Optimization and grouping method for power distribution cabinet wire harness data

Abstract

The application provides a power distribution cabinet wire harness data optimization and grouping method, including the following steps: S1, optimizing the wire harness data and dividing it into three parts: a header, a skeleton and a tail; S2, calculating the length of each wire harness skeleton part and arranging them in descending order according to the skeleton length; taking the wire harness with the longest skeleton as the group head of the first group, and then calculating the coincidence rate of the skeleton part of each subsequent wire harness with each group head; according to the coincidence rate, the wire harness is divided into large groups; S3, rearranging the wire harnesses in each large group according to the length of the coincident part, and establishing a loss function to determine the minimum unit group; S4, establishing a matching degree function, calculating the matching degree between each minimum unit, taking the maximum value, and continuously iterating until convergence to integrate the data to obtain the final grouping result. The application realizes the optimization and grouping of the power distribution cabinet wire harness data, provides data support for the production of prefabricated wire harness groups on the nail plate diagram, and greatly improves the feasibility and implementation efficiency of the automatic wiring of the power distribution cabinet.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automatic wiring, in particular to a power distribution cabinet wiring harness data optimization and grouping method. BACKGROUND

[0002] As the control terminal of power distribution management, power distribution cabinets are almost everywhere where electricity is used. The production of such widely used equipment has not yet fully realized automation, especially the wiring of power distribution cabinets, more than 90% of which still needs to be completed manually by skilled workers. Therefore, the automatic wiring of power distribution cabinets has always been a popular research topic.

[0003] For the automatic wiring of power distribution cabinets, one approach is to wire one by one in the cabinet box. This scheme requires high control precision of the mechanical arm and high flexibility of the gripper, so it has not been widely commercialized. To solve the above problems, inspired by cable assembly, a more feasible wiring scheme is to change from wiring in the box to wiring on the pinboard diagram (outside the box). This scheme has better feasibility and research value because it is not constrained by the space inside the box. However, in order to facilitate transplantation into the cabinet, the wiring harness needs to be grouped to make pre-made wiring harnesses. However, the existing technology does not provide a method for grouping wiring harnesses. Therefore, the present application proposes a wiring harness data optimization and grouping method. SUMMARY

[0004] The purpose of the present application is to provide a power distribution cabinet wiring harness data optimization and grouping method, which realizes the optimization and grouping of power distribution cabinet wiring harness data, provides data support for the production of pre-made wiring harness groups on the pinboard diagram, and greatly improves the feasibility and implementation efficiency of automatic wiring of power distribution cabinets.

[0005] To achieve the above purpose, the technical scheme of the present application is as follows: a power distribution cabinet wiring harness data optimization and grouping method, specifically comprising the following steps:

[0006] S1, obtain wiring harness data, and divide the wiring harness route into three parts: head, skeleton, and tail after removing non-inflexion points from the wiring harness data to obtain optimized wiring harness data;

[0007] S2, calculate the length of each wiring harness skeleton part, and arrange them in descending order according to the skeleton length; take the wiring harness with the longest skeleton as the head of the first group, and then calculate the coincidence rate of the subsequent wiring harnesses with each group head; divide the wiring harnesses into large groups according to the coincidence rate of the wiring harness skeleton parts;

[0008] S3, rearrange the wiring harnesses in each large group according to the length of the coincident part, and then establish a loss function to determine the minimum unit group after the rearrangement is completed;

[0009] S4, a matching degree function is established, the matching degree between each minimum unit is calculated, the maximum value is combined, and iteration is continuously performed until convergence, and the final grouping result is obtained by integrating the data.

[0010] Preferably, the optimized bundle data is obtained by non-inflexion point elimination on the bundle data, specifically: for each path point in each bundle except the first and last path points, the differences of the path points in X, Y and Z axes are calculated, the variation amounts of the current path point and the front and rear path points in each axis are compared, and the front and rear path variation directions of the current path point are positioned according to the direction with the largest variation amount; if the front and rear variation directions are consistent, the non-inflexion point is determined, and the non-inflexion point is eliminated to obtain the optimized bundle data.

[0011] Preferably, the coordinates of the skeleton part have the same Z value.

[0012] Preferably, the large group division of the bundle is performed according to the coincidence rate of the bundle skeleton part, specifically: the following operations are performed on each bundle in the subsequent bundle until the large group division of all the subsequent bundles is completed: find out the group head with the largest coincidence rate with the current bundle, if the largest coincidence rate meets the set threshold, the current bundle is divided into the large group corresponding to the group head with the largest coincidence rate, and if not, the current bundle is divided into a new group head.

[0013] Preferably, the calculation of the bundle skeleton part coincidence rate is as follows:

[0014]

[0015] In the formula: l b represents the length of the skeleton b to be compared; l ab represents the length of the coincident part of the original comparison skeleton a and the skeleton b to be compared.

[0016] Preferably, the length of the coincident part of the original comparison skeleton a and the skeleton b to be compared is calculated as follows:

[0017] 1) The original comparison skeleton a and the skeleton b to be compared are divided into k sections according to the coordinate difference, and it is judged whether each section has coincidence or not;

[0018] 2) If there is coincidence, it is further judged whether the point position is coincident or not:

[0019] Let the left end point coordinate of the i-th section of the original comparison skeleton a be a1, the right end point coordinate be a2, the left end point coordinate of the i-th section of the skeleton b to be compared be b1, and the right end point coordinate be b2, a1-b1 and a2-b2 are calculated respectively, the length of the original comparison skeleton a in the i-th section is the length of the skeleton b to be compared in the i-th section is the coincident length in the i-th section of the two bundles.

[0020] If (a1-b1)(a2-b2)≤0, then compare with the length of the overlap; if there is then else

[0021] If (a1-b1)>0 and (a2-b2)>0, then calculate b2-a1; if b2-a1>0, then else

[0022] If (a1-b1)<0 and (a2-b2)<0, then calculate a2-b1; if a2-b1>0, then else

[0023] 3) Calculate the length of the overlap between the original comparison skeleton a and the skeleton to be compared b:

[0024]

[0025] where n is the number of overlapping segments.

[0026] Preferably, the S3 is specifically:

[0027] S31, calculate the length of the skeleton overlap between each group header and each remaining beam in the group, and arrange the remaining beams in the group in descending order according to the length of the skeleton overlap, with the group header as the starting point;

[0028] S32, for each group, take the group header as the group header of the first minimum unit group, and calculate the loss rate of the remaining beams arranged in descending order with the previous beam one by one, if the set threshold is met, the current beam and the previous beam are divided into the same minimum unit group, otherwise the current is divided into a new minimum unit group.

[0029] Preferably, the establishment of the loss function is specifically:

[0030] Define variables: L0 is the length of the original comparison wire overlap; L1 is the length of the wire to be compared overlap; Ax, Ay are the average values of the x, y coordinates of each inflection point of the beam, respectively:

[0031]

[0032] Establish the loss function:

[0033] Loss=a1L len (L0,L1)+a2L pos (L0,Ax0,Ax1,Ay0,Ay1) (3)

[0034]

[0035] wherein j is the index of the inflection point, m is the number of inflection points, x j , y j are the x, y coordinates of the inflection point j, L len represents the coincidence length loss rate of the two conductors, L pos represents the coincidence position loss rate of the two conductors, a1, a2 are weight values, Ax0, Ay0 represent the average values of the x, y coordinates of the inflection points of the original comparison conductor, and Ax1, Ay1 represent the average values of the x, y coordinates of the inflection points of the conductor to be compared.

[0036] Preferably, the matching degree function is specifically:

[0037] Fit = b1F pos (L0, L1, Ax0, Ax1, Ay0, Ay1) + b2F pot (n') + b3F num (n0, n1) (6)

[0038] wherein b1, b2, b3 are weight values, F pos represents the position and length matching degree of each unit group:

[0039]

[0040] d = Max(|Ax0-Ax1|, |Ay0-Ay1|) (8)

[0041] F pot represents the end point matching degree of each unit group, i.e. the number of common inflection points:

[0042] F pot = Min(5n', 10) (9)

[0043] In the above formula, n' is the number of common inflection points of the two bundles,

[0044] F num represents the number matching degree of the unit group:

[0045]

[0046] In the above formula, n0 is the number of the original combined minimum unit group bundle, n1 is the number of the minimum unit group bundle to be combined, and s is the preset optimal number of the bundle per group.

[0047] Preferably, the S4 is specifically: for each minimum unit group to be matched, the following operation is performed for the integration of the minimum unit group until the integration of all minimum units is completed:

[0048] The matching degree function is used to calculate the matching degree between the current minimum unit group head and the heads of each of the other minimum unit groups.

[0049] Select the smallest unit group with the highest matching degree and combine it with the current smallest unit group to be matched. Determine whether the number of wire bundles after combination reaches s. If not, continue to select the smallest unit group with the highest matching degree among the remaining smallest unit groups and combine it until the number of wire bundles after combination reaches s, thus completing the integration of the current smallest unit group to be matched.

[0050] Compared with the prior art, the present invention has the following beneficial effects:

[0051] This invention optimizes and groups the wiring harness data of power distribution cabinets, providing data support for the production of prefabricated wiring harness groups on the nail board diagram, and greatly improving the feasibility and efficiency of automated wiring of power distribution cabinets. Attached Figure Description

[0052] Figure 1 This is a diagram of the original wire harness data in one embodiment of the present invention;

[0053] Figure 2 This is an optimized wire harness data diagram in one embodiment of the present invention;

[0054] Figure 3 This is an example diagram showing the skeleton lengths arranged in descending order according to one embodiment of the present invention;

[0055] Figure 4 This is a schematic diagram of the large group division result in one embodiment of the present invention;

[0056] Figure 5 This is a diagram showing the length of the overlapping portion of each group in one embodiment of the present invention;

[0057] Figure 6 This is a schematic diagram of the division of the smallest unit groups, Group 1 and Group 2, in one embodiment of the present invention;

[0058] Figure 7 This is a schematic diagram of the recombination of the smallest unit groups of group 1 and group 2 in one embodiment of the present invention;

[0059] Figure 8 This is a diagram showing the final grouping results in one embodiment of the present invention;

[0060] Figure 9 This is a flowchart of the overall algorithm implementation in one embodiment of the present invention. Detailed Implementation

[0061] The following is in conjunction with the appendix Figures 1-9 The technical solution of the present invention will be described in detail below.

[0062] This invention proposes a method for optimizing and grouping wiring harness data in power distribution cabinets, referencing...Figure 9 , including the following detailed steps:

[0063] Step 1: optimization of harness data processing.

[0064] After obtaining the harness data from the harness design software or CAD software, for each path point in each harness except the first and last path points, the differences in X, Y and Z axes between the current path point and the previous and next path points are calculated, the change amounts of the current path point in each axis are compared, and the previous and next path change directions of the current path point are positioned according to the direction with the largest change amount; if the previous and next change directions are consistent, the current path point is determined as a non-kink point, and the non-kink points are removed to obtain the optimized harness data.

[0065] Then the harness path is divided into a head part, a skeleton part and a tail part, wherein the coordinates of the skeleton part have the same Z value and can be regarded as coordinates in a two-dimensional plane.

[0066] Step 2: calculation of coincidence rate and division of large groups.

[0067] This step first calculates the lengths of the skeleton parts of the harnesses, and arranges the harnesses in descending order according to the skeleton lengths, then takes the harness with the longest skeleton as the group head of the first group, and then calculates the coincidence rate of the subsequent harnesses with the group head, finds out the group head with the largest coincidence rate, and if it meets the set threshold, the harness is divided into the group, if not, the harness is divided into the group head of a new group, and the process is repeated to finally obtain the divided large groups. The coincidence rate is calculated as follows:

[0068] The coincidence rate is calculated, that is, the coincidence degree of the skeleton parts of two wires is calculated, and if the coincidence rate η of a and b is calculated, the calculation formula is:

[0069]

[0070] In the formula: l a represents the length of the original compared skeleton a;

[0071] l b represents the length of the skeleton to be compared b;

[0072] l ab represents the length of the overlapping part of the skeleton a and the skeleton b.

[0073] For two paths, the method for calculating the coincidence rate in this paper is as follows:

[0074] 1) Each harness is divided into k sections according to the coordinate difference, and it is judged whether each section overlaps, wherein k sections are referred to the number of wire slots passed, and different path harnesses pass different wire slots, so k generally refers to the maximum number of wire slots passed;

[0075] 2) If there is overlap, it is further judged whether the point positions coincide.

[0076] Let the original comparison skeleton have a1 as the left end point coordinate and a2 as the right end point coordinate of a certain segment, and let the skeleton to be compared have b1 as the left end point coordinate and b2 as the right end point coordinate of the segment. Calculate a1-b1 and a2-b2, respectively, and then there are nine cases as shown in Table 1:

[0077] Table 1

[0078]

[0079]

[0080] 1) The results shown in ①, ②, 5, 6, 7, and 8 can be combined for judgment, i.e., (a1-b1)(a2-b2)≤0. If this is the case, then only the lengths of and need to be compared. If , then Otherwise,

[0081] 2) If it is the case shown in 9, then

[0082] 3) If it is the case shown in 3, further calculation of b2-a1 is required. If b2-a1>0, then Otherwise, the length of the segment that coincides is

[0083] 4) If it is the case shown in 4, further calculation of a2-b1 is required. If a2-b1>0, then Otherwise, the length of the segment that coincides is

[0084] Wherein is the length of the original comparison skeleton in the i-th segment, is the length of the skeleton to be compared in the i-th segment, is the length of the i-th segment that coincides,

[0085] Then

[0086] n is the number of coinciding segments,

[0087] According to formula (1), the coincidence rate η can be calculated.

[0088] Step 3: Loss rate calculation divides the minimum unit group.

[0089] The minimum unit group refers to each wire harness in the group having very similar path data and being unable to be further divided. In order to obtain the minimum unit group, the previous arrangement according to the skeleton length cannot divide the wires suitable for the minimum unit group into a group. Therefore, we re-arrange each wire harness in the group according to the length of the overlapping part. After the arrangement is completed, a loss function is established to determine the division of the minimum unit group.

[0090] Before establishing the loss function, some variables are defined:

[0091] L0: the length of the overlapping part of the original comparison wire;

[0092] L1: the length of the overlapping part of the wire to be compared;

[0093] Ax, Ay: the average value of the x, y coordinates of each inflection point of the wire harness;

[0094]

[0095] In order to compare the correlation of each wire harness, a loss function is established:

[0096] Loss = a1L len (L0, L1) + a2L pos (L0, Ax0, Ax1, Ay0, Ay1) (3)

[0097]

[0098] Wherein, j is the inflection point index, m is the number of inflection points, x j , y j are the x, y coordinates of the inflection point j, L len represents the loss rate of the overlapping length of the two wires, L pos represents the position loss rate of the two wires, a1, a2 are weight values, Ax0, Ay0 represent the average value of the x, y coordinates of each inflection point of the original comparison wire, and Ax1, Ay1 represent the average value of the x, y coordinates of each inflection point of the wire to be compared.

[0099] After re-arranging the wires in the group according to the length of the overlapping part, the loss rate of each wire and the previous wire is calculated according to the loss function. If it is less than the set threshold value, it can be divided into a minimum unit group, otherwise it is divided into a new minimum unit group. The specific steps are as follows:

[0100] (1) Calculate the skeleton overlapping length of each wire harness in the group and the remaining wire harnesses in the group, and arrange the remaining wire harnesses in the group in descending order according to the skeleton overlapping length, with the group head as the starting point;

[0101] (2) For each large group, the large group header is taken as the group header of the first minimum unit group, and the loss rate of the remaining line bundle in descending order is calculated in turn with the previous line bundle. If the set threshold is met, the current line bundle and the previous line bundle are divided into the same minimum unit group, otherwise the current is divided into a new minimum unit group

[0102] Step 4: Match degree calculation of minimum unit group recombination.

[0103] After establishing the minimum unit group, in order to get better clustering effect, the minimum unit group needs to be recombined. When combining, the line bundle position, line bundle endpoint coincidence, and the number of line bundles in each group are considered. According to this, a matching degree function is established:

[0104] Fit=b1F pos (L'0,L'1,A'x0,A'x1,A'y0,A'y1)+b2F pot (n)+b3F num (n0,n1) (6)

[0105] In the above formula, b1, b2, and b3 are weight values, L'0 and L'1 represent the group headers of two minimum unit groups, A'x0, A'y0, and A'x1, A'y1 represent the average values of the x and y coordinates of the two group headers, F pos represents the position and length matching degree of each unit group:

[0106]

[0107] d=Max(|Ax0-Ax1|,|Ay0-Ay1|) (8)

[0108] F pot represents the endpoint matching degree of each unit group, that is, the number of common inflection points:

[0109] F pot =Min(5n',10) (9)

[0110] In the above formula, n' is the number of common inflection points of two line bundles,

[0111] F num represents the number matching degree of the unit group. Since the optimal number of line bundles in each group is about 10, the number matching degree calculation formula is:

[0112]

[0113] In the above formula, n0 is the number of line bundles in the original merged minimum unit group, and n1 is the number of line bundles in the minimum unit group to be merged,

[0114] After the matching degree function is established, the matching degree between each minimum unit is calculated, and iteration is continuously performed until convergence; specifically, for each minimum unit group to be matched, the following operations are performed for minimum unit group integration until the integration of all minimum units is completed:

[0115] According to the matching degree function, the matching degree of the group header of the current minimum unit group to be matched and the group header of each remaining minimum unit group is calculated.

[0116] The minimum unit group with the largest matching degree is selected and combined with the current minimum unit group to be matched, and it is determined whether the number of harnesses after combination reaches s; if not, the minimum unit group with the largest matching degree among the remaining minimum unit groups is continuously selected for combination until the number of harnesses after combination reaches s, and the integration of the current minimum unit group to be matched is completed.

[0117] Step 5: The final grouping result is obtained by integrating the data.

[0118] An example demonstration is provided below to show the process and results of a specific implementation for a certain power distribution cabinet:

[0119] 1) Figure 1 For the harness data of a certain power distribution cabinet obtained from a CAD harness design software, the power distribution cabinet has a total of 174 harness paths;

[0120] Harness data optimization: through harness division processing, the three-dimensional coordinate harness trajectory points are converted into two-dimensional harness trajectory points with only skeletons, as shown in Figure 2 ;

[0121] 2) Arrange each harness in descending order according to the skeleton length, as shown in Figure 3 ; calculate the coincidence rate according to formula (1) to obtain the large group division result, as shown in Figure 4 ;

[0122] 3) Reorder each group according to the length of the overlapping part and calculate the loss rate to obtain each minimum unit group, taking group 1 and group 2 as examples, as shown in Figures 5-6 ;

[0123] 4) Calculate the matching degree between each minimum unit group, take the maximum value to combine, and continuously iterate until convergence, and recombine the minimum unit groups, taking group 1 and group 2 as examples, as shown in Figure 7 ;

[0124] 5) The final grouping result is obtained by integrating the data of each group, and the 174 harnesses of the power distribution cabinet are divided into 10 groups, and the grouping situation is shown in FIG. 8.

[0125] In summary, the automatic wiring of power distribution cabinet is a hot research direction at present, and the wiring in the cabinet of the traditional idea is limited by the control precision of the mechanical arm and the size of the gripper, and cannot be applied on a large scale. A more feasible way is to group the wire harness on the nail plate (outside the cabinet) and make a pre-wire harness, and then put it into the cabinet to complete the wiring. In view of this, the technical problem solved by the present application is to provide a wire harness optimization and grouping method for power distribution cabinet, which comprises: obtaining the wire harness trajectory by using wire harness simulation software or CAD software, dividing the wire harness into large groups according to the self-built coincidence rate calculation algorithm of three-dimensional coordinate characteristics, then establishing a loss function to determine the loss rate and divide the large groups into minimum unit groups, and finally establishing a matching degree function according to the wire harness length, position and number of wire harness in each group to calculate the matching degree value, and then recombine the minimum unit groups to obtain the final grouping result. This method realizes the optimization and grouping of power distribution cabinet wire harness data, provides data support for the production of pre-wire harness group on the nail plate, and greatly improves the feasibility and implementation efficiency of the automatic wiring of power distribution cabinet.

[0126] The above is the preferred embodiment of the present application, any changes made according to the technical solutions of the present application, as long as the function generated does not exceed the scope of the technical solutions of the present application, belongs to the protection scope of the present application.

Claims

1. A method for optimization and grouping of power distribution cabinet wiring harness data, comprising: Specifically comprising the following steps: S1, obtaining the wire harness data, and dividing the wire harness route into three parts of a head, a skeleton and a tail after non-inflexion point elimination is performed on the wire harness data to obtain optimized wire harness data; S2, calculating the lengths of the skeleton parts of each wire harness, and arranging the skeleton parts in descending order according to the skeleton lengths; taking the wire harness with the longest skeleton as the group head of a first group, and then calculating the coincidence rates of subsequent wire harnesses with each group head, and dividing the wire harnesses into large groups according to the coincidence rates of the skeleton parts of the wire harnesses; S3, rearranging the wire harnesses in each large group according to the lengths of the coincident parts, and establishing a loss function after the rearrangement to determine a minimum unit group; S4, establishing a matching degree function, calculating the matching degrees between each minimum unit, taking the maximum value, and iteratively converging until the final grouping result is obtained by integrating the data; The S3 specifically comprises: S31, calculating the lengths of the skeleton coincident parts of each wire harness in each large group except the group head, and arranging the remaining wire harnesses in descending order according to the lengths of the skeleton coincident parts with the group head as the starting point; S32, for each large group, taking the group head as the group head of the first minimum unit group, and calculating the loss rates of the remaining wire harnesses arranged in descending order with the previous wire harness one by one, if the loss rate meets the set threshold, the current wire harness and the previous wire harness are divided into the same minimum unit group, otherwise the current wire harness is divided into a new minimum unit group; The establishment of the loss function specifically comprises: Define variables: L0 is the length of the coincident part of the original comparison wire; L1 is the length of the coincident part of the wire to be compared; Ax and Ay are the average values of the x and y coordinates of each inflection point of the wire harness respectively: Establish a loss function: Loss = a1L len (L0, L1) + a2L pos (L0, Ax0, Ax1, Ay0, Ay1) (3) wherein j is an index of the inflection point, m is the number of inflection points, x j , y j are the x, y coordinates of the inflection point j, L len represents the coincidence length loss rate of the two conductors, L pos represents the coincidence position loss rate of the two conductors, a1, a2 are weight values, Ax0, Ay0 represent the average values of the x, y coordinates of the original comparison conductor, and Ax1, Ay1 represent the average values of the x, y coordinates of the conductor to be compared.

2. The method of claim 1, wherein, The optimized wire harness data obtained by performing non-inflexion point elimination on the wire harness data specifically comprises: for each path point in each wire harness except the first and last path points, calculating the differences of the path points in X, Y and Z axes, comparing the size of the changes of the path points in each axis, and positioning the front and rear path change direction of the current path point according to the direction with the largest change; if the front and rear change directions are consistent, it is determined as a non-inflexion point, and the non-inflexion point is eliminated to obtain the optimized wire harness data.

3. The method of claim 1, wherein, The coordinates of the skeleton part have the same Z value.

4. The method of claim 1, wherein, The large group division of the wire harness according to the coincidence rate of the skeleton part of the wire harness specifically comprises: finding the group head with the maximum coincidence rate with the current wire harness, if the maximum coincidence rate meets the set threshold, the current wire harness is divided into the large group corresponding to the group head with the maximum coincidence rate; if not, the current wire harness is divided into the group head of a new group.

5. The method of claim 1, wherein, The calculation of the coincidence rate of the skeleton part of the wire harness is specifically as follows: wherein: l b represents the length of the skeleton b to be compared; l ab represents the length of the coinciding part of the original comparison skeleton a and the skeleton b to be compared.

6. The method for optimization and grouping of power distribution cabinet wiring harness data according to claim 5, characterized in that, The length calculation of the coincident part of the original comparison skeleton a and the wire to be compared b is specifically as follows: 1) dividing the original comparison skeleton a and the wire to be compared b into k segments according to the coordinate difference, and judging whether each segment has coincidence; 2) if there is coincidence, further judging whether the point positions coincide; Let the left end point of the i-th segment of the original comparison skeleton a have a coordinate a1 in the skeleton length direction, and the right end point have a coordinate a2 in the skeleton length direction; let the left end point of the i-th segment of the skeleton to be compared b have a coordinate b1 in the skeleton length direction, and the right end point have a coordinate b2 in the skeleton length direction; calculate a1-b1 and a2-b2 respectively; the length of the original comparison skeleton a in the i-th segment is the length of the skeleton to be compared b in the i-th segment is the coinciding length in the i-th segment of the two line beams; If (al-bl)(a2-b2) < 0, then compare with the length of the interval; if there then else If (a1-b1) > 0 and (a2-b2) > 0, then calculate b2-a1; if b2-a1 > 0, then Otherwise If (a1-b1) < 0 and (a2-b2) < 0, then calculate a2-b1; if a2-b1 > 0, then Otherwise 3) calculating the length of the coincident part of the original comparison skeleton a and the wire to be compared b: In the formula, n is the number of coincident segments.

7. The method of claim 1, wherein, The establishment of the matching degree function specifically comprises: Fit = b1F pos (L'0, L'1, A'x0, A'x1, A'y0, A'y1) + b2F pot (n') + b3F num (n0, n1) (6) where b1, b2, b3 are weight values, L'0 and L'1 represent the group heads of the two groups of minimum unit groups, A'x0, A'y0 and A'x1, A'y1 represent the average values of the x, y coordinates of the respective inflection points of the two group heads, F pos represents the position, length matching degree of each unit group: d=Max(|Ax0-Ax1|,|Ay0-Ay1|) (8) F pot represents the end point match degree of each unit group, i.e. the number of common inflection points: F pot = Min(5n', 10) (9) In the formula, n' is the number of common inflection points of two line bundles, F num representing a number of unit groups matching degree: In the formula, n0 is the number of line bundles of the original combined minimum unit group, n1 is the number of line bundles of the minimum unit group to be combined, and s is a preset optimal number of line bundles per group.

8. The method of claim 7, wherein, The S4 specifically comprises, for each minimum unit group to be matched, performing the following operations for minimum unit group integration until the integration of all minimum units is completed: calculating the matching degree of the group head of the current minimum unit group to be matched and the group head of each remaining minimum unit group according to the matching degree function; selecting the minimum unit group with the largest matching degree from the remaining minimum unit groups to combine with the current minimum unit group to be matched, and determining whether the number of line bundles after the combination reaches s; if not, the minimum unit group with the largest matching degree from the remaining minimum unit groups is continuously selected for combination until the number of line bundles after the combination reaches s, and the integration of the current minimum unit group to be matched is completed.

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