TWI453557B - Tooling machine intelligent adaptive load cutting control method and system - Google Patents

Description

Tool-tool intelligent adaptive fixed-load cutting control method and system

The invention relates to an intelligent adaptive fixed load cutting control system for a machine tool, in particular to an integrated adaptive cutting tool, an adaptive fixed load cutting control and a tool monitoring function, and an intelligent adaptive fixed load tool capable of adapting to different cutting processing conditions. Machine cutting control system.

When designing new machine tools, the existing tool machine manufacturers aim to improve the machining efficiency of the machine tool. Therefore, high efficiency and high quality are the future development direction of the machine tool. The existing high-end machine tools are integrated and automatically measured and automatically adjusted. With the automatic recording of three functions, it has high efficiency, high precision and good tool life management, but the high-end machine built-in functions need to be matched with expensive signal analysis and computing equipment, resulting in a significant increase in machine manufacturing costs, even if it is high. Processing efficiency and high quality, but there are problems of high price and not easy to popularize.

At present, in order to improve the processing efficiency of the machine of the general machine tool, in addition to increasing the motor power of each axis of the machine to speed up its moving speed, or modifying the acceleration/deceleration time constant of the servo motor, there is no other way to greatly Shorten the machining time of the machine tool to improve its efficiency, and the above method will not only increase the manufacturing cost of the machine, but also cause other problems due to the rapid movement of the axial transmission elements, such as the expansion and deformation of the screw due to the rapid movement of heat. It is easy to wear and greatly increase the maintenance cost of the machine.

As mentioned above, the existing high-end machine tools have high efficiency and high quality, but the price is high and not easy to popularize, and the general machine tool needs to increase the motor power or modify the acceleration/deceleration time of the motor to accelerate the axial movement speed. The constant is easy to cause deformation and wear of the transmission component and increase the maintenance cost of the machine tool. Therefore, the main object of the present invention is to provide a tool-tool intelligent adaptive fixed-load cutting control method and system, which is integrated and calculated by the controller of the machine tool. The optimal cutting control parameters during cutting, combined with fixed-load cutting control and tool monitoring, control the cutting speed by the corresponding load value of the controller, which can achieve high efficiency, high quality and reduce failure, and can reduce the production and maintenance of the machine tool. cost.

The main technical means adopted to achieve the above objectives is to make the above-mentioned tool machine intelligent adaptive fixed-load cutting control method. The following steps are performed by a controller: obtaining the optimal cutting control parameters of the machine tool machine, and the optimal cutting control parameters It includes a cutting fixed load value, which is integrated with one of the spindle load values of the machine, and is processed under the most suitable cutting conditions to avoid the spindle load value being greater than the cutting load value; determining whether the spindle load value of the machine is greater than the cutting The fixed load value, if it is, the feed speed is reduced, and if the spindle load value is exceeded after the feed speed is reduced, the cutting is stopped. If the spindle load value is less than the cutting load value, the machining is performed at a maximum cutting feed rate; the spindle load value is judged. Whether it is greater than the maximum load value of the machine, if it means that the spindle tool is aging or damaged, that is, the machining is stopped.

The main technical means to achieve the above objectives is to provide a machine tool The intelligent adaptive fixed load cutting control system comprises a controller and a database, wherein the controller is connected with the database and has a built-in cutting learning module, which obtains a load value of the spindle cutting of the machine tool and Stored in the database, the cutting learning module obtains a plurality of optimal cutting control parameters of the spindle through analysis and calculation. The optimal cutting control parameters include a cutting fixed load value, a maximum cutting feed rate, and a minimum cutting feed. The speed, the feed rate is increased each time, the feed rate and the maximum load value are reduced each time; an adaptive fixed load cutting control module, which measures the spindle load value of the machine, the adaptive fixed load cutting control The module integrates the cutting control parameters with the spindle load value, and adjusts the feed speed within the maximum/minimum cutting feed speed range to avoid the spindle load value being greater than the cutting fixed load value; a tool monitoring module, which records and Compare whether the spindle load value is greater than a maximum load value as a basis for judging whether the tool is aging. If the spindle load value is greater than the maximum load value, the table The machining is stopped when the tool is aged; wherein the cutting load value represents the spindle load value recorded by the cutting learning module, and the maximum cutting feed speed represents the maximum cutting speed of the adaptive fixed-cut machining of the machine tool, and the minimum cutting speed The speed represents the minimum cutting speed of the tool for the adaptive load cutting process. The maximum load value is the maximum load value that the tool can withstand. The increase of the feed rate each time represents the adaptability of the machine tool. The constant load cutting process increases the speed per unit time, and the reduced feed rate each time represents the speed of the tooling machine's adaptive fixed-cut machining process per unit time.

The utility model intelligently adapts the fixed load cutting control system by using the machine tool composed of the foregoing components, and the cutting learning module records the load of the spindle cutting of the machine tool The change of value is stored in the database, and the cutting learning module analyzes and calculates the optimal cutting control parameters required for the spindle cutting of the machine, such as the cutting load value, the maximum cutting feed rate, and the minimum cutting feed rate. Each time the feed rate is increased, the feed rate is reduced and the maximum load value is reduced, so that the controller can process the most suitable cutting conditions to improve the machining efficiency of the machine tool; the adaptive fixed load cutting control module is cut by Learning the optimal cutting control parameters obtained by the module, calculating the spindle load value and the cutting fixed load value and adjusting the cutting feed speed. If the spindle load value is greater than the cutting fixed load value, and the machine cutting speed is greater than the minimum cutting When the speed is processed, the tool is protected by reducing the feed rate to the minimum cutting feed rate each time. When the cutting process is continued at the minimum cutting feed rate, the tool monitoring module is started to monitor the condition of the tool; If the load value is less than the cutting load value and the machine cutting speed is less than the maximum cutting feed rate, the feed rate is increased by each time. Increase the cutting feed rate, increase the machining efficiency of the machine, and at the maximum cutting feed rate as the upper limit to ensure that the tool cutting conditions are met; the tool monitoring module determines that the spindle load value is greater than the maximum load value, and immediately stops the machine operation actively. Protecting the integrity of the workpiece and extending the life of the machine, it can also remind the tool to be replaced immediately to restart the machine to continue processing, which can effectively improve the efficiency of the machine and ensure the processing quality of the workpiece to avoid waste.

It can be seen from the above that the controller of the present invention does not need to additionally install a hardware device on the controller as the existing high-order tool machine, and can effectively reduce the manufacturing cost, and the cutting control module obtains the optimal cutting control parameters of the machine. And it is loaded into the adaptive fixed-load cutting control module calculation, which can adapt to different cutting processing conditions of the machine and process it under the most suitable cutting conditions. Work efficiency, avoiding machine failures caused by human error and reducing maintenance costs and improving machine efficiency.

For a preferred embodiment of the present invention, as shown in FIG. 1 , a controller 10 for a machine tool includes a cutting learning module 20 , an adaptive fixed load cutting control module 30 , and a tool monitoring module . Group 40, wherein the controller 10 is further provided with a database 50.

Referring to FIG. 2, the controller 10 sequentially executes the workflows of the cutting learning module 20, the adaptive fixed load cutting control module 30, and the tool monitoring module 40, so that the controller 10 can optimally cut the conditions. The cutting process is performed to effectively improve the machining efficiency of the machine tool.

The cutting learning module 20 is configured to obtain the load value of the spindle cutting of the machine tool and store it in the database 50. The cutting learning module 20 obtains a plurality of optimal cutting control parameters 21 of the spindle through analysis and calculation, please refer to the drawing. 3 is an operation screen of the cutting learning module 20, wherein the optimal cutting control parameter 21 includes a cutting fixed load value 211, a maximum cutting feed speed 212, a minimum cutting feed speed 213, and a per-cutting The feed rate 214, the feed rate 215 and the maximum load value 216 are respectively increased, wherein the cut load value 211 represents a spindle load value recorded by the cutting learning module 20, and the maximum cutting feed speed 212 represents The maximum cutting speed of the tool-assisted fixed-cut machining, which represents the minimum cutting speed of the adaptive fixed-cut machining of the machine tool, and the increased feed rate 214 represents the adaptability of the machine tool. Fixed load cutting process increases the speed per unit time, each time reduction The feed speed 215 represents the speed of the fixed load of the machine tool for each reduction in the unit time, and the maximum load value 216 is the maximum load value that the tool can bear in the spindle clamping; in this embodiment, The cutting learning module 20 can display a curve of the load value of the main shaft and a limit of the aforementioned maximum load value 216 by a graphical interface.

The adaptive fixed load cutting control module 30 is configured to measure the load value of the spindle of the machine during machining, and the optimal cutting control parameter 21 of the cutting learning module 20 and the load value of the main shaft are cut by an adaptive fixed load. The control module 30 integrates the calculations to adjust the feed rate within the range of the maximum/minimum cutting feed speeds 212, 213 to prevent the spindle load value from being greater than the set cutting load value 211 and causing the tool or spindle to fail.

The tool monitoring module 40 records and compares whether the spindle load value is greater than the maximum load value 216. If the spindle load value is greater than the maximum load value 216 indicating that the tool is aged or faulty, the spindle machining is immediately stopped.

Referring to FIG. 4, the cutting learning module 20 records the change of the load value during the spindle cutting and stores it in the database 50 (101). The cutting learning module 20 analyzes and calculates the machine tool to meet the requirements of the spindle cutting of the machine. Each of the optimal cutting control parameters 21 (102), such as the aforementioned cutting fixed load value 211, the maximum cutting feed rate 212, the minimum cutting feed rate 213, the increasing feed rate 214 each time, and the decreasing feed rate 215 each time. And the maximum load value 216, and can be supplemented by increasing the processing program number of one of the controllers 10 and a tool number (103) for processing program comparison to reduce human error, and can be performed by a human-machine interface 22 Manually adjust each of the optimal cutting control parameters 21 (104) to machine the machine with the most appropriate cutting conditions. The adaptive fixed-load cutting control module 30 is based on cutting. The optimal cutting control parameter 21 obtained by the module 20 is used to calculate the spindle load value and the cutting fixed load value 211 when the machine performs the cutting process, and adjust the cutting feed rate (105), when the spindle load value is greater than the cutting When the load value is 211, if the cutting speed of the machine is greater than the minimum cutting feed speed 213 (106), the cutting speed is successively reduced according to the set feed reduction speed 215 to protect the tool (107), when the machine is cut. When the speed is continuously cut at the minimum cutting feed speed 213, the tool monitoring module 40 monitors the use state of the tool. If the spindle load value is less than the cutting fixed load value 211 and the cutting speed of the machine is less than the maximum cutting feed rate 212 ( 108), the cutting speed (109) is sequentially increased according to the set increase feed rate 214, which can improve the machining efficiency of the machine, and the maximum cutting feed speed 212 is the upper limit value (110) of the cutting speed to ensure In accordance with the cutting condition of the tool, the tool monitoring module 40 determines that the spindle load value is greater than the maximum load value 216 (111), and will actively stop the machine operation to protect the workpiece integrity and extend the life of the machine (112). The tool is changed immediately to restart the machine to continue machining, and the cutting learning module 20 maintains the calculated feed speed cutting (113) and records the spindle load value and the cutting feed rate in the database 50 (114). By continuously obtaining and recording the spindle machining state, the efficiency of the machine can be effectively improved, and the processing quality can be avoided to avoid waste.

It can be seen from the above that the present invention does not need to additionally install a hardware device on the controller as in the existing high-order tool machine, and can effectively reduce the manufacturing cost, and the relevant cutting value can be obtained by the cutting learning module 20 to obtain the optimal cutting control parameter 21 And the operation is performed by the adaptive fixed-load cutting control module 30, and processing is performed under the most suitable cutting conditions to improve the processing efficiency and reduce the repair This will improve the efficiency of the machine.

10‧‧‧ Controller

20‧‧‧Cutting Learning Module

21‧‧‧Optimal cutting control parameters

211‧‧‧cutting the load value

212‧‧‧Maximum cutting feed rate

213‧‧‧Minimum cutting feed rate

214‧‧‧Increase feed rate each time

215‧‧‧Reducing the feed rate each time

216‧‧‧Maximum load value

22‧‧‧Human Machine Interface

30‧‧‧Adaptable fixed load cutting control module

40‧‧‧Tool monitoring module

50‧‧‧Database

Figure 1 is a block diagram of a system in accordance with a preferred embodiment of the present invention.

Figure 2 is a block diagram of a flow of a preferred embodiment of the present invention.

3 is a schematic view showing the use of a cutting learning module in accordance with a preferred embodiment of the present invention.

4 is a flow chart of a preferred embodiment of the present invention.

10‧‧‧ Controller

20‧‧‧Cutting Learning Module

30‧‧‧Adaptable fixed load cutting control module

40‧‧‧Tool monitoring module

50‧‧‧Database

Claims (8)

The utility model relates to an intelligent adaptive fixed load cutting control method, wherein a controller performs the following steps: obtaining an optimal cutting control parameter of a machine tool machine, and the optimal cutting control parameter comprises a cutting fixed load value, the cutting fixed load The value is integrated with the spindle load value of the machine, and processed under the most appropriate cutting conditions to avoid the spindle load value being greater than the cutting load value; determining whether the spindle load value of the machine is greater than the cutting load value, and if so, reducing the feed speed, If the spindle load value is less than the cutting load value after the feed speed is reduced, the cutting is stopped. If the spindle load value is less than the cutting load value, the machining is performed at a maximum cutting feed rate; if the spindle load value is greater than the maximum load value of the machine, if It means that the spindle tool is aging or damaged, that is, the machining is stopped. The tool machine intelligent adaptive fixed load cutting control method according to claim 1, wherein the optimal cutting control parameter includes a maximum cutting feed rate and a minimum cutting feed rate, and the maximum cutting feed rate represents a machine tool The maximum cutting speed for adaptive fixed-cut machining, which represents the minimum cutting speed for the adaptive fixed-cut machining of the machine tool. The machine tool intelligent adaptive fixed load cutting control method according to claim 1 or 2, wherein the optimal cutting control parameter includes a feed rate increase each time and a feed rate decrease each time, the feed increase each time The speed represents the adaptability of the machine tool. The increasing speed of the load cutting process per unit time is the speed of each time reduction per unit time. The utility model relates to an intelligent adaptive fixed load cutting control system, which comprises a controller and a database, wherein the controller is connected with a database and has a built-in cutting learning module, which acquires a spindle cutting of the machine tool. The load value is stored in the database, and the cutting learning module obtains a plurality of optimal cutting control parameters of the spindle through analysis and calculation. The optimal cutting control parameters include a cutting load value, a maximum cutting feed rate, a minimum cutting feed rate and a maximum load value; an adaptive fixed load cutting control module for measuring the spindle load value of the machine, the adaptive fixed load cutting control module for the cutting control parameters and the spindle load The value integration operation adjusts the feed rate within the maximum/minimum cutting feed rate range to avoid the spindle load value being greater than the cutting fixed load value; a tool monitoring module that records and compares whether the spindle load value is greater than a maximum load value, As a basis for judging whether the tool is aging, if the spindle load value is greater than the maximum load value, it means that the tool is aging and the machining is stopped; The cutting fixed load value represents the spindle load value recorded by the cutting learning module, and the maximum cutting feed speed represents the maximum cutting speed of the adaptive fixed-cut machining of the machine tool, and the minimum cutting feed speed represents the adaptability of the machine tool. The minimum cutting speed for fixed-load cutting. The maximum load value is the maximum load that the tool can withstand. The machine tool intelligent adaptive fixed load cutting control system according to claim 4, wherein the optimal cutting control parameter of the cutting learning module further comprises a feed rate increase each time and a feed rate decrease each time, each time The increasing feed rate represents the adaptability of the machine tool. The load is increased by the speed per unit time. The reduction of the feed rate represents the machine tool. The adaptive fixed-load cutting process reduces the speed per unit time. The machine tool intelligent adaptive fixed load cutting control system according to claim 4 or 5, wherein the cutting control module preferably includes a machining program number and a tool number According to the intelligent adaptive load cutting control system of the machine tool described in claim 4 or 5, the optimal cutting control parameter of the cutting learning module is manually adjusted by a man-machine interface. The intelligent machine adaptive load cutting control system according to claim 6 is characterized in that the optimal cutting control parameter of the cutting learning module is manually adjusted by a human machine operation interface.