Fractal feature recognition method for complexity of instantaneous energy consumption distribution of square shoulder milling cutter teeth

Abstract

The present invention proposes a fractal feature recognition method for the complexity of instantaneous energy consumption distribution of square shoulder milling cutter teeth, which belongs to the technical field of energy consumption distribution difference of cutter teeth. It includes: S1. A method for solving the fractal dimension of the instantaneous energy consumption distribution of the primary and secondary cutting edges, treating the instantaneous energy consumption distribution curve of the milling cutter teeth as a spatial sequence, solving the instantaneous energy consumption distribution curve, and obtaining the fractal dimension of the instantaneous energy consumption distribution curve of the primary and secondary cutting edges; S2. According to the fractal dimension of the instantaneous energy consumption distribution curve of the primary and secondary cutting edges, identify the overall level and variation range of the fractal dimension of the instantaneous energy consumption distribution of the primary and secondary cutting edges; S3. Identify the fluctuation degree and increase and decrease characteristics of the fractal dimension of the instantaneous energy consumption distribution; S4. Identify the degree of deviation of the fractal dimension of the instantaneous energy consumption distribution along the cutting time period direction; S5. Identify the difference in instantaneous energy consumption distribution between different teeth. Solve the problem that the complexity and uncertainty of the instantaneous energy consumption distribution cannot be quantitatively described and compared.

Description

Technical Field

[0001] The present application relates to a fractal feature recognition method, and in particular to a fractal feature recognition method of the complexity of instantaneous energy consumption distribution of square shoulder milling cutter teeth, belonging to the technical field of tooth energy consumption distribution differences. Background Art

[0002] In the process of intermittent cutting, the square shoulder milling cutter is affected by milling vibration and tooth wear. The instantaneous cutting boundaries of the main and auxiliary cutting edges change constantly, and the instantaneous cutting layer parameters of the milling microelement also change continuously, resulting in the complexity of the distribution of instantaneous energy consumption on the milling cutter cutting edge, which directly affects the milling performance and surface quality of the milling cutter. Proposing a correct identification method for the complexity of the instantaneous energy consumption distribution of the square shoulder milling cutter and revealing the complexity of the instantaneous energy consumption distribution of the milling cutter are of great significance to reducing energy consumption and improving the surface quality of the machining.

[0003] There are existing methods for identifying the complexity of the instantaneous energy consumption distribution of milling cutter teeth, which directly solve the instantaneous energy consumption and its distribution function, and compare and analyze the complexity of energy consumption distribution through the distribution function of instantaneous energy consumption at different times. The above method cannot directly and quantitatively analyze the complexity of the instantaneous energy consumption distribution of a certain tooth, nor can it clearly reveal the differences in the instantaneous energy consumption distribution of different teeth in the same cycle and the same tooth in different cycles. Summary of the invention

[0004] A brief overview of the present invention is provided below in order to provide a basic understanding of certain aspects of the present invention. It should be understood that this overview is not an exhaustive overview of the present invention. It is not intended to identify key or important parts of the present invention, nor is it intended to limit the scope of the present invention. Its purpose is merely to present certain concepts in a simplified form as a prelude to a more detailed description discussed later.

[0005] In view of this, in order to solve the technical problem that the complexity and uncertainty of instantaneous energy consumption distribution cannot be quantitatively described and compared in the prior art, the present invention provides a fractal feature recognition method for the complexity of instantaneous energy consumption distribution of square shoulder milling cutter teeth. The present invention utilizes the maximum, minimum and difference of the fractal dimension of the instantaneous energy consumption distribution, combined with the coefficient of variation, first-order difference and skewness of the fractal dimension curve, to reveal the complexity of the instantaneous energy consumption distribution on the teeth; and solves the existing problem that it is impossible to directly quantitatively compare the differences in instantaneous energy consumption distribution between different teeth of the same period and between different periods of the same tooth.

[0006] Solution 1: A fractal feature recognition method for the complexity of instantaneous energy consumption distribution of square shoulder milling cutter teeth, comprising the following steps:

[0007] S1. A method for calculating the fractal dimension of the instantaneous energy consumption distribution of the primary and secondary cutting edges. The instantaneous energy consumption distribution curve of the milling cutter teeth is regarded as a spatial sequence, and the instantaneous energy consumption distribution curve is calculated to obtain the fractal dimension of the instantaneous energy consumption distribution curve of the primary and secondary cutting edges;

[0008] S2. according to the fractal dimension of the instantaneous energy consumption distribution curve of the primary and secondary cutting edges, identifying the overall level and variation range of the fractal dimension of the instantaneous energy consumption distribution of the primary and secondary cutting edges;

[0009] S3. Identify the fluctuation degree and increase / decrease characteristics of the fractal dimension of instantaneous energy consumption distribution;

[0010] S4. Identify the degree of deviation of the fractal dimension of the instantaneous energy consumption distribution along the cutting time period;

[0011] S5. Identify the differences in instantaneous energy consumption distribution between different cutting teeth.

[0012] Preferably, according to the fractal dimension of the instantaneous energy consumption distribution curve of the primary and secondary cutting edges, the method for identifying the overall level and variation range of the fractal dimension of the instantaneous energy consumption distribution of the primary and secondary cutting edges is: taking the maximum value D of the fractal dimension of the tooth in one cycle as max With the minimum value D min The overall level of the fractal dimension of the instantaneous energy consumption distribution is characterized. The difference d between the maximum and minimum values ​​is used to characterize the variation range of the fractal dimension of the instantaneous energy consumption distribution within the period. The larger the difference, the larger the variation range of the fractal dimension of the energy consumption distribution within the period, and vice versa.

[0013] Preferably, the method for identifying the fluctuation degree and increase / decrease characteristics of the fractal dimension of the instantaneous energy consumption distribution is: using the coefficient of variation CV of the fractal dimension within a period to characterize the fluctuation degree of the fractal dimension of the instantaneous energy consumption distribution in the period, the larger the coefficient of variation, the greater the degree of change of the fractal dimension of the periodic energy consumption distribution, and the more unstable the instantaneous energy consumption distribution; using the first-order difference ΔD(t) of the fractal dimension to characterize the increase / decrease characteristics of the fractal dimension of the instantaneous energy consumption distribution within a period, the larger the value of the first-order difference, the more drastic the change of the fractal dimension of the energy consumption distribution between two moments.

[0014] Preferably, the method for identifying the degree of deviation of the fractal dimension of the instantaneous energy consumption distribution along the cutting time period is: using the skewness G of the fractal dimension of the instantaneous energy consumption distribution within a period to characterize the degree of deviation of the fractal dimension along the cutting time period. The larger the absolute value of the skewness, the closer the period of complex and changeable energy consumption distribution is to the cutting-in or cutting-out moment. When the skewness value is positive, the closer the period of complex and changeable energy consumption distribution is to the cutting-in moment, and vice versa, it is close to the cutting-out moment.

[0015] Preferably, the method for identifying the difference in instantaneous energy consumption distribution between different teeth is: the smaller the fractal dimension of the instantaneous energy consumption distribution, the lower the complexity of the distribution, the closer the fractal dimension curve is to a straight line, and the smaller the change in the complexity of the distribution is. In the same period, the tooth with the smallest characteristic parameter value of the fractal curve is used as the benchmark, and ΔD is used to identify the difference in instantaneous energy consumption distribution between different teeth. max With ΔD min Characterizes the overall level difference between different teeth, ΔD max With ΔD min The larger the value is, the more obvious the difference in the overall level of fractal dimension between different teeth is; Δd is used to characterize the difference in the range of fractal dimension variation between different teeth. The larger the Δd is, the more obvious the difference in the range of fractal dimension variation between different teeth is; ΔCV is used to characterize the difference in the degree of fractal dimension fluctuation between different teeth. The larger the ΔCV is, the greater the difference in the degree of fractal dimension fluctuation between different teeth is; taking the tooth with the least number of fractal dimension increases and decreases in the increase and decrease characteristics as the benchmark, ΔB is used to characterize the difference in fractal dimension fluctuation characteristics between different teeth; finally, the skewness of the tooth with the most characteristic parameter benchmark times is selected as the benchmark, and ΔG is used to characterize the difference in fractal dimension skewness between different teeth. The larger the ΔG is, the greater the difference in skewness between different teeth is.

[0016] Solution 2: An electronic device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the fractal feature recognition method of the complexity of the instantaneous energy consumption distribution of the teeth of a square shoulder milling cutter as described in Solution 1 are implemented.

[0017] Solution three: A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the fractal feature recognition method for the complexity of instantaneous energy consumption distribution of square shoulder milling cutter teeth as described in Solution one.

[0018] The beneficial effects of the present invention are as follows:

[0019] 1. The present invention constructs a solution model for the fractal dimension of the instantaneous energy consumption distribution of the cutter teeth, solves the fractal dimension of the instantaneous energy consumption distribution of the milling cutter teeth, and reveals the complexity of the instantaneous cutting force energy consumption and the instantaneous shear force energy consumption along the primary and secondary cutting edges, as well as the complexity of the instantaneous cumulative friction energy consumption along the primary and secondary back surfaces of the cutter teeth; it solves the problem that the existing methods cannot directly quantitatively analyze the complexity of the instantaneous energy consumption distribution of the cutter teeth.

[0020] 2. The present invention proposes a method for identifying the complexity of the instantaneous energy consumption distribution of the blade teeth. It uses the maximum, minimum and the difference between the maximum and minimum values ​​of the fractal dimension of the instantaneous energy consumption distribution within a period, combined with the coefficient of variation, first-order difference and skewness of the fractal dimension change curve, to reveal the complexity and uncertainty of the instantaneous energy consumption distribution on the blade teeth; it solves the problem that the existing methods cannot directly and quantitatively compare the differences in the complexity of the instantaneous energy consumption distribution of the same blade teeth between different periods.

[0021] 3. The present invention proposes a method for identifying the difference in complexity of instantaneous energy consumption distribution of different teeth. The tooth with the smallest characteristic parameter value is used as the benchmark, and the deviation value between the characteristic parameters of the remaining teeth and the characteristic parameters of the benchmark teeth is used to identify the difference in energy consumption distribution of different teeth in the same cycle. This method can be used to evaluate the dynamic cutting performance of the milling cutter and provide a basic model for predicting the surface morphology and tooth wear of the machined surface. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0023] Figure 1 The flowchart of the fractal feature recognition method for the complexity of instantaneous energy consumption distribution of square shoulder milling cutter teeth is shown;

[0024] Figure 2 Schematic diagram of the instantaneous cutting force energy consumption solution results of the main and secondary cutting edges of tooth 1 at the 189th cycle with a contact angle of 90°; (a) is the instantaneous cutting force energy consumption distribution of the main cutting edge; (b) is the instantaneous cutting force energy consumption distribution of the secondary cutting edge;

[0025] Figure 3 Schematic diagram of the instantaneous shear energy consumption solution results of the main and secondary cutting edges of tooth 1 at the 189th cycle with a contact angle of 90°; (a) is the instantaneous shear energy consumption distribution of the main cutting edge; (b) is the instantaneous shear energy consumption distribution of the secondary cutting edge;

[0026] Figure 4 Schematic diagram of the instantaneous cumulative friction energy consumption solution results of the primary and secondary flank surfaces of tooth 1 at the 189th cycle with a contact angle of 90°; (a) is the instantaneous cumulative friction energy consumption distribution of the primary flank surface; (b) is the instantaneous cumulative friction energy consumption distribution of the secondary flank surface;

[0027] Figure 5 Schematic diagram of fractal dimension of instantaneous cutting force energy consumption distribution of main cutting edge;

[0028] Figure 6 The fractal dimension diagram of the instantaneous cutting force energy consumption distribution of the secondary cutting edge;

[0029] Figure 7 Schematic diagram of fractal dimension of instantaneous shear force energy consumption distribution of main cutting edge;

[0030] Figure 8 The fractal dimension diagram of the instantaneous shear force energy consumption distribution of the secondary cutting edge;

[0031] Fig. 9 Schematic diagram of the fractal dimension of the instantaneous cumulative friction energy consumption distribution of the main flank;

[0032] Fig.10 Schematic diagram of the fractal dimension of the instantaneous cumulative friction energy consumption distribution of the secondary flank. DETAILED DESCRIPTION

[0033] In order to make the technical solutions and advantages in the embodiments of the present application more clearly understood, the exemplary embodiments of the present application are further described in detail below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than an exhaustive list of all the embodiments. It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict.

[0034] Example 1, reference Figure 1-Figure 10 This embodiment describes the fractal feature recognition method for the complexity of instantaneous energy consumption distribution of square shoulder milling cutter teeth. Based on the curve of instantaneous energy consumption distribution of milling cutter teeth, the fractal dimension of the instantaneous energy consumption distribution curve of the cutter teeth is solved to characterize the complexity of the distribution. The maximum and minimum values ​​of the fractal dimension of the energy consumption distribution curve of the cutter teeth in one cycle are used to identify the overall level of the fractal dimension of the instantaneous energy consumption distribution of the cutter teeth; the difference between the maximum and minimum values ​​of the fractal dimension of the cutter teeth in one cycle is used to identify the variation range of the fractal dimension of the instantaneous energy consumption distribution; the coefficient of variation and the first-order difference of the fractal dimension of the cutter teeth in one cycle are used to identify the fluctuation degree and increase and decrease characteristics of the fractal dimension of the distribution; the skewness of the fractal dimension in one cycle is used to identify the degree of deviation of the fractal dimension along the cutting time period. The cutter tooth with the smallest characteristic parameter value is selected as the benchmark, and the difference in energy consumption distribution between different cutter teeth is compared by solving the characteristic parameter deviation values ​​of the remaining cutter teeth and the benchmark cutter teeth.

[0035] Based on the instantaneous boundary solution model of the primary and secondary cutting edges, the instantaneous cutting posture of the milling microelement, the instantaneous velocity solution model and the instantaneous cutting layer parameter solution model, taking the 1st, 189th, 239th, 289th and 478th cycles as examples, six contact angles are selected for the cutter teeth in each cutting cycle, and each contact angle corresponds to a characteristic moment, namely, six characteristic moments: t1, t2, t3, t4, t5 and t6. Then, the instantaneous cutting force energy consumption of the cutting edges of the three cutter teeth at the characteristic moments, the distribution of the instantaneous shear force energy consumption along the cutting edges, and the distribution of the instantaneous accumulated friction energy consumption of the primary and secondary flanks of the cutter teeth are solved.

[0036] The instantaneous cutting force energy consumption of the main and secondary cutting edges of tooth 1 at a contact angle of 90° in the 189th cycle is calculated, and the results are as follows: Figure 2 shown.

[0037] Depend on Figure 2 It can be seen that the distribution of instantaneous cutting force energy consumption on the main and secondary cutting edges is uneven. Milling vibration and tooth wear change the kinematic and mechanical behaviors of the tooth micro-element, which is an important reason for the irregular distribution of instantaneous cutting energy consumption.

[0038] The instantaneous shear energy consumption of the main and secondary cutting edges of tooth 1 at a contact angle of 90° in the 189th cycle is calculated. The results are as follows: Figure 3 shown.

[0039] Depend on Figure 3 It can be seen that the distribution of instantaneous shear force energy consumption on the primary and secondary cutting edges is uneven, and the milling vibration causes the uneven distribution of instantaneous shear velocity and instantaneous cutting layer parameters. The cutting layer is the main factor affecting the shear force. It can be seen that milling vibration is an important reason for the irregular distribution of instantaneous shear force energy consumption.

[0040] The instantaneous cumulative friction energy consumption of the primary and secondary flanks of tooth 1 at the 189th cycle with a contact angle of 90° is calculated. The results are as follows: Figure 4 shown.

[0041] Depend on Figure 4 It can be seen that the distribution of instantaneous cumulative friction energy consumption on the primary and secondary flanks is uneven. Milling vibration and tooth wear change the micro-element kinematic and mechanical behavior of the tooth, which is an important reason for the irregular distribution of instantaneous cumulative friction energy consumption. Specifically, the following steps are included:

[0042] S1. The method for calculating the fractal dimension of the instantaneous energy consumption distribution of the primary and secondary cutting edges is to quantitatively describe the dynamic change process of the complexity of the instantaneous energy consumption distribution of the cutter teeth. According to the fractal theory, the complexity of the instantaneous energy consumption distribution of the cutter teeth is characterized. Therefore, the instantaneous energy consumption distribution curve of the milling cutter teeth is regarded as a spatial sequence, and the instantaneous energy consumption distribution curve is solved to obtain the fractal dimension of the instantaneous energy consumption distribution curve of the primary and secondary cutting edges.

[0043]

[0044] Where S(τ) is the measure of the instantaneous energy consumption distribution structure function, which is the arithmetic mean of the square difference of the energy consumption values ​​at two positions of the cutter tooth; τ is the scale of the sampling interval, which is an arbitrary increment of the distance between two points on the cutter tooth; P(ω) is the power spectrum density function; D is the fractal dimension; U0 is the position coordinate along the cutting edge direction; P(U0) is the energy consumption value of the energy consumption distribution curve at U0; ω is the cutoff frequency of the energy consumption distribution curve; G is the scale coefficient of the energy consumption distribution curve;

[0045] For the discrete signals of several τ pairs, S(τ) is calculated, and the relationship curve of log S(τ)-logτ is drawn in double logarithmic coordinates. The least squares method is used to fit it through MATLAB, and then the slope k and intercept A of the fitted straight line are used to convert the fractal dimension D of the instantaneous energy consumption distribution curve of the primary and secondary cutting edges. The conversion relationship between the fractal dimension D and the slope k is:

[0046] D=2-k / 2 (2)

[0047] Among them, the fractal dimension D reflects the complexity of the distribution of instantaneous energy consumption on the blade teeth;

[0048] In order to reveal the changing characteristics of the instantaneous energy consumption distribution of the cutter teeth under vibration, the fractal dimensions of the instantaneous cutting energy consumption of the cutting edge of the cutter teeth, the instantaneous shear force energy consumption and the instantaneous cumulative friction energy consumption of the flank face are solved by taking the 1st, 189th, 239th, 289th and 478th cycles as examples. The solution results are shown in Figure 2. Figure 5-Figure 9 shown.

[0049] S2. Identify the overall level and variation range of the fractal dimension of the instantaneous energy consumption distribution of the primary and secondary cutting edges;

[0050] The maximum value D of the fractal dimension of the blade teeth in one cycle max With the minimum value D min Characterize the overall level of the fractal dimension of the instantaneous energy consumption distribution. The difference d between the maximum and minimum values ​​is used to characterize the variation range of the fractal dimension of the instantaneous energy consumption distribution within the period. The larger the difference, the larger the variation range of the fractal dimension of the energy consumption distribution within the period, and vice versa.

[0051] The maximum value D of the fractal dimension of the blade teeth in one cycle max With the minimum value D min Calculation method:

[0052] D max = {D(t1) , D(t2),…,D(t6)},t∈T (3)

[0053] D min = {D(t1) ,D(t2),…,D(t6)},t∈T (4)

[0054] Where T is the time required for a cutting cycle; D(t1) is the fractal dimension of the energy consumption distribution curve of the cutter tooth at the characteristic time t1.

[0055] The calculation method of the variation range Δd of the fractal dimension of the instantaneous energy consumption distribution of the cutter teeth in one cycle is:

[0056] d=D max -D min (5)

[0057] pass Figure 5 , Figure 6 The overall level and variation range of the fractal dimension of the instantaneous cutting force energy consumption distribution of the primary and secondary cutting edges are characterized by equations (3), (4) and (5). The characterization results are shown in Table 1.

[0058] Table 1 Overall level and variation range of fractal dimension of instantaneous cutting force energy consumption distribution of primary and secondary cutting edges

[0059]

[0060] As shown in Table 1, the overall level and variation range of the fractal dimension of the instantaneous cutting force energy consumption distribution of the main and secondary cutting edges of the three teeth change with the cycle, and there are obvious differences. Comparing the overall level and variation range of the fractal dimension of the energy consumption distribution of the same tooth in different cycles, taking tooth 1 as an example, in the 239th cycle, the fractal dimension of the energy consumption distribution of the main cutting edge of tooth 1 has the maximum moment, and the fractal dimension has the minimum moment in the 1st cycle, and the fractal dimension variation range of the energy consumption distribution in the 1st cycle is the largest; taking tooth 1 as an example, in the 239th cycle, the fractal dimension of the energy consumption distribution of the secondary cutting edge of tooth 1 has the maximum moment, and the fractal dimension has the minimum moment, and the fractal dimension variation range of the energy consumption distribution in the 239th cycle is the largest.

[0061] pass Figure 7 , Figure 8 The overall level and variation range of the instantaneous shear force energy consumption distribution of the primary and secondary cutting edges are characterized by equations (3), (4) and (5). The characterization results are shown in Table 2:

[0062] Table 2 Overall level and variation range of fractal dimension of instantaneous shear force energy consumption distribution of primary and secondary cutting edges

[0063]

[0064] It can be seen from Table 2 that the overall level and variation range of the fractal dimension of the instantaneous shear force energy consumption distribution of the main and secondary cutting edges of the three cutters change with the cycle, and there are obvious differences. Comparing the overall level and variation range of the fractal dimension of the energy consumption distribution of the same cutter in different cycles, taking cutter tooth 1 as an example, the fractal dimension of the energy consumption distribution of the main cutting edge of cutter tooth 1 appears at the maximum moment in the 289th cycle, and the fractal dimension appears at the minimum moment in the 189th cycle, and the fractal dimension variation range of the energy consumption distribution in the 189th cycle is the largest; taking cutter tooth 1 as an example, the fractal dimension of the energy consumption distribution of the secondary cutting edge of cutter tooth 1 appears at the maximum moment in the 189th cycle, and the fractal dimension appears at the minimum moment in the 239th cycle, and the fractal dimension variation range of the energy consumption distribution in the 239th cycle is the largest.

[0065] pass Fig. 9 , Fig.10 The overall level and variation range of the instantaneous cumulative friction energy consumption distribution of the primary and secondary flanks are characterized by equations (3), (4) and (5). The characterization results are shown in Table 3:

[0066] Table 3 Overall level and variation range of fractal dimension of instantaneous cumulative friction energy consumption distribution of primary and secondary flank faces

[0067]

[0068]

[0069] It can be seen from Table 3 that the overall level and variation range of the fractal dimension of the instantaneous cumulative friction energy consumption distribution of the main and secondary flanks of the three teeth change with the cycle, and there are obvious differences. Comparing the overall level and variation range of the fractal dimension of the energy consumption distribution of the same tooth in different cycles, taking tooth 1 as an example, the fractal dimension of the energy consumption distribution of the main flank of tooth 1 is the maximum moment in the 289th cycle, and the fractal dimension is the minimum moment in the 239th cycle, and the fractal dimension variation range of the energy consumption distribution in the 1st cycle is the largest; taking tooth 1 as an example, the fractal dimension of the energy consumption distribution of the secondary flank of tooth 1 is the maximum moment in the 189th cycle, and the fractal dimension is the minimum moment in the 239th cycle, and the fractal dimension variation range of the energy consumption distribution in the 239th cycle is the largest.

[0070] S3. Identify the fluctuation degree and increase / decrease characteristics of the fractal dimension of instantaneous energy consumption distribution;

[0071] The coefficient of variation CV of the fractal dimension in a cycle is used to characterize the fluctuation degree of the fractal dimension of the instantaneous energy consumption distribution in the cycle. The larger the coefficient of variation, the greater the degree of variation of the fractal dimension of the periodic energy consumption distribution, and the more unstable the instantaneous energy consumption distribution; the first-order difference ΔD(t) of the fractal dimension is used to characterize the increase and decrease characteristics of the fractal dimension of the instantaneous energy consumption distribution in a cycle. The larger the value of the first-order difference, the more drastic the change of the fractal dimension of the energy consumption distribution between two moments;

[0072] Calculation method of coefficient of variation CV:

[0073]

[0074] Where s is the standard deviation of the fractal dimension; is the mean value of the fractal dimension;

[0075] The calculation method of the first-order difference ΔD(tk) of the fractal dimension is:

[0076] ΔD(t k )=D(t k+1 )-D(t k ),(k=1,2,...,6) (7)

[0077] Where k is the serial number of the characteristic moment in a cutting cycle; t k is the corresponding characteristic moment

[0078] pass Figure 5-Figure 10 With formula (7), the increase and decrease characteristics of the fractal dimension curve of instantaneous energy consumption distribution are analyzed. The analysis results are shown in Tables 4 to 9:

[0079] Table 4 Increase and decrease characteristics of fractal dimension of instantaneous cutting force energy consumption distribution of main cutting edge

[0080]

[0081]

[0082] It can be seen from Table 4 that the fractal dimension of the instantaneous cutting force energy consumption distribution of the main cutting edge shows obvious increase and decrease differences. Comparing the increase and decrease characteristics of the fractal dimension of the energy consumption distribution of the same tooth in different cycles, taking tooth 1 as an example, the increase and decrease characteristics of the fractal dimension in the 1st cycle, the 289th cycle, and the 478th cycle are increase-decrease-increase-decrease, the increase and decrease characteristics of the curve in the 189th cycle are decrease first and then increase, and the increase and decrease characteristics of the curve in the 239th cycle are decrease-increase-decrease-increase, which shows that the increase and decrease characteristics of the fractal dimension of the instantaneous cutting force energy consumption distribution of the main cutting edge in the 189th cycle and the 239th cycle are significantly different from those in the other three cycles.

[0083] Table 5 Increasing and decreasing characteristics of the complexity of the energy consumption distribution of the instantaneous cutting force of the secondary cutting edge

[0084]

[0085] It can be seen from Table 5 that the fractal dimension of the instantaneous cutting force energy consumption distribution of the secondary cutting edge shows obvious differences in increase and decrease. Comparing the increase and decrease characteristics of the fractal dimension of the energy consumption distribution of the same tooth in different cycles, taking tooth 1 as an example, the increase and decrease characteristics of the curve in the first cycle are decrease-increase-decrease, the increase and decrease characteristics of the fractal dimension in the 189th and 289th cycles are increase-decrease-increase-decrease, the increase and decrease characteristics of the curve in the 239th cycle are increase-decrease-increase, and the increase and decrease characteristics of the curve in the 478th cycle are decreasing, which shows that in the entire cutting process, the increase and decrease characteristics of the fractal dimension of the instantaneous cutting force energy consumption distribution of the secondary cutting edge show obvious differences.

[0086] Table 6 Increase and decrease characteristics of the fractal dimension of the instantaneous shear force energy consumption distribution of the main cutting edge

[0087]

[0088] As can be seen from Table 6, the fractal dimension of the instantaneous shear force energy consumption distribution of the main cutting edge shows obvious increase and decrease differences. Comparing the increase and decrease characteristics of the fractal dimension of the energy consumption distribution of the same tooth in different cycles, taking tooth 1 as an example, the increase and decrease characteristics of the fractal dimension in the 1st cycle, the 289th cycle, and the 478th cycle are increase-decrease-increase-decrease, the increase and decrease characteristics of the curve in the 189th cycle are increase first and then decrease, and the increase and decrease characteristics of the curve in the 239th cycle are increase-decrease-increase-decrease-increase, which shows that the increase and decrease characteristics of the fractal dimension of the instantaneous shear force energy consumption distribution of the main cutting edge in the 189th cycle are significantly different from those in the other three cycles, while the increase and decrease characteristics of the fractal dimension of the instantaneous shear force energy consumption distribution of the main cutting edge in the 239th cycle are not significantly different from those in the other three cycles.

[0089] Table 7 Increase and decrease characteristics of fractal dimension of the instantaneous shear force energy consumption distribution of the secondary cutting edge

[0090]

[0091]

[0092] It can be seen from Table 7 that the fractal dimension of the instantaneous shear force energy consumption distribution of the secondary cutting edge shows obvious increase and decrease differences. Comparing the increase and decrease characteristics of the fractal dimension of the energy consumption distribution of the same tooth in different cycles, taking tooth 1 as an example, the increase and decrease characteristics of the curve in the first cycle are first increase and then decrease, the increase and decrease characteristics of the curve in the 189th cycle are decrease-increase-decrease-increase, the increase and decrease characteristics of the fractal dimension in the 239th and 289th cycles are increase-decrease-increase-decrease, and the increase and decrease characteristics of the curve in the 478th cycle are increase-decrease-increase, which shows that in the entire cutting process, the increase and decrease characteristics of the fractal dimension of the instantaneous shear force energy consumption distribution of the secondary cutting edge in different cycles show obvious differences.

[0093] Table 8 Increase and decrease characteristics of the fractal dimension of the instantaneous cumulative friction energy consumption distribution of the main flank

[0094]

[0095] It can be seen from Table 8 that the increase and decrease differences in the fractal dimension of the instantaneous cumulative friction energy consumption distribution of the main flank face are not obvious. Comparing the increase and decrease characteristics of the fractal dimension of the energy consumption distribution of the same tooth in different cycles, taking tooth 1 as an example, the increase and decrease characteristics of the fractal dimension in the 1st cycle, the 189th cycle, the 239th cycle and the 289th cycle are all decrease-increase-decrease, and the increase and decrease characteristics of the curve in the 478th cycle are decrease first and then increase, which shows that there is no obvious difference in the increase and decrease characteristics of the fractal dimension of the instantaneous cumulative friction energy consumption distribution of the main flank face in different cycles.

[0096] Table 9 Increase and decrease characteristics of the fractal dimension of the instantaneous cumulative friction energy consumption distribution of the secondary flank

[0097]

[0098]

[0099] As can be seen from Table 9, the increase and decrease differences in the fractal dimension of the distribution of the instantaneous cumulative friction energy consumption of the secondary flank face are not obvious. Comparing the increase and decrease characteristics of the fractal dimension of the energy consumption distribution of the same tooth in different cycles, taking tooth 1 as an example, the increase and decrease characteristics of the fractal dimension in the 1st cycle, the 239th cycle and the 289th cycle are all increased first and then decreased, the increase and decrease characteristics of the curve in the 189th cycle are decreased-increased-decreased, and the increase and decrease characteristics of the curve in the 478th cycle are increased-decreased-increased-decreased, which indicates that the increase and decrease characteristics of the fractal dimension of the distribution of the instantaneous cumulative friction energy consumption of the secondary flank face in the 189th cycle are not significantly different from those in the other three cycles, while the increase and decrease characteristics of the fractal dimension of the distribution of the instantaneous cumulative friction energy consumption of the secondary flank face in the 478th cycle are significantly different from those in the other three cycles.

[0100] It can be seen from Tables 4 to 9 that the increase and decrease characteristics of the curves of the fractal dimension of the instantaneous energy consumption distribution changing with time show obvious differences. There are a total of 9 increase and decrease characteristics, namely: increase-decrease-increase-decrease; increase-decrease-increase; decrease-increase; increase-decrease-increase-decrease-increase; decrease-increase-decrease-increase; decrease-increase-decrease; increase-decrease; decreasing; decrease-increase-decrease-increase-decrease, and the serial numbers ①, ②, ③, ④, ⑤, ⑥, ⑦, ⑧ and ⑨ are used to represent different increase and decrease characteristics.

[0101] pass Figure 5-Figure 10 The instantaneous cutting force energy consumption P of the main and secondary cutting edges of the cutter teeth is calculated by formula (6): ci , instantaneous shear force energy consumption P si , and the instantaneous cumulative friction energy consumption P of the blade back surface miThe fluctuation degree of the fractal dimension of the distribution is characterized, and the characterization results are shown in Table 10:

[0102] Table 10 Fluctuation degree of fractal dimension of instantaneous energy consumption distribution of blade teeth

[0103]

[0104]

[0105] As shown in Table 10, the fluctuation degree of the fractal dimension of the instantaneous cutting force energy consumption distribution of the main and secondary cutting edges of the three teeth changes with time, and there are obvious differences. Comparing the fluctuation degree of the fractal dimension of the energy consumption distribution of the same tooth in different cycles, taking tooth 1 as an example, the coefficient of variation of the fractal dimension of the instantaneous cutting force energy consumption distribution of the main cutting edge of tooth 1 decreases with the increase of the cycle, which indicates that the variation degree of the fractal dimension of the energy consumption distribution of the main cutting edge of tooth 1 is the largest in the first cycle, and then gradually stabilizes; the coefficient of variation of the fractal dimension of the instantaneous cutting force energy consumption distribution of the secondary cutting edge of tooth 1 increases first and then decreases with the increase of the cycle, which indicates that the variation degree of the fractal dimension of the energy consumption distribution increases first and then decreases, and the variation degree is the most drastic in the 239th cycle.

[0106] It can be seen from Table 10 that the fractal dimensions of the instantaneous shear force energy consumption distribution of the main and secondary cutting edges of the three teeth change with time and have obvious differences. Comparing the fluctuation degree of the fractal dimension of the energy consumption distribution of the same tooth in different cycles, taking tooth 1 as an example, the coefficient of variation of the fractal dimension of the instantaneous shear force energy consumption distribution of the main cutting edge of tooth 1 first increases and then decreases with the increase of the cycle, and then increases again, which indicates that the degree of change of the fractal dimension of the energy consumption distribution is significantly different in different cycles; the coefficient of variation of the fractal dimension of the instantaneous shear force energy consumption distribution of the secondary cutting edge of tooth 1 increases first and then decreases with the increase of the cycle, which indicates that the degree of change of the fractal dimension of the energy consumption distribution increases first and then decreases, and the degree of change is the most drastic in the 239th cycle.

[0107] As shown in Table 10, the fractal dimensions of the instantaneous cumulative friction energy consumption distribution of the main and secondary flanks of the three teeth change continuously over time, and there are obvious differences. Comparing the fluctuation degree of the fractal dimension of the energy consumption distribution of the same tooth in different cycles, taking tooth 1 as an example, the coefficient of variation of the fractal dimension of the instantaneous cumulative friction energy consumption distribution of the main flank of tooth 1 first decreases, then increases, and then decreases again with the increase of the cycle, which indicates that the degree of change of the fractal dimension of the energy consumption distribution is obviously different in different cycles; the coefficient of variation of the fractal dimension of the instantaneous cumulative friction energy consumption distribution of the secondary flank of tooth 1 first decreases, then increases, and then decreases again with the increase of the cycle, which indicates that the degree of change of the fractal dimension of the energy consumption distribution is obviously different in different cycles.

[0108] S4. Identify the degree of deviation of the fractal dimension of the instantaneous energy consumption distribution along the cutting time period;

[0109] The skewness G of the fractal dimension of the instantaneous energy consumption distribution within a cycle represents the degree of deviation of the fractal dimension along the cutting time period. The larger the absolute value of the skewness, the closer the period of complex and changeable energy consumption distribution is to the cutting-in or cutting-out moment. When the skewness value is positive, the period of complex and changeable energy consumption distribution is closer to the cutting-in moment, and vice versa, it is closer to the cutting-out moment. Calculation method of skewness G:

[0110]

[0111] Where n is the number of contact angles selected by the cutter teeth in one cycle.

[0112] pass Figure 5-Figure 10 The instantaneous cutting force energy consumption P of the main and secondary cutting edges of the cutter teeth is calculated by formula (8): ci , instantaneous shear force energy consumption P si , and the instantaneous cumulative friction energy consumption P of the blade back surface mi The skewness of the fractal dimension of the distribution is characterized, and the characterization results are shown in Table 11:

[0113] Table 11 Deviation of the fractal dimension of the instantaneous energy consumption distribution of the cutter teeth along the cutting time period

[0114]

[0115] It can be seen from Table 11 that the degree of deviation of the fractal dimension of the instantaneous cutting force energy consumption distribution of the main and secondary cutting edges of the three teeth along the cutting period direction changes with the cycle, and there are obvious differences. Comparing the changes in the degree of deviation of the fractal dimension of the energy consumption distribution of the same tooth in different cycles, taking tooth 1 as an example, the period of complex and changeable energy consumption distribution of the main cutting edge of tooth 1 in the 1st cycle, the 289th cycle, and the 478th cycle is close to the cutting moment, and the period of complex and changeable energy consumption distribution of the secondary cutting edge of tooth 1 in the 1st cycle, the 189th cycle, and the 289th cycle is close to the cutting moment, and the period of complex and changeable energy consumption distribution of the secondary cutting edge of tooth 1 in the 239th cycle and the 478th cycle is close to the cutting moment.

[0116] It can be seen from Table 11 that the degree of deviation of the fractal dimension of the instantaneous shear force energy consumption distribution of the main and secondary cutting edges of the three teeth along the cutting period direction changes with the cycle, and there are obvious differences. Comparing the changes in the degree of deviation of the fractal dimension of the energy consumption distribution of the same tooth in different cycles, taking tooth 1 as an example, the period of complex and changeable energy consumption distribution of the main cutting edge of tooth 1 in the 1st cycle, the 289th cycle, and the 478th cycle is close to the cutting-in time, and the period of complex and changeable energy consumption distribution of the 189th cycle and the 239th cycle is close to the cutting-out time; the period of complex and changeable energy consumption distribution of the secondary cutting edge of tooth 1 in the 1st cycle, the 239th cycle, and the 289th cycle is close to the cutting-out time, and the period of complex and changeable energy consumption distribution of the secondary cutting edge of tooth 1 in the 1st cycle, the 239th cycle, and the 289th cycle is close to the cutting-in time.

[0117] It can be seen from Table 11 that the degree of deviation of the fractal dimension of the instantaneous cumulative friction energy consumption distribution of the main and secondary flanks of the three teeth along the cutting period direction changes with the cycle, and there are obvious differences. Comparing the changes in the degree of deviation of the fractal dimension of the energy consumption distribution of the same tooth in different cycles, taking tooth 1 as an example, the period of complex and changeable energy consumption distribution of the main flank of tooth 1 in the 1st cycle, the 189th cycle and the 239th cycle is close to the cutting-out time, and the period of complex and changeable energy consumption distribution of the secondary flank of tooth 1 in the 289th cycle and the 478th cycle is close to the cutting-in time; the period of complex and changeable energy consumption distribution of the secondary flank of tooth 1 in the 1st cycle, the 239th cycle, the 289th cycle and the 478th cycle is close to the cutting-out time, and the period of complex and changeable energy consumption distribution of the secondary flank of tooth 1 in the 189th cycle is close to the cutting-in time.

[0118] S5. Identify the differences in instantaneous energy consumption distribution between different cutting teeth.

[0119] The smaller the fractal dimension of the instantaneous energy consumption distribution, the lower the complexity of the distribution. The closer the fractal dimension curve is to a straight line, the smaller the change in the complexity of the distribution. Therefore, in the same period, the blade with the smallest characteristic parameter value of the fractal curve is used as the benchmark, and ΔD is used to calculate the energy consumption distribution. max With ΔD min Characterizes the overall level difference between different teeth, ΔD max With ΔD min The larger the value is, the more obvious the difference in the overall level of fractal dimension between different teeth is; Δd is used to characterize the difference in the range of fractal dimension variation between different teeth. The larger the Δd is, the more obvious the difference in the range of fractal dimension variation between different teeth is; ΔCV is used to characterize the difference in the degree of fractal dimension fluctuation between different teeth. The larger the ΔCV is, the greater the difference in the degree of fractal dimension fluctuation between different teeth is; taking the tooth with the least number of fractal dimension increases and decreases in the increase and decrease characteristics as the benchmark, ΔB is used to characterize the difference in fractal dimension fluctuation characteristics between different teeth; finally, the skewness of the tooth with the most characteristic parameter benchmark times is selected as the benchmark, and ΔG is used to characterize the difference in fractal dimension skewness between different teeth. The larger the ΔG is, the greater the difference in skewness between different teeth is.

[0120] ΔD max With ΔD min Calculation method:

[0121]

[0122] Among them, D 0max It is the benchmark for the maximum value of the fractal dimension of the instantaneous energy consumption distribution of different teeth in the same period; D imax is the maximum value of the fractal dimension of the instantaneous energy consumption distribution of different teeth;

[0123]

[0124] Among them, D 0min It is the benchmark for the minimum value of the fractal dimension of the instantaneous energy consumption distribution of different teeth in the same period; D imin is the minimum value of the fractal dimension of the instantaneous energy consumption distribution of different teeth;

[0125] Calculation method of Δd:

[0126]

[0127] Among them, d0 is the benchmark of the variation range of the fractal dimension of the instantaneous energy consumption distribution of different teeth in the same period; d i is the variation range of the fractal dimension of instantaneous energy consumption distribution of different teeth;

[0128] Calculation method of ΔCV:

[0129]

[0130] Among them, CV0 is the benchmark of the coefficient of variation of the fractal dimension of the instantaneous energy consumption distribution of different teeth in the same period; CV i is the coefficient of variation of the fractal dimension of the instantaneous energy consumption distribution of different teeth;

[0131] Calculation method of ΔB:

[0132]

[0133] Among them, B0 is the benchmark for the increase and decrease of the fractal dimension of the instantaneous energy consumption distribution of different teeth in the same period; B i is the number of increases and decreases of the fractal dimension of the instantaneous energy consumption distribution of different teeth;

[0134] Calculation method of ΔG:

[0135]

[0136] Among them, G0 is the benchmark of the skewness of the fractal dimension of the instantaneous energy consumption distribution of different teeth in the same period; j is the number of the tooth whose five characteristic parameters are selected as the benchmark the most times; G i is the skewness of the fractal dimension of the instantaneous energy consumption distribution of different teeth.

[0137] By using equations (9) to (14), taking the first cycle as an example, the difference in the instantaneous cutting force energy consumption distribution between the main and secondary cutting edges of the three cutter teeth is identified. The results are shown in Table 12:

[0138] Table 12 Differences in the distribution of instantaneous cutting force energy consumption between the main and secondary cutting edges of the cutter teeth

[0139]

[0140] As can be seen from Table 12, there are obvious differences in the distribution of instantaneous cutting force energy consumption between the main and secondary cutting edges of different teeth. In the first cycle, the main cutting edge of tooth 3 is selected as the most characteristic parameters of the benchmark, so the complexity of the instantaneous cutting force energy consumption distribution of tooth 3 is the lowest; compared with the characteristic parameters of tooth 2, the number of characteristic parameters with large deviation values ​​of tooth 1 is larger, so the distribution difference between tooth 1 and tooth 3 is the largest. The secondary cutting edge of tooth 1 is selected as the most characteristic parameters of the benchmark, so the complexity of the instantaneous cutting force energy consumption distribution of tooth 1 is the lowest; compared with the characteristic parameters of tooth 3, the number of characteristic parameters with large deviation values ​​of tooth 2 is larger, so the distribution difference between tooth 1 and tooth 2 is the largest.

[0141] Through equations (9) to (14), taking the first cycle as an example, the difference in the complexity of the instantaneous shear force energy consumption distribution between the main and secondary cutting edges of the three teeth is identified. The results are shown in Table 13:

[0142] Table 13 Differences in instantaneous shear force energy consumption distribution between the main and secondary cutting edges of the cutter teeth

[0143]

[0144] As can be seen from Table 13, there are obvious differences in the distribution of instantaneous shear force energy consumption between the main and secondary cutting edges of different teeth. In the first cycle, the main cutting edge of tooth 3 is selected as the most characteristic parameters of the benchmark, so the complexity of the instantaneous shear force energy consumption distribution of tooth 3 is the lowest; compared with the characteristic parameters of tooth 2, the number of characteristic parameters with large deviation values ​​of tooth 2 is larger, so the distribution difference between tooth 2 and tooth 3 is the largest. The secondary cutting edge of tooth 1 is selected as the most characteristic parameters of the benchmark, so the complexity of the instantaneous shear force energy consumption distribution of tooth 1 is the lowest; compared with the characteristic parameters of tooth 2 and tooth 3, the number of characteristic parameters with large deviation values ​​of tooth 3 is larger, so the distribution difference between tooth 1 and tooth 3 is the largest.

[0145] Through equations (9) to (14), taking the first cycle as an example, the difference in the complexity of the instantaneous cumulative friction energy consumption distribution between the primary and secondary flank surfaces of the three cutter teeth is identified. The results are shown in Table 14:

[0146] Table 14 Differences in instantaneous friction energy consumption distribution between the primary and secondary flank surfaces of the cutter teeth

[0147]

[0148] As can be seen from Table 14, there are obvious differences in the distribution of instantaneous friction energy consumption between the main and secondary flanks of different teeth. In the first cycle, the main flank of tooth 2 has the most characteristic parameters selected as the benchmark, so the complexity of the instantaneous friction energy consumption distribution of tooth 2 is the lowest; compared with the characteristic parameters of tooth 3, the number of characteristic parameters with large deviation values ​​of tooth 1 is larger, so the distribution difference between tooth 1 and tooth 2 is the largest. The secondary flank of tooth 1 has the most characteristic parameters selected as the benchmark, so the complexity of the instantaneous friction energy consumption distribution of tooth 1 is the lowest; compared with the characteristic parameters of tooth 3, the number of characteristic parameters with large deviation values ​​of tooth 3 is larger, so the distribution difference between tooth 1 and tooth 3 is the largest.

[0149] Embodiment 2: The computer device of the present invention may be a device including a processor and a memory, such as a single chip microcomputer including a central processing unit. Furthermore, the processor is used to implement the steps of the above-mentioned fractal feature recognition method of the instantaneous energy consumption distribution complexity of the square shoulder milling cutter teeth when executing the computer program stored in the memory.

[0150] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0151] The memory may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0152] Embodiment 3, computer readable storage medium embodiment.

[0153] The computer-readable storage medium of the present invention can be any form of storage medium that can be read by the processor of a computer device, including but not limited to non-volatile memory, volatile memory, ferroelectric memory, etc. The computer-readable storage medium stores a computer program. When the processor of the computer device reads and executes the computer program stored in the memory, the steps of the above-mentioned fractal feature recognition method of the complexity of the instantaneous energy consumption distribution of the teeth of a square shoulder milling cutter can be implemented.

[0154] The computer program includes computer program code, which may be in source code form, object code form, executable file or some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0155] Although the present invention has been described according to a limited number of embodiments, it will be apparent to those skilled in the art, with the benefit of the above description, that other embodiments may be envisioned within the scope of the invention thus described. In addition, it should be noted that the language used in this specification is selected primarily for readability and teaching purposes, rather than for explaining or defining the subject matter of the present invention. Therefore, many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the appended claims. The disclosure of the present invention is illustrative, not restrictive, with respect to the scope of the present invention, which is defined by the appended claims.

Claims

1. A fractal feature recognition method for the complexity of instantaneous energy consumption distribution of square shoulder milling cutter teeth, characterized in that: The following steps are involved: S1. A method for calculating the fractal dimension of the instantaneous energy consumption distribution of the primary and secondary cutting edges. The instantaneous energy consumption distribution curve of the milling cutter teeth is regarded as a spatial sequence, and the instantaneous energy consumption distribution curve is calculated to obtain the fractal dimension of the instantaneous energy consumption distribution curve of the primary and secondary cutting edges; Where S(τ) is the measure of the instantaneous energy consumption distribution structure function, which is the arithmetic mean of the square difference of the energy consumption values ​​at two positions of the cutter tooth; τ is the scale of the sampling interval, which is an arbitrary increment of the distance between two points on the cutter tooth; P(ω) is the power spectrum density function; D is the fractal dimension; U0 is the position coordinate along the cutting edge direction; P(U0) is the energy consumption value of the energy consumption distribution curve at U0; ω is the cutoff frequency of the energy consumption distribution curve; G is the scale coefficient of the energy consumption distribution curve; For the discrete signals of several τ pairs, S(τ) is calculated, and the relationship curve of log S(τ)-logτ is drawn in double logarithmic coordinates. The least squares method is used to fit it through MATLAB, and then the slope k of the fitted straight line is used to convert the fractal dimension D of the instantaneous energy consumption distribution curve of the primary and secondary cutting edges. The conversion relationship between the fractal dimension D and the slope k is: D=2-k / 2 S2. According to the fractal dimension of the instantaneous energy consumption distribution curve of the main and auxiliary cutting edges, identify the overall level and variation range of the fractal dimension of the instantaneous energy consumption distribution of the main and auxiliary cutting edges; take the maximum value D of the fractal dimension of the tooth in one cycle as the max With the minimum value D min Characterize the overall level of the fractal dimension of the instantaneous energy consumption distribution, and use the difference d between the maximum and minimum values ​​to characterize the variation range of the fractal dimension of the instantaneous energy consumption distribution within the period; S3. Identify the fluctuation degree and increase / decrease characteristics of the fractal dimension of the instantaneous energy consumption distribution; characterize the fluctuation degree of the fractal dimension of the instantaneous energy consumption distribution in the cycle by the coefficient of variation CV of the fractal dimension in a cycle, and characterize the increase / decrease characteristics of the fractal dimension of the instantaneous energy consumption distribution in a cycle by the first-order difference ΔD(t) of the fractal dimension; Calculation method of coefficient of variation CV: Where s is the standard deviation of the fractal dimension; is the mean value of the fractal dimension; S4. Identify the degree of deviation of the fractal dimension of the instantaneous energy consumption distribution along the cutting time period direction; characterize the degree of deviation of the fractal dimension along the cutting time period direction by the skewness G of the fractal dimension of the instantaneous energy consumption distribution within a cycle; Calculation method of skewness G: In the formula, n is the number of contact angles selected by the cutter teeth in one cycle; S5. Identify the difference in instantaneous energy consumption distribution between different teeth. In the same cycle, take the tooth with the smallest characteristic parameter value of the fractal curve as the benchmark and use ΔD max With ΔD min Characterize the overall level difference between different teeth, use Δd to characterize the difference in the range of fractal dimension change between different teeth, use ΔCV to characterize the difference in the degree of fractal dimension fluctuation between different teeth, take the tooth with the least increase and decrease times of fractal dimension in the increase and decrease characteristics as the benchmark, use ΔB to characterize the difference in fractal dimension fluctuation characteristics between different teeth; finally, select the skewness of the tooth with the most characteristic parameter benchmark times as the benchmark, and use ΔG to characterize the difference in fractal dimension skewness between different teeth; ΔD max With ΔD min Calculation method: Among them, D 0max It is the benchmark for the maximum value of the fractal dimension of the instantaneous energy consumption distribution of different teeth in the same period; D imax is the maximum value of the fractal dimension of the instantaneous energy consumption distribution of different teeth; Among them, D 0min It is the benchmark for the minimum value of the fractal dimension of the instantaneous energy consumption distribution of different teeth in the same period; D imin is the minimum value of the fractal dimension of the instantaneous energy consumption distribution of different teeth; Calculation method of Δd: Among them, d0 is the benchmark of the variation range of the fractal dimension of the instantaneous energy consumption distribution of different teeth in the same period; d i is the variation range of the fractal dimension of instantaneous energy consumption distribution of different teeth; Calculation method of ΔCV: Among them, CV0 is the benchmark of the coefficient of variation of the fractal dimension of the instantaneous energy consumption distribution of different teeth in the same period; CV i is the coefficient of variation of the fractal dimension of the instantaneous energy consumption distribution of different teeth; Calculation method of ΔB: Among them, B0 is the benchmark for the increase and decrease of the fractal dimension of the instantaneous energy consumption distribution of different teeth in the same period; B i is the number of increases and decreases of the fractal dimension of the instantaneous energy consumption distribution of different teeth; Calculation method of ΔG: Among them, G0 is the skewness benchmark of the fractal dimension of the instantaneous energy consumption distribution of different teeth in the same period; j is D max , D min The five characteristic parameters, d, CV and B, are selected as the number of the cutter teeth with the most benchmark times; G i is the skewness of the fractal dimension of the instantaneous energy consumption distribution of different teeth.

2. The fractal feature recognition method for the complexity of instantaneous energy consumption distribution of square shoulder milling cutter teeth according to claim 1 is characterized in that: According to the fractal dimension of the instantaneous energy consumption distribution curve of the primary and secondary cutting edges, the method for identifying the overall level and variation range of the fractal dimension of the instantaneous energy consumption distribution of the primary and secondary cutting edges is: the larger the difference d, the larger the variation range of the fractal dimension of the energy consumption distribution within one cycle, and vice versa.

3. The fractal feature recognition method of instantaneous energy consumption distribution complexity of square shoulder milling cutter teeth according to claim 2 is characterized in that: The method for identifying the fluctuation degree and increase and decrease characteristics of the fractal dimension of the instantaneous energy consumption distribution is: the larger the coefficient of variation CV, the greater the degree of change of the fractal dimension of the periodic energy consumption distribution, and the more unstable the instantaneous energy consumption distribution; the larger the value of the first-order difference ΔD(t), the more drastic the change of the fractal dimension of the energy consumption distribution between two moments.

4. The fractal feature recognition method of instantaneous energy consumption distribution complexity of square shoulder milling cutter teeth according to claim 3 is characterized in that: The method for identifying the degree of deviation of the fractal dimension of the instantaneous energy consumption distribution along the cutting time period is: the larger the absolute value of the skewness G, the closer the period of complex and changeable energy consumption distribution is to the cutting-in or cutting-out moment; when the value of the skewness G is positive, the closer the period of complex and changeable energy consumption distribution is to the cutting-in moment, and vice versa.

5. The fractal feature recognition method of instantaneous energy consumption distribution complexity of square shoulder milling cutter teeth according to claim 4 is characterized in that: The larger the ΔDmax and ΔDmin are, the more obvious the difference in the overall level of fractal dimension between different teeth is; the larger the Δd is, the more obvious the difference in the range of fractal dimension variation between different teeth is; the larger the ΔCV is, the greater the difference in the degree of fractal dimension fluctuation between different teeth is; the larger the ΔG is, the greater the difference in skewness between different teeth is.

6. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the fractal feature recognition method of the instantaneous energy consumption distribution complexity of the square shoulder milling cutter teeth as described in any one of claims 1 to 5 when executing the computer program.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the fractal feature recognition method of the complexity of instantaneous energy consumption distribution of a square shoulder milling cutter tooth as described in any one of claims 1 to 5 is implemented.

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