CN111185803B - In-place posture adjusting method for worn cutter - Google Patents
In-place posture adjusting method for worn cutter Download PDFInfo
- Publication number
- CN111185803B CN111185803B CN202010115904.4A CN202010115904A CN111185803B CN 111185803 B CN111185803 B CN 111185803B CN 202010115904 A CN202010115904 A CN 202010115904A CN 111185803 B CN111185803 B CN 111185803B
- Authority
- CN
- China
- Prior art keywords
- wear
- tool
- abrasion
- tool life
- worn
- Prior art date
- Legal status (The legal status 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 status listed.)
- Active
Links
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
- B23Q17/0952—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 during machining
- B23Q17/0957—Detection of tool breakage
-
- 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
- B23Q15/00—Automatic control or regulation of feed movement, cutting velocity or position of tool or work
- B23Q15/007—Automatic control or regulation of feed movement, cutting velocity or position of tool or work while the tool acts upon the workpiece
- B23Q15/16—Compensation for wear of the tool
Abstract
The invention discloses an in-place posture adjusting method for a worn cutter, which comprises the following steps: obtaining a measuring moment according to the tool life model; measuring the abrasion of the cutter at the measuring time to obtain an abrasion value; and adjusting the in-place posture of the tool according to the wear value. By using the method, the tool wear information can be rapidly acquired, accurate judgment can be realized, the cutting parameters can be timely adjusted, the cutting quality can be guaranteed, the service life of the tool can be prolonged, and the cost can be saved.
Description
Technical Field
The invention relates to an in-place posture adjusting method for a worn cutter.
Background
The state of wear of the tool directly affects the stability of the cutting process, the precision of the product and the surface quality of the product. Tool wear is one of the main wear modes of a tool during a cutting process. In order to guarantee the processing quality of the product, the existing operation is to install a measuring device on a machine tool, which has the following disadvantages: 1. because the area of the abrasion area is small, the width of the abrasion area of the tool face is generally 2-5mm, and the height of the abrasion area of the tool face is generally 0.1-0.5mm, so that the requirement on the imaging quality of a measuring device is very high; 2. the requirement on the measurement precision is high, the measurement precision of the abrasion area generally needs to reach 0.01-0.001mm, and the change of the abrasion value can be responded in time; 3. the available space of the measuring device is small, and on the premise of not changing the structure of the existing machine tool and not adopting a dynamic manipulator, because the camera must be positioned on one side of the external normal line of the rear tool face of the turning tool, and the side is usually a side plate of a box body of the machine tool, on the premise of not influencing the normal work of the machine tool, the installation and working width of the camera are only about 250mm at the limit position; 4. when cutting fluid is used as a cooling medium, the cutter cannot acquire the wear condition of the cutter in real time due to the interference of the cutting fluid in the cutting process, and the measurement can be carried out only through the clearance during cutter changing or process replacement. Therefore, the existing measuring device cannot really realize the real-time acquisition of the wear information of the cutter, and the cutting quality is ensured.
Disclosure of Invention
The invention aims to provide an in-place posture adjusting method for a worn cutter, which can be used for quickly acquiring the wear information of the cutter, realizing accurate judgment and timely adjusting cutting parameters, ensuring the cutting quality, prolonging the service life of the cutter and saving the cost.
In order to achieve the purpose, the invention adopts the technical scheme that: an in-place attitude adjustment method for a worn tool, comprising:
obtaining a measuring moment according to the tool life model;
measuring the abrasion of the cutter at the measuring time to obtain an abrasion value;
and adjusting the in-place posture of the tool according to the wear value.
In the above technical solution, the tool life model is constructed by the following steps:
establishing a wear sample library;
establishing a tool life prediction model from a wear sample library;
and correcting the tool life prediction model to obtain a tool life model.
In the above technical solution, the wear sample library is constructed by the following steps:
acquiring a sample image;
extracting a wear edge of the sample image;
acquiring abrasion depth information from the abrasion edge;
and establishing a wear sample library according to the wear depth information.
In the technical scheme, the Canny algorithm is adopted in the step of acquiring the abrasion depth information from the abrasion edge.
In the above technical solution, the Canny algorithm includes the following steps:
carrying out gray processing on the sample image;
performing Gaussian smooth noise reduction on the sample image subjected to the graying treatment;
calculating a first order gradient by using a Canny operator;
performing non-maximum suppression of the first order gradient;
and detecting edges according to the double thresholds, performing edge connection, and determining the position of the worn edge in the sample image.
In the above technical solution, the step of correcting the tool life prediction model to obtain the tool life model specifically includes:
acquiring a detection image;
obtaining a detection wear value from the detection image;
and correcting the tool life prediction model by using the detected wear value to obtain a tool life model.
In the technical scheme, the detection image is obtained by photographing through a machine vision method under the condition that the cutter is switched to the station or is abnormal.
Due to the application of the technical scheme, compared with the prior art, the invention has the following advantages:
1. according to the invention, the predicted wear value is indirectly obtained in real time through the tool life model to determine the measurement time when the wear value needs to be directly measured, so that the highest-precision tracking of the real wear condition is realized with the least direct measurement times, the cutting parameters are timely adjusted through accurate judgment, the cutting quality is guaranteed, the service life of the tool is prolonged, and the cost is saved.
Detailed Description
The invention is further described below with reference to the following examples:
the first embodiment is as follows: an in-place attitude adjustment method for a worn tool, comprising:
obtaining a measuring moment according to the tool life model;
measuring the abrasion of the cutter at the measuring time to obtain an abrasion value;
and adjusting the in-place posture of the tool according to the wear value.
Wherein the tool life model is constructed by the following steps:
establishing a wear sample library;
establishing a tool life prediction model from a wear sample library;
and correcting the tool life prediction model to obtain a tool life model.
Wherein the wear sample library is constructed by:
acquiring a sample image;
extracting a wear edge of the sample image;
acquiring abrasion depth information from the abrasion edge;
and establishing a wear sample library according to the wear depth information.
The Canny algorithm is adopted in the step of acquiring the abrasion depth information from the abrasion edge. The Canny algorithm includes the following steps:
carrying out gray processing on the sample image;
performing Gaussian smooth noise reduction on the sample image subjected to the graying treatment;
calculating a first order gradient by using a Canny operator;
performing non-maximum suppression of the first order gradient;
and detecting edges according to the double thresholds, performing edge connection, and determining the position of the worn edge in the sample image.
The step of correcting the tool life prediction model to obtain the tool life model specifically comprises the following steps:
acquiring a detection image;
obtaining a detection wear value from the detection image;
and correcting the tool life prediction model by using the detected wear value to obtain a tool life model.
And the detection image is obtained by photographing through a machine vision method under the condition that the cutter is switched to the station or is abnormal.
In the prior art, real-time direct measurement cannot be achieved, a measurement result has large errors, a detection wear value is obtained by photographing and measuring through a machine vision method under the condition that a cutter is switched to a station or is abnormal, a high-quality correction sample is provided by the real detection wear value, so that the accuracy of a cutter life model is ensured, and a real-time predicted wear value is indirectly provided by the cutter life model to determine the time when the direct measurement needs to be performed. Thus, a tracking of the actual wear situation with the highest accuracy is achieved with the least direct measurements.
The above embodiments are merely illustrative of the technical ideas and features of the present invention, and the purpose thereof is to enable those skilled in the art to understand the contents of the present invention and implement the present invention, and not to limit the protection scope of the present invention. All equivalent changes and modifications made according to the spirit of the present invention should be covered within the protection scope of the present invention.
Claims (6)
1. An in-place attitude adjustment method for a worn tool, comprising:
obtaining a measuring moment according to the tool life model;
measuring the abrasion of the cutter at the measuring time to obtain an abrasion value;
adjusting the in-place posture of the cutter according to the abrasion value;
wherein the tool life model is constructed by the following steps:
establishing a wear sample library;
establishing a tool life prediction model from a wear sample library;
and correcting the tool life prediction model to obtain a tool life model.
2. The in-place attitude adjustment method for a worn tool according to claim 1, characterized in that: the wear sample library is constructed by the following steps:
acquiring a sample image;
extracting a wear edge of the sample image;
acquiring abrasion depth information from the abrasion edge;
and establishing a wear sample library according to the wear depth information.
3. The in-place attitude adjustment method for a worn tool according to claim 2, characterized in that: the Canny algorithm is adopted in the step of acquiring the abrasion depth information from the abrasion edge.
4. The in-place attitude adjustment method for a worn tool according to claim 3, characterized in that: the Canny algorithm includes the following steps:
carrying out gray processing on the sample image;
performing Gaussian smooth noise reduction on the sample image subjected to the graying treatment;
calculating a first order gradient by using a Canny operator;
performing non-maximum suppression of the first order gradient;
and detecting edges according to the double thresholds, performing edge connection, and determining the position of the worn edge in the sample image.
5. The in-place attitude adjustment method for a worn tool according to claim 1, characterized in that: the step of correcting the tool life prediction model to obtain the tool life model specifically comprises the following steps:
acquiring a detection image;
obtaining a detection wear value from the detection image;
and correcting the tool life prediction model by using the detected wear value to obtain a tool life model.
6. The in-place attitude adjustment method for a worn tool according to claim 5, characterized in that: and the detection image is obtained by photographing through a machine vision method under the condition that the cutter is switched to the station or is abnormal.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202010115904.4A CN111185803B (en) | 2020-02-25 | 2020-02-25 | In-place posture adjusting method for worn cutter |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202010115904.4A CN111185803B (en) | 2020-02-25 | 2020-02-25 | In-place posture adjusting method for worn cutter |
Publications (2)
Publication Number | Publication Date |
---|---|
CN111185803A CN111185803A (en) | 2020-05-22 |
CN111185803B true CN111185803B (en) | 2021-09-14 |
Family
ID=70687533
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202010115904.4A Active CN111185803B (en) | 2020-02-25 | 2020-02-25 | In-place posture adjusting method for worn cutter |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN111185803B (en) |
Citations (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN1116740A (en) * | 1993-12-27 | 1996-02-14 | 村田机械株式会社 | Method of and device for correcting of cutting-edge of tool in numerically controlled machine tool |
CN101670532A (en) * | 2008-09-08 | 2010-03-17 | 鸿富锦精密工业(深圳)有限公司 | Tool wear-compensating system and method |
CN102699763A (en) * | 2012-06-13 | 2012-10-03 | 哈尔滨理工大学 | Cutter wear intelligent-measurement instrument and measuring method thereof |
CN202701986U (en) * | 2012-06-28 | 2013-01-30 | 苏州佳宏光电有限公司 | Cutter position adjusting device |
CN105014481A (en) * | 2015-08-11 | 2015-11-04 | 哈尔滨理工大学 | Portable tool wear measuring instrument and method for predicting remaining service life of tool through measuring instrument |
CN108959833A (en) * | 2018-09-26 | 2018-12-07 | 北京工业大学 | Tool wear prediction technique based on improved BP neural network |
CN109093447A (en) * | 2018-09-21 | 2018-12-28 | 北京航空航天大学 | A kind of knife rail design method based on cutter uniform wear |
CN109909805A (en) * | 2019-03-28 | 2019-06-21 | 西北工业大学 | A kind of tool selection method based on predicting residual useful life |
CN110153802A (en) * | 2019-07-04 | 2019-08-23 | 西南交通大学 | A kind of cutting-tool wear state discrimination method based on convolutional neural networks and long Memory Neural Networks conjunctive model in short-term |
JP2020015106A (en) * | 2018-07-23 | 2020-01-30 | 三菱電機株式会社 | Tool wear determination device |
Family Cites Families (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP5301380B2 (en) * | 2009-07-16 | 2013-09-25 | 本田技研工業株式会社 | Method for predicting the life of rotating blades |
DE102017120570A1 (en) * | 2017-09-07 | 2019-03-07 | Liebherr-Verzahntechnik Gmbh | Device for processing a workpiece with a tool |
CN109623494B (en) * | 2019-01-18 | 2023-08-15 | 四川大学 | Three-in-one sensor clamp and multi-mode cutter wear state monitoring system |
-
2020
- 2020-02-25 CN CN202010115904.4A patent/CN111185803B/en active Active
Patent Citations (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN1116740A (en) * | 1993-12-27 | 1996-02-14 | 村田机械株式会社 | Method of and device for correcting of cutting-edge of tool in numerically controlled machine tool |
CN101670532A (en) * | 2008-09-08 | 2010-03-17 | 鸿富锦精密工业(深圳)有限公司 | Tool wear-compensating system and method |
CN102699763A (en) * | 2012-06-13 | 2012-10-03 | 哈尔滨理工大学 | Cutter wear intelligent-measurement instrument and measuring method thereof |
CN202701986U (en) * | 2012-06-28 | 2013-01-30 | 苏州佳宏光电有限公司 | Cutter position adjusting device |
CN105014481A (en) * | 2015-08-11 | 2015-11-04 | 哈尔滨理工大学 | Portable tool wear measuring instrument and method for predicting remaining service life of tool through measuring instrument |
JP2020015106A (en) * | 2018-07-23 | 2020-01-30 | 三菱電機株式会社 | Tool wear determination device |
CN109093447A (en) * | 2018-09-21 | 2018-12-28 | 北京航空航天大学 | A kind of knife rail design method based on cutter uniform wear |
CN108959833A (en) * | 2018-09-26 | 2018-12-07 | 北京工业大学 | Tool wear prediction technique based on improved BP neural network |
CN109909805A (en) * | 2019-03-28 | 2019-06-21 | 西北工业大学 | A kind of tool selection method based on predicting residual useful life |
CN110153802A (en) * | 2019-07-04 | 2019-08-23 | 西南交通大学 | A kind of cutting-tool wear state discrimination method based on convolutional neural networks and long Memory Neural Networks conjunctive model in short-term |
Non-Patent Citations (1)
Title |
---|
基于机器视觉的刀具磨损检测技术;杨建国等;《东华大学学报(自然科学版)》;20121031;第38卷(第5期);第506-508页 * |
Also Published As
Publication number | Publication date |
---|---|
CN111185803A (en) | 2020-05-22 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN111230593B (en) | Milling cutter abrasion loss visual measurement method based on dynamic image sequence | |
Su et al. | An automated flank wear measurement of microdrills using machine vision | |
CN104400086B (en) | Aircraft skin mirror image method for milling and equipment | |
US10466037B1 (en) | System and method for controlling gear mounting distance using optical sensors | |
CN103962394B (en) | A kind of online test method of hot-rolling mill roll rolling direction side-play amount | |
CN109013716B (en) | Method, system and storage medium for online detection of position change of central axis of roller | |
JP7158195B2 (en) | Tool wear determination device | |
Xu et al. | Fast on-machine profile characterization for grinding wheels and error compensation of wheel dressing | |
CN105108578A (en) | Apparatus and method for online testing numerical control lathe and intelligently compensating cutter abrasion | |
CN112907556A (en) | Automatic measuring method for abrasion loss of rotary cutter based on machine vision | |
Shahabi et al. | Assessment of flank wear and nose radius wear from workpiece roughness profile in turning operation using machine vision | |
CN111185803B (en) | In-place posture adjusting method for worn cutter | |
CN113752086A (en) | Method and device for detecting state of numerical control machine tool cutter | |
WO2020135636A1 (en) | Hub tool management system and method | |
CN104668915A (en) | Method for machining large-sized piston-type compressor air cylinder body | |
CN205254685U (en) | Position correction device | |
CN207472156U (en) | Axial workpiece radial slot axial position detection instrument | |
WO2023097711A1 (en) | New intelligent machine tool machining system | |
CN109647902A (en) | A kind of real-time method for obtaining gap between rolling mill bearing and memorial archway | |
CN112355712B (en) | Trigger type on-machine measurement precision calibration method and system | |
CN111113268B (en) | Cutter correction method and system for machine tool | |
JP2001124533A (en) | Valve seat surface inspection instrument method | |
CN115138991A (en) | Dynamic error compensation method and system for three laser head cutting blanking lines in triangular layout | |
EP3950222B1 (en) | Method for recalibrating a non-contact sensor in a cnc processing device | |
CN211588658U (en) | Machine vision auxiliary curved surface machining device |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |