Method for online monitoring milling cutter defects

A milling and cutting tool technology, applied in the direction of manufacturing tools, metal processing equipment, metal processing machinery parts, etc., can solve the problems of low processing efficiency, high operator skill requirements, missing milling tools, etc., to improve processing efficiency, monitor The effect is obvious and the effect of reducing the processing loss

Active Publication Date: 2019-12-20
CHONGQING UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

On-line detection basically determines the damage of the tool by the operator listening to the sound or judging the vibration of the process, and rarely uses instruments and equipment to detect
[0004] The first method has the problems that it cannot be detected online, the auxiliary proces

Method used

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  • Method for online monitoring milling cutter defects
  • Method for online monitoring milling cutter defects
  • Method for online monitoring milling cutter defects

Examples

Experimental program
Comparison scheme
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Example Embodiment

[0032] Example 1:

[0033] This embodiment discloses a method for online monitoring of milling tool defects, see figure 1 , Including the following steps:

[0034] 1) See figure 2 , Establish a three-dimensional space coordinate system oxyz with the machine tool spindle as the center. Among them, the z axis is located on the axis of the machine tool spindle, and the x and y axes are respectively perpendicular to the z axis. Install the vibration sensor module on the machine tool spindle, start the machine tool spindle, and debug the vibration sensor module to ensure that the signals in the x, y, and z directions meet the requirements.

[0035] 2) See image 3 , The initial sample data collection. specifically,

[0036] 2.1) Take one revolution of the spindle as a cycle T 0 .

[0037] 2.2) In this embodiment, the number of blades on the cutter head is 4, and the blade numbers are 1, 2, 3, and 4 respectively. When the 4 blades on the cutter head enter normal milling, the vibration sen...

Example Embodiment

[0051] Example 2:

[0052] This embodiment discloses a relatively basic implementation, a method for online monitoring of milling tool defects, see figure 1 , Including the following steps:

[0053] 1) See figure 2 , Establish a three-dimensional space coordinate system oxyz with the machine tool spindle as the center. Among them, the z axis is located on the axis of the machine tool spindle, and the x and y axes are respectively perpendicular to the z axis. Install the vibration sensor module on the machine tool spindle, start the machine tool spindle, and debug the vibration sensor module to ensure that the signals in the x, y, and z directions meet the requirements.

[0054] 2) See image 3 , The initial sample data collection. specifically,

[0055] 2.1) Take one revolution of the spindle as a cycle T 0 .

[0056] 2.2) In this embodiment, the number of blades on the cutter head is 4, and the blade numbers are 1, 2, 3, and 4 respectively. When the 4 blades on the cutter head ente...

Example Embodiment

[0068] Example 3:

[0069] The main steps of this embodiment are the same as those of embodiment 2. Further, in step 7), if the subsequent two consecutive sets of data do not satisfy It can be ruled out that the phenomenon of increased local vibration due to casting or forging defects during tool cutting, rather than increased vibration caused by tool defects, goes to step 8).

[0070] Example 3:

[0071] The main steps of this embodiment are the same as those in embodiment 2, and further include step 9). If the alarm module does not issue an alarm during the whole machining process, the data comparison and analysis module records the machining parameters of the whole process, and the collected strong vibration cutting After the wave data analysis process obtains the cutting wave area, save it and save it as the signal comparison sample material for the later processing of the same kind of workpiece.

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Abstract

The invention discloses a method for online monitoring milling cutter defects. The method comprises the following steps that 1) a vibration sensor module is arranged on a machine tool spindle; 2) initial sample data is collected; 3) a threshold value delta S0, a time interval period T, a threshold value delta S1 are set; 4) vibration signals of n blades in the x, y, and z directions at each periodT0 are measured; 5) shaping is carried out to obtain n strong vibration cutting wave data formed by the n blades in the x, y, and z directions at each period T0 correspondingly; 6) the strong vibration cutting wave data is analyzed and processed to obtain difference values among cutting strong vibration wave areas formed by each blade at each period T0; and the like. According to the method for online monitoring the milling cutter defects, based on the precision requirement of a machined workpiece, rapid cutter defect monitoring, alarming and machine tool shutdown processing can be achieved through online vibration signal collection and analysis processing; the method is simple, the monitoring effect is obvious, the machining loss caused by cutter wear or defect can be remarkably reduced,and therefore the quality of the machined workpiece is improved.

Description

technical field [0001] The invention belongs to the field of numerical control milling, and in particular relates to a method for online monitoring of milling tool defects. Background technique [0002] In CNC milling, such as plane milling and curved surface milling, the cutter head is installed on the cutter bar, and the blade is installed on the cutter head for processing. The wear of the blade in milling has a great influence on the machining dimensional accuracy, surface roughness and surface texture of the workpiece. Even, if the blade defect cannot be found in time, it will have a serious impact on the quality of the workpiece, and will also have a harmful impact on the precision of the spindle of the CNC machine tool. [0003] At present, in actual processing, tool detection adopts two forms: offline detection and online detection: offline detection refers to the naked eye observation of the blade before and after processing or the use of imaging and laser imaging t...

Claims

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Application Information

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IPC IPC(8): B23Q17/09
CPCB23Q17/0957G05B2219/35176G05B2219/50041G05B19/406G05B2219/37434B23Q17/0971
Inventor 曹华军邱德贵刘虎柴迎庆
Owner CHONGQING UNIV
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