Disclosure of Invention
Object of the invention
Aiming at the defects and shortcomings of the prior art, the invention aims to provide a geometric self-adaptive processing error compensation and optimization method for a complex curved surface, which solves the problems that the prior art cannot comprehensively and effectively evaluate the processing error compensation capability of the curved surface, is difficult to optimize the processing error compensation capability of the curved surface and the like by comprehensively carrying out error monitoring and real-time compensation on the complex curved surface and combining a self-adaptive error compensation strategy and multi-parameter coupling optimization. Specifically, the method adopts a mode of combining partition monitoring and error evaluation, and the complex curved surface is divided into a plurality of areas according to the equal area, the precision data after the area processing is completed are collected, the processing parameters are dynamically adjusted based on the error result to automatically perform error compensation, and meanwhile, the processing parameters are globally optimized by utilizing an optimization algorithm, so that the processing efficiency is remarkably improved on the basis of meeting the processing precision. In addition, the invention ensures the stability and the high efficiency of the error compensation process by monitoring the processing performance in real time and generating an early warning signal or an optimization suggestion.
(II) technical scheme
In order to achieve the aim of the invention and solve the technical problems, the invention adopts the following technical scheme:
The method for compensating and optimizing the geometric self-adaptive machining error of the complex curved surface is used for realizing error monitoring, self-adaptive compensation and machining parameter optimization in the machining process of the complex curved surface and improving the machining precision, efficiency and quality of the complex curved surface part, and at least comprises the following steps when in implementation:
SS1. Regional division and precision data acquisition
Dividing a complex curved surface to be processed into a plurality of processing areas according to an equal area mode, and collecting real processing precision data after the processing of each area is finished in real time through a high-precision sensor and a machine vision technology in the curved surface processing process, wherein the real processing precision data at least comprises surface geometric precision data, surface processing quality data, processing stability data and cutter state data;
SS2 error analysis determination and region marking
Presetting standard precision data according to design requirements and material characteristics of a complex curved surface to be processed and taking the standard precision data as a standard for error judgment, comparing the actual processing precision data after the processing of the region with preset standard precision data based on the acquired actual processing precision data after the processing of the region, generating an error judgment result, if the actual processing precision data is greater than or equal to the preset standard precision data, indicating that the processing of the current region meets the preset process standard, processing the next region, and if the actual processing precision data is smaller than the preset standard precision data, indicating that the initial processing of the current region does not meet the preset process standard, carrying out error compensation processing on the current region, and marking the current region as an error region;
SS3 adaptive error Compensation
According to the error judgment result generated in the step SS2, dynamically adjusting processing parameters in real time aiming at an error area based on a PID control algorithm to realize self-adaptive compensation of processing errors and ensure that the error area reaches a preset process standard, ending error compensation of a current area if a compensation effect reaches the preset process standard, and continuing iterative compensation adjustment until the compensation effect does not reach the preset process standard, wherein the processing parameters at least comprise cutting speed, feeding amount, spindle rotating speed and cutter path, and the control law of the PID control algorithm is expressed as follows:
Wherein u (t) is a processing parameter adjustment instruction of time t, e (t) is a real-time deviation value of time t and is used for representing a difference value between actual processing precision data and preset standard precision data, and Kp、Ki and Kd are respectively a proportional coefficient, an integral coefficient and a differential coefficient of a PID algorithm and respectively correspond to adjustment weights of current influence, past accumulated influence and future change trend influence of deviation;
SS4 Compensation coefficient calculation
In the error compensation process, the lead processing completion time and the compensation processing completion time of each error area are obtained and respectively marked as error area lead time TQi and error area compensation time TBi, and the compensation coefficient XB in the curved surface processing process is calculated through the following algorithm formula:
Where i is the error region number and i=1, 2,3,..j, j, indicates the number of error regions, TBKi is the start time of error region compensation time TBi, TQJi is the end time of error region preamble time TQi, D (TBi) is the variance of all error region compensation times,In order to compensate for the response mean value,In order to compensate for the value of the energy efficiency,To compensate for the applicable coefficient;
SS5 Compensation Effect evaluation
Comparing the compensation coefficient XB of the curved surface machining process calculated in the step SS4 with a preset compensation coefficient threshold value in a numerical mode, generating a compensation early warning signal if the compensation coefficient XB of the curved surface machining process exceeds the preset compensation coefficient threshold value, and generating a compensation qualified signal if the compensation coefficient XB of the curved surface machining process does not exceed the preset compensation coefficient threshold value;
SS6 global optimization of process parameters
Based on the compensation effect evaluation result in the step SS5, global optimization is carried out on the machining parameters by utilizing an optimization algorithm according to the specific requirements of the machining task, a multi-objective optimization model of the machining efficiency and the machining quality is established by analyzing historical machining data, real-time error data and a compensation coefficient XB, and an optimal machining parameter combination is generated so as to dynamically adjust the machining parameters of the cutting speed, the feeding amount, the spindle rotating speed and the tool path, and realize double improvement of the machining efficiency and the machining quality;
SS7 evaluation of processing quality and anomaly Signal Generation (optional step)
Setting a monitoring period with a duration of L1, collecting multidimensional data at least comprising the generation times of compensation early warning signals, quality detection data of processed parts and processing efficiency in the monitoring period, obtaining a compensation early warning risk value, a curved surface processing abnormal quality value, a curved surface work efficiency value and a curved surface processing analysis value through numerical calculation, analyzing the processing performance of complex curved surface geometric processing in the monitoring period, generating a curved surface processing qualified signal or a curved surface processing abnormal signal through analysis, and realizing comprehensive monitoring and evaluation of a processing process.
SS8 tool State detection and Life assessment (optional step)
When the machining is finished or the geometric machining of the curved surface is stopped, detecting and analyzing surface cracks, abrasion loss and high risk areas of the cutter to evaluate the service life condition of the cutter, judging whether to generate a cutter service life end signal according to the service life condition, and if the detection result of the cutter shows that the machining requirement is not met, generating the cutter service life end signal and reminding to replace the cutter to prevent the machining quality from being influenced by the failure of the cutter.
(III) technical effects
Compared with the prior art, the complex curved surface geometric self-adaptive processing error compensation and optimization method has the following beneficial and remarkable technical effects:
(1) According to the invention, the self-adaptive compensation of the machining errors is realized by monitoring the curved surface machining process in real time and carrying out error judgment, dynamically adjusting the machining parameters in real time according to the error judgment result and combining a PID control algorithm, the machining parameters are globally optimized by utilizing an optimization algorithm, the compensation efficiency performance is accurately judged by monitoring and tracking the error compensation process and combining calculation of compensation coefficients, and the reason investigation analysis is carried out and corresponding improvement measures are carried out when a compensation early warning signal is generated, so that the error compensation efficiency is ensured to improve the curved surface machining quality;
(2) The invention introduces the concept of compensation coefficient and comprehensively evaluates the error compensation capability through three indexes of compensation response mean value, compensation energy efficiency value and compensation application coefficient. The compensation response mean value reflects the response speed of error compensation, the compensation energy efficiency value reflects the stability and efficiency of error compensation, and the compensation application coefficient reflects the adaptability of the error compensation method to different processing areas. The combination of the three indexes can evaluate the effect of error compensation more comprehensively and objectively. By comparing the compensation coefficient with a preset threshold value, a compensation qualified signal or a compensation early warning signal can be generated, and operators can be timely reminded to intervene and adjust, so that the reliability and stability of the processing process are further improved;
(3) According to the invention, the processing performance of complex curved surface geometric processing in the monitoring period is analyzed, an operator is reminded to adjust a subsequent processing management scheme and timely strengthen subsequent processing supervision when a curved surface processing abnormal signal is generated, the processing effect and processing efficiency of a curved surface of a part are ensured, the processing cost is reduced, the service life condition of the part is evaluated by detecting and analyzing the cutter, the corresponding cutter is scrapped timely, the processing accident is avoided, the processing quality and processing stability of the curved surface are ensured, the management difficulty of the operator is remarkably reduced, and the intelligent and automatic level is further improved.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention become more apparent, the technical solutions in the embodiments of the present invention will be described in more detail below with reference to the accompanying drawings in the embodiments of the present invention. The described embodiments are some, but not all, embodiments of the invention and are exemplary and intended to be illustrative of the invention and not to be construed as limiting the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1:
As shown in fig. 1, the method for compensating and optimizing the geometric adaptive machining error of the complex curved surface according to the embodiment of the invention mainly comprises the following steps:
SS1. Regional division and precision data acquisition
The complex curved surface to be processed is divided into a plurality of areas according to the mode of equal area, a high-precision sensor and a machine vision technology (real-time monitoring is carried out through a laser range finder, a displacement sensor, a force sensor and the like) are utilized in the curved surface processing process, actual processing precision data after the processing of each area is completed are collected in real time, and the actual processing precision data at least comprises surface geometric precision data, surface processing quality data, processing stability data, cutter state data and the like, so that data support is provided for error analysis and prediction.
Preferably, the surface geometric accuracy data at least comprises a size deviation, a shape error and a position error of a machining area, the surface machining quality data at least comprises a roughness value (Ra) and a waviness value (Rw) of the surface of the area, the machining stability data at least comprises a cutting force, a feeding force and a vibration signal generated in the machining process, and the tool state data at least comprises a tool wear degree, a cutting track deviation and a tool surface temperature change.
SS2 error analysis determination and region marking
And (3) presetting standard precision data according to design requirements and material characteristics of the complex curved surface to be processed, taking the standard precision data as a standard for error judgment, comparing the actual processing precision data after the processing of the region with the preset standard precision data based on the actual processing precision data after the processing of the region, generating an error result, wherein if the actual processing precision data is greater than or equal to the preset standard precision data, the initial processing of the region is in accordance with the process standard, then processing the next region, and if the actual processing precision data is smaller than the preset standard precision data, the initial processing of the region is not in accordance with the process standard, and then carrying out error compensation processing on the region and marking the region as an error region.
SS3 adaptive error Compensation
According to the error judgment result generated in the step SS2, processing parameters (including cutting speed, feeding amount, main shaft rotating speed and the like) and a cutter path are dynamically adjusted in real time by utilizing an intelligent algorithm (such as a PID control algorithm) to realize real-time self-adaptive compensation of errors, and a compensation strategy can be dynamically adjusted according to the processing stage, material characteristics and cutter abrasion condition, so that the errors in the processing process are effectively controlled, the curved surface processing effect is ensured, and the automation and intelligent level is improved. Preferably, processing parameters are dynamically adjusted in real time based on a PID control algorithm aiming at an error area to realize self-adaptive compensation of processing errors and ensure that the error area reaches a preset process standard, if the compensation effect reaches the preset process standard, the error compensation of the current area is ended, if the compensation effect does not reach the preset process standard, iterative compensation adjustment is continued until the preset process standard is reached, wherein the processing parameters at least comprise cutting speed, feeding amount, spindle rotation speed and cutter path, and the control law of the PID control algorithm is expressed as:
Wherein u (t) is a processing parameter adjustment instruction of time t, e (t) is a real-time deviation value of time t and is used for representing a difference value between actual processing precision data and preset standard precision data, and Kp、Ki and Kd are respectively a proportional coefficient, an integral coefficient and a differential coefficient of a PID algorithm and respectively correspond to adjustment weights of current influence, past accumulated influence and future change trend influence of deviation.
SS4 Compensation coefficient calculation
In the error compensation process, the preamble processing completion time of each error region is acquired, and the compensation processing completion time of the error region is acquired again, and the preamble processing completion time of the error region and the compensation processing completion time of the error region are respectively marked as an error region preamble time TQi and an error region compensation time TBi. Respectively calculating a compensation response mean value, a compensation energy efficiency value and a compensation application coefficient through the error region lead time and the error region compensation time, and carrying out data processing on the compensation response mean value, the compensation energy efficiency value and the compensation application coefficient to obtain a compensation coefficient XB in the curved surface processing process:
Where i is the error region number and i=1, 2,3,..j, j, indicates the number of error regions, TBKi is the start time of error region compensation time TBi, TQJi is the end time of error region preamble time TQi, D (TBi) is the variance of all error region compensation times,In order to compensate for the response mean value,In order to compensate for the value of the energy efficiency,To compensate for the applicable coefficients.
SS5 Compensation Effect evaluation
And (3) comparing the compensation coefficient XB of the curved surface machining process calculated in the step (SS 4) with a preset compensation coefficient threshold value in a numerical mode, generating a compensation early warning signal if the compensation coefficient XB of the curved surface machining process exceeds the preset compensation coefficient threshold value, and generating a compensation qualified signal if the compensation coefficient XB of the curved surface machining process does not exceed the preset compensation coefficient threshold value.
SS6 global optimization of process parameters
Based on the compensation effect evaluation result in the step SS5, the processing parameters are globally optimized by utilizing an optimization algorithm according to the specific requirements of the processing task, a multi-objective optimization model of the processing efficiency and the processing quality is established by analyzing historical processing data, real-time error data and a compensation coefficient XB, and an optimal processing parameter combination is generated so as to dynamically adjust the cutting speed, the feeding amount, the spindle rotating speed and the processing parameters of the cutter path, thereby realizing the dual improvement of the processing efficiency and the processing quality.
SS7 evaluation of processing quality and anomaly Signal Generation (optional step)
Setting a monitoring period with a duration of L1, collecting multidimensional data at least comprising the generation times of compensation early warning signals, quality detection data of processed parts and processing efficiency in the monitoring period, obtaining a compensation early warning risk value, a curved surface processing abnormal quality value, a curved surface work efficiency value and a curved surface processing analysis value through numerical calculation, analyzing the processing performance of complex curved surface geometric processing in the monitoring period, generating a curved surface processing qualified signal or a curved surface processing abnormal signal through analysis, and realizing comprehensive monitoring and evaluation of a processing process.
SS8 tool State detection and Life assessment (optional step)
When the machining is finished or the geometric machining of the curved surface is stopped, detecting and analyzing surface cracks, abrasion loss and high risk areas of the cutter to evaluate the service life condition of the cutter, judging whether to generate a cutter service life end signal according to the service life condition, and if the detection result of the cutter shows that the machining requirement is not met, generating the cutter service life end signal and reminding to replace the cutter to prevent the machining quality from being influenced by the failure of the cutter.
Through the steps, the method can realize real-time monitoring, dynamic compensation and global optimization of errors in the geometric machining process of the complex curved surface, remarkably improve machining precision, efficiency and quality, and realize intelligent monitoring and management of the machining process.
Example 2:
On the basis of the above example 1, this example 2 further provides a further optimized and complementary implementation of the above method for step SS 3. Specifically, the specific process of automatically adjusting the processing parameters by using an intelligent algorithm (such as a PID control algorithm) is as follows:
The cutting parameter is dynamically adjusted according to a specific value of the dimensional accuracy deviation by using a preset control algorithm, wherein the preset control algorithm is specifically a PID control algorithm, the PID control algorithm calculates an adjustment instruction of the processing parameter according to the dimensional accuracy deviation value, and the processing parameter is dynamically adjusted specifically by calculating the deviation value, the accumulation of the deviation value and the change rate of the deviation value, and the PID control algorithm is as follows:
Wherein u (t) is a processing parameter adjustment instruction of time t, e (t) is a real-time deviation value of time t and is used for representing a difference value between actual processing precision data and preset standard precision data, and Kp、Ki and Kd are respectively a proportional coefficient, an integral coefficient and a differential coefficient of a PID algorithm and respectively correspond to adjustment weights of current influence, past accumulated influence and future change trend influence of deviation.
Then, according to the specific value of the dimensional deviation, the adjustment instruction generating unit firstly calculates a deviation value e (t), namely a difference value between the actual machining size and the preset machining size, then calculates an adjustment instruction for parameters of the cutting speed, the feeding amount and the spindle rotation speed by using a PID algorithm to reduce or eliminate the dimensional deviation, and finally dynamically adjusts the machining parameters by using the preset PID control algorithm.
The method and the device have the working principle that when the method and the device are used, the processing parameters are automatically adjusted according to error results by monitoring the curved surface processing process in real time and judging errors, the processing errors are effectively controlled, the processing parameters are globally optimized by utilizing an optimization algorithm, the processing efficiency and the surface quality are improved, the compensation efficiency performance is monitored, tracked and accurately judged by the error compensation process, and the reason investigation and the analysis are carried out and the corresponding improvement measures are carried out when the compensation early warning signal is generated, so that the error compensation efficiency is ensured to improve the curved surface processing quality.
Example 3:
on the basis of example 1 above, this example 3 further provides a further optimized and complementary implementation of the above method for step SS 4.
First, specifically, the response mean is compensatedThe method comprises the steps of firstly obtaining the lead time TQi of each error area and the corresponding compensation time TBi of the error area, then carrying out difference value calculation on the starting time of the compensation time TBi of the error area and the ending time of the lead time TQi of the error area to obtain a compensation response value of each error area, and secondly carrying out average value processing on the compensation response values of all the error areas to obtain a compensation response average value. The compensation response mean value reflects the time length of starting compensation processing after the curve surface preliminary processing is finished through error judgment, wherein the larger the compensation response mean value is, the weaker the self-adaptive processing error compensation capability is, and the smaller the compensation response mean value is, the stronger the self-adaptive processing error compensation capability is.
Second, specifically, compensating the energy efficiency valueThe calculation process of the method comprises the steps of obtaining each error region compensation time TBi, carrying out variance processing on all error region compensation time TBi to obtain a compensation stable value, carrying out mean value processing on all error region compensation time to obtain a curved surface compensation energy efficiency mean value, and carrying out product operation on the compensation stable value and the curved surface compensation energy efficiency mean value to obtain a compensation energy efficiency value. The compensation energy efficiency value reflects that the consistency of the completion of the compensation working time when the error compensation work is carried out on different error areas, if the compensation energy efficiency value is smaller, the compensation time tends to be more consistent when the processing compensation work is carried out on different areas, and therefore, the smaller the compensation energy efficiency value is, the higher and more stable the working efficiency of the processing error compensation is.
Third, specifically, compensating for the applicable coefficientThe method comprises the steps of firstly obtaining the lead time TQi of each error area and the corresponding compensation time TBi of the error area, carrying out difference value calculation on the beginning time TBKi of the compensation time of the error area and the ending time TQJi of the lead time of the error area to obtain a compensation response value of each error area, carrying out ratio operation on the compensation response value of the error area and the lead time TQi of the curved surface to obtain a compensation applicable value of each error area, and finally carrying out average value processing on the compensation applicable values of all the error areas to obtain a compensation applicable coefficient. The compensation application coefficient reflects the relation between the response time and the processing time of all error areas, and the processing difficulty of the area can be indirectly reflected by the front time of the error area, namely, the larger the front time of the error area is, the larger the processing difficulty is, the smaller the response time is, the stronger the self-adaptive processing error compensation capability is, so that the smaller the value of the compensation application coefficient is, the stronger the application capability of the processing error compensation is.
In step SS5 of the present invention, the compensation coefficient XB of the surface processing process calculated in step SS4 is compared with the preset compensation coefficient threshold value, if the compensation coefficient XB of the surface processing process exceeds the preset compensation coefficient threshold value, it indicates that the error compensation efficiency performance of the complex surface is poor in combination, a compensation early warning signal is generated, and if the compensation coefficient XB of the surface processing process does not exceed the preset compensation coefficient threshold value, it indicates that the error compensation efficiency performance of the complex surface is good in combination, a compensation qualified signal is generated. In the actual machining production process, after the compensation effect is evaluated, the generated compensation early warning signal or compensation qualified signal is sent to a machine tool machining management end, and when the machine tool machining management end receives the compensation early warning signal, corresponding early warning is sent out so as to remind operators to conduct reason investigation and analysis and make corresponding improvement measures, and therefore error compensation efficiency is guaranteed so as to improve curved surface machining quality.
Example 4:
On the basis of example 1 above, this example 4 further provides a further optimized and complementary implementation of the above method for step SS 7. Specifically, step SS7 in the embodiment of the present invention specifically includes:
Setting a monitoring period with a duration of L1 (L1 can be twenty days preferably), collecting multidimensional data at least comprising compensation early warning signal generation times, quality detection data of processed parts and processing efficiency in the monitoring period, obtaining a compensation early warning risk value, a curved surface processing abnormal quality value, a curved surface work efficiency value and a curved surface processing analysis value through numerical calculation, analyzing the processing performance of complex curved surface geometric processing in the monitoring period, generating a curved surface processing qualified signal or a curved surface processing abnormal signal through analysis, subsequently sending the curved surface processing qualified signal or the curved surface processing abnormal signal to a machine tool processing management end, and sending corresponding early warning when the machine tool processing management end receives the curved surface processing abnormal signal so as to remind operators to adjust a subsequent processing management scheme, timely strengthen subsequent processing supervision, ensure the curved surface processing effect and processing efficiency of the parts and reduce processing cost.
More specifically, as shown in fig. 2, the analysis process of the geometric processing performance of the complex curved surface is as follows:
Acquiring the generation times of compensation early warning signals in a monitoring period, calculating the ratio of the generation times to the total curved surface machining time length of the monitoring period to obtain compensation early warning risk values, acquiring quality detection information of parts machined in the monitoring period (namely, judging information whether the curved surface machining quality of all the parts meets the requirements) and acquiring the quantity ratio of defective curved surface machining products (namely, the curved surface machining quality of the corresponding parts does not meet the requirements) based on all the quality detection information and marking the quantity ratio as a curved surface machining defective product value;
the number of the parts processed in the monitoring period is collected, the ratio of the number of the parts processed in the monitoring period to the total length of the curved surface processing is calculated to obtain the work efficiency value of the curved surface, by the formula: carrying out numerical calculation on the curved surface machining abnormal value WP and the curved surface work efficiency value WL to obtain a curved surface machining analysis value WX, wherein sw1、sw2 is a preset proportionality coefficient, sw2＞sw1 is more than 0, and the larger the numerical value of the curved surface machining analysis value WX is, the worse the curved surface machining effect and the efficiency of the part are comprehensively;
And respectively carrying out numerical comparison on the compensation early warning risk value and the curved surface machining analysis value WX and a preset compensation early warning risk threshold value and a preset curved surface machining analysis threshold value, and if the compensation early warning risk value or the curved surface machining analysis value WX exceeds the corresponding preset threshold value, indicating that the curved surface machining performance of the part is poor in the monitoring period, generating a curved surface machining abnormal signal.
Further, if the compensation early warning risk value and the curved surface machining analysis value WX do not exceed the corresponding preset threshold values, all the rejected tools in the monitoring period are obtained, the machining time of the corresponding tools before rejection is collected and marked as a pre-damage working time value, the pre-damage working time value is compared with the preset pre-damage working time threshold value in numerical value, if the pre-damage working time value does not exceed the preset pre-damage working time threshold value, the corresponding tools are marked as abnormal damage objects, the number of the corresponding abnormal damage objects in the monitoring period is obtained and marked as abnormal damage detection values, and the average value calculation is carried out on the pre-damage working time values of all the rejected tools in the monitoring period to obtain the tool damage detection values, wherein the tool damage detection values are obtained through the formula:
The method comprises the steps of carrying out numerical calculation on a compensation early warning risk value QL, a curved surface machining analysis value WX, an abnormal damage detection value QS and a cutter damage detection value QW to obtain a curved surface machining table evaluation value QX, wherein hy1、hy2、hy3、hy4 is a preset proportionality coefficient with a value larger than zero, the larger the numerical value of the curved surface machining table evaluation value QX is, the worse the operation performance synthesis of curved surface machining in a monitoring period is indicated, comparing the curved surface machining table evaluation value QX with a preset curved surface machining table evaluation threshold value, generating a curved surface machining abnormal signal if the curved surface machining table evaluation value QX exceeds the preset curved surface machining table evaluation threshold value, and generating a curved surface machining qualified signal if the curved surface machining table evaluation value QX does not exceed the preset curved surface machining table evaluation threshold value, and indicates that the curved surface machining operation performance synthesis in the monitoring period is good.
Example 5:
On the basis of the above example 1, this example 5 further provides a further optimized and complementary implementation of the above method for step SS 8. And step SS8, when the tool state detection and life assessment are carried out, and when the machining is finished or the geometric machining of the curved surface is stopped, detecting and analyzing surface cracks, abrasion loss and high-risk areas of the tool to assess the life condition of the tool, judging whether to generate a tool life end signal according to the life condition, and sending the tool life end signal to a machining management end. And when the processing management end receives the cutter life end signal, corresponding early warning is sent out, the corresponding cutter is scrapped in time, the processing accident is avoided, the curved surface processing quality and the processing stability are guaranteed, the management difficulty is reduced, and the intelligentized and automatic level is improved.
In a further preferred example, as shown in fig. 3, the generation of the tool life end signal is as follows:
Acquiring a surface image of a cutter in the processing process, identifying surface cracks and unfilled corners of the cutter based on the surface image, marking the identified surface cracks and unfilled corners as target objects, marking the corresponding target objects as high damage objects if the corresponding target objects have dimension data which do not meet the requirements (namely the corresponding surface cracks or unfilled corners are serious), generating cutter life end signals if the cutter has high damage objects, indicating that the corresponding cutter is not suitable for continuous processing, acquiring wear amounts of a plurality of positions on the cutter if the cutter does not have the high damage objects, carrying out average calculation on the wear amounts of all the positions to obtain wear representation values, and marking the wear amount with the largest numerical value on the cutter as the wear width representation value;
The method comprises the steps of dividing a cutter into a plurality of grids, marking the corresponding grids as red grids if surface cracks or unfilled corners relate to the corresponding grids, obtaining the number of the red grids on the cutter, and calculating the ratio of the number of the red grids to the total number of the grids to obtain a red grid detection value;
By the formulaCarrying out numerical calculation on the wear representation value PN, the wear amplitude value YF, the red lattice detection value HM and the red lattice aggregation value HF to obtain a cutter life evaluation value LW, wherein rq1、rq2、rq3、rq4 is a preset proportionality coefficient with a value larger than zero, and the larger the value of the cutter life evaluation value LW is, the worse the current condition of the cutter is, the more unsuitable the cutter is for continuous processing;
And comparing the tool life evaluation value LW with a preset tool life evaluation threshold value, and generating a tool life end signal if the tool life evaluation value LW exceeds the preset tool life evaluation threshold value, which indicates that the current condition of the tool is poor and the tool is not suitable for continuous processing.
The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.