CN109909804B - Tool wear damage online monitoring method based on spindle driving current and process steps - Google Patents

Tool wear damage online monitoring method based on spindle driving current and process steps Download PDF

Info

Publication number
CN109909804B
CN109909804B CN201811574686.XA CN201811574686A CN109909804B CN 109909804 B CN109909804 B CN 109909804B CN 201811574686 A CN201811574686 A CN 201811574686A CN 109909804 B CN109909804 B CN 109909804B
Authority
CN
China
Prior art keywords
current
load
cutter
processing
tool
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
Application number
CN201811574686.XA
Other languages
Chinese (zh)
Other versions
CN109909804A (en
Inventor
王民
宋铠钰
朱葛龙
程大勇
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Wuxi Honor Mechanical & Electrical Equipment Co ltd
Beijing University of Technology
Original Assignee
Wuxi Honor Mechanical & Electrical Equipment Co ltd
Beijing University of Technology
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.)
Filing date
Publication date
Application filed by Wuxi Honor Mechanical & Electrical Equipment Co ltd, Beijing University of Technology filed Critical Wuxi Honor Mechanical & Electrical Equipment Co ltd
Priority to CN201811574686.XA priority Critical patent/CN109909804B/en
Publication of CN109909804A publication Critical patent/CN109909804A/en
Application granted granted Critical
Publication of CN109909804B publication Critical patent/CN109909804B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Landscapes

  • Machine Tool Sensing Apparatuses (AREA)
  • Numerical Control (AREA)

Abstract

The invention discloses a tool wear damage online monitoring method based on spindle driving current and process steps, which obtains processing process step information by realizing communication with a numerical control system, simultaneously monitors spindle driving current and load, reasonably formulates a control chart control line by drawing a control chart of average current/load required by processing of each process step based on analysis of difference of cutting torque of a normal tool and a wear damage tool and a statistical quality control principle, judges the wear state of the tool used by each process step and formulates a tool changing or tool sharpening rule. And judging the damage of the cutter according to the condition that the instantaneous spindle current or the instantaneous load deviates from the instantaneous current/load change rule in normal processing along with the processing process in each step of processing, and sending an alarm signal to inform a numerical control system of emergency shutdown so as to avoid serious consequences of damaging the workpiece and the machine tool. The method can reduce the rejection rate of parts and the failure rate of a machine tool, prolong the service life of the cutter to the maximum extent and reduce the use cost of the cutter in a factory.

Description

Tool wear damage online monitoring method based on spindle driving current and process steps
Technical Field
The invention relates to a method and a device for monitoring the abrasion damage state of a numerical control machine tool on line, in particular to a method for monitoring the abrasion damage of the tool on line based on the driving current of a main shaft of a numerical control machine tool and the processing step information of a workpiece, and belongs to the technical field of monitoring the state of the numerical control machine tool.
Background
Along with the continuous development of the intelligent manufacturing technology, the automation degree of a manufacturing system is higher and higher, the production process tends to be in an unattended state, and particularly, a cutter is frequently used and continuously worn in the cutting process for a long time in the actual production process. The abrasion and damage of the cutter are the most common phenomena in the machining and manufacturing process, and the serious consequences of scrapping the workpiece and damaging the cutter and the main shaft are caused by the light cutter. Conventional tool wear detection is direct and indirect measurement. The direct measurement method measures the appearance and the geometric dimension of the cutting edge, but the shutdown detection is required to occupy public time, and the shutdown time caused by the detection accounts for about 20 to 30 percent of the total shutdown time of the machine tool according to the indication of industrial statistical data; in the indirect measurement method, a sensor is mostly installed to monitor characteristic signals, but the installation and the use of the sensor can influence normal machining and even change the structure of a machine tool, and the sensor is mostly applied to verification theory research. Scholars at home and abroad obtain remarkable achievements in the aspect of research in the field of online monitoring of cutter abrasion, but part of problems still exist in the actual production link, actual machining conditions are separated in the actual production process, and the applicability to variable factors such as production processes, machined workpieces, machine tool characteristics and the like is poor.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides an on-line tool wear and damage monitoring method based on the drive current of a numerical control machine and the processing step information of a workpiece.
In order to achieve the purpose, the technical scheme adopted by the invention is a tool wear damage online monitoring method based on spindle driving current and process steps, and the method is characterized in that: for processing machine parts in batches, monitoring processing step information and main shaft current/load information at the same time, judging the wear degradation state of a cutter by automatically drawing a statistical process control chart of the average current/load of each step of processing workpieces in batches, and formulating cutter changing and sharpening rules; the damage state of the cutter is judged by automatically drawing an instantaneous current/load change trend graph of each step of batch processing workpieces and comparing the instantaneous current/load change trend graph with the instantaneous current/load change trend graph in normal processing, and a stop alarm signal is sent.
The tool wear damage database is used for storing control chart sample data, process step data and historical data.
The data acquisition is mainly used for establishing communication with a machine tool numerical control system through a data interface to acquire corresponding spindle current/load data and step information.
The system learning process acquires the designated data volume through human-computer interaction, and automatically creates the step information and the control chart information.
Acquiring a plurality of groups of step current/load data in the normal machining process (for a worn cutter), and creating a standard oscillogram of instantaneous current/load changing along with machining time in the corresponding step normal machining process by fitting after averagely eliminating random errors.
And acquiring the average current/load data of the process steps in the fixed batch normal machining (for the worn cutters), and calculating an average range control line and a control chart by adopting a process control theory.
And analyzing the average main shaft current/load control chart of the corresponding process step by adopting a statistical process control theory, and judging the wear degradation condition of the cutter used in the corresponding process step.
And monitoring the instantaneous spindle current/load change condition in the machining process of each step on line, and automatically drawing an instantaneous current/load change oscillogram.
The damage of the cutter is judged by comparing and analyzing the current/load oscillogram with the difference of the instantaneous current/load change oscillogram in the database during the normal processing of the corresponding process step, when the ratio of the instantaneous parameter to the sample parameter is continuously detected for multiple times and exceeds N (warning multiplying power), the cutter is judged to be damaged, and an alarm signal is sent to a numerical control system to trigger the emergency stop of the numerical control machine.
And analyzing the average main shaft current/load control chart, judging the wear degradation state of the cutter according to the fluctuation principle of the control chart when the control chart is abnormally fluctuated, and sending an alarm signal to inform an operator to replace the cutter or sharpen the cutter when the cutter used in the corresponding step is judged to be in a limit state.
The invention has the obvious benefits that the workpiece processing step is combined with the used cutter, the cutter state on multiple cutter positions can be monitored on line simultaneously, the cutter damage alarm in the processing process of a numerical control machine tool is realized, and the cutter abrasion state dynamically formulates the cutter changing or sharpening rule of the cutter. The method can realize advanced prediction management based on the state for the service life management of the cutters in the batch processing production workshop, reduce the rejection rate of workpieces and the failure rate of a machine tool on the one hand, furthest prolong the service life of the cutters on the other hand, and reduce the use cost of the cutters in factories.
Drawings
FIG. 1 is a schematic diagram of the system of the present invention;
FIG. 2 is a graph of the normal average load control during normal machining (for worn tools);
FIG. 3 is a graph showing the average load of abnormal process steps in the forecast phase;
FIG. 4 illustrates the time points corresponding to the forecast phase when the instantaneous load exceeds the standard curve;
Detailed Description
The monitoring system provided by the invention obtains the main shaft driving current/load and the processing step information through the data interface of the numerical control system, and fits a standard waveform curve of instantaneous current/load changing along with the processing time in the normal processing process of the processing step after random errors are averagely eliminated. And monitoring instantaneous current/load in the machining process of the numerical control machine tool, comparing the instantaneous current/load with a standard curve, and sending an alarm signal to trigger emergency shutdown protection of the machine tool when judging that the cutter is damaged. And in addition, after the workpiece is machined, an average current/load average control chart is created, the abrasion state of the cutter is analyzed, and the cutter changing or sharpening rule of the machining cutter is dynamically adjusted.
The tool wear damage on-line monitoring method based on the main shaft driving current and the process steps is characterized in that for processing mechanical parts in batches, processing process step information and main shaft current/load information are monitored at the same time, the tool wear degradation state is judged by automatically drawing a statistical process control chart of the average current/load of each process step of the batch processing parts, and tool changing and sharpening rules are formulated; the damage state of the cutter is judged by automatically drawing an instantaneous current/load change trend graph of each step of batch processing parts and comparing the instantaneous current/load change trend graph with the instantaneous current/load change trend graph in normal processing, and a stop alarm signal is sent.
Aiming at the batch processing of mechanical parts, the change condition of the main shaft current/load in each step of processing is monitored by acquiring the step information of a numerical control processing program, the average main shaft current/load data in each step of processing of the batch processing of parts is analyzed by adopting a mean value range control chart in a statistical process control theory, when the mean value range control chart is abnormally fluctuated, the abrasion of the tool used in the corresponding step is judged to reach a limit state, and an alarm signal is sent to inform an operator to replace the tool or to sharpen the tool.
Aiming at batch processing machine parts, the instantaneous spindle current/load change condition in the processing process of each step is monitored by acquiring the step information of a numerical control processing program, and an instantaneous current/load change oscillogram of each step is automatically drawn. And then judging the damage of the cutter by analyzing the difference between the current/load oscillogram and the instantaneous current/load change oscillogram in normal processing of each step, and sending an alarm signal to inform a numerical control system of emergency shutdown so as to avoid the serious consequence of damaging the workpiece and the machine tool.
The control line of the mean current/load control chart of each step of batch processing of parts needs to be obtained by acquiring the mean current/load acquisition data of each step during normal processing, namely when the tool is not worn, and performing calculation analysis according to the mean range control chart control line calculation method. When the abrasion state of the cutter is judged on line, after current/load data of a fixed batch of parts are collected, an average current/load average extreme difference control chart of each working step is drawn in steps, and the abrasion degradation condition of the cutter used in each working step is judged on line according to the principle that the control chart is judged to be abnormally fluctuated by statistical quality control.
The instantaneous current/load oscillogram of each step of the batch processing parts needs to acquire instantaneous current/load data of each step in normal processing, acquire at least a plurality of groups of data, averagely eliminate random errors, and obtain a standard wave curve of the instantaneous current/load changing along with the processing time in the normal processing process of each step through curve fitting. When the cutter damage is judged on line in real time, the instantaneous current/load data is compared with the instantaneous current/load in the standard waveform curve at the same processing time every time the instantaneous current/load data is monitored, if the instantaneous current/load monitored continuously for many times is obviously higher than N times of the instantaneous current/load at the moment corresponding to the positive standard waveform curve, the cutter damage is judged, and an alarm signal is sent to a numerical control system. And N is warning multiplying power, and is set and corrected according to experience.
A small-sized computing device (such as an embedded industrial personal computer) is installed on an electric control cabinet of the numerical control machine tool, communication is established with a numerical control system of the machine tool through a data interface, a current processing program of the numerical control system and state information such as the rotating speed of a main shaft of the machine tool, the load of the main shaft and the like are collected, the rotating speed or the load information of the main shaft can also directly monitor the current of a driving motor of the main shaft through a current sensor, and the rotating speed and the.
In order to reliably and accurately identify the wear and damage state of the cutter on line, the working process of the system is divided into a learning stage and a forecasting stage. In the learning stage, an operator acquires the step information and the state information of the complete machining process of the specified number of parts meeting the calculation requirements of the system through human-computer interaction, the system automatically identifies and divides the steps and the cutter models, and draws an average current/load mean range control chart and an instantaneous current/load standard waveform curve of each step. And in the forecasting stage, judging the wear state of the cutter according to the control chart of the current average current/load, and judging the damage state of the cutter according to the current instantaneous current/load.
As shown in fig. 1, the monitoring system provided by the present invention includes a data acquisition module, a learning module, a damage alarm module, a wear prediction module, and a tool wear damage database. The numerical control system data interface is respectively connected with the damage alarm module, the tool wear damage database and the learning module through the data acquisition module. The damage alarm module is connected with the wear prediction module, and the damage alarm module, the wear prediction module and the learning module are all connected with the tool wear damage database.
And the data acquisition module is connected with a data interface of the numerical control system of the machine tool and is used for monitoring the current machining state of the numerical control machine tool in real time and triggering the acquisition module to start data acquisition when judging that the numerical control machine tool is machining.
The acquisition module mainly acquires current processing program information, spindle load and rotating speed parameters and submits the current processing program information, the spindle load and the rotating speed parameters to the learning module or the damage alarm module in the corresponding state for data processing.
And the data acquisition module establishes a data storage file when judging that the numerical control machine tool is in machining, and writes the cutting parameters stored in the memory into the corresponding data file in a non-covering mode in the database when judging that the data reaches a certain amount or the working steps are finished and the workpiece is machined.
And the learning module receives a batch number input by a user through a human-computer interaction interface in the learning stage, and replaces and uses the unworn cutter to operate.
A standard waveform curve of instantaneous current/load over time, an average current/load control map (as shown in fig. 2), process step parameters are created and saved to a database as a fit after the specified batch process is completed.
And the forecast stage damage alarm module inquires a database for a matched process step standard waveform curve according to the current process step information.
And comparing the difference between the instantaneous current/load data and the standard waveform curve, and judging that the cutter is damaged when the instantaneous data continuously judge for multiple times exceeds N times of the instantaneous current/load at the corresponding moment of the standard waveform curve, as shown in figure 4.
And after the cutter is judged to be damaged, an alarm signal is sent to the numerical control system to trigger the emergency shutdown protection of the machine tool.
In the forecasting stage, after a workpiece is machined, the wear forecasting module inquires turn-off data generated in the workpiece machining process from a database, and average current/load mean range control charts corresponding to the working steps are respectively created.
Analyzing a control chart, judging the wear degradation condition of the cutter according to the abnormal fluctuation principle of the control chart when the control chart is abnormal, dynamically adjusting the cutter changing or sharpening rule,
when the abnormal fluctuation of the control chart is judged as shown in figure 3, an alarm is sent out to prompt an operator to replace the cutter when the cutter is judged to be worn to the limit.

Claims (7)

1. The tool wear damage on-line monitoring method based on the main shaft driving current and the process steps is characterized in that: for processing machine parts in batches, monitoring processing step information and main shaft current/load information at the same time, judging the wear degradation state of a cutter by automatically drawing a statistical process control chart of the average current/load of each step of processing the parts in batches, and formulating cutter changing and sharpening rules; the damage state of the cutter is judged by automatically drawing the instantaneous current/load change oscillogram of each step of batch processing parts and comparing the instantaneous current/load change oscillogram with the instantaneous current/load change oscillogram in normal processing, and a shutdown alarm signal is sent out;
aiming at the batch processing of mechanical parts, the current/load change condition of a main shaft in each step of processing is monitored by acquiring the step information of a numerical control processing program, the average current/load data of the main shaft in each step of processing of the batch processing of parts is analyzed by adopting an average range control chart in a statistical process control theory, when the average range control chart is abnormally fluctuated, the abrasion of a cutter used in the corresponding step is judged to reach a limit state, and an alarm signal is sent to inform an operator to replace the cutter or to sharpen the cutter.
2. The on-line tool wear and tear monitoring method based on spindle drive current and process steps as claimed in claim 1, wherein: aiming at batch processing machine parts, monitoring the instantaneous spindle current/load change condition in the processing process of each step by acquiring step information of a numerical control processing program, and automatically drawing an instantaneous current/load change oscillogram of each step; and then judging the damage of the cutter by analyzing the difference between the instantaneous current/load change oscillogram and the instantaneous current/load change oscillogram in normal processing of each step, and sending an alarm signal to inform a numerical control system of emergency shutdown so as to avoid the serious consequence of damaging the workpiece and the machine tool.
3. The on-line tool wear and tear monitoring method based on spindle drive current and process steps as claimed in claim 1, wherein: the control line of the statistical process control chart of the average current/load of each step of batch machining parts needs to be obtained by acquiring the average current/load acquisition data of each step when the tool is normally machined, namely not worn, and performing calculation analysis according to the statistical process control chart of the average current/load; when the abrasion state of the cutter is judged on line, after current/load data of a fixed batch of parts are collected, a statistical process control chart of the average current/load of each process step is drawn in a work step mode, and the abrasion degradation condition of the cutter used in each process step is judged on line according to the principle that the statistical quality control judgment control chart is abnormally fluctuated.
4. The on-line tool wear and tear monitoring method based on spindle drive current and process steps as claimed in claim 1, wherein: acquiring instantaneous current/load change oscillograms of each step of the batch processed parts, acquiring instantaneous current/load data of each step in normal processing, acquiring at least a plurality of groups of data, averagely eliminating random errors, and then obtaining a standard wave curve of the instantaneous current/load changing along with processing time in the normal processing process of each step through curve fitting; when the cutter is judged to be damaged on line in real time, each time instantaneous current/load data is monitored, the instantaneous current/load data is compared with the instantaneous current/load in the standard waveform curve at the same processing time, if the instantaneous current/load monitored continuously for multiple times is obviously higher than N times of the instantaneous current/load at the moment corresponding to the standard waveform curve, the cutter is judged to be damaged, and an alarm signal is sent to a numerical control system; and N is warning multiplying power, and is set and corrected according to experience.
5. The on-line tool wear and tear monitoring method based on spindle drive current and process steps as claimed in claim 1, wherein: a small-sized computing device is installed on an electric control cabinet of the numerical control machine tool, communication is established with a numerical control system of the machine tool through a data interface, a current processing program of the numerical control system, the rotating speed of a main shaft of the machine tool and the load state information of the main shaft are collected, the rotating speed or the load information of the main shaft can also directly monitor the current of a main shaft driving motor through a current sensor, and the rotating speed and the load of the main shaft are computed according to a current.
6. The on-line tool wear and tear monitoring method based on spindle drive current and process steps as claimed in claim 1, wherein: in order to reliably and accurately identify the wear and damage state of the cutter on line, the working process of the system is divided into a learning stage and a forecasting stage; in the learning stage, an operator acquires the step information and the state information of the complete machining process of a specified number of parts meeting the calculation requirements of the system through human-computer interaction, the system automatically identifies and divides the steps and the cutter model, and draws a statistical process control chart of the average current/load and an instantaneous current/load standard waveform curve of each step; and in the forecasting stage, judging the wear state of the cutter according to the control chart of the current average current/load, and judging the damage state of the cutter according to the current instantaneous current/load.
7. A monitoring system for implementing the monitoring method according to claim 1, characterized in that: the tool wear and tear prediction system comprises a data acquisition module, a learning module, a wear warning module, a wear prediction module and a tool wear and tear database; the numerical control system data interface is respectively connected with the damage alarm module, the tool wear damage database and the learning module through the data acquisition module; the damage alarm module is connected with the wear prediction module, and the damage alarm module, the wear prediction module and the learning module are all connected with a tool wear damage database;
the data acquisition module is connected with a data interface of the numerical control system of the machine tool and is used for monitoring the current processing state of the numerical control machine tool in real time and triggering the data acquisition module to start data acquisition when the numerical control machine tool is judged to be processing;
the data acquisition module acquires current processing program information, spindle load and rotating speed parameters and submits the current processing program information, the spindle load and the rotating speed parameters to the learning module or the damage alarm module in a corresponding state for data processing;
the data acquisition module establishes a data storage file when judging that the numerical control machine tool is in machining, and writes cutting parameters stored in a memory into a corresponding data file in a non-covering mode in a database when judging that the data reaches a certain amount or the process steps are finished and the workpiece is machined;
and the learning module receives a batch number input by a user through a human-computer interaction interface in the learning stage, and replaces and uses the unworn cutter to operate.
CN201811574686.XA 2018-12-21 2018-12-21 Tool wear damage online monitoring method based on spindle driving current and process steps Active CN109909804B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201811574686.XA CN109909804B (en) 2018-12-21 2018-12-21 Tool wear damage online monitoring method based on spindle driving current and process steps

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201811574686.XA CN109909804B (en) 2018-12-21 2018-12-21 Tool wear damage online monitoring method based on spindle driving current and process steps

Publications (2)

Publication Number Publication Date
CN109909804A CN109909804A (en) 2019-06-21
CN109909804B true CN109909804B (en) 2021-06-25

Family

ID=66959943

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201811574686.XA Active CN109909804B (en) 2018-12-21 2018-12-21 Tool wear damage online monitoring method based on spindle driving current and process steps

Country Status (1)

Country Link
CN (1) CN109909804B (en)

Families Citing this family (22)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112238367A (en) * 2019-07-19 2021-01-19 福建省嘉泰智能装备有限公司 Real-time monitoring and alarming method utilizing sensor to monitor data
KR20220058898A (en) * 2019-09-06 2022-05-10 스미또모 덴꼬 쇼오께쯔 고오낑 가부시끼가이샤 Machining systems and methods of manufacturing workpieces
CN110614539B (en) * 2019-10-31 2021-12-03 四川普什宁江机床有限公司 Online real-time monitoring and analyzing method for state of spindle of numerical control machine tool
CN111007801B (en) * 2019-12-27 2023-06-02 中国一拖集团有限公司 Real-time acquisition method for cutter life based on multi-dimensional attribute state judgment
CN111308960B (en) * 2020-01-20 2024-01-12 广西玉柴机器股份有限公司 Load monitoring method and system
CN111660141B (en) * 2020-05-14 2022-02-15 北京工业大学 Milling cutter wear state identification method based on spindle driving current and irrelevant to working conditions
CN113941901B (en) * 2020-07-17 2024-04-23 智能云科信息科技有限公司 Machine tool cutter monitoring method, machine tool cutter monitoring device and electronic equipment
CN111948976B (en) * 2020-07-31 2022-03-15 深圳吉兰丁智能科技有限公司 Cutter state monitoring method, non-volatile readable storage medium and electronic device
CN112720069B (en) * 2020-12-22 2022-03-22 北京工业大学 Cutter wear monitoring method and device, electronic equipment and storage medium
CN112925265B (en) * 2021-02-02 2022-02-18 安徽众成合金科技有限公司 Alloy material processing monitoring system
CN113211188B (en) * 2021-04-26 2023-12-22 苏州市伯太数字科技有限公司 Cutter switching method based on cutter load waveform mode detection
CN113627304A (en) * 2021-08-03 2021-11-09 深圳市今日标准精密机器有限公司 Machine tool spindle health monitoring method and system based on artificial intelligence
CN113608482A (en) * 2021-08-13 2021-11-05 重庆允成互联网科技有限公司 Intelligent monitoring method, system and management system for precision machining tool
WO2023092311A1 (en) * 2021-11-24 2023-06-01 蔡国志 High-resolution monitoring system and method for processing machine
CN113835396B (en) * 2021-11-26 2022-03-04 四川省机械研究设计院(集团)有限公司 CNC (computer numerical control) cutter monitoring method and system and scheduling management method and system
CN114237156A (en) * 2021-12-07 2022-03-25 纽控(广东)数控技术有限公司 CNC automatic production line processing process monitoring method, device, terminal and medium
CN114571285B (en) * 2022-03-07 2024-01-19 博世华域转向系统有限公司 Method for intelligently identifying micro-tipping of extrusion tap
CN116000329B (en) * 2022-12-26 2024-08-06 中钢集团邢台机械轧辊有限公司 Control method for numerical control finish turning anti-pricking knife
CN116141511A (en) * 2022-12-29 2023-05-23 深圳智赛机器人有限公司 Wafer cutting on-line detection system
CN116048003A (en) * 2023-02-09 2023-05-02 长春工业大学 Full-automatic lathe control system
CN116441999A (en) * 2023-06-16 2023-07-18 陕西元值云创智能科技有限公司 Intelligent management and tool compensation method for industrial master tool
CN117260407B (en) * 2023-11-20 2024-03-12 铭扬半导体科技(合肥)有限公司 Detection method of polishing equipment

Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPS57158539A (en) * 1981-03-26 1982-09-30 Agency Of Ind Science & Technol Abnormal tool monitoring system
JPS59169750A (en) * 1983-03-15 1984-09-25 Hitachi Metals Ltd Machining abnormality detecting method
JPS60263649A (en) * 1984-06-11 1985-12-27 Mitsubishi Electric Corp Numeric controller
JPS61252052A (en) * 1985-04-30 1986-11-10 Mazda Motor Corp Device for detecting abnormality of perforating tool
JP2000198047A (en) * 1999-01-08 2000-07-18 Okuma Corp Machine tool
CN105364633A (en) * 2014-08-11 2016-03-02 日立金属株式会社 Tool abnormity detection method
JP2016040071A (en) * 2014-08-11 2016-03-24 日立金属株式会社 Tool failure detection method
CN106475855A (en) * 2016-11-22 2017-03-08 无锡职业技术学院 A kind of online detection instrument of main shaft of numerical control machine tool load and detection method
CN107491038A (en) * 2016-06-09 2017-12-19 发那科株式会社 Learn rote learning machine, numerical control device and the learning by rote of the threshold value of abnormal load detection
CN108015626A (en) * 2017-11-30 2018-05-11 成都飞机工业(集团)有限责任公司 A kind of cutting tool state recognition methods for being capable of the adjust automatically monitoring limit
CN108788927A (en) * 2018-06-19 2018-11-13 珠海格力智能装备有限公司 Method and device for monitoring machine tool

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP5089618B2 (en) * 2009-01-13 2012-12-05 三菱電機株式会社 Tool life detection method and tool life detection device
CN102091972B (en) * 2010-12-28 2013-06-05 华中科技大学 Numerical control machine tool wear monitoring method
CN106563972A (en) * 2015-10-13 2017-04-19 颜均泰 Tool state monitoring and predicting method
CN108620950B (en) * 2018-05-08 2021-02-02 华中科技大学无锡研究院 Method and system for monitoring machining state of turning tool

Patent Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPS57158539A (en) * 1981-03-26 1982-09-30 Agency Of Ind Science & Technol Abnormal tool monitoring system
JPS59169750A (en) * 1983-03-15 1984-09-25 Hitachi Metals Ltd Machining abnormality detecting method
JPS60263649A (en) * 1984-06-11 1985-12-27 Mitsubishi Electric Corp Numeric controller
JPS61252052A (en) * 1985-04-30 1986-11-10 Mazda Motor Corp Device for detecting abnormality of perforating tool
JP2000198047A (en) * 1999-01-08 2000-07-18 Okuma Corp Machine tool
CN105364633A (en) * 2014-08-11 2016-03-02 日立金属株式会社 Tool abnormity detection method
JP2016040071A (en) * 2014-08-11 2016-03-24 日立金属株式会社 Tool failure detection method
CN107491038A (en) * 2016-06-09 2017-12-19 发那科株式会社 Learn rote learning machine, numerical control device and the learning by rote of the threshold value of abnormal load detection
CN106475855A (en) * 2016-11-22 2017-03-08 无锡职业技术学院 A kind of online detection instrument of main shaft of numerical control machine tool load and detection method
CN108015626A (en) * 2017-11-30 2018-05-11 成都飞机工业(集团)有限责任公司 A kind of cutting tool state recognition methods for being capable of the adjust automatically monitoring limit
CN108788927A (en) * 2018-06-19 2018-11-13 珠海格力智能装备有限公司 Method and device for monitoring machine tool

Also Published As

Publication number Publication date
CN109909804A (en) 2019-06-21

Similar Documents

Publication Publication Date Title
CN109909804B (en) Tool wear damage online monitoring method based on spindle driving current and process steps
CN107738140B (en) Method and system for monitoring state of cutter and processing equipment
CN108490880A (en) A kind of numerical control machine tool cutting cutting-tool wear state method of real-time
US10719061B2 (en) Method for judging key moments in whole process of machining step for computer numerical control machine tools
CN102929210A (en) Control and optimization system for feature-based numerical control machining process and control and optimization method therefor
CN108873813B (en) Cutter abrasion degree detection method based on numerical control machine tool spindle servo motor current signal
CN111113150B (en) Method for monitoring state of machine tool cutter
CN109048494B (en) energy consumption type based tool life comprehensive management method and system
CN111069975A (en) Real-time monitoring and self-adaptive control system and method for terminal running state of numerically controlled milling machine
CN114571285B (en) Method for intelligently identifying micro-tipping of extrusion tap
CN113608482A (en) Intelligent monitoring method, system and management system for precision machining tool
CN103576615A (en) Method and system for controlling intelligent adaptability fixed load cutting of toolroom machine
CN114323664A (en) Method for detecting abnormal gas vibration of gas turbine
CN112904800A (en) Intelligent machine tool optimization method and auxiliary system
CN117850317B (en) Bending equipment running state monitoring system
CN114800040A (en) Cutter wear monitoring method and system based on process-state data correlation
KR20190025133A (en) The method and device for optimizing machine tool cutting conditions using vibration acceleration
CN105573250A (en) On-line quality control method and system for machining, and processing machine tool
CN115922442A (en) Cutter grinding damage real-time monitoring method based on spindle vibration signal and related device
CN111308960B (en) Load monitoring method and system
CN113199304B (en) Tool changing monitoring method based on extended Kalman filtering and cutting force model
CN104503361A (en) Multimodal fusion based gear machining process tool change decision method
JP2020191043A (en) Abnormality detector, abnormality detection server, and abnormality detection method
CN116690313B (en) Failure monitoring method for machining cutter of web plate of aircraft structural member
CN116000329B (en) Control method for numerical control finish turning anti-pricking knife

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