Processing optimization method for real-time control numerical control machine tool

Abstract

The invention provides a real-time control numerical control machine tool processing optimization method, which comprises the following steps of: determining a processing interval type of a current processing procedure by utilizing a pre-trained characteristic value calculation model according to acquired main shaft power data; according to the processing interval type of the current processing procedure, obtaining a corresponding optimization adjustment strategy and a correspondingly set constant power value; and finally, transmitting the calculated feed rate adjustment value to a numerical control system of the numerical control machine tool. The machining parameters can be automatically adjusted, accurate control over the machining process can be achieved, and therefore the higher machining speed and better machining quality are obtained.

Description

Technical Field

[0001] The invention relates to the field of machine tool control, and in particular to a processing optimization method for a real-time controlled numerically controlled machine tool. Background Art

[0002] In modern manufacturing, numerical control (NC) machine tools play a vital role. The efficiency and accuracy of NC machine tools directly affect product quality and production efficiency. With the rapid development of the manufacturing industry, the traditional NC machine tool processing methods often rely on preset processing parameters and fixed processing programs. This method can ensure high processing accuracy and consistency in a stable processing environment. However, since the parameters and programs are pre-set, the machine tool will not be affected by external interference factors during the processing, and it is difficult to adapt to complex and changeable processing requirements and real-time changing processing environments. These traditional methods often seem to be unable to cope with the ever-changing workpiece materials, shapes and sizes, and cannot achieve efficient and accurate processing.

[0003] Specifically, the traditional CNC machine tool processing methods have the following problems: First, the preset processing parameters and fixed processing procedures cannot fully take into account the various changing factors in the actual processing process, such as the physical properties of the workpiece material such as hardness, toughness, thermal expansion coefficient, and dynamic factors such as tool wear and thermal deformation of the machine tool. Secondly, the traditional CNC machine tool processing methods lack real-time monitoring and feedback mechanisms, and cannot perceive and adjust the processing status in time, which may lead to error accumulation and low processing efficiency during the processing process. Finally, when faced with complex and changing processing requirements, traditional CNC machine tool processing methods often require manual intervention and adjustment, which increases the difficulty and cost of operation. Summary of the invention

[0004] In order to solve the above problems, the present invention proposes a real-time controlled CNC machine tool processing optimization method.

[0005] The main contents of the present invention include:

[0006] A real-time controlled CNC machine tool processing optimization method comprises the following steps:

[0007] Load the process list of the workpiece to be processed;

[0008] Determine the type of machining interval of the current machining process according to the acquired spindle power data and the characteristic value calculation model; the machining interval type includes acceleration and deceleration interval, steady cutting interval and air cutting interval;

[0009] According to the processing interval type of the current processing procedure, the corresponding optimization adjustment strategy and the corresponding set constant power value are obtained;

[0010] According to the current spindle power data and the corresponding set constant power value, the feed rate adjustment value is transmitted to the CNC system of the CNC machine tool according to the corresponding optimization adjustment strategy.

[0011] Preferably, according to the processing interval type of the current processing step, the corresponding optimization adjustment strategy and the corresponding set constant power data are obtained, including:

[0012] When the machining interval type of the current machining process is the acceleration / deceleration interval, the optimal feed speed is calculated according to the set constant power value; the feed rate calculated according to the optimal feed speed and the preset feed speed is transmitted to the CNC system of the CNC machine tool as the feed rate adjustment value.

[0013] Preferably, according to the set constant power value, the optimal feed speed is calculated, including:

[0014] Obtain tool information and part material information of the current processing step;

[0015] The optimal feed speed is calculated based on the tool information, part material information and the set constant power value.

[0016] Preferably, when the machining interval type of the current machining process is a steady cutting interval, if the current spindle power value is greater than the set constant power value, the corresponding feed speed is reduced according to the set step size; if the current spindle power value is less than the set constant power value, the corresponding feed speed is increased according to the set step size until the current machining process is completed.

[0017] Preferably, determining the type of machining interval of the current machining process according to the acquired spindle power data and the characteristic value calculation model includes:

[0018] Input the acquired spindle power data into the pre-trained eigenvalue calculation model to obtain the corresponding eigenvalue;

[0019] The processing interval type of the current processing step is determined according to the corresponding characteristic value and the preset characteristic value threshold.

[0020] Preferably, the working process of the pre-trained eigenvalue calculation model includes:

[0021] According to the machining program file of the workpiece to be machined, the corresponding tool position number and the number of machining pieces are obtained;

[0022] Record the process revelation time, and obtain the corresponding processing parameter values ​​according to the set collection frequency, wherein the processing parameter values ​​include spindle speed, feed speed, and cutting force;

[0023] Determine whether the tool position number has changed. If so, stop collecting data and record the current time as the process end time to calculate the processing time of the current process.

[0024] Calculate the processing characteristic value of the current process according to the obtained processing parameter value and processing time, wherein the processing characteristic value includes mean value, maximum value, minimum value and standard deviation;

[0025] According to the acquired processing feature values, the process list of the workpiece to be processed is updated.

[0026] Preferably, before updating the process list of the workpiece to be processed, the following steps are also included:

[0027] Calculate the sum of the number of processed pieces and the preset learning interval;

[0028] Determine whether the sum of the number of processed pieces and the preset learning interval is greater than the set piece number threshold. If it is less, continue to obtain the current processing parameter value to update the corresponding processing feature value; otherwise, update the process list of the workpiece to be processed.

[0029] The beneficial effect of the present invention lies in: a real-time controlled CNC machine tool processing optimization method proposed by the present invention obtains the machine tool operation data in real time, utilizes the pre-trained eigenvalue calculation model, distinguishes different types of processing intervals, and then dynamically adjusts and optimizes the different processing intervals accordingly. It can not only automatically adjust the processing parameters, but also realize precise control of the processing process, thereby obtaining faster processing speed and better processing quality. DETAILED DESCRIPTION

[0030] The technical solution protected by the present invention is described in detail below.

[0031] The present invention discloses a processing optimization method for a real-time controlled CNC machine tool. According to corresponding processing characteristic values, the processing process is divided into different processing interval types, and different adaptive adjustments and optimized feed speeds are performed for different processing interval types to achieve constant spindle power and ensure processing stability and accuracy. At the same time, the optimized and adjusted parameters are written into the corresponding addresses of the CNC system in real time, avoiding modification of the processing program and avoiding problems such as abnormal revision of the machining program and upload failure that may be introduced thereby.

[0032] Specifically, the processing optimization method proposed in the present invention comprises the following steps:

[0033] First, according to the workpiece to be processed, the corresponding process list is loaded to obtain information such as the material of the workpiece to be processed, the tool information used, and the processing program segments involved;

[0034] Then, the spindle power data and other processing data are obtained through the power sensor set on the output shaft of the spindle motor. Other processing data include the cutting force, feed rate, cutting speed, etc. involved in the corresponding program segment; then, the processing interval type of the current processing procedure is determined according to the pre-trained eigenvalue calculation model; the processing interval types include acceleration and deceleration intervals, stable cutting intervals and air cutting intervals.

[0035] Among them, the pre-trained eigenvalue calculation model can calculate the corresponding eigenvalue according to the acquired real-time processing data, and by comparing it with the preset eigenvalue threshold, the processing interval type of the current process can be determined. The eigenvalue threshold is determined according to actual problems and experience, and is adjusted as the processing conditions change. At the same time, in the judgment process, a combination of multiple eigenvalues ​​can be considered to judge the processing interval type to improve the accuracy and reliability of the judgment. Specifically, the working process of the pre-trained eigenvalue calculation model is as follows:

[0036] According to the machining program file of the workpiece to be machined, the corresponding tool position number and the number of machining pieces are obtained;

[0037] Record the process revelation time, and obtain the corresponding processing parameter values ​​according to the set collection frequency, wherein the processing parameter values ​​include spindle speed, feed speed, and cutting force;

[0038] Determine whether the tool position number has changed. If so, stop collecting data and record the current time as the process end time to calculate the processing time of the current process.

[0039] Calculate the processing characteristic value of the current process according to the obtained processing parameter value and processing time, wherein the processing characteristic value includes mean value, maximum value, minimum value and standard deviation;

[0040] Then, the sum of the number of processed pieces and the preset learning interval is calculated;

[0041] Determine whether the sum of the number of processed pieces and the preset learning interval is greater than the set piece number threshold. If it is less, continue to obtain the current processing parameter value to update the corresponding processing feature value; otherwise, update the process list of the workpiece to be processed. Update the process list of the workpiece to be processed.

[0042] The eigenvalue calculation model can use historical data as a training set, evaluate the performance and generalization ability of the model through methods such as cross-validation, and update the model parameters through real-time collected data to improve the accuracy and adaptability of the model.

[0043] After the machining interval type of the current machining process is determined, the corresponding optimization adjustment strategy and the corresponding set constant power value are obtained; specifically, when the machining interval type of the current machining process is an acceleration / deceleration interval, the optimal feed speed is calculated according to the set constant power value; the feed rate calculated according to the optimal feed speed and the preset feed speed is transmitted to the CNC system of the CNC machine tool as a feed rate adjustment value.

[0044] When the machining interval type of the current machining process is a steady cutting interval, if the current spindle power value is greater than the set constant power value, the corresponding feed speed is reduced according to the set step size; if the current spindle power value is less than the set constant power value, the corresponding feed speed is increased according to the set step size until the current machining process is completed.

[0045] Among them, according to the set constant power value, the optimal feed speed is calculated, including:

[0046] Obtain tool information and part material information of the current processing step;

[0047] The optimal feed speed is calculated based on the tool information, part material information and the set constant power value.

[0048] Finally, according to the current spindle power data and the corresponding set constant power value, the feed rate adjustment value is transmitted to the CNC system of the CNC machine tool according to the corresponding optimization adjustment strategy.

[0049] Specifically, the adjustment value can be sent to the CNC system through the communication interface between the industrial computer and the CNC machine tool (such as RS-232, RS-485, Ethernet, etc.). The data transmission and control instruction sending between the computer and the CNC system can also be realized by writing a communication protocol (such as the MQTT protocol) and an instruction set; at the same time, remote monitoring and diagnosis technology can be used to monitor the system's operating status and fault information in real time so as to handle and solve potential problems in a timely manner.

[0050] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A real-time controlled CNC machine tool processing optimization method, characterized in that: The steps include: Load the process list of the workpiece to be processed; Determine the type of machining interval of the current machining process according to the acquired spindle power data and the characteristic value calculation model; the machining interval type includes acceleration and deceleration interval, steady cutting interval and air cutting interval; According to the processing interval type of the current processing procedure, the corresponding optimization adjustment strategy and the corresponding set constant power value are obtained; According to the current spindle power data and the corresponding set constant power value, the feed rate adjustment value is transmitted to the CNC system of the CNC machine tool according to the corresponding optimization adjustment strategy.

2. The processing optimization method of a real-time controlled CNC machine tool according to claim 1 is characterized in that: According to the processing interval type of the current processing step, the corresponding optimization adjustment strategy and the corresponding set constant power data are obtained, including: When the machining interval type of the current machining process is the acceleration / deceleration interval, the optimal feed speed is calculated according to the set constant power value; the feed rate calculated according to the optimal feed speed and the preset feed speed is transmitted to the CNC system of the CNC machine tool as the feed rate adjustment value.

3. The processing optimization method of a real-time controlled CNC machine tool according to claim 2 is characterized in that: According to the set constant power value, calculate the optimal feed speed, including: Obtain tool information and part material information of the current processing step; The optimal feed speed is calculated based on the tool information, part material information and the set constant power value.

4. The method for optimizing the processing of a CNC machine tool with real-time control according to claim 2, characterized in that: When the machining interval type of the current machining process is a steady cutting interval, if the current spindle power value is greater than the set constant power value, the corresponding feed speed is reduced according to the set step size; if the current spindle power value is less than the set constant power value, the corresponding feed speed is increased according to the set step size until the current machining process is completed.

5. The method for optimizing machining of a CNC machine tool with real-time control according to claim 1, characterized in that: According to the acquired spindle power data and characteristic value calculation model, the processing interval type of the current processing step is determined, including: Input the acquired spindle power data into the pre-trained eigenvalue calculation model to obtain the corresponding eigenvalue; The processing interval type of the current processing step is determined according to the corresponding characteristic value and the preset characteristic value threshold.

6. The method for optimizing machining of a CNC machine tool with real-time control according to claim 5, characterized in that: The working process of the pre-trained eigenvalue calculation model includes: According to the machining program file of the workpiece to be machined, the corresponding tool position number and the number of machining pieces are obtained; Record the process revelation time, and obtain the corresponding processing parameter values ​​according to the set collection frequency, wherein the processing parameter values ​​include spindle speed, feed speed, and cutting force; Determine whether the tool position number has changed. If so, stop collecting data and record the current time as the process end time to calculate the processing time of the current process. Calculate the processing characteristic value of the current process according to the obtained processing parameter value and processing time, wherein the processing characteristic value includes mean value, maximum value, minimum value and standard deviation; According to the acquired processing feature values, the process list of the workpiece to be processed is updated.

7. The method for optimizing machining of a CNC machine tool with real-time control according to claim 6, characterized in that: Before updating the process list of the workpiece to be processed, it also includes: Calculate the sum of the number of processed pieces and the preset learning interval; Determine whether the sum of the number of processed pieces and the preset learning interval is greater than the set piece number threshold. If it is less, continue to obtain the current processing parameter value to update the corresponding processing feature value; otherwise, update the process list of the workpiece to be processed.