Efficient plane machining method for cylinder cover machining

Abstract

The invention relates to the technical field of grinding adjustment, in particular to an efficient plane machining method for cylinder cover machining, which comprises the following steps: acquiring the cutting temperature and the cutting force of a cutter in each cylinder cover plane machining process, and the cutting depth, the cutting speed and the machining duration set in each cylinder cover plane machining process, and screening the efficient machining duration, according to the cutting speed range and the corresponding cutting depth range corresponding to all the efficient machining durations and the difference between the maximum value in the cutting depths corresponding to all the efficient machining durations and the maximum value of the cutting depth sequence, a cutting speed up-regulation index is constructed in combination with the data comparison condition of the cutting speed and the cutting depth, and the cutting speed up-regulation index is calculated; and constructing a cutting mutation index and a cutter wear confidence coefficient according to a constraint cutting speed, so as to set food and natural enemy positions of a dragonfly optimization algorithm and obtain an optimal cutting speed. The plane machining efficiency of the cylinder cover can be improved, and the precision of machining adjustment is guaranteed.

Description

Technical Field

[0001] The present application relates to the field of grinding adjustment technology, and in particular to a high-efficiency plane processing method for cylinder head machining. Background Art

[0002] The engine is the power core of the car and drives the vehicle to run normally. The cylinder head is one of the key components of the engine. It is mainly responsible for closing the cylinder and forming a combustion chamber together with the cylinder body. Due to the complex structure of the cylinder head, the processing process involves multiple links, and its plane processing efficiency is particularly critical in production. In the current processing technology, the plane processing efficiency is mainly affected by factors such as the processing performance of the machining center (also known as CNC machine tools), tool design, and processing parameters. Efficient plane processing efficiency can not only increase production speed, but also reduce manufacturing costs. Therefore, improving the efficiency of cylinder head plane processing is very important for the entire production process.

[0003] At present, the machining efficiency is usually improved by adjusting the cutting speed. However, since excessively increasing the cutting speed will lead to increased vibration during the machining process, affecting the surface quality of the workpiece and the tool life, the existing technology usually uses the exhaustive method to conduct feedback experiments. However, when conducting feedback experiments, the existing technology does not take into account that the cutting depth needs to be changed according to the current size of the cylinder head, resulting in that at different cutting depths, the adjusted cutting speed not only cannot achieve the highest machining efficiency, but may also cause tool wear, and the adjustment effect is not good. Summary of the invention

[0004] In order to solve the above technical problems, the present application provides an efficient plane processing method for cylinder head machining to solve the existing problems.

[0005] An efficient plane processing method for cylinder head machining in this application adopts the following technical solution: An embodiment of the present application provides an efficient plane machining method for cylinder head machining, comprising the following steps: The tool cutting temperature sequence and cutting force sequence in each cylinder head plane machining process are obtained. The cutting depth, cutting speed and machining time set in each cylinder head plane machining process constitute a cutting depth sequence, a cutting speed sequence and a machining time sequence respectively. The efficient processing time is screened by clustering the processing time sequence. The cutting speed increase index is constructed based on the cutting speed range and cutting depth range corresponding to all efficient processing times, as well as the difference between the maximum value of the cutting depth corresponding to all efficient processing times and the maximum value of the cutting depth sequence, and the degree of consistency between the cutting speed sequence and the cutting depth sequence. The cutting speed constraint condition is constructed based on the maximum and minimum values ​​of the cutting speed corresponding to all efficient processing times. According to the change of cutting force in each machining cutting force sequence and the mutation degree of each mutation point in the first-order difference sequence of the cutting force sequence, the cutting mutation index of each machining is constructed; based on the change of the cutting temperature sequence corresponding to each machining and combined with the cutting mutation index, the tool wear confidence of each machining is constructed; The tool wear confidence of all processing is threshold segmented, and the optimal processing data and bad data are screened to set the food and natural enemy positions of the dragonfly optimization algorithm. Combined with the cutting speed constraint, the dragonfly optimization algorithm is used to obtain the optimal cutting speed and adjust the cutting speed of the cylinder head plane processing.

[0006] Preferably, the cutting temperature sequence and cutting force sequence corresponding to each processing are respectively composed of the tool cutting temperatures and cutting forces at all collection moments in each processing process arranged in the order of collection moments, and the cutting depth sequence, cutting speed sequence and processing time sequence are respectively composed of the cutting depths, cutting speeds and processing times set in all processing processes arranged in the order of processing time.

[0007] Preferably, the screening of efficient processing time includes: clustering the processing time sequence using a clustering algorithm to obtain multiple cluster clusters, recording the cluster cluster with the smallest average processing time as the efficient cluster cluster, and recording the processing time in the efficient cluster cluster as the efficient processing time.

[0008] Preferably, the expression of the cutting speed increase index is: ;Wherein, A is the cutting speed increase index; is the maximum value in the cutting depth sequence; QX is the maximum value in the cutting depth data corresponding to all efficient processing time; B is the speed adjustment coefficient, which is determined by the degree of consistency between the cutting speed and cutting depth corresponding to the efficient processing time; C is the unit speed change index of the cutting speed, which is the average value of the ratio of all elements in the same position in the cutting speed sequence and the cutting depth sequence.

[0009] Preferably, the speed adjustment coefficient is further a ratio of the range between the cutting speeds corresponding to all the efficient machining times to the range between the cutting depths corresponding to all the efficient machining times.

[0010] Preferably, the cutting speed constraint condition is specifically: ; In the formula, are the minimum and maximum values ​​of the cutting speed data corresponding to all efficient processing times; SD is the cutting speed during plane processing; A is the cutting speed increase index.

[0011] Preferably, the expression of the cutting mutation index of each processing is: ; In the formula, is the cutting mutation index of the u-th processing; is the normal coefficient of change of the cutting force of the u-th machining process, specifically, the ratio of the absolute value of the cumulative sum of all negative numbers to the cumulative sum of all positive numbers in the first-order difference sequence of the cutting force sequence of the u-th machining process; is the sudden fluctuation coefficient of the cutting force for the u-th machining process, specifically: the average of the absolute values ​​of the differences between each mutation point and its adjacent elements in the first-order difference sequence of the cutting force sequence for the u-th machining process is taken as the sudden fluctuation coefficient of the cutting force for the u-th machining process; the product of the average value and the variance of the sudden fluctuation coefficient of the cutting force for the u-th machining process is taken as the sudden fluctuation coefficient of the cutting force for the u-th machining process; is the variance of the cutting force series; is the number of mutation points in the first-order difference sequence of the cutting force sequence of the u-th machining.

[0012] Preferably, the expression of the tool wear confidence of each processing is: ; In the formula, is the tool wear confidence of the u-th processing; is the cutting mutation index of the u-th processing; is the temperature rise difference coefficient of the u-th processing, specifically: the cutting temperature sequence of the u-th processing is divided into each temperature subsequence, each temperature subsequence is fitted with a straight line, and the difference between the maximum fitting straight line slope and the slopes of all other fitting straight lines is calculated and averaged, and then the product of the maximum fitting straight line slope is taken as the temperature rise difference coefficient of the u-th processing.

[0013] Preferably, the screening of optimal processing data and bad data includes: All tool wear confidences are threshold segmented to obtain the wear threshold. The processing data corresponding to all tool wear confidences greater than or equal to the wear threshold are recorded as bad data, and the remaining processing data are recorded as good data. The processing data that is both good data and belongs to an efficient clustering cluster is recorded as the optimal processing data. The processing data includes the cutting force sequence, cutting temperature sequence, cutting speed data, cutting depth data, and processing time in each processing process.

[0014] Preferably, the food and natural enemy positions of the dragonfly optimization algorithm are respectively the optimal processing data and the bad data; wherein the objective function expression of the dragonfly optimization algorithm is: ; In the formula, Y is the objective function value; is the minimum value function; SC is the processing time; is the tool wear confidence of the u-th processing.

[0015] This application has at least the following beneficial effects: This application can fully consider the difference in cutting depth between high-efficiency and low-efficiency processing by constructing a cutting speed increase index, and dynamically adjust the maximum upper limit of the cutting speed based on this. At the same time, considering that excessively high cutting speeds can improve processing efficiency but may cause tool damage, a cutting mutation index is constructed to analyze the cutting force change characteristics under the current cutting speed and preliminarily evaluate the tool wear state. Then, combined with the temperature characteristics, the tool wear confidence is further constructed to achieve a comprehensive assessment of the tool state.

[0016] The beneficial effect is that: the present application takes into account the problem that the existing cutting speed adjustment method does not take into account the cutting depth, resulting in poor machining efficiency and possible tool wear; the present application constructs a speed increase index and a tool wear confidence level to obtain the maximum cutting speed without causing tool wear, thereby significantly improving the plane machining efficiency of the cylinder head. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 A flowchart of the steps of an efficient plane machining method for cylinder head machining provided in this application. DETAILED DESCRIPTION

[0019] In order to further explain the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation method, structure, features and effects of a high-efficiency plane machining method for cylinder head machining proposed in accordance with the present application in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0020] Unless otherwise defined, terms such as "comprises", "comprising" or any other variants thereof are intended to cover non-exclusive inclusion, so that a circuit structure, article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such articles or devices. In the absence of further restrictions, an element defined by the statement "comprising a ..." does not exclude the presence of other identical elements in the article or device comprising the element. In addition, the term "and\or" used herein includes any and all combinations of one or more related listed items. All technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which the present application belongs.

[0021] The specific scheme of an efficient plane processing method for cylinder head machining provided by the present application is described in detail below with reference to the accompanying drawings.

[0022] An embodiment of the present application provides an efficient plane processing method for cylinder head machining. For details, please refer to Figure 1 , including the following steps: Step 1: Obtain the tool cutting temperature sequence and cutting force sequence in each cylinder head plane machining process. The cutting depth, cutting speed and machining time set in each cylinder head plane machining process constitute the cutting depth sequence, cutting speed sequence and machining time sequence respectively.

[0023] In this embodiment, a four-axis machining center is used to perform plane machining on the bottom surface of the cylinder head after rough machining, the cylinder head is clamped in a manner of four-point symmetrical and evenly distributed, the tool rake angle is set to 5°, and the machine tool speed is set to 2000r / min.

[0024] The central control system of the machining center obtains the tool cutting temperature in real time during each cylinder head bottom surface machining, and the cutting force data of the tool during the bottom surface machining process is collected through the cutting force measuring instrument. All data are collected synchronously and in real time, with a data collection frequency of 100HZ. The data collection time is from the beginning to the end of the machining of the cylinder head bottom surface. The cutting temperature and cutting force of the tool at each collection time are obtained, and the cutting temperature sequence and cutting force sequence of each cylinder head bottom surface machining are constructed according to the order of the collection time.

[0025] At the same time, the cutting depth, cutting speed and processing time set in each plane processing process of the bottom surface of the cylinder head are obtained. The cutting speed data, cutting depth data, cutting force sequence, cutting temperature sequence and processing time in each cylinder head bottom surface processing process are recorded as one plane processing data.

[0026] In order to analyze the plane machining of the cylinder head, the plane machining data of the bottom surface of the cylinder head M times are obtained from the historical database of the four-axis machining center. In this embodiment, M is set to 200, and the cutting speed sequence, cutting depth sequence, and machining time sequence are constructed according to the time sequence of the plane machining. In order to eliminate the dimensional influence between the data, all the data are normalized to the maximum and minimum values.

[0027] Step 2: Cluster the processing time sequence to select the efficient processing time. According to the cutting speed range and cutting depth range corresponding to all efficient processing times, as well as the difference between the maximum value of the cutting depth corresponding to all efficient processing times and the maximum value of the cutting depth sequence, and combined with the consistency of the changes in the cutting speed sequence and the cutting depth sequence, construct the cutting speed increase index. Combined with the maximum and minimum values ​​of the cutting speed corresponding to all efficient processing times, construct the cutting speed constraint condition.

[0028] After the initial rough machining, only the burrs, protrusions and other excess materials are removed from each surface of the cylinder head. However, the surface of the cylinder head is not smooth enough and the size of the cylinder head does not meet the production requirements. Therefore, further cutting operations are required to improve the flatness of the cylinder head plane and adjust the size of the cylinder head.

[0029] However, because there will be certain size differences between the cylinder heads after rough machining, the cutting depth of the bottom surface of the cylinder head will also be different in the historical database. At the same time, changes in cutting speed and cutting depth will also cause changes in cutting force during plane machining. Excessive cutting force will not only lead to poor stability between the machining center and the cylinder head, but also cause serious wear of the cutting tool, resulting in deformation of the cylinder head or reduced surface quality, resulting in changes in flatness after machining. Therefore, first of all, the clustering algorithm can be used to select the data with the shortest machining time, so as to analyze the degree of change in cutting speed and cutting depth under the condition of the highest machining efficiency; then further evaluate the impact of cutting speed on tool wear.

[0030] The processing time sequence is used as the input of the DPC density clustering algorithm, and the cross-validation method is used to obtain the truncation distance of the DPC clustering algorithm. The output of the DPC clustering algorithm is multiple clusters, and the cluster with the smallest mean among the clusters is recorded as the efficient cluster.

[0031] Furthermore, in this embodiment, the processing time in the efficient cluster is recorded as the efficient processing time, and the range between the cutting depths corresponding to all the efficient processing times is recorded as the maximum depth difference; the range between the cutting speeds corresponding to all the efficient processing times is recorded as the maximum speed difference. The ratio of the maximum speed difference to the maximum depth difference is recorded as the speed adjustment coefficient. The larger the speed adjustment coefficient, the greater the change in cutting speed needs to be in order to achieve the ideal processing efficiency as the cutting depth changes.

[0032] Furthermore, the influence between cutting speed and cutting depth is quantified. Specifically, the average value of the ratio of all elements at the same position in the cutting speed sequence to the cutting depth sequence is calculated and recorded as the unit speed change index of the cutting speed. The unit speed change index reflects the proportional relationship between the cutting speed and the cutting depth.

[0033] Furthermore, the cutting speed increase index is determined by combining the speed adjustment coefficient and the unit speed change index of the cutting speed, and the difference between the maximum value in the cutting depth sequence and the maximum value in the cutting depth data corresponding to all efficient processing times. The specific expression in this embodiment is: . Where A is the cutting speed increase index; is the maximum value in the cutting depth sequence; QX is the maximum value of the cutting depth data corresponding to all efficient processing times; B is the speed adjustment coefficient; C is the unit speed change index of the cutting speed.

[0034] In the above formula, It reflects the difference between the maximum cutting depth in the historical processing data and the maximum cutting depth when the processing efficiency is high. The larger the difference, the greater the range of cutting speed adjustment. The speed adjustment coefficient B reflects the degree to which the cutting speed needs to be adjusted when the cutting depth changes. The unit speed change index C reflects the degree of change in cutting speed when the cutting depth changes by unit. The cutting speed increase index A reflects the range in which the cutting speed can still be increased compared with the processing data with high processing efficiency.

[0035] According to the cutting speed corresponding to the efficient processing time, combined with the cutting speed increase index, the cutting speed constraint condition is constructed. The specific cutting speed constraint expression is: In the formula, are the minimum and maximum values ​​of the cutting speed data corresponding to all efficient processing times; SD is the cutting speed during plane processing; A is the cutting speed increase index.

[0036] Step 3: According to the change of cutting force in the cutting force sequence of each processing and the mutation degree of each mutation point in the first-order difference sequence of the cutting force sequence, the cutting mutation index of each processing is constructed; based on the change of the cutting temperature sequence corresponding to each processing and combined with the cutting mutation index, the tool wear confidence of each processing is constructed.

[0037] Furthermore, when the cutting speed is faster, the cutting efficiency is higher and the processing time is shorter. However, if the cutting speed is simply increased, the cylinder head may become unstable during plane processing and the tool may be severely worn, thus affecting the surface quality and processing efficiency of the cylinder head.

[0038] If the cutting speed is set reasonably, the cutting force will remain stable during plane machining. As the cutting time increases, the temperature of the cylinder head cutting tool rises, softening the cut part of the cylinder head, and the cutting force will slowly decrease. If the cutting speed is set unreasonably, the cutting speed is too fast, causing the tool to wear significantly during the cutting process, which will cause the cutting force to increase instantaneously and cause the cutting force to fluctuate violently.

[0039] In this embodiment, the cutting force sequence corresponding to the u-th processing is taken as an example for analysis, the data change of the cutting force sequence and the mutation of the first-order difference sequence of the cutting force sequence are analyzed, and the cutting mutation index is constructed. The specific process is as follows: In this embodiment, for the convenience of description and understanding, the first-order difference sequence of the cutting force sequence of the uth processing is recorded as the cutting force change sequence, and the absolute value h1 of the cumulative sum of all negative numbers and the cumulative sum h2 of all positive numbers in the cutting force change sequence are calculated respectively, and the ratio of h1 to h2 is recorded as the normal coefficient of the change of the cutting force of the uth processing. If the normal coefficient of change is smaller, it means that in the cutting force change sequence, the cumulative sum of negative elements is smaller than the cumulative sum of positive elements, and it is less consistent with the overall slow decrease of the cutting force sequence.

[0040] Furthermore, if tool wear occurs, the cutting force will increase instantaneously, and the cutting force data after the instantaneous increase will fluctuate greatly. Therefore, the cutting force change sequence is used as the input of the PELT mutation point algorithm to obtain all the mutation points in the cutting force change sequence. PELT mutation point detection is a well-known technology and will not be described here.

[0041] Taking each mutation point as the center, the average value of the absolute value of the difference between each mutation point and its previous element and the next element is calculated, which is recorded as the mutation mean of each mutation point. Furthermore, the product of the average value and variance of the mutation means of all mutation points is recorded as the mutation fluctuation coefficient of the cutting force for the uth machining. The larger the mutation fluctuation coefficient, the greater the instantaneous mutation degree at each mutation point, and the greater the difference in the instantaneous mutation degree between each mutation point.

[0042] Further, according to the normal coefficient of change and the sudden change fluctuation coefficient, as well as the fluctuation degree of the cutting force sequence, the cutting sudden change index of each processing is calculated. In this embodiment, the specific expression is: In the formula, is the cutting mutation index of the u-th processing; is the normal coefficient of change of cutting force in the uth processing; is the sudden fluctuation coefficient of cutting force in the u-th processing; is the variance of the cutting force series; is the number of mutation points in the first-order difference sequence of the cutting force sequence of the u-th machining; Among them, the smaller the normal coefficient of change is, the more it reflects that in the u-th processing cutting force sequence, the change trend of the cutting force does not conform to the characteristics of overall slow decrease, that is, the greater the possibility of abnormal increase in cutting force; the larger the mutation fluctuation coefficient is, the greater the difference in the instantaneous mutation degree at each mutation point and the overall mutation difference are, and the greater the possibility of tool wear; the larger the variance of the cutting force sequence is, the greater the degree of fluctuation of the cutting force sequence is; at the same time, the more mutation points are detected in the cutting force change sequence, the larger the cutting mutation index in the processing process, and the higher the possibility of tool wear in the corresponding plane processing process.

[0043] Furthermore, before wear occurs, the cutting temperature increases gradually and slowly as the tool is in the cutting process; however, if wear occurs, more heat is generated, causing the tool temperature to rise suddenly, and the temperature rises very quickly, much faster than the normal temperature rise rate. At the same time, the worn tool is not stable during the cutting process, which will also cause large temperature fluctuations.

[0044] Therefore, in this embodiment, the cutting temperature sequence of the u-th processing is used as the input of the BG sequence segmentation algorithm, and the output of the BG sequence segmentation algorithm is a plurality of temperature subsequences. All temperature subsequences are respectively used as the input of the least squares method for straight line fitting, and the output of the least squares method corresponds to the fitting straight line. Further, the difference between the maximum fitting straight line slope and the slopes of all other fitting straight lines is calculated and averaged, and then multiplied by the product of the maximum fitting straight line slope as the temperature rise difference coefficient of the u-th processing. The BG sequence segmentation algorithm and the least squares method are well-known technologies and will not be described here.

[0045] It can be understood that the larger the temperature rise difference coefficient is, the faster the temperature rise rate of the temperature subsequence corresponding to the maximum fitting straight line slope is compared with the temperature rise rates of other temperature subsequences.

[0046] make ; In the formula, is the tool wear confidence of the u-th processing; is the cutting mutation index of the u-th processing; is the temperature rise difference coefficient of the u-th processing.

[0047] If the cutting mutation index is larger, it means that the possibility of abnormal mutation of cutting force is greater during the u-th plane processing; if the temperature rise difference coefficient is larger, it means that the possibility of abnormal increase of temperature data is greater during the u-th plane processing, and the corresponding tool wear confidence is larger, then the possibility of tool wear is greater during the u-th plane processing.

[0048] Step 4: Perform threshold segmentation on the tool wear confidence of all processing, screen the optimal processing data and bad data, set the food and natural enemy positions of the dragonfly optimization algorithm, combine the cutting speed constraints, use the dragonfly optimization algorithm to obtain the optimal cutting speed, and adjust the cutting speed of the cylinder head plane processing.

[0049] Further, according to the above process of this embodiment, the tool wear confidence of each processing is obtained, and all tool wear confidences are used as inputs of the Otsu threshold method. The output of the Otsu threshold method is the wear threshold. The processing data corresponding to all tool wear confidences greater than or equal to the wear threshold are recorded as bad data, and the remaining processing data are recorded as good data. Further, the processing data that is both good data and belongs to an efficient cluster is recorded as the optimal processing data.

[0050] In order to find the optimal cutting speed, this application uses the dragonfly optimization algorithm to find the optimal solution. Since the initial distribution position of dragonflies in the dragonfly algorithm directly affects the convergence speed and calculation accuracy of the algorithm, a good initial distribution can accelerate the finding of the global optimal solution. Therefore, in this embodiment, the optimal processing data is used as the food position (local optimal solution) in the dragonfly optimization algorithm, and the bad data is used as the natural enemy position (local worst solution). The number of dragonflies is the processing times M obtained from the historical database, and the value in this embodiment is 200. After placing dragonflies at the food position, the remaining dragonflies are randomly distributed, but they cannot be placed at the natural enemy position.

[0051] Construct the objective function: . In the formula, Y is the objective function value; is the minimum value function; SC is the processing time; is the confidence of tool wear for the uth processing. The relevant parameters of the dragonfly optimization algorithm are set as follows: separation weight is 0.1, alignment weight is 0.1, aggregation weight is 0.7, food factor is 1, natural enemy weight is 1, inertia weight is initially 0.9, and linearly decreases to 0.4 with the number of iterations, and the number of iterations is 50. The number of dragonflies, initial position, weights of various parameters, objective function, and set cutting depth are used as inputs of the dragonfly algorithm. The output of the dragonfly algorithm is the cutting speed that minimizes the objective function value. At this point, under the premise of not causing tool wear, the optimal cutting speed is output, so that the processing time of the cylinder head plane processing is the shortest.

[0052] At this point, the cylinder head plane machining process is adjusted according to the above process of this embodiment, which can improve the cylinder head plane machining efficiency.

[0053] It is understood that references to "one embodiment" or "some embodiments" etc. described in the specification of the present application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, if "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. appear in different places in this specification, they do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0054] It should be noted that the sequence of the above-mentioned embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. In addition, the process depicted in the accompanying drawings does not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-tasking and parallel processing are also possible or may be advantageous. At the same time, the size of the sequence number of each step in the embodiment does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments in this specification.

[0055] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. An efficient plane processing method for cylinder head machining, characterized in that: The following steps are involved: The tool cutting temperature sequence and cutting force sequence in each cylinder head plane machining process are obtained. The cutting depth, cutting speed and machining time set in each cylinder head plane machining process constitute a cutting depth sequence, a cutting speed sequence and a machining time sequence respectively. The efficient processing time is screened by clustering the processing time sequence. The cutting speed increase index is constructed based on the cutting speed range and cutting depth range corresponding to all efficient processing times, as well as the difference between the maximum value of the cutting depth corresponding to all efficient processing times and the maximum value of the cutting depth sequence, and the degree of consistency between the cutting speed sequence and the cutting depth sequence. The cutting speed constraint condition is constructed based on the maximum and minimum values ​​of the cutting speed corresponding to all efficient processing times. According to the change of cutting force in each machining cutting force sequence and the mutation degree of each mutation point in the first-order difference sequence of the cutting force sequence, the cutting mutation index of each machining is constructed; based on the change of the cutting temperature sequence corresponding to each machining and combined with the cutting mutation index, the tool wear confidence of each machining is constructed; The tool wear confidence of all processing is threshold segmented, and the optimal processing data and bad data are screened to set the food and natural enemy positions of the dragonfly optimization algorithm. Combined with the cutting speed constraint, the dragonfly optimization algorithm is used to obtain the optimal cutting speed and adjust the cutting speed of the cylinder head plane processing.

2. The high-efficiency plane machining method for cylinder head machining according to claim 1, characterized in that: The cutting temperature sequence and cutting force sequence corresponding to each processing are respectively composed of the tool cutting temperature and cutting force at all acquisition moments in each processing process arranged in the order of acquisition moments. The cutting depth sequence, cutting speed sequence and processing time sequence are respectively composed of the cutting depth, cutting speed and processing time set in all processing processes arranged in the order of processing time.

3. The high-efficiency plane machining method for cylinder head machining according to claim 1, characterized in that: The screening of efficient processing time includes: clustering the processing time sequence using a clustering algorithm to obtain multiple clusters, recording the cluster with the smallest average processing time as the efficient cluster, and recording the processing time in the efficient cluster as the efficient processing time.

4. The high-efficiency plane machining method for cylinder head machining according to claim 1, characterized in that: The expression of the cutting speed increase index is: ; Where A is the cutting speed increase index; is the maximum value in the cutting depth sequence; QX is the maximum value in the cutting depth data corresponding to all efficient processing time; B is the speed adjustment coefficient, which is determined by the degree of consistency between the cutting speed and cutting depth corresponding to the efficient processing time; C is the unit speed change index of the cutting speed, which is the average value of the ratio of all elements in the same position in the cutting speed sequence and the cutting depth sequence.

5. A high-efficiency plane machining method for cylinder head machining as claimed in claim 4, characterized in that: The speed adjustment coefficient is further a ratio of the range of cutting speeds corresponding to all efficient machining time periods to the range of cutting depths corresponding to all efficient machining time periods.

6. The high-efficiency plane machining method for cylinder head machining according to claim 1, characterized in that: The cutting speed constraint conditions are specifically: ; In the formula, are the minimum and maximum values ​​of the cutting speed data corresponding to all efficient processing times; SD is the cutting speed during plane processing; A is the cutting speed increase index.

7. The high-efficiency plane machining method for cylinder head machining according to claim 1, characterized in that: The expression of the cutting mutation index of each processing is: ; In the formula, is the cutting mutation index of the u-th processing; is the normal coefficient of change of the cutting force of the u-th machining process, specifically, the ratio of the absolute value of the cumulative sum of all negative numbers to the cumulative sum of all positive numbers in the first-order difference sequence of the cutting force sequence of the u-th machining process; is the sudden fluctuation coefficient of the cutting force for the u-th machining process, specifically: the average of the absolute values ​​of the differences between each mutation point and its adjacent elements in the first-order difference sequence of the cutting force sequence for the u-th machining process is taken as the sudden fluctuation coefficient of the cutting force for the u-th machining process; the product of the average value and the variance of the sudden fluctuation coefficient of the cutting force for the u-th machining process is taken as the sudden fluctuation coefficient of the cutting force for the u-th machining process; is the variance of the cutting force series; is the number of mutation points in the first-order difference sequence of the cutting force sequence of the u-th machining.

8. The high-efficiency plane machining method for cylinder head machining according to claim 1, characterized in that: The expression of tool wear confidence for each machining is: ; In the formula, is the tool wear confidence of the u-th processing; is the cutting mutation index of the u-th processing; is the temperature rise difference coefficient of the u-th processing, specifically: the cutting temperature sequence of the u-th processing is divided into each temperature subsequence, each temperature subsequence is fitted with a straight line, and the difference between the maximum fitting straight line slope and the slopes of all other fitting straight lines is calculated and the average is taken, and then the product of the maximum fitting straight line slope is taken as the temperature rise difference coefficient of the u-th processing.

9. The high-efficiency plane machining method for cylinder head machining as claimed in claim 3, characterized in that: The screening of optimal processing data and bad data includes: All tool wear confidences are threshold segmented to obtain the wear threshold. The processing data corresponding to all tool wear confidences greater than or equal to the wear threshold are recorded as bad data, and the remaining processing data are recorded as good data. The processing data that is both good data and belongs to an efficient clustering cluster is recorded as the optimal processing data. The processing data includes the cutting force sequence, cutting temperature sequence, cutting speed data, cutting depth data, and processing time in each processing process.

10. The high-efficiency plane machining method for cylinder head machining according to claim 1, characterized in that: The food and natural enemy positions of the dragonfly optimization algorithm are the optimal processing data and the bad data respectively; wherein the objective function expression of the dragonfly optimization algorithm is: ; In the formula, Y is the objective function value; is the minimum value function; SC is the processing time; is the tool wear confidence of the u-th processing.

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