CN113721575A - Intelligent monitoring system and method for service life of cutter - Google Patents
Intelligent monitoring system and method for service life of cutter Download PDFInfo
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- CN113721575A CN113721575A CN202111049278.4A CN202111049278A CN113721575A CN 113721575 A CN113721575 A CN 113721575A CN 202111049278 A CN202111049278 A CN 202111049278A CN 113721575 A CN113721575 A CN 113721575A
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- 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
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
- G05B19/4183—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by data acquisition, e.g. workpiece identification
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- 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
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/31—From computer integrated manufacturing till monitoring
- G05B2219/31282—Data acquisition, BDE MDE
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- 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
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- 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]
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Abstract
本发明公开了一种刀具寿命智能化监控系统及方法，该监控系统包括车间现场层、单元总控层、车间总控层和可视化管控层，车间现场层用于为系统提供实时现场数据；在现场机床上布置数据采集线，实时获取机床在线刀具位置和刀具状态，为刀具监测的可视化管理提供原始数据，单元总控层用于实现车间现场层各单元内设备间的逻辑控制，并实现底层设备的信息采集及向上层设备的信息反馈。本发明实现对“刀具流”的全链条式系统化管理；采用累计策略可配置的加工工件个数或累计加工时间的方式预测刀具剩余寿命，然后利用系统自身所设定的刀具寿命的预警值，实现对刀具剩余寿命预测结果更可靠、更科学和数值更准确的在线监测可视化管理功能。
The invention discloses an intelligent monitoring system and method for tool life. The monitoring system includes a workshop field layer, a unit general control layer, a workshop general control layer and a visual control layer, and the workshop field layer is used to provide real-time field data for the system; The data acquisition line is arranged on the on-site machine tool to obtain the online tool position and tool status of the machine tool in real time, and provide raw data for the visual management of tool monitoring. Information collection of equipment and information feedback to upper-layer equipment. The invention realizes the whole-chain systematic management of the "tool flow"; the remaining life of the tool is predicted by means of the number of processed workpieces that can be configured by the cumulative strategy or the cumulative processing time, and then the early warning value of the tool life set by the system is used. , to achieve a more reliable, scientific and numerically accurate online monitoring and visual management function for predicting the remaining tool life.
Description
Technical Field
The invention belongs to the technical field of intelligent manufacturing, and particularly relates to a system and a method for intelligently monitoring the service life of a cutter.
Background
Intelligent manufacturing is the leading direction of future manufacturing industry, and high-end manufacturing equipment represented by the aerospace and automobile fields is concerned with national defense safety and national economic life. The complex and diversified part processing puts higher requirements on tool management and control. The cutter is the most active and most state-changing element in the cutting process, and the performance of the cutter directly influences the machining precision and the production efficiency. The production mode of aviation products is mostly single piece and small batch, the production process technology is complex, the quantity of needed resources such as cutters is large, and the cost is high, so that the effective management of the resources such as the cutters is very important.
At present, the problems of tool life management in a manufacturing system are as follows: the using condition of the cutter is not recorded, and the statistical management of the usability, the durability and the like of the cutter cannot be carried out; secondly, the cutter has no service life tracking, and whether the cutter needs to be repaired or not is judged by the experience of workers; the cutter can not be guaranteed to be optimally utilized, and the utilization rate is not high; and fourthly, aiming at one or more links in the process, the full-chain type systematic management of the cutter flow is not formed, so that the information among systems is lack of communication, and the accuracy of the cutter service life management is influenced. Therefore, it is necessary to realize a system with intelligent monitoring of tool life.
Disclosure of Invention
In order to solve the problems, the invention provides a system and a method for intelligently monitoring the service life of a cutter, which realize the full-chain type systematic management of cutter flow; the method predicts the residual life of the cutter by adopting the mode of processing the number of workpieces or accumulating the processing time which can be configured by an accumulation strategy, and then realizes the online monitoring visual management function which is more reliable, more scientific and more accurate in numerical value for the prediction result of the residual life of the cutter by utilizing the early warning value of the cutter life set by the system.
In order to achieve the purpose, the invention adopts the technical scheme that: an intelligent tool life monitoring system, comprising:
the workshop field layer is used for providing real-time field data for the system; arranging a data acquisition line on an on-site machine tool, acquiring the on-line cutter position and the cutter state of the machine tool in real time, and providing original data for visual management of cutter monitoring; the unit master control layer is used for realizing logic control among equipment in each unit of a workshop field layer, generally adopts a PLC (programmable logic controller) to carry out distributed control, and realizes information acquisition of bottom-layer equipment and information feedback of upper-layer equipment so that field personnel can know equipment state information, production management information, quality statistical information and the like in time; the workshop master control layer is used for realizing the scheduling of production tasks and the coordination control of equipment in the units, the issuing of the production tasks and the scheduling of the tasks according to priority, and simultaneously realizing the scheduling of agv trolleys in each processing unit and the path planning of the trolleys, and realizing the acquisition of field information and the visual monitoring of equipment state information, production management information, quality statistical information and the like; the visual management and control layer is a workshop execution system and is presented in a visual mode, so that enterprise managers can remotely check the production condition of the whole workshop, and the monitoring of the overall information of the workshop and the making of correct operation decisions are facilitated.
Further, the equipment of the workshop field layer comprises a flexible processing unit, an agv material transportation trolley, a material storage unit, a tool storage unit and the like.
Further, the system meets network connection of devices with different protocols, and cutter life early warning of a heterogeneous numerical control network is achieved, for example, a Siemens numerical control system adopting OPC UA, a Sendai adopting FOCAS communication protocol, a numerical control system adopting ethercat protocol i5 and the like.
Further, the visual management and control layer represents various information in a modular form, wherein the information comprises production management information, quality management information, equipment management information, process information, material management information and the like.
The invention also provides an intelligent monitoring method for the service life of the cutter, which comprises the following steps:
step 1: tool information digitization
The geometric information, the splicing information, the cutting parameters, the process information, the service life of the cutter and other information of the cutter are digitally described;
step 2: setting of monitoring terminal and numerical control system
(1) Setting of monitoring terminal
The monitoring end needs to be set as follows:
1) for applying for general material setting of cutter
Selecting a general material menu to create a material blank, inputting a material number, selecting a process type from material types, and storing the information;
2) setting of new tools
Selecting a cutter maintenance menu in cutter management software, executing operation of the newly added cutter, and filling the serial number, sister cutter information, cutter geometric parameter information and cutter service life early warning value of the newly added cutter; determining a tool life early warning value by adopting a statistical analysis method in combination with historical tool life information; assuming that the tool life follows a normal distribution, i.e.
(ii) a Solving parameters using maximum likelihood estimation
、
A value of (d); likelihood function
Comprises the following steps:
in the formula:
the number of samples;
simplifying to obtain:
the normal distribution probability density function of the wear life is as follows:
the distribution function of tool life is:
the tool life calculation satisfying the reliability is that the reliability of the tool is set as
Calculating a tool life early warning value according to the allowable reliability;
3) product processing technology setting
Selecting a process data menu, setting a machining process, inputting process parameters including cutting diameter, spindle rotating speed, cutting depth and feeding speed, and binding a cutter and materials;
4) tool life monitoring function
Selecting a tool life menu, monitoring the life of the tool, and determining the type code of the tool used by each machine tool according to the machining process; if the tool display is green, indicating that the tool life is normal; if the cutter display is yellow, the cutter service life is indicated to reach an early warning value, and the cutter is reminded to be replaced; if the cutter display is red, the service life of the cutter is indicated to reach an alarm value, and the cutter is replaced;
(2) setting of numerical control system
The set and program flow is as follows: opening a tool life management function page and selecting a tool life calculation mode (frequency); setting the theoretical life of the cutter and clearing the actual life on a cutter deviation-cutter life page; inputting TLIFE _ M in the program; fourthly, the service life of the cutter is counted by M30\ M02\ M90; running a corresponding cutter measuring program in the program; when the cutter reaches the service life, the system gives a prompt that the cutter has reached the service life.
The following codes are added into an automatic line processing program:
G54
T2M6
T3
M3S3200F400
TLIFE _ M; tool set life start
G0G90X0Y0Z50
MCALL CYCLE83 (50，0，3，-19，19，0，3，3，2，1，1，0)
HOLES2(0，0，37，30，60，6)
MCALL
G0Z71.185
X0Y200
M90; tool set life count
M5
And step 3: calculation of tool life loss
Relevant parameters in the step 1 cutter life management module are a life set value, a life early warning value and a life remaining value; the timing management takes minutes as the unit of the service life of the blade, the service life set value is the maximum accumulated processing time of the blade, and when a cutter is newly built, the residual service life value of the blade is equal to the service life set value;
whether step 3 reaches the time interval of tool detection, if not, step4 is switched, if yes, the tool wear amount is detected, and the detected tool wear amount is taken as:
taking the maximum value as the current abrasion loss of the cutter position:
calculating the current tool life:
in the formula (I), the compound is shown in the specification,
is the maximum wear alarm value of the cutter,
is an ideal life value of the cutter
Correcting the service life of the cutter: judgment of
If the current tool life timing value is greater than the current tool life timing value, setting the current tool life as the current tool life timing value
；
step4, judging whether the remaining value of the service life of the current blade is equal to the lower limit of the service life of the blade, if the remaining value of the service life of the current blade is equal to the lower limit of the service life of the blade, updating the state of the current blade to be a service life early warning value by the cutter management module, and triggering PLC to give an alarm;
step 5, when the remaining life value is reduced to 0, the state of the cutting edge is updated to be 'end of life', the PLC gives an alarm, and the current cutting edge of the cutter is forbidden.
The invention has the following beneficial effects:
1) has the characteristic of intellectualization. The invention considers the management of the whole life cycle information of the cutter, comprehensively masters the management information of the cutter and has the traceability of historical information;
2) the reliability is high. The existing method for predicting the residual service life of the cutter mainly uses the number of machined workpieces, is only suitable for an ideal machining environment and cannot be dynamically adjusted according to actual conditions, and the method provided by the invention meets the dynamic adjustment of users.
Drawings
Fig. 1 is a block diagram of a hierarchical modular system according to an embodiment of the present invention.
FIG. 2 is a flow chart of tool management services according to an embodiment of the present invention.
Fig. 3 is a flowchart of tool remaining life prediction according to an embodiment of the present invention.
Fig. 4 is a diagram of a new tool material setup according to an embodiment of the present invention.
FIG. 5 is a diagram of a maintenance screen for adding a new tool according to an embodiment of the present invention.
FIG. 6 is a process data set-up diagram for an embodiment of the present invention.
Fig. 7 is a diagram illustrating the effect of monitoring the remaining life of the tool according to the embodiment of the present invention.
Detailed Description
In order that the objects and advantages of the invention will be more clearly understood, the invention is further described in detail below with reference to examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 1, an intelligent monitoring system for tool life according to an embodiment of the present invention includes:
(1) and the workshop field layer is used for providing real-time field data for the system. The equipment of the workshop field layer comprises a flexible processing unit, an agv material transportation trolley, a material storage unit, a tool storage unit and the like. A data acquisition line is arranged on the on-site machine tool, the on-line tool position and the tool state of the machine tool are acquired in real time, and original data are provided for visual management of tool monitoring. The invention meets the network connection of devices with different protocols, realizes the cutter service life early warning of a heterogeneous numerical control network, such as a Siemens numerical control system adopting OPC UA, a Sendai adopting FOCAS communication protocol, a numerical control system adopting ethercat protocol i5 and the like;
(2) the unit main control layer is used for realizing logic control among equipment in each unit of a workshop field layer, usually adopts a PLC (programmable logic controller) to carry out distributed control, and realizes information acquisition of bottom-layer equipment and information feedback of upper-layer equipment so that field personnel can know equipment state information, production management information, quality statistical information and the like in time;
(3) the workshop master control layer is used for realizing the scheduling of production tasks and the coordination control of equipment in the units, realizing the issuing of the production tasks and the scheduling of the tasks according to priority, simultaneously realizing the scheduling of agv trolleys in each processing unit and the path planning of the trolleys, and realizing the acquisition of field information and the visual monitoring of equipment state information, production management information, quality statistical information and the like;
(4) the visual management and control layer is a workshop execution system and is presented in a visual mode, so that enterprise managers can remotely check the production condition of the whole workshop, and the monitoring of the overall information of the workshop and the making of correct operation decisions are facilitated. The layer represents various information in a modular form, including production management information, quality management information, tool detection information, process information, material management information, and the like.
Fig. 2 shows a tool management flow of this embodiment. The management process is mainly characterized in that:
(1) the method aims at the full-chain type systematic management of the 'cutter flow'. The content of the management information covers the whole life cycle information from the registration of the cutter to the scrapping of the cutter, so that on one hand, the processing information is convenient to trace; on the other hand, the accurate prediction of the service life of the cutter is convenient to realize;
(2) and flexibly configuring the service life early warning value of the cutter according to actual requirements. According to different actual requirements, the method for determining the service life early warning value of the cutter is different. When batch processing or processing contents are fixed, the processing times adopting static configuration are more reasonable; and for the task processing with large processing content change, the processing time is reasonable. Aiming at the determination of the early warning value of the service life of the dynamic cutter, scholars at home and abroad have obtained certain research results, and a corresponding model is established for the distribution of the service life of the cutter. The system provides an open development interface for developing a corresponding algorithm module so as to ensure the accuracy of the calculation of the service life of the cutter;
(3) and adopting the abnormal detection of the cutter as the judgment basis for monitoring the residual service life of the cutter. The processing content of the cutter breaking detection is added in the flow, the machine tool adopts a cutter instrument to detect every certain processing time or processing part number, and if the size of the cutter exceeds a specified range, the cutter can not be used continuously.
As shown in fig. 3, the present invention further provides an intelligent monitoring system for tool life, comprising the following steps:
step 1: tool information digitization
In order to realize management of the cutter information, firstly, the geometric information, the assembly information, the cutting parameters, the process information, the service life of the cutter and other information of the cutter need to be digitally described.
Step 2: setting of monitoring terminal and numerical control system
(1) Setting of monitoring terminal
The monitoring end needs to be set as follows:
1) for applying for general material setting of cutter
Selecting a general material menu to newly create a material blank, inputting a material number, selecting a process category from the material categories, and storing the information. As shown in fig. 4.
2) Setting of new tools
In the tool management software, a tool maintenance menu is selected, the operation of newly added tools is executed, and the number of the newly added tools, sister knife information, tool geometric parameter information, tool service life early warning values and the like are filled. As shown in fig. 5.
And determining a tool life early warning value by adopting a statistical analysis method in combination with historical tool life information.
Assuming that the tool life follows a normal distribution, i.e.
。
Solving parameters using maximum likelihood estimation
、
The value of (c).
Likelihood function
Comprises the following steps:
in the formula:
the number of samples;
simplifying to obtain:
the normal distribution probability density function of the wear life is as follows:
the distribution function of tool life is:
the tool life calculation satisfying the reliability is that the reliability of the tool is set as
And calculating the early warning value of the service life of the cutter according to the allowable reliability.
3) Product processing technology setting
Selecting a process data menu, setting a machining process, inputting process parameters including cutting diameter, spindle rotating speed, cutting depth and feeding speed, and binding a cutter and materials. As shown in fig. 6.
4) Tool life monitoring function
The tool life menu is selected to monitor the tool life. And determining the type code of the cutter used by each machine tool according to the machining process. If the tool display is green, indicating that the tool life is normal; if the cutter display is yellow, the cutter life is indicated to reach the early warning value, and the cutter is reminded to be replaced. If the tool display is red, the tool life is indicated to reach the alarm value, and the tool is replaced.
(2) Setting of numerical control system
The set and program flow is as follows: opening a tool life management function page and selecting a tool life calculation mode (frequency); setting the theoretical life of the cutter and clearing the actual life on a cutter deviation-cutter life page; inputting TLIFE _ M in the program; fourthly, the service life of the cutter is counted by M30\ M02\ M90; running a corresponding cutter measuring program in the program; when the cutter reaches the service life, the system gives a prompt that the cutter has reached the service life. The following codes are added into an automatic line processing program:
G54
T2M6
T3
M3S3200F400
TLIFE _ M; tool set life start
G0G90X0Y0Z50
MCALL CYCLE83 (50，0，3，-19，19，0，3，3，2，1，1，0)
HOLES2(0，0，37，30，60，6)
MCALL
G0Z71.185
X0Y200
M90; tool set life count
M5
And step 3: calculation of tool life loss
The tool life loss calculation is divided into two modes of timing and piece counting, and since the two modes have the same principle, the following description is collectively expressed in a life timing mode.
Relevant parameters in the step 1 cutter service life management module are a service life set value, a service life early warning value and a service life remaining value. The timing management takes minutes as the unit of the service life of the blade, the service life set value is the maximum accumulated processing time of the blade, and when a cutter is newly built, the residual service life value of the blade is equal to the service life set value.
Whether step 3 reaches the time interval of tool detection, if not, step4 is switched, if yes, the tool wear amount is detected, and the detected tool wear amount is taken as:
taking the maximum value as the current abrasion loss of the cutter position:
calculating the current tool life:
in the formula (I), the compound is shown in the specification,
is the maximum wear alarm value of the cutter,
is an ideal life value of the cutter
Correcting the service life of the cutter: judgment of
If the current tool life timing value is greater than the current tool life timing value, setting the current tool life as the current tool life timing value
。
step4 judges whether the remaining value of the service life of the current blade is equal to the lower limit of the service life of the blade, if the lower limit of the service life time of the blade is reached, the cutter management module updates the state of the current blade to be a service life early warning value, and triggers PLC alarm.
step 5, when the remaining life value is reduced to 0, the state of the cutting edge is updated to be 'end of life', the PLC gives an alarm, and the current cutting edge of the cutter is forbidden. The tool life intelligent monitoring system is applied to a digital factory project, and a tool remaining life monitoring effect graph is shown in an attached figure 7. The system realizes the service life monitoring of each cutter of the flexible processing unit, wherein numerical control systems adopted by each processing unit are respectively an i5 numerical control system, a Seneko numerical control system, a Siemens numerical control system and the like. The practical processing verification shows that the monitoring system has the effectiveness and the reliability of monitoring the service life of the cutter, and the service performance of the cutter is exerted to the maximum extent, so that the production cost of a digital factory is obviously reduced, and the monitoring system has certain popularization and application values.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be construed as the protection scope of the present invention.
Claims (5)
1. The utility model provides an intelligent monitored control system of cutter life-span which characterized in that: the method comprises the following steps: the workshop field layer is used for providing real-time field data for the system; arranging a data acquisition line on an on-site machine tool, acquiring the on-line cutter position and the cutter state of the machine tool in real time, and providing original data for visual management of cutter monitoring; the unit master control layer is used for realizing logic control among equipment in each unit of a workshop field layer, realizing information acquisition of bottom equipment and information feedback of upper equipment so as to facilitate field personnel to know equipment state information, production management information and quality statistical information in time; the workshop master control layer is used for realizing the scheduling of production tasks and the coordination control of equipment in the units, realizing the issuing of the production tasks and the scheduling of the tasks according to priority, and simultaneously realizing the scheduling of agv trolleys in each processing unit and the path planning of the trolleys, and realizing the acquisition of field information and the visual monitoring of equipment state information, production management information and quality statistical information; the visual management and control layer is a workshop execution system and is presented in a visual form, so that enterprise managers can remotely check the production condition of the whole workshop, and the monitoring of the overall information of the workshop and the making of correct operation decisions are facilitated; the enterprise resource planning layer is mainly used for carrying out management decision and production planning, excavating resource potential, giving full play to resource functions, obtaining management activities such as good economic benefits of enterprises and the like, integrating resources inside and outside the enterprises, and realizing sales management, purchase management, inventory management, material demand planning, cutter service life management and the like.
2. The intelligent monitoring system for the service life of the cutter as claimed in claim 1, wherein: the equipment of the workshop field layer comprises a flexible processing unit, an agv material transport trolley, a material storage unit and a tool magazine unit.
3. The intelligent monitoring system for the service life of the cutter as claimed in claim 1, wherein: the system meets the network connection of devices with different protocols, and the cutter service life early warning of the heterogeneous numerical control network is realized.
4. The intelligent monitoring system for the service life of the cutter as claimed in claim 1, wherein: the visual management and control layer represents various information in a modular form, wherein the information comprises production management information, quality management information, equipment management information, process information and material management information.
5. An intelligent monitoring method for the service life of a cutter is characterized in that: the method comprises the following steps:
step 1: tool information digitization
Carrying out digital description on the geometric information, the assembly information, the cutting parameters, the process information and the service life of the cutter;
step 2: setting of monitoring terminal and numerical control system
(1) Setting of monitoring terminal
The monitoring end needs to be set as follows:
1) for applying for general material setting of cutter
Selecting a general material menu to create a material blank, inputting a material number, selecting a process type from material types, and storing the information;
2) setting of new tools
Selecting a cutter maintenance menu in cutter management software, executing operation of the newly added cutter, and filling the serial number, sister cutter information, cutter geometric parameter information and cutter service life early warning value of the newly added cutter; determining a tool life early warning value by adopting a statistical analysis method in combination with historical tool life information; assuming that the tool life follows a normal distribution, i.e.
(ii) a Solving parameters using maximum likelihood estimation
、
Value of (A)(ii) a Likelihood function
Comprises the following steps:
in the formula:
the number of samples;
simplifying to obtain:
the normal distribution probability density function of the wear life is as follows:
the distribution function of tool life is:
the tool life calculation satisfying the reliability is that the reliability of the tool is set as
Calculating a tool life early warning value according to the allowable reliability;
3) product processing technology setting
Selecting a process data menu, setting a machining process, inputting process parameters including cutting diameter, spindle rotating speed, cutting depth and feeding speed, and binding a cutter and materials;
4) tool life monitoring function
Selecting a tool life menu, monitoring the life of the tool, and determining the type code of the tool used by each machine tool according to the machining process; if the tool display is green, indicating that the tool life is normal; if the cutter display is yellow, the cutter service life is indicated to reach an early warning value, and the cutter is reminded to be replaced; if the cutter display is red, the service life of the cutter is indicated to reach an alarm value, and the cutter is replaced;
(2) setting of numerical control system
The set and program flow is as follows: opening a tool life management function page and selecting a tool life calculation mode (frequency); setting the theoretical life of the cutter and clearing the actual life on a cutter deviation-cutter life page; inputting TLIFE _ M in the program; fourthly, the service life of the cutter is counted by M30\ M02\ M90; running a corresponding cutter measuring program in the program; sixthly, when the cutter reaches the service life, the system gives a prompt that the cutter reaches the service life,
the following codes are added into an automatic line processing program:
G54
T2M6
T3
M3S3200F400
TLIFE _ M; tool set life start
G0G90X0Y0Z50
MCALL CYCLE83 (50，0，3，-19，19，0，3，3，2，1， 1，0)
HOLES2(0，0，37，30，60，6)
MCALL
G0Z71.185
X0Y200
M90; tool set life count
M5
And step 3: calculation of tool life loss
Relevant parameters in the step 1 cutter life management module are a life set value, a life early warning value and a life remaining value; the timing management takes minutes as the unit of the service life of the blade, the service life set value is the maximum accumulated processing time of the blade, and when a cutter is newly built, the residual service life value of the blade is equal to the service life set value;
step 2, in the processing process, the numerical control system updates the residual life value and subtracts 1 from the residual life value every other minute;
whether step 3 reaches the time interval of tool detection, if not, step4 is switched, if yes, the tool wear amount is detected, and the detected tool wear amount is taken as:
taking the maximum value as the current abrasion loss of the cutter position:
calculating the current tool life:
in the formula (I), the compound is shown in the specification,
is the maximum wear alarm value of the cutter,
is an ideal life value of the cutter
Correcting the service life of the cutter: judgment of
If the current tool life timing value is greater than the current tool life timing value, setting the current tool life as the current tool life timing value
；
step4, judging whether the remaining value of the service life of the current blade is equal to the lower limit of the service life of the blade, if the remaining value of the service life of the current blade is equal to the lower limit of the service life of the blade, updating the state of the current blade to be a service life early warning value by the cutter management module, and triggering PLC to give an alarm;
step 5, when the remaining life value is reduced to 0, the state of the cutting edge is updated to be 'end of life', the PLC gives an alarm, and the current cutting edge of the cutter is forbidden.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111049278.4A CN113721575A (en) | 2021-09-08 | 2021-09-08 | Intelligent monitoring system and method for service life of cutter |
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|---|---|---|---|
| CN202111049278.4A CN113721575A (en) | 2021-09-08 | 2021-09-08 | Intelligent monitoring system and method for service life of cutter |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114305702A (en) * | 2022-03-07 | 2022-04-12 | 极限人工智能有限公司 | Method and device for detecting surgical robot system, robot and medium |
| CN115344007A (en) * | 2022-06-24 | 2022-11-15 | 陕西法士特齿轮有限责任公司 | An intelligent tool change method, system and storage medium |
| CN115951635A (en) * | 2022-11-15 | 2023-04-11 | 海宁红狮宝盛科技有限公司 | Cutter monitoring and managing method, device and system |
| CN117592976A (en) * | 2024-01-19 | 2024-02-23 | 山东豪泉软件技术有限公司 | Cutter residual life prediction method, device, equipment and medium |
| CN117798742A (en) * | 2024-03-01 | 2024-04-02 | 深圳丹弗科技有限公司 | Tool life monitoring method, system, computer equipment and storage medium |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105824300A (en) * | 2016-03-16 | 2016-08-03 | 沈阳恒久安泰科技发展有限公司 | Heavy type intelligent factory system based on IoT (Internet of Things) technology and digital management technology |
| JP2019082836A (en) * | 2017-10-30 | 2019-05-30 | 株式会社ジェイテクト | Tool life prediction device |
| CN110989511A (en) * | 2019-11-14 | 2020-04-10 | 苏州宏软信息技术有限公司 | Tool life visual early warning method |
-
2021
- 2021-09-08 CN CN202111049278.4A patent/CN113721575A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105824300A (en) * | 2016-03-16 | 2016-08-03 | 沈阳恒久安泰科技发展有限公司 | Heavy type intelligent factory system based on IoT (Internet of Things) technology and digital management technology |
| JP2019082836A (en) * | 2017-10-30 | 2019-05-30 | 株式会社ジェイテクト | Tool life prediction device |
| CN110989511A (en) * | 2019-11-14 | 2020-04-10 | 苏州宏软信息技术有限公司 | Tool life visual early warning method |
Non-Patent Citations (2)
| Title |
|---|
| 赵科学;赵元;刘业峰;陆潇俊;李合川;张天缘;成建峰;: "基于i5系统的柔性加工单元刀具寿命管理系统", 工具技术, no. 08, 20 August 2020 (2020-08-20), pages 34 - 38 * |
| 马晓帆;姚斌;陈彬强;王建军;王维龙;: "智能制造刀具管理系统及刀具剩余寿命监测功能开发", 航空制造技术, no. 18, 15 September 2018 (2018-09-15) * |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114305702A (en) * | 2022-03-07 | 2022-04-12 | 极限人工智能有限公司 | Method and device for detecting surgical robot system, robot and medium |
| CN115344007A (en) * | 2022-06-24 | 2022-11-15 | 陕西法士特齿轮有限责任公司 | An intelligent tool change method, system and storage medium |
| CN115951635A (en) * | 2022-11-15 | 2023-04-11 | 海宁红狮宝盛科技有限公司 | Cutter monitoring and managing method, device and system |
| CN117592976A (en) * | 2024-01-19 | 2024-02-23 | 山东豪泉软件技术有限公司 | Cutter residual life prediction method, device, equipment and medium |
| CN117592976B (en) * | 2024-01-19 | 2024-04-26 | 山东豪泉软件技术有限公司 | Cutter residual life prediction method, device, equipment and medium |
| CN117798742A (en) * | 2024-03-01 | 2024-04-02 | 深圳丹弗科技有限公司 | Tool life monitoring method, system, computer equipment and storage medium |
| CN117798742B (en) * | 2024-03-01 | 2024-05-10 | 深圳丹弗科技有限公司 | Tool life monitoring method, system, computer equipment and storage medium |
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