，Ⅰ-0302-阶梯孔，Ⅰ-0401-传感器连接头，Ⅰ-0201-伸缩杆圆锥销孔，Ⅰ-0701-伸缩杆链接部件圆锥销孔，Ⅰ-0702-传感器连接头固定螺纹孔，Ⅰ-0703-X轴伸缩杆固定孔，Ⅰ-0801-圆锥销拆卸螺纹孔，Ⅰ-0901-伸缩杆连接头，Ⅰ-0902固定键槽，Ⅰ-0903-连接螺纹孔，Ⅰ-1201-相机支架连接螺纹孔，Ⅰ-1202-连接键槽通孔，Ⅰ-1203-传感器连接头固定螺纹孔，Ⅰ-1701-相机固定卡扣，Ⅰ-1702-相机旋转驱动装置，Ⅰ-1703-连接螺纹孔；
Ⅰ-0501-滚轮箱体顶板，Ⅰ-0502-法兰盖连接固定螺栓，Ⅰ-0503-联轴节连接螺母，Ⅰ-0504-联轴节，Ⅰ-0505-平键，Ⅰ-0506-顶板连接螺栓，Ⅰ-0507-联轴节连接螺栓，Ⅰ-0508-滚轮驱动步进电机，Ⅰ-0509-电机固定螺栓，Ⅰ-0510-垫片，Ⅰ-0511-联轴节螺栓垫片，Ⅰ-0512-电机固定板，Ⅰ-0513-滚轮主箱体，Ⅰ-0514-滚轮主箱体部件连接螺栓，Ⅰ-0515-六角螺母，Ⅰ-0516-垫片，Ⅰ-0517-滚轮箱体下壳，Ⅰ-0518-滚轮箱体上下壳连接螺母，Ⅰ-0519-绕线滚轮，Ⅰ-0520-深沟球轴承，Ⅰ-0521-轴承套，Ⅰ-0522-滚轮箱体上壳，Ⅰ-0523-滚轮箱体上下壳连接螺栓，Ⅰ-0524-滚轮箱体端盖；
Ⅰ-051301-滚轮箱体下壳连接通孔，Ⅰ-050101-图像信号数据线孔，Ⅰ-050102-滚轮驱动电机电源线孔，Ⅰ-051201-驱动电机连接板固定孔，Ⅰ-051301-滚轮箱体下壳阶梯孔，Ⅰ-052201-滚轮箱体上壳侧壁螺纹孔，Ⅰ-052202-上下壳连接通孔，Ⅰ-050801-驱动电机固定螺纹孔，Ⅰ-051201-连接板固定电机连接孔，Ⅰ-051202-连接板及下壳连接通孔；
Ⅰ-2101-无线射频器，Ⅰ-2102-射频器固定架，Ⅰ-2103-固定架装配轴承，Ⅰ-2104-线圈上端支承轴承，Ⅰ-2105-旋转滚动体上端支承轴承，Ⅰ-2106-电源模块，Ⅰ-2107-旋转滚动体，Ⅰ-2108-旋转滚动体下端支撑轴承，Ⅰ-2109-法兰盖，Ⅰ-2115-信号发射孔，Ⅰ-2116-传感器数据线孔，Ⅰ-211001-线圈绕线凸台，Ⅰ-210401-电源储电模块，Ⅰ-210402-电源整流模块，Ⅰ-211002-电线输送管，Ⅰ-2112-中轴传送线管，Ⅰ-2113-振动传感器，Ⅰ-2114-振动传感器固定夹，Ⅰ-211401-固定夹定位孔，Ⅰ-211402-数据线孔，Ⅰ-2111-线圈固定轴承，Ⅰ-211101-固定夹定位螺纹孔，Ⅰ-211102-线圈固定槽，Ⅰ-211103-传感器固定孔，，Ⅰ-211104-轴承滚动体及支架，Ⅰ-211105-轴承底部外圈。
Ⅲ-01-智能刀库固定孔，Ⅲ-02-刀套，Ⅲ-03-刀库换刀口，Ⅲ-04-刀库换刀驱动装置，Ⅲ-05-刀库固定架，Ⅲ-06换刀固定台，Ⅲ-07-换刀旋转轴，Ⅲ-08-换刀夹手。
具体实施方式
应该指出，以下详细说明都是示例性的，旨在对本发明提供进一步的说明。除非另有指明，本文使用的所有技术和科学术语具有与本发明所属技术领域的普通技术人员通常理解的相同含义。
需要注意的是，这里所使用的术语仅是为了描述具体实施方式，而非意图限制根据本发明的示例性实施方式。如在这里所使用的，除非上下文另外明确指出，否则单数形式也意图包括复数形式，此外，还应当理解的是，当在本说明书中使用术语“包含”和/或“包括”时，其指明存在特征、步骤、操作、器件、组件和/或它们的组合。
在不冲突的情况下，本发明中的实施例及实施例中的特征可以相互组合。
实施例一
参见附图1所示，本实施例公开了数控机床刀具状态监测及控制系统，包括数据采集单元Ⅰ，数据分析处理单元Ⅱ，Ⅶ数据库单元，Ⅵ决策及控制单元，智能刀库单元Ⅲ，显示单元Ⅴ及异常刀具输送单元Ⅳ。系统通过数据采集和数据分析处理单元可以实现刀具状态的精确判断，智能刀库单元和决策及控制单元实现机床刀具异常情况下新刀具的更换及异常刀具的精确判断分类及后续智能处理。
在一实施例子中，图23为系统各单元连接示意图；数据采集单元包括功率传感器、数据采集卡、工业CCD相机及AD转换器，完成数据的采集并传输至数据分析及处理单元，数据分析及处理单元包括工业计算机及工业计算机运行的软件处理模块，数据分析及处理单元与决策及控制单元通信，决策及控制单元包括工业计算机中央处理器及数控机床控制系统，决策及控制单元与智能刀库单元通信，智能刀库单元包括盘行刀库、换刀装置及刀库智能模块，辅助设备为工业机械抓手，智能刀库单元、决策及控制单元及数据分析及处理单元、数据库服务器分别与显示单元通信，进行所需数据的显示。
具体实施例子中，数据采集单元结构及部件连接方式如下：数据采集单元Ⅰ分为两部分，包括振动状态检测装置及视觉检测装置，视觉检测装置主体由电动伸缩杆及拉绳式位移传感器组成，通过其他辅助装置组装成可拆卸的外置式图像视觉采集装置。
视觉检测装置的实现方式参见附图2所示，视觉检测装置包括相机、X轴位移传感器Ⅰ-11、Z轴位移传感器Ⅰ-04及磁座Ⅰ-01；
所述Z轴位移传感器Ⅰ-04通过Z轴电动伸缩杆Ⅰ-02固定在磁座的一侧，磁座的底侧通过伸缩杆连接部件Ⅰ-07连接至X轴电动伸缩杆，X轴电动伸缩杆连接有X轴位移传感器，X轴电动伸缩杆还连接至相机旋转支架固定装置，所述相机旋转支架固定装置Ⅰ-12上安装有相机旋转支架，相机旋转支架Ⅰ-17上安装有相机，所述磁座安装固定至工作刀台上。
其中，磁座的一侧还安装有滚轮安装箱Ⅰ-05，滚轮安装箱安装在滚轮安装箱固定壳Ⅰ-06内，伸缩杆连接部件上设置有圆锥销Ⅰ-08，Z轴位移传感器与Z轴电动伸缩杆通过Z轴位移传感器连接板Ⅰ-03依靠螺栓进行固定安装，X轴位移传感器与X轴电动伸缩杆Ⅰ-09通过X轴位移传感器连接板Ⅰ-10依靠螺栓进行固定安装，X轴电动伸缩杆的一端利用X轴伸缩杆端固定圆头螺母Ⅰ-13、X轴伸缩杆端固定螺母Ⅰ-14及垫片Ⅰ-15安装在相机旋转支架固定装置上。
在一实施子中，相机采用CCD相机Ⅰ-16，X轴位移传感器、Z轴位移传感器采用拉绳式位移传感器。
具体实施例子中，磁座与Z轴电动伸缩杆轴测图参见附图3(a)、3(b)所示，图3(a)中，磁座Ⅰ-01侧壁开有侧壁螺纹孔Ⅰ-0102，磁座的另一侧中部开有固定凹槽Ⅰ-0101，磁座的顶部安装有磁座旋钮Ⅰ-0103，
图3(b)中，Z轴电动伸缩杆的杆体的一端开设有圆锥销孔Ⅰ-0204，Z轴电动伸缩杆的 杆体的另一端为固定凸台，固定凸台两个侧面上分别设置有第一螺纹孔Ⅰ-0202及第二螺纹孔Ⅰ-0203。
具体实施例子中，图3(c)为相机数据线收放装置固定箱体结构示意图，该箱体上底板上开设有底板连接通孔Ⅰ-0602，垂直侧壁上开设有垂直侧壁连接通孔Ⅰ-0603，另一垂直侧壁的上边缘向外水平延申，形成水平侧壁，开设有水平侧壁连接通孔Ⅰ-0601。
具体实施例子中，图4(a)为位移传感器与伸缩杆连接板结构图；图4(b)为图4(a)所示连接板A-A截面剖视图；
X轴位移传感器连接板及Z轴位移传感器连接板为相同的结构，板上分别开设有连接板通孔Ⅰ-0301及阶梯孔Ⅰ-0302，在一实施例子中，阶梯孔为4个，位于连接板的中部，连接板通孔为4个，两个一组，分别位于连接板的靠近两端的结构上。
位移传感器主体部分固定在电动伸缩杆的驱动设备上，另一端固定于伸缩杆末端。CCD相机与X轴电动伸缩杆末端通过旋转控制器连接，能实现Y轴方向旋转，配合X轴及Y轴的直线位移即可实现对刀具图像的有效采集。
具体实施例子中，图5(a)为电动伸缩杆，连接部件及传感器装配图；图5(b)为图5(a)B-B截面剖视图；图5(c)为图5(a)ⅰ出局部放大图；
伸缩杆连接部件Ⅰ-07开设的伸缩杆圆锥销孔Ⅰ-0204与伸缩杆链接部件Ⅰ-07圆锥销定位孔Ⅰ-0701相匹配，伸缩杆连接部件Ⅰ-07还设置有传感器连接头固定螺纹孔Ⅰ-0702，用于固定传感器，Z轴位移传感器Ⅰ-04的下端为传感器连接头Ⅰ-0401。
具体实施例子中，图6(a)为伸缩杆连接部件轴测图；图6(b)为伸缩杆连接部件主视图；图6(c)为图6(b)ⅱ处局部放大图；图6(d)为图6(b)处C-C截面剖视图；
伸缩杆连接部件Ⅰ-07的端部底座的侧壁上开设有X轴伸缩杆固定孔Ⅰ-0703。
具体实施例子中，图7为圆锥销结构，圆锥销的底部开设有圆锥销拆卸螺纹孔Ⅰ-0801。
图8为X轴电动伸缩杆轴测图；X轴电动伸缩杆的一端为伸缩杆连接头Ⅰ-0901，伸缩杆连接头上开有固定键槽Ⅰ-0902，X轴电动伸缩杆的另一端的底座上开设有连接螺纹孔Ⅰ-0903。
图9(a)为相机旋转支架固定装置；图9(b)为相机旋转支架固定装置俯视图；图9(c)为伸缩杆连接装置，伸缩杆及相机旋转支架固定装置装配图；图9(d)为图9(c)ⅲ处局部放大图；
相机旋转支架固定装置的上部支撑结构上开设相机支架连接螺纹孔Ⅰ-1201，用于与相机固定，中部支撑结构开设连接键槽通孔Ⅰ-1202，用于与X轴电动伸缩杆固定键槽相连，底部支撑结构上开设传感器连接头固定螺纹孔Ⅰ-1203。
图10(a)为相机旋转支架轴测图；图10(b)为相机旋转支架及固定装置装配图；相机旋转支架上设置有相机固定卡扣Ⅰ-1701，相机旋转驱动装置Ⅰ-1702，机旋转驱动装置上开设有连接螺纹孔Ⅰ-1703，用于与相机支架连接螺纹孔Ⅰ-1201配合，实现与相机旋转支架固定装置的连接。
图11为相机数据线收放装置爆炸图；相机数据线收放装置包括滚轮主箱体Ⅰ-0513，所述滚轮主箱体上为滚轮箱体顶板Ⅰ-0501，利用顶板连接螺栓Ⅰ-0506将滚轮箱体顶板固定在滚轮主箱体上，滚轮主箱体采用滚轮主箱体部件连接螺栓Ⅰ-0514固定。
轴承套Ⅰ-0521、深沟球轴承Ⅰ-0520、绕线滚轮Ⅰ-0519、滚轮箱体端盖Ⅰ-0524、法兰盖连接固定螺栓Ⅰ-0502、联轴节连接螺母Ⅰ-0503、联轴节Ⅰ-0504、Ⅰ-0511-联轴节螺栓垫片、平键Ⅰ-0505、联轴节连接螺栓Ⅰ-0507、滚轮驱动步进电机依次配合连接，滚轮驱动步进电机Ⅰ-0508利用电机固定螺栓Ⅰ-0509及垫片Ⅰ-0510固定在电机固定板Ⅰ-0512上，滚轮箱体下壳Ⅰ-0517及滚轮箱体上壳Ⅰ-0522通过滚轮箱体上下壳连接螺母Ⅰ-0518、滚轮箱体上下壳连接螺栓Ⅰ-0523、六角螺母Ⅰ-0515、垫片Ⅰ-0516进行固定连接。
图12(a)为相机数据线收放装置外壳；图12(b)为滚轮安装箱下箱体；图12(c)为滚轮安装箱下箱体俯视图；图12(d)为图12(c)D-D截面剖视图；
滚轮主箱体上开设有滚轮箱体下壳连接通孔Ⅰ-051301、图像信号数据线孔Ⅰ-050101、滚轮驱动电机电源线孔Ⅰ-050102、驱动电机连接板固定孔Ⅰ-051201、滚轮箱体下壳阶梯孔Ⅰ-051301。
图13(a)为滚轮安装箱轴测图；图13(b)为滚轮安装箱上箱体轴测图；图13(c)为滚轮安装箱下箱体轴测图；图13(d)为滚轮安装箱装配主视图；图13(e)为图13(d)处E-E截面剖视图；图13(f)为滚轮安装箱法兰盖主视图；图13(g)为图13(f)处F-F截面剖视图；
滚轮安装箱上箱体上开设有滚轮箱体上壳侧壁螺纹孔Ⅰ-052201及上下壳连接通孔Ⅰ-052202。
滚轮箱体下壳上开设有上下壳连接通孔1Ⅰ-051701、法兰盖连接螺纹孔Ⅰ-051702及滚轮箱体下壳与滚轮主箱体连接通孔Ⅰ-051703。
上下壳连接通孔1Ⅰ-051701及上下壳连接通孔2Ⅰ-052202相配合安装螺栓，实现滚轮安装箱。
图14(a)为滚轮单元装配俯视图；图14(b)为图14(a)处G-G截面剖视图；
滚轮单元装配时，利用深沟球轴承外圈Ⅰ-052001、深沟球轴承内圈Ⅰ-052002、法兰盖连接定位孔Ⅰ-052401及法兰盖内顶圈Ⅰ-052402进行定位装配。
图15为滚轮驱动电机轴测图；电机固定板上开设有连接板固定电机连接孔Ⅰ-051201、连接板及下壳连接通孔Ⅰ-051202，滚轮驱动步进电机利用驱动电机固定螺纹孔安装在电机固定板上。
图16(a)为驱动电机连接板主视图；图16(b)为图16(a)处H-H截面剖视图；图16(c)为图16(a)ⅳ处局部放大图；图16(d)为电机与连接板连接示意图；图16(e)为图16(d)ⅴ处局部放大图。
图17(a)为智能检测刀柄轴测图；图17(b)为智能检测刀柄爆炸图；刀柄包括刀柄固定部Ⅰ-18、刀柄工作部及加工刀盘。刀柄固定部、刀柄工作部之间设置有刀柄连接处加强环，刀柄连接处加强环Ⅰ-20通过加强环固定螺栓Ⅰ-19、加强环固定螺母Ⅰ-22固定，刀柄工作部Ⅰ-21与加工刀盘之间设置有刀盘安装止挡螺栓Ⅰ-23、刀盘安装止挡块Ⅰ-24，加工刀盘Ⅰ-25安装在刀盘安装部Ⅰ-26上，刀盘安装部与刀柄工作部螺纹连接。
图18(a)为侧边铣刀盘轴测图，图18(b)为平面铣刀盘轴测图；图19(a)为一种平面铣可转位刀片轴测图；图19(b)为一种开槽加工刀具可更换刀片轴测图；图19(c)为刀片切削工件轴测图。
图20(a)为智能刀柄中部内部部件结构图，图20(b)为智能刀柄中部主视图；图20(c)为图20(b)处I-I截面剖视图；图20(d)为智能刀柄中部剖视图。
智能刀柄内部依次设置有无线射频器Ⅰ-2101，射频器固定架Ⅰ-2102，固定架装配轴承Ⅰ-2103，线圈上端支承轴承Ⅰ-2104，旋转滚动体上端支承轴承Ⅰ-2105，电源模块Ⅰ-2106，旋转滚动体Ⅰ-2107，旋转滚动体下端支撑轴承Ⅰ-2108，法兰盖Ⅰ-2109，上述部件依次装配安装在智能刀柄内部。
智能刀柄的柄壳上开设有信号发射孔Ⅰ-2115及传感器数据线孔Ⅰ-2116。
图21(a)为发电装置内部线圈轴测图；图21(b)为线圈组装单元主视图；图21(c)为图21(b)处J-J截面剖视图；图21(d)为图21(b)ⅵ处局部放大图。
发电装置包括线圈绕线凸台Ⅰ-211001；
线圈上端支承轴承上分别安装有电源储电模块Ⅰ-210401、电源整流模块Ⅰ-210402，电线输送管Ⅰ-211002、振动传感器固定夹Ⅰ-2114、振动传感器Ⅰ-2113、换向轴承Ⅰ-2111。
图22(a)振动传感器单元轴测图；发电装置内部线圈：数据线孔Ⅰ-211402、振动传感器Ⅰ-2113、固定夹定位孔Ⅰ-211401、中轴传送线管Ⅰ-2112；数据线孔Ⅰ-211402通过中轴传送线管Ⅰ-2112保持在同一轴线上，螺栓通过固定夹定位孔Ⅰ-211401固定振动传感器。
图22(b)线圈固定轴承；线圈组装单元包括：固定夹定位螺纹孔Ⅰ-211101，线圈固定 槽Ⅰ-211102，传感器固定孔Ⅰ-211103，轴承滚动体及支架Ⅰ-211104，轴承底部外圈Ⅰ-211105。固定夹定位螺纹孔Ⅰ-211101与固定夹定位孔Ⅰ-211401通过螺栓将传感器紧紧固定在线圈单元上。将振动传感器Ⅰ-2113安装在传感器固定孔Ⅰ-211103中定位并用粘合剂固定，保证刀具振动信号的有效传递。
图26为数控设备换刀装置轴测图；数控设备换刀装置包括换刀固定台Ⅲ-06及换刀夹手Ⅲ-08，换刀固定台Ⅲ-06及换刀夹手Ⅲ-08通过换刀旋转轴Ⅲ-07连接。
图28为智能刀库单元轴测图；智能刀库单元包括刀库固定架Ⅲ-05，所述刀库固定架内设置有刀套Ⅲ-02，刀库固定架的底部为刀库换刀口Ⅲ-03，刀库固定架上开设有智能刀库固定孔Ⅲ-01，刀库固定架还设有刀库换刀驱动装置Ⅲ-04。
在具体实施例子中，磁座Ⅰ-01侧壁开有侧壁螺纹孔Ⅰ-0102，与滚轮安装箱固定壳上水平侧壁连接通孔Ⅰ-0601配合安装固定螺栓，同时Z轴电动伸缩杆上第二螺纹盲孔Ⅰ-0203与垂直侧壁连接通孔Ⅰ-0603安装固定螺栓，通过以上两处连接可将滚轮安装箱Ⅰ-05安装至固定壳内，使其处于指定工作位置。磁座跟Z轴电动伸缩杆通过固定凹槽Ⅰ-0101和固定凸台Ⅰ-0201配合安装，依靠重力等完成伸缩杆的轴向固定安装，通过以上连接方式实现了可拆卸方便，便于对装置损坏部件进行更换，提高了装置的使用寿命，并且使其安装操作简单。Z轴位移传感器与电动伸缩杆通过Z轴位移传感器连接板Ⅰ-03依靠螺栓进行固定安装，普通螺栓通过连接板通孔Ⅰ-0301将连接板固定在电动伸缩杆上，通过穿过连接板阶梯孔Ⅰ-0302的沉头螺钉固定住位移传感器，装配图如图5(a)电动伸缩杆，连接部件及传感器装配图所示，固定后传感器连接头Ⅰ-0401与伸缩杆连接部件Ⅰ-07上连接头螺纹孔保持在同一轴线上，使连接后的拉绳保持与水平面垂直，此种安装方式保证测量相机的竖直位移的准确性。
同理，X轴拉绳式位移传感器与伸缩杆的连接方式与上述所述方法相同，X轴位移传感器连接头以同样的连接方式固定在相机旋转支架固定装置Ⅰ-12传感器连接头固定螺纹孔Ⅰ-1203处，使X轴传感器的拉绳方位与水平面平行，保证测量相机的水平位移的准确性。相机两个方位的直线移动是通过两个电动伸缩杆来完成，并且两个伸缩杆通过伸缩杆连接部件Ⅰ-07进行连接，Z轴伸缩杆通过杆部底端的螺纹与连接部件内部螺纹孔连接起来，螺纹连接的剖视图如图5(b)中图5(a)中B-B截面的剖视图所示，并通过圆锥销Ⅰ-08进行锁定，避免在往复直线运动中部件之间出现松动等不良情况，X轴电动伸缩杆通过螺栓穿过X轴伸缩杆固定孔Ⅰ-0703固定在螺纹孔Ⅰ-0903处，前后端面共计四个螺纹连接部位，保证连接强度。X轴电动伸缩杆末端螺纹杆Ⅰ-0901上开有键槽Ⅰ-0902，通过安装平键对安装的相机旋转支架固定装置Ⅰ-12进行周向定位，同时通过v垫片Ⅰ-15，固定螺母Ⅰ-13及圆头螺母Ⅰ-14对其进行轴向定位，采用双螺母紧固结构能够在很大程度上起到防松作用。相机旋转支架固定装置连接了相机部分与平移装置部分。
整个X轴及直接连接部件的装配图如图9(c)伸缩杆连接装置，伸缩杆及相机旋转支架固定装置装配图所示。相机旋转支架Ⅰ-17通过沉头螺钉Ⅰ-1201固定在相机旋转支架固定装置Ⅰ-12上，如图10(b)相机旋转支架及固定装置装配图所示。相机支架旋转装置Ⅰ-1702，内置步进电机及控制单元驱动相机按指定角度进行绕机床Y轴旋转，在安装方式及部件结构能够实现特定角度的图像采集。相机支架卡扣Ⅰ-1701，方便CCD相机的拆卸更换，满足系统按照不同功能要求更换相机。
视觉系统滚轮部分主要满足伸缩杆运动过程中相机数据线及电机电源线等动态长度调整，运动过程在下文中相机运动功能设计中详细阐述。所有部件都集成安装在滚轮安装箱Ⅰ-05内，主体结构为连接有控制单元的步进电机Ⅰ-0508驱动线滚轮Ⅰ-0519，根据系统指令线收放长度，控制单元控制步进电机旋转对应转数，线束缠绕在滚轮滚槽中，通过电机的正反转实现线束的收放，绕线滚轮Ⅰ-0519安装滚轮箱体Ⅰ-0517下壳中，下壳通过其定位通孔及箱体阶梯孔Ⅰ-051201进行定位安装，由沉头螺栓Ⅰ-0514，螺母Ⅰ-0515及垫片Ⅰ-0516进行螺栓连接，同理驱动电机安放在电机连接板上，电机连接板同样按照螺栓连接方式安装固定在滚轮主箱体，保证了滚轮及电机主轴轴线重合，两轴通过联轴节Ⅰ-0504和平键Ⅰ-0505 进行连接，使电机能带动滚轮旋转。滚轮Ⅰ-0519安放在滚轮箱体内，箱体分上下两部分，内部铸造出设计特定结构的型腔，配合轴承套Ⅰ-0521，深沟球轴承Ⅰ-0521，端部法兰盖Ⅰ-0524及特定结构的型腔完成滚轮的装配，装配后的剖视图如图14(b)中图14(a)G-G截面剖视图所示，最终滚轮箱体上下壳及法兰盖由特定位置螺栓完成连接及整个结构的封装。
在具体实施例子中，振动信号采集由智能刀柄完成，智能刀柄内置振动传感器，并且通过旋转带动机构实现加工过程中智能刀柄的自发电，供给振动传感器及顶部无线信号发射装置使用。智能刀柄主体由刀柄固定部Ⅰ-18，刀柄核心工作部Ⅰ-21刀盘固定部Ⅰ-26组成。刀柄核心工作部Ⅰ-19为中空部件，内部集成各种工作部件，上下两端口处为螺纹孔，刀柄上下两部分都加工有螺纹，通过螺纹连接实现三个部分的整体连接。为了保证刀柄整体强度，在螺纹连接处通过刀柄加强环Ⅰ-20对连接处进行部件固定，保证刀柄在加工过程中拥有足够的抗变形强度。刀盘用以安装各种刀片，根据不同加工过程可更换不同的刀盘，如图18所示两种不同刀盘，不同刀盘可安装不同型号的刀片，如图19(a)与图19(b)可转位式刀片轴测图所示，实现系统对各种安装不同刀片的监测功能。
刀柄工作部Ⅰ-21内部有发电装置，发电原理为电磁感应原理，刀柄在加工过程中高速旋转，带动内部发电装置滚动体Ⅰ-2107跟随旋转，其跟随旋转主要通过圆柱滚动体与工作部内壁摩擦力作用，滚动体Ⅰ-2107轴测图如图20(a)智能刀柄中部内部部件结构图所示，其顶部与底部采用如图22(b)智能刀柄中部主视图所示的轴承，此轴承滚动体及保持架Ⅰ-211104如图22(b)智能刀柄中部主视图中相应部件所示，滚动体上下两个支撑体为内、外圈，规定上部为内圈，下部为外圈。在滚动体作用下内、外圈可相对旋转。此发电装置中所有轴承均采用此种类型的轴承。滚动体及两端轴承安装在刀柄工作部中空部分内，底部通过法兰盖将滚动体封装在工作部中空型腔内，旋转滚动体Ⅰ-2107内安装线圈，线圈轴测图如图21(a)发电装置内部线圈轴测图所示，线圈固定在安装在旋转滚动体下端封闭实体上的减速轴承上减速轴承底部外圈与封闭实体过渡配合，减速轴承Ⅰ-211102凹槽形状跟线圈凸起部分形状相同，可实现插入式安装。刀柄高速旋转带动旋转滚动体跟随旋转，旋转滚动体带动减速轴承底部外圈旋转，顶部内圈在滚动体摩擦力的作用下同样跟随旋转，在通过此机构后，刀柄高速旋转，然而内部线圈以很慢的速度跟随旋转，两者产生一个很大转差率，在刀柄中空内部安装永久磁铁，线圈部分集成闭合线圈，在此种旋转状态下永久磁铁由于旋转产生变化的磁场，使闭合线圈切割磁感线，产生电流，闭合线圈产生的电流通过图21(c)中21(b)J-J截面剖视图所示，电流输送部分Ⅰ-211002输送至电流整流模块Ⅰ-210402进行整流后储存在储电模块Ⅰ-210401中，通过内部供电管路由电源线给振动传感器及无线射频发射装置提供电源。发电装置及上部无线信号发射装置中间有特定材料制成的磁场屏蔽板，用以屏蔽发电装置磁场对无线射频装置在信号传输过程中的磁场干扰。线圈内部集成振动传感器，通过固定架Ⅰ-2114固定在减速轴承上，用以获取加工过程中由于刀具变化实时产生的振动信号，线圈内部集成部件装配剖视图如图21(c)中21(b)线圈组装单元主视图所示。
各单元通过智能模块进行通讯以实现信息互通，进而实现总控系统在不同阶段对动作进行优先级的排序，以保障机床的正常运转。如图24初判断刀具异常后机床工作流程图所示，当机床刀具状态异常时，机器视觉系统与机床伺服系统进行连接，伺服系统接受机器视觉系统的动作指令，配合机器视觉系统完成图像的采集后，断开连接，恢复机床正常加工。同时能实现各个单元对加工参数的实时获取，以实现各部分按照加工要求完成既定工作。如向系统输入加工精度后，刀具监测单元实时获取，则对刀具异常预判断阈值进行实时更改，保证机床的刀具能一直处于有效状态。
系统核心运算部分由外置工业计算机执行，包括对各个子系统实时数据的实时获取与分析判断决策，针对不同工况向各个子系统的命令发送传达，各个机床不同阶段动作的执行及子系统工作的协调分配等。
数据库单元Ⅶ用以对智能监控过程中产生的海量数据进行储存，在此系统中主要针对刀具监测过程中采集的振动信号及机器视觉采集的图像信号进行信号数据的存储及与系统之间 的传输，同时本单元中数据库同时完成数控机床加工中设计及工艺参数，该数据多数情况下呈现动态模式，需要在设计及制造过程中随机储存。本系统最终实现的功能要求除了在显示界面进行实时显示之外，还应具备相关制造及企业管理人员能随时对数控设备信息进行实时查询，故本系统选取基于C/S结构的Web数据库系统作为数据库单元的主要工作载体，通过与整个系统的通讯连接实现数据的输入储存及数据的输出，成为各个系统运行的中转站，极大的节省了工业计算机的内存负荷，为系统的正常稳定运行提供保障，同时能实现相关人员通过手机等智能设备通过Web客户端实现设备信息的实时获取。由于现代数据库已经具备全面的数据中心处理的能力，飞快的性能以及无限制的虚拟化能力，使得本系统中的数据库可以在完成本系统数据库功能的同时兼顾数控设备其他系统数据存储的功能要求，即此模块在实际应用中拥有可扩展能力。
决策及控制单元Ⅵ主要由外置工业计算机及数控设备内部控制系统组成。当专业计算机内部处理器对采集数据进行如上所述的智能分析后得出决策，进而通过给机床控制系统下达指令完成不同的动作。
智能刀库单元Ⅱ基于ARM微处理器进行开发。设计自动换刀系统，能根据机床换刀指令进行自动换刀动作。本实施例通过盘形刀库为例进行刀库功能介绍，加工过程中所用的不同类型刀具在盘形刀库中进行备份安装，相同类型的两把刀具就近安装，便于刀具管理。选刀方式采用任意选刀方式，根据程序指令的要求来选择所需要的刀具，即当正在加工过程中的刀具发生异常时，根据决策单元发出的程序换刀指令，从刀库指定选定备用刀具进行更换。智能刀库单元中的自动换刀系统中有刀具识别装置。刀具的识别主要通过对刀库中不同刀座进行编号，不同编号的刀座安装不同类型的刀具并且在加工之前输入到ARM换刀系统中。智能刀库能根据数据分析模块对刀具的状态识别后进行标定。当数据分析单元分析得出刀具异常后，该单元对该刀具所在的刀座号进行异常标定，更换刀具，异常刀具入库。当图像信号数据分析完成得出刀具精确状态后，传送至智能刀库单元进行异常状态的信息更新。然而当确认刀具状态预判断模块为误判时，则将信息传送至智能刀库单元对标定异常的刀具进行异常标定解除。
本单元的换刀装置由两个朝向相反的机械手装置，通过驱动装置对旋转轴的定向旋转完成刀库与工作台之间刀具的更换。
异常刀具输送单元Ⅳ主要指工业机械抓手，如ABB工业机器人等设备。通过将工业机器人与智能刀库建立通讯连接实现信息的相互传递共享，指导辅助设备完成既定工作。具体工作为：当智能刀库对标定的异常刀具进行精确状态更新后，机械手根据不同刀具的异常类型进行分类输送至刀具处理区域，如刀具刀刃发生破损则将刀具输送至换刀区域；当刀具刀刃变钝将刀具输送至刀具刃磨区域等。
实施例二
该实施例子公开了数控机床刀具状态监测及控制方法，图24为初判断刀具异常后机床工作流程图；图25为可换位刀具刀片磨损示意图；图27为刀具初判断模块原理图；包括：
数据采集单元及数据分析处理单元分为两个子系统部分，分别用以刀具状态的预判断及精确判断。
刀具状态的预判断实现方式如下所述：
通过智能刀柄内部的振动传感器，检测加工过程中振动信号并以此作为系统刀具检测预判断的信号输入。
振动传感器集成在智能刀柄内部，并在刀柄内部采用无线传输，采用此装置不会压缩机床正常的工作空间，不干涉工作运动部件的方向及角度移动，适合运用在实际生产中。振动传感器采集的信号通过无线设备实时传输至外置工业计算机中进行数据的处理分析与判断。数据的分析处理判断主要通过工业计算机中的相关软件完成，如数据处理分析时采用matlab软件等。
在实际加工过程中，刀具的故障类型主要分为刀片的过度磨损及刀具破损两种情况。刀 具磨损会使刀具的几何形状发生改变，刀刃变钝，在切削过程中切削力会发生变化，进而导致工件加工区域产生不同程度的振动。当刀具破损时，刀具切削部分变形明显，切削力在瞬间会发生急剧变化，振动信号同样会发生急剧变化，此状态只要实时监测振动信号的瞬时变化情况即可实现对刀具破损状态的监测。而刀具磨损量的变化过程是一个渐进过程，在实际加工过程中，刀具后刀面最易发生磨损，则刀具的状态监测通常选取后刀面磨损量最为监测对象。后刀面磨损过程曲线与浴盆曲线的形状基本相似，如图25所示，磨损分为三个阶段，初期磨损，正常磨损，急剧磨损三个阶段。
刀具状态的预判断模块对刀具磨损量的监测则通过机器学习SVM进行实时监测。SVM是在统计学习理论的VC维理论和结构风险最小化原理基础上建立起来的机器学习算法，向量特征的维数不影响算法本身复杂度，不仅节约了时间和成本，还使得监测模型的建立更为简便。SVM的分类是一个基于二分类原理为基础的算法，是通过将刀具磨损特征训练样本映射到一个更加高维的空间之中，在此高维空间之中建立一个最优分类超平面对空间中不同种类的向量进行划分，在此实施例中即对上述所述的刀具三种磨损向量进行超平面的选取划分。该分类超平面可以作为上述所述数据分析处理单元中相对应的分类器，最优分类超平面可以表示为ω TΦ(x)+b＝0,其中ω是可调的权重向量；b是偏置参数，决定相对于原点的偏移值；Φ(x)为特征映射函数。此监测方式是一种间接测量，通过刀具磨损历史实验数据进行机器学习训练，得出满足系统需求的机器学习模型。为了避免机床加工过程其他因素对采集的振动信号的影响，对采集的信号进行特征提取，作为SVM的输入，刀具磨损量作为输出，训练适合本系统要求的刀具状态预判断的模型。为了使最终训练的模型准确性高，在特征提取部分采取信号特征多方法融合提取方法以最大程度的去除噪声干扰及有效信息的提取。
本实施例中以EMD经验模态分解和主成分分析两种信号处理方式结合的方法进行信号振动信号特征提取的说明。EMD是近几年兴起的一种新的非平稳信号希尔伯特-黄变换的重要组成部分，即适合线性、平稳信号的分析，也适应非线性、非平稳信号的分析。此方法的实质是通过特征时间尺度来识别信号中所内含的所有振动模态，在这一过程中，特征时间尺度及IMF的定义都具有一定的经验性和近似性。与其他方法相比，EMD方法具有直观的、间接的、后验的、自适应的，其分解所用的特征时间尺度是源自于原始信号的，即信号来源于机床内部主轴等驱动电机采集的随时间尺度变化的电振动信号，其具体分解过程如下：
(1)找到电流振动信号x(t)所有的极值点；
(2)用3次样条曲线拟合出上下极值点的包络线e max(t)和e min(t)，并求出上下包络线的平均值m(t)，在x(t)中减去它:h(t)＝x(t)-m(t)；
(3)根据预设判据判断h(t)是否为IMF；；
(4)如果不是，则以h(t)代替x(t)，重复以上步骤直到h(t)满足判据，则h(t)就是需要提取的IMF；
(5)每得到一阶IMF，就从原信号中扣除它，重复以上步骤；直到信号最后剩余部分r n就只是单调序列或者常值序列。
这样，经过EMD方法分解就将原始电流振动信号x(t)分解成一系列IMF以及剩余部分的线性叠加：
Figure PCTCN2020089260-appb-000001
采集的电流振动信号经过EMD分解后得到各阶固有模态函数涵盖了加工过程中刀具磨损的所有信息，为了降低机器学习算法的特征维度，提高机器学习的效率及避免机器学习的过拟合问题，采用主成分分析方法对EMD分解后得到的固有模态函数进行主成分分析。主成分分析是一种统计方法。通过正交变换将一组可能存在相关性的变量转换为一组线性不相关的变量，转换后的这组变量叫做主成分。在此方案中，即将EMD分解后的各阶固有模态函数作 为各组不相关的向量处理，最终得出EMD分解后电振动信号的主成分。通过不同成分的贡献率的计算，选取信息贡献率到达85％以上的前几阶主成分作为机器学习中向量的输入。
在加工过程中，根据实时监测的信号输入到SVM可以得到刀具磨损的估计值，根据加工精度要求系统自动设置磨损量阈值，对于大多数情况一般取刀具后刀面磨损量VB＝0.3mm为默认阈值，当刀具VB＞0.3mm后，刀具会进入急剧磨损阶段，对加工精度的影响较大，特别的当对加工精度要求很高时，在人工界面可进行参数要求输入，此时刀具状态预判断模块根据参数要求自动调整VB磨损阈值，以保证机床刀具对加工精度的要求。
近年来随着机器学习理论及技术水平的不断提高，人工智能对设备状态监测方面的识别准确性越来越高。然而为了达到刀具状态的精准识别，直接检测方法是一种不二选择。故本系统通过基于机器学习的刀具预判断后，通过施加机器视觉系统对预判断结果进行验证及状态的精确判断，同时对预判断模块中出现的状态误判进行更改，进一步提高数控设备的智能化水平。
在预判断之后，进行刀具状态的精准判断实现方式如下所述：
所采用的刀具直接测量方法为刀具视觉图像采集及后续图像比对。在系统数据库单元中储存数控机床智能刀库中所有刀具的标准几何尺寸图像。在机床发生刀具异常状态下，数据分析模块可根据当前状态下刀具的参数信息从数据库中调取标准刀具几何图像与机器视觉采集的图像运用数据处理单元中专业图像处理功能模块进行多角度，多方位的几何尺寸对比计算，得出刀具是否发生异常及对异常刀具状态的具体量化，此系统中主要指刀具磨损量的具体数值及刀具是否发生破损。随着对加工过程刀具监测状态的分类，本模块可进行扩展。
为了实现图像采集，需要对CCD相机的支撑运动部件进行相关运动功能及视觉系统实现图像采集的性能要求进行设计，具体设计措施及方案如下所述：
(1)机器视觉采集装置包括磁座部分，通过磁座部分将采集装置安装固定至工作刀台上，在刀台上将固定位置原点类似于机床坐标形式将其设置为机床中一个工件坐标系，作为整个机器视觉系统在机床坐标系中的一个工件坐标系，称其为零点坐标，在此零点坐标的串联下将外置的机器视觉采集装置的与机床坐标系建立连接，使图像采集装置成为数控加工系统中的一部分。固定位置为圆柱形刀台的圆周线与X轴方向的交点位置，保证其Y轴坐标点与刀具坐标点一致。在后续机器视觉系统工作过程中，只进行Z轴和X轴两个方向的运动即可满足此系统的运动性能的要求，对刀具底部轴向方向的图像采集通过CCD镜头与刀杆连接部安装的旋转机构实现镜头沿Y轴线上下旋转。机器视觉系统只进行周向及轴向两个方位角度的图像采集技能满足图像处理模块中几何尺寸比对的要求。机器视觉系统整体设计有可伸展压缩的工作导杆，在处于工作状态时可以通过X和Y方向轴上的导杆实现工作区域任意空间位置的到达。在两轴导杆的末端内部设置有直线拉绳式位移传感器，通过直线拉绳式位移传感器得出X轴和Z轴在工作时的坐标值，结合零点坐标在机床工件坐标系中位置数据，计算得出镜头位置在机床中的坐标，实现视觉系统后续图像采集过程中的位置自动判断及调整。机器视觉系统与数控系统建立通讯连接，使机器视觉系统的镜头位置能像刀具一样受到数控系统的实时监测与控制。当系统处于非工作状态时，各工作导杆处于收缩状态，此时系统整体所占空间体积最小，不压缩机床正常的工作空间。
工作导杆采用电动伸缩杆装置以实现Z轴及X轴方向的移动，在电动伸缩杆头部装置拉绳式位移传感器，以检测计算相机镜头位置坐标。安装时，将直线拉绳式位移传感器的测杆与电动伸缩杆的驱动器直接连接，驱动器带动传感器内部滑动电刷发生位移变化，输出呈线性变化的直流电压信号，提供给系统进行相机镜头位置坐标的计算储存至数控系统内部，同时在显示板进行坐标显示。由于CCD相机与系统之间需要连线，为避免杆在伸缩过程中对线的损害，设计连接线收放装置，其原理为设计带有凹槽的滚轮，线通过凹槽缠绕在滚轮上，根据系统检测伸缩杆伸缩长度自动驱动滚轮电机进行正反转实现线束的收放，从而避免数据线在伸缩过程中面临的过度拉扯或蜷曲问题。
(2)机器视觉系统的正常运行的前提是有较强的自动聚焦能力。为了使机器视觉系统拥 有结构简单，系统稳定且鲁棒性强的特点，此系统选用CCD相机采用被动式自动聚焦技术，根据成像清晰度进行自动对焦以满足图像采集要求。由于此系统主要功能的实现是对初期监测判断的异常刀具类别进行进一步状态确认及异常程度计算量化，初期的刀具异常状态主要来源于刀具切削刃区域，故视觉系统的聚焦窗口大小根据数控系统实时状态参数数据进行自动判断，例如根据刀具对刀点坐标判断视觉系统镜头工作中心位置，根据数控系统传输的目前刀具号进行工作刀具的参数检录，使机器视觉系统根据目前刀具本身参数特点进行聚焦区域窗口的自动判断划分及图像采集过程中采样频率等相关参数进行自行决策设置，通过以上手段以保证采集图像的有效性及准确率，避免采集图片信息的冗余或者缺失。
(3)机器视觉系统的核心是图像的采集和处理，图像本身的质量对整个系统的影响极为关键。而照明光源则是决定机器视觉系统图像质量的最重要因素，通过选择合适的光源，可以使图像中的目标特征与背景信息得到最佳分离，从而大大降低图像处理的难度，提高系统的稳定性和可靠性。本着结构设计简单及光源稳定且服役时间较长等优点，本机器视觉系统采用LED光源，根据机床刀具的几何特征，光学属性等工程要求进行光源的选择以满足此机器视觉系统的要求。
(4)机床在加工过程中出现刀具异常状态后，主控系统将发出机床停转指令，刀具上升至安全位置。与此同时，机床同时向机器视觉系统发出开始工作指令，机器视觉系统处于工作状态，根据机床内部传输的刀具位置坐标，通过系统内部位置判断功能模块及控制系统模块将CCD相机快速输送至刀具周边位置后，向机床工作系统发出刀具图像采集低速间歇旋转指令，主轴慢速间歇旋转，在主轴旋转间歇使刀具处于静止状态下，CCD相机进行快速对焦并在短时间内完成图像采集，此过程，主轴间歇旋转运动与镜头采集图像频率及动态图像采集情况下的对焦时间在节拍上高度契合，避免转速过快影响采集图像的质量，过慢增加采集过程时间，影响机床后续换刀及加工过程。图像采集接受后，将采集的图片信息送至数据信息处理模块，并且再次向机床发出主轴停转指令，并且系统工作导杆全部收回，使系统处于非工作状态。
整个机器视觉系统采用嵌入式系统进行开发，来实现图像数据采集，数据传输，部件控制及通讯等功能，嵌入式系统技术包括集成电路技术，系统结构技术，传感与检测技术及实时操作系统等技术，在此系统的技术支持下能实现上述机器视觉系统所述的全部功能。
此系统与整个数控设备中多个模块系统都进行通讯连接，与数据分析处理模块连接实现图像信息的进一步分析，完成刀具异常状态的精确诊断。与机床控制系统通讯连接以完成图像采集过程中机床配合动作的完成。与数据存储模块连接以实现数据的保存及数据库内容的不断填充更新。与显示模块连接以实现图像数据采集过程中的过程监控显示。
以上所述仅为本发明的优选实施例而已，并不用于限制本发明，对于本领域的技术人员来说，本发明可以有各种更改和变化。凡在本发明的精神和原则之内，所作的任何修改、等同替换、改进等，均应包含在本发明的保护范围之内。
上述虽然结合附图对本发明的具体实施方式进行了描述，但并非对本发明保护范围的限制，所属领域技术人员应该明白，在本发明的技术方案的基础上，本领域技术人员不需要付出创造性劳动即可做出的各种修改或变形仍在本发明的保护范围以内。

Claims (10)

  1. 数控机床刀具状态监测及控制系统，其特征是，包括：数据采集单元及数据分析处理单元；所述数据采集单元包括振动状态检测装置及机器视觉采集装置；
    所述振动状态检测装置实时采集到刀具加工过程中的异常振动信号并传输至数据分析处理单元；
    所述数据分析处理单元利用刀具状态预判断的模型对异常情况进行状态预判断并确定刀具发生异常的时间点；
    所述机器视觉采集装置在状态预判断后且在不影响刀具加工的连续性的情况下完成刀具图像的采集并传输至数据分析处理单元，实现对刀具异常状态做出准确判断。
  2. 数控机床刀具状态监测及控制方法，其特征是，包括：
    实时采集到刀具加工过程中的异常振动信号；
    利用刀具状态预判断的模型对异常情况进行状态预判断并确定刀具发生异常的时间点；
    在状态预判断后且在不影响刀具加工的连续性的情况下完成刀具图像的采集，实现对刀具异常状态做出准确判断。
  3. 如权利要求2所述的数控机床刀具状态监测及控制方法，其特征是，对刀具进行状态预判断时，针对不同的故障类型分别处理，对于刀具破损，通过实时监测振动信号的瞬时变化情况即可实现对刀具破损状态的监测，对刀具磨损量的监测则通过机器学习SVM进行实时监测。
  4. 如权利要求3所述的数控机床刀具状态监测及控制方法，其特征是，对刀具磨损量的监测则通过机器学习SVM进行实时监测时，对采集的振动信号进行特征提取，作为SVM的输入，刀具磨损量作为输出，训练刀具状态预判断的模型。
  5. 如权利要求4所述的数控机床刀具状态监测及控制方法，其特征是，以EMD经验模态分解和主成分分析两种信号处理方式结合的方法进行振动信号特征提取：
    经过EMD方法分解就将原始电流振动信号分解成一系列IMF以及剩余部分的线性叠加；
    采用主成分分析方法对EMD分解后得到的固有模态函数进行主成分分析，即将EMD分解后的各阶固有模态函数作为各组不相关的向量处理，最终得出EMD分解后电振动信号的主成分。
  6. 如权利要求2所述的数控机床刀具状态监测及控制方法，其特征是，根据实时监测的信号输入到SVM得到刀具磨损的估计值，设置磨损量阈值，当刀具磨损量大于设定阈值后，刀具会进入急剧磨损阶段。
  7. 如权利要求2所述的数控机床刀具状态监测及控制方法，其特征是，在机床发生刀具异常状态下，根据当前状态下刀具的参数信息从数据库中调取标准刀具几何图像与机器视觉采集的图像运用数据处理单元中专业图像处理功能模块进行多角度，多方位的几何尺寸对比计算，得出刀具是否发生异常及对异常刀具状态的具体量化，主要指刀具磨损量的具体数值及刀具是否发生破损。
  8. 如权利要求2所述的数控机床刀具状态监测及控制方法，其特征是，机床在加工过程中出现刀具异常状态后，发出机床停转指令，刀具上升至安全位置；
    与此同时，机床同时向机器视觉采集装置发出开始工作指令，机器视觉采集装置根据机床内部传输的刀具位置坐标，将CCD相机快速输送至刀具周边位置后，向机床工作系统发出刀具图像采集低速间歇旋转指令，主轴慢速间歇旋转，在主轴旋转间歇过程中刀具处于静止状态下，CCD相机进行快速对焦并在短时间内完成图像采集，此过程，主轴间歇旋转运动与镜头采集图像频率及动态图像采集情况下的对焦时间在节拍上契合，图像信号采集结束后，再次向机床发出主轴停转指令，使系统处于非工作状态。
  9. 如权利要求8所述的数控机床刀具状态监测及控制方法，其特征是，机器视觉采集装置包括磁座部分，通过磁座部分将采集装置安装固定至工作刀台上，在刀台上将固定位置原点设置为机床中一个工件坐标系，作为整个机器视觉采集装置在机床坐标系中的一个工件坐标系，称其为零点坐标，在此零点坐标的串联下将外置的机器视觉采集装置的与机床坐标系建立连接，使图像采集装置成为数控加工系统中的一部分；
    固定位置为圆柱形刀台的圆周线与X轴方向的交点位置，保证其Y轴坐标点与刀具坐标点一致，在后续机器视觉采集装置工作过程中，只进行Z轴和X轴两个方向的运动即可满足此系统的运动性能的要求，对刀具底部轴向方向的图像采集通过CCD镜头与刀杆连接部安装的旋转机构实现镜头沿Y轴线上下旋转。
  10. 如权利要求9所述的数控机床刀具状态监测及控制方法，其特征是，机器视觉采集装置只进行周向及轴向两个方位角度的图像采集；
    在处于工作状态时通过X和Y方向轴上的导杆实现工作区域任意空间位置的到达，在两轴导杆的末端内部设置有位移传感器，通过位移传感器得出X轴和Z轴在工作时的坐标值，结合零点坐标在机床工件坐标系中位置数据，计算得出镜头位置在机床中的坐标，实现后续图像采集过程中的位置自动判断及调整。
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