Series structure part selective assembly method based on KM algorithm

Abstract

The invention relates to the technical field of mechanical product part assembly, in particular to a series structure part selection assembly method based on a KM algorithm, and the method comprises the steps: obtaining a plurality of to-be-selected parts in a series assembly structure; establishing a part information matrix of each part in each type of parts to be selected and matched; establishing an assembly relation constraint matrix between two adjacent to-be-selected parts; according to the assembly relation constraint matrix, two adjacent parts in the series structure are matched through a KM algorithm, and matching result matrixes of the two adjacent parts are obtained respectively; the matching result matrixes of all the two adjacent parts are subjected to optimization combination, and an overall optimal assembly matrix is obtained; and outputting a part pairing scheme according to the overall optimal assembly matrix. According to the invention, the problem of selective assembly of parts with series structures is solved, and the assembly success rate and the assembly efficiency of the parts are improved.

Description

Technical Field

[0001] The invention relates to the technical field of assembly of mechanical product parts, and in particular to a method for selecting and assembling serial structure parts based on a KM algorithm. Background Art

[0002] The assembly of mechanical products is a key link in controlling product quality. Assembly accuracy, quality consistency and efficiency are important factors that restrict product performance and mass production. In the assembly of some parts with high assembly accuracy requirements, due to processing costs, the processing accuracy of parts cannot meet the needs of direct interchangeable assembly. Experienced workers are required to conduct multiple trial installations and repeated adjustments, which seriously affects the assembly efficiency and production capacity requirements of the products. At the same time, human factors such as wrong selection and rough installation increase the safety hazards of the products. Therefore, the selection of assembly methods is often used in the assembly of such parts. This method optimizes the pairing relationship between the parts to make more parts meet the assembly accuracy requirements, thereby improving the assembly success rate and assembly efficiency.

[0003] As a common assembly structure of parts in mechanical products, the selection and assembly problem of the serial structure is a key problem that needs to be solved in the assembly process of mechanical products. Traditional selection and assembly methods are often based on intelligent optimization algorithms such as evolutionary algorithms. Due to the limitations of the characteristics of such algorithms, it is necessary to construct individual styles in the initial population according to the number of parts to be selected, resulting in the solution time for the problem of parts selection and assembly increasing exponentially with the increase in the number of parts, and the solution effect cannot meet the high quality requirements. Summary of the invention

[0004] In order to solve the above technical problems, the present invention provides a method for selecting and assembling components of a serial structure based on a KM algorithm. The algorithm has higher solution stability, solution effect and solution quality, and can well solve the problem of selecting and assembling components of a serial structure, thereby improving the assembly success rate and efficiency of such components.

[0005] The first object of the present invention is to provide a method for selecting and assembling parts of a series structure based on a KM algorithm, comprising:

[0006] Acquire multiple parts to be selected in a serial assembly structure, wherein the serial assembly structure is sequentially composed of multiple parts in series, and each part to be selected includes multiple parts;

[0007] Establish a parts information matrix for each part in each type of parts to be selected;

[0008] An assembly relationship constraint matrix between two adjacent parts to be selected is established according to the part information matrix of each part;

[0009] According to the assembly relationship constraint matrix, the KM algorithm is used to match the two adjacent parts in the series structure, and the matching result matrices of the two adjacent parts are obtained respectively;

[0010] Optimize and combine the matching result matrices of all two adjacent parts to obtain the overall optimal assembly matrix;

[0011] Output the pairing scheme of parts according to the overall optimal assembly matrix.

[0012] Preferably, each element in the assembly relationship constraint matrix represents whether the two parts meet the assembly accuracy requirement. If the two parts meet the assembly requirement, the corresponding element is 1, otherwise it is 0.

[0013] Preferably, according to the assembly relationship constraint matrix, the KM algorithm is used to match two adjacent parts in the series structure, including:

[0014] Step 3.1: According to the assembly relationship constraint matrix, establish the weight matrix between the two parts;

[0015] Step 3.2: Initialize the top labels of the two part information matrices according to the weight matrix between the two parts;

[0016] Step 3.3: Perform an augmentation operation on an element in one part information matrix to determine whether an element in another part information matrix and the element meet the assembly accuracy requirement;

[0017] If the assembly requirements are not met, go to step 3.4;

[0018] If the assembly requirements are met, go to step 3.5;

[0019] Step 3.4: record the elements accessed in the two part information matrices during the augmentation operation; update the top marks of the two part information matrices, and return to step 3.3;

[0020] Step 3.5: performing an augmentation operation on the remaining elements in the one part information matrix, and calculating a matching result matrix between the two parts according to the matching relationship of the elements;

[0021] Step 3.6: Repeat steps 3.1 to 3.5 to calculate the matching result matrix of two adjacent parts in turn.

[0022] Preferably, when establishing a weight matrix between two parts, when an element in the assembly relationship constraint matrix is ​​1, the corresponding weight between the two parts is calculated; when an element in the assembly relationship constraint matrix is ​​0, the corresponding element in the weight matrix is ​​0.

[0023] Preferably, the matching result matrices of all two adjacent parts are optimized and combined to obtain the overall optimal assembly matrix, including:

[0024] From the matching result matrix of the first part and the second part, and the matching result matrix of the second part and the third part, obtain the elements corresponding to the co-existing second part.

[0025] Combine the elements corresponding to the second type of parts that exist together with the elements corresponding to the first type of parts and the second type of parts, respectively, to obtain the optimal assembly matrix of the three types of parts in series;

[0026] Then, the common elements are searched in the optimal assembly matrix of the three parts and the matching result matrix of the third part and the fourth part, and they are combined in sequence until the overall optimal assembly matrix is ​​obtained.

[0027] Preferably, the method further comprises: obtaining an assembly body that meets the assembly precision requirement according to the overall optimal assembly, and obtaining an assembly success rate according to the assembly body that meets the assembly precision requirement.

[0028] The second object of the present invention is a computer program product, comprising a computer program, characterized in that when the computer program is executed by a processor, a method for selecting and assembling serial structure parts based on a KM algorithm is implemented.

[0029] The third object of the present invention is an electronic device, characterized in that it includes:

[0030] Processor; and

[0031] A memory, configured to store executable instructions of the processor;

[0032] The processor is configured to execute the serial structure parts selection and assembly method based on the KM algorithm by executing the executable instructions.

[0033] A fourth object of the present invention is a serial structure parts selection and assembly system based on a KM algorithm, comprising:

[0034] A data acquisition module is used to obtain a plurality of parts to be selected in a serial assembly structure, wherein the serial assembly structure is sequentially composed of a plurality of parts in series, and each of the parts to be selected includes a plurality of parts;

[0035] Construct a constraint matrix module, which is used to establish a part information matrix of each part in each type of parts to be selected; and establish an assembly relationship constraint matrix between two adjacent parts to be selected based on the part information matrix of each part;

[0036] The optimal assembly module is used to match two adjacent parts in the series structure using the KM algorithm according to the assembly relationship constraint matrix, and obtain the matching result matrices of the two adjacent parts respectively; optimize the matching result matrices of all two adjacent parts to obtain the overall optimal assembly matrix; and output the pairing plan of the parts according to the overall optimal assembly matrix.

[0037] The present invention has at least the following beneficial effects:

[0038] The present invention can solve the selective assembly problem of multiple parts in series by setting the weights in the KM algorithm. When there are many types and quantities of parts, the invention has higher solution stability, solution efficiency and solution quality than the prior art, which helps to improve the assembly success rate and assembly efficiency of such parts, reduce production costs, and promote the development of intelligent manufacturing technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a schematic diagram of the series structure parts;

[0040] Figure 2 The technical flow chart of the KM algorithm for selecting the assembly method of serial structure parts;

[0041] Figure 3 It is the front view of the arc-tooth servo mechanism of the position marker;

[0042] Figure 4 This is a cross-sectional view of the arc-tooth servo mechanism of the position marker. DETAILED DESCRIPTION

[0043] In order to illustrate the technical means and effects adopted by the present invention to achieve the predetermined purpose of the invention, the following is a detailed description in conjunction with embodiments.

[0044] The purpose of the present invention is to provide a method for selecting and assembling parts of a serial structure based on a KM algorithm. The method has higher solution stability and solution effect, can well solve the problem of selecting and assembling parts of a serial structure, and improve the assembly success rate and assembly efficiency of such parts.

[0045] In order to achieve the above object, the present invention provides a method for selecting and assembling serial structure parts based on the KM algorithm, comprising:

[0046] S1. Acquire multiple parts to be selected in a serial assembly structure, wherein the serial assembly structure is sequentially composed of multiple parts in series, and each part to be selected includes multiple parts;

[0047] When obtaining multiple parts to be selected in a serial assembly structure, first determine whether the parts to be selected are a serial assembly structure, including:

[0048] Step 1.1: The parts to be selected are recorded as P1, P2, ..., P n .

[0049] Step 1.2: Determine part P i Is it only with P j (j=i+1 or j=i-1) there is a matching relationship. If the above judgment is established, the part to be selected is a serial structure part.

[0050] Step 1.3: If the part to be matched is a serial structure part, the method of the present invention can be used to solve the part matching scheme and proceed to the next step.

[0051] See also Figure 1 As shown, P1, P2, ..., P n The various parts connected in series are respectively called serial assembly structures.

[0052] S2, establishing a part information matrix for each part in each type of parts to be selected;

[0053] An assembly relationship constraint matrix between two adjacent parts to be selected is established according to the part information matrix of each part;

[0054] For example, for n types of parts, the number of each type of part is N. n The part information matrix of each part is established for the serial structure parts selection problem.

[0055]

[0056] in For part P n Nth n Dimensional information of each part.

[0057] Each element in the assembly relationship constraint matrix represents whether the two parts meet the assembly accuracy requirements. If the two parts meet the assembly requirements, the corresponding element is 1, otherwise it is 0.

[0058] Establish the assembly relationship constraint matrix between the two parts. For the quantities N i and N j Parts P i and P j , if part P i The mth part P im With part P j The nth part P in The assembly accuracy requirements are met, and the assembly relationship element a between the two mn is 1 if the value is set to true, otherwise it is 0.

[0059]

[0060] In the formula, A ij Represents two parts P i With P j The assembly relationship constraint matrix between them; Indicates part P i The last part of the j The assembly relationship element between the last parts.

[0061] S3, according to the assembly relationship constraint matrix, using the KM algorithm to match the two adjacent parts in the series structure, and respectively obtain the matching result matrix of the two adjacent parts;

[0062] According to the assembly relationship constraint matrix, the KM algorithm is used to match two adjacent parts in the series structure, including:

[0063] Step 3.1: According to the assembly relationship constraint matrix, establish the weight matrix between the two parts;

[0064] Step 3.2: Initialize the top labels of the two part information matrices according to the weight matrix between the two parts;

[0065] Step 3.3: Perform an augmentation operation on an element in one part information matrix to determine whether an element in another part information matrix and the element meet the assembly accuracy requirement;

[0066] If the assembly requirements are not met, go to step 3.4;

[0067] If the assembly requirements are met, go to step 3.5;

[0068] Step 3.4: record the elements accessed in the two part information matrices during the augmentation operation; update the top marks of the two part information matrices, and return to step 3.3;

[0069] Step 3.5: performing an augmentation operation on the remaining elements in the one part information matrix, and calculating a matching result matrix between the two parts according to the matching relationship of the elements;

[0070] Step 3.6: Repeat steps 3.1 to 3.5 to calculate the matching result matrix of two adjacent parts in turn.

[0071] When establishing the weight matrix between two parts, when the element in the assembly relationship constraint matrix is ​​1, the corresponding weight between the two parts is calculated; when the element in the assembly relationship constraint matrix is ​​0, the corresponding element in the weight matrix is ​​0.

[0072] In this embodiment, the KM algorithm is used to match two adjacent parts in the series structure, and the matching result matrix of the two adjacent parts is obtained in sequence, including:

[0073] Step 3.1: Establish a weight matrix between two parts according to the assembly relationship constraint matrix. When the element in the assembly relationship constraint matrix is ​​1, calculate the corresponding weight matrix;

[0074] Select the assembly model according to the part to establish the part P i＝1,2,…,n-1 and part P j＝i+1 The weight matrix between the parts P. i The mth part P im With part P j The nth part P in The weight element ω mn :

[0075]

[0076] Where ω(P im P (i-1)k ) is part P i The mth part and part P (i-1) The weight between the kth parts, ω(P jn P (j+1)k ) is part P j The nth part and part P (j+1) The weight between the kth parts. For part P i-1 The priority coefficient of For part P j+1 The priority coefficient of the part. The higher the priority coefficient, the higher the priority of the part in the assembly, and its assembly success rate must be given priority.

[0077] Step 3.2: Initialize part P i With part P j Top label of the part information matrix.

[0078] l(P im )=max(ω(P im P jn ))

[0079] l(P jn )=0

[0080] In the formula, l(P im ) is part P i The top mark of the mth part, l(P jn ) is part P j The top mark of the nth part.

[0081] Step 3.3: For part P i The element P in the part information matrix im Perform augmentation operation. Use the formula to determine the part Pj The element P in the part information matrix jn With element P im Whether the assembly accuracy requirements are met.

[0082] l(P im )+l(P jn )-ω(P im P jn )=0

[0083] If the assembly requirements are not met, continue to judge element P j(n+1) With element P im Whether the assembly accuracy requirements are met until the part P j The last element in the part information matrix Complete the judgment. If there is no element P im Find the matching element and proceed to step 3.4.

[0084] If the assembly requirements are met, if the current target element P jn If there is no matching element or a new matching element can be found, the current element P jn Become the current element P im , and go to step 3.5.

[0085] Step 3.4: Record the elements visited during the augmentation process. Create a set S ij and T ij Record the parts P visited during the augmentation process i With part P j The elements in the information matrix; and update the part P i With part P j The top label of the part information matrix. Use the top label update formula to update the part P i With part P j The top label l of the visited element in the part information matrix and return to step 3.3.

[0086]

[0087] Step 3.5: Part P i The remaining elements in the part information matrix are augmented, and the part P is calculated based on the matching relationship of the elements. i With part P j The matching result matrix R i .

[0088] Step 3.6: Repeat steps 3.1 to 3.5 to calculate the matching result matrix R between the remaining adjacent types of parts. i+1 ,R i+2 ,…,R n-1 .

[0089] S4, optimizing and combining the matching result matrices of all two adjacent parts to obtain the overall optimal assembly matrix;

[0090] Output the pairing scheme of parts according to the overall optimal assembly matrix.

[0091] In the present invention, an overall matching result matrix is ​​established to record the matching results.

[0092]

[0093] In the formula, m is the number of assemblies that meet the requirements in the current selected assembly solution X, n is the type of parts to be selected, For part P n The element used for the mth assembly in the currently selected assembly solution X.

[0094] Based on the overall matching result matrix, the combinations that can be matched are recorded in the matching result matrix, so as to obtain the overall optimal assembly matrix; the details are as follows.

[0095] The matching result matrices of all two adjacent parts are optimized and combined to obtain the overall optimal assembly matrix, including:

[0096] From the matching result matrix of the first part and the second part, and the matching result matrix of the second part and the third part, obtain the elements corresponding to the co-existing second part.

[0097] Combine the elements corresponding to the second type of parts that exist together with the elements corresponding to the first type of parts and the second type of parts, respectively, to obtain the optimal assembly matrix of the three types of parts in series;

[0098] Then, the common elements are searched in the optimal assembly matrix of the three parts and the matching result matrix of the third part and the fourth part, and they are combined accordingly until the overall optimal assembly matrix is ​​obtained.

[0099] Optimize and combine the obtained n-1 matching result matrices to obtain the overall matching result matrix. Search for the common element P2 in R1 and R2, and combine the elements P1 and P3 that match these elements with these elements to generate the optimal assembly matrix R′ for parts P1, P2 and P3. Then search for the common element P3 in R′ and R3, retain the row vector where the above element is located, and add the matching element P4 of the above element in R3 to R′ to obtain the new R′, that is, the optimal assembly matrix of parts P1 to P4. Repeat the above steps until the overall optimal assembly matrix R is obtained.

[0100] The present invention further comprises: obtaining an assembly body that meets the assembly precision requirement according to the overall optimal assembly, and obtaining an assembly success rate according to the assembly body that meets the assembly precision requirement.

[0101] Evaluation index based on assembly success rate. Assembly success rate: After selecting and assembling, a total of m groups of assemblies that meet the assembly accuracy requirements are obtained. The assembly success rate of the selected solution δ c The calculation is as follows:

[0102]

[0103] Where n is the type of parts, N k is the number of each type of parts.

[0104] In order to illustrate a method for selecting and assembling parts of a series structure based on a KM algorithm provided by the present invention, it is described in conjunction with the accompanying drawings.

[0105] Taking the arc tooth servo mechanism of the position marker as an example, Figure 3 and Figure 4 The arc-toothed position marker servo mechanism shown in the figure needs to meet the assembly clearance requirements for the positioning holes, radial fixed shafts and bearings. The size information and assembly requirements of each part are shown in Table 1:

[0106] Table 1 Dimension information and assembly requirements of each part

[0107]

[0108] The assembly clearance between the locating hole and the radial fixed shaft is calculated as follows:

[0109]

[0110] The assembly clearance between the radial fixed shaft and the bearing is calculated as follows:

[0111]

[0112] It can be seen that if all the parts to be assembled are randomly interchanged, the assembly clearance between the shaft and the hole will change to 14μm, and the assembly clearance between the shaft and the bearing will change to 9μm, which are far from the assembly requirements. When the product is mass-produced, a large part of the parts will not meet the assembly requirements, which will seriously restrict the assembly efficiency and output of the product, so it is necessary to perform matching operations on them.

[0113] The 50 groups of parts to be assembled collected were analyzed as shown in Table 2. The individual part size deviation in the table is the error of the actual measured size of the part relative to the standard size.

[0114] Table 2 Dimensional deviations of 50 groups of assembled parts collected for each part

[0115]

[0116] like Figure 2 As shown, the present invention discloses a method for selecting and assembling serial structure parts based on the KM algorithm, which is aimed at the problem of selecting and assembling parts of the arc tooth servo mechanism of the marker, and includes the following steps:

[0117] Step 1: Determine whether the part to be selected is a serial assembly structure.

[0118] Furthermore, step 1 includes the following steps:

[0119] Step 1.1: Label the positioning hole, radial fixing shaft and bearing as P1, P2 and P3.

[0120] Step 1.2: Determine part P i Is it only with P j (j=i+1 or j=i-1) there is a matching relationship. If the above judgment is established, the part to be selected is a serial structure part.

[0121] In this example, P1 only has a matching relationship with P2, and P3 only has a matching relationship with P2. Figure 1 The serial structure parts shown have 3 parts.

[0122] Step 1.3: If the parts to be matched are serial structure parts, the method of the present invention can be used to solve the parts matching scheme and then proceed to step 2.

[0123] Step 2: Construct the selection assembly model of the parts to be selected.

[0124] Further, step 2 includes the following steps:

[0125] Step 2.1: For n types of parts, the number of each type is N. n The part information matrix of each part is established for the serial structure parts selection problem.

[0126]

[0127] In this example, there are 3 types of parts, and the quantity of each type of part is 50.

[0128] Step 2.2: Establish the assembly relationship constraint matrix between the two parts. i and N j Parts P i and P j , if part P i The mth part P im With part P j The nth part P inThe assembly accuracy requirements are met, and the assembly relationship element a between the two mn is 1 if the value is set to true, otherwise it is 0.

[0129]

[0130] In this example, the assembly relationship constraint matrix A is constructed based on the part size information and assembly clearance requirements. 12 and A 23 .

[0131] Step 2.3: Establish the overall matching result matrix to record the matching results.

[0132]

[0133] Step 2.4: Evaluation index based on assembly success rate. Assembly success rate: After selecting and assembling, a total of m groups of assemblies that meet the assembly accuracy requirements are obtained. The assembly success rate of the selected solution δ c The calculation is as follows:

[0134]

[0135] In this example, n=3, N k =50.

[0136] Step 3: Use the serial structure parts selection and assembly method based on the KM algorithm to solve the selection and assembly model of the parts to be selected and obtain the parts pairing solution.

[0137] Further, step 3 includes the following steps:

[0138] Step 3.1: Select the assembly model according to the part to establish the part P i＝1,2,…,n-1 and part P j＝i+1 The weight matrix between the parts P. i The mth part P im With part P j The nth part P in The weight element ω mn :

[0139]

[0140] In this example, all parts have the same priority, so First, a weight matrix between part P1 and part P2 is established.

[0141] Step 3.2: Initialize part P i With part P j Top label of the part information matrix.

[0142] l(P im)=max(ω(P im P jn ))

[0143] l(P jn )=0

[0144] In this example, the top labels of the part information matrices of part P1 and part P2 are initialized first.

[0145] Step 3.3: For part P i The element P in the part information matrix im Perform augmentation operation. Use the formula to determine the part P j The element P in the part information matrix jn With element P im Whether the assembly accuracy requirements are met.

[0146] l(P im )+l(P jn )-ω(P im P jn )=0

[0147] If the assembly requirements are met, if the current target element P jn If there is no matching element or a new matching element can be found, the current element P jn Become the current element P im If the assembly requirements are not met, continue to determine the matching element P. j(n+1) With element P im Whether the assembly accuracy requirements are met until the part P j The last element P in the part information matrix jNj Complete the judgment. If there is no element P im Find the matching element and proceed to step 3.4.

[0148] In this example, firstly, the element P in the part information matrix of part P1 is 1-1 Perform augmentation operations to find matching elements for it. If you access the element P in the part information matrix of part P2 2-50 The first pair of elements P 1-1 If the match is successful, go to step 3.6; if the element P in the part information matrix of access part P2 2-50 After that, there is still no element P 1-1 If the match is successful, go to step 3.4.

[0149] Step 3.4: Record the elements visited during the augmentation process. Create a set S ij and T ij Record the elements in the information matrix of parts Pi and Pj that have been visited during the augmentation process.

[0150] In this example, we first create a set S 12 and T 12 Record the elements in the information matrix of parts P1 and P2 that have been visited during the augmentation process.

[0151] Step 3.5: Update Part P i With part P j The top label of the part information matrix. Use the top label update formula to update the part P i With part P j The top label l of the visited element in the part information matrix and return to step 3.3.

[0152]

[0153] In this example, the top mark update formula is first used to update the top marks l of the visited elements in the part information matrices of part P1 and part P2.

[0154] Step 3.6: For part P i The remaining elements in the part information matrix are augmented, and the part P is calculated based on the matching relationship of the elements. i With part P j The matching result matrix R i .

[0155] In this example, for the remaining parts P in part P1 1-2 To P 1-50 Perform an augmentation operation to obtain the matching result matrix R1 of P1 and part P2.

[0156] Step 3.7: Repeat steps 3.1 to 3.6 to calculate the matching result matrix R of the remaining parts. i+1 ,R i+2 ,…,R n-1 .

[0157] In this example, steps 3.1 to 3.6 are repeated to calculate the matching result matrix R2 of parts P2 and P3.

[0158] Step 3.8: Optimize and combine the obtained n-1 matching result matrices to obtain the overall matching result matrix. Search for the common element P2 in R1 and R2, and combine the elements P1 and P3 that match these elements with these elements to generate the optimal assembly matrix R′ for parts P1, P2 and P3. Then search for the common element P3 in R′ and R3, retain the row vector where the above element is located, and add the matching element P4 of the above element in R3 to R′ to obtain the new R′, which is the optimal assembly matrix of parts P1 to P4. Repeat the above steps until the overall optimal assembly matrix R is obtained. X .

[0159] In this example, the commonly existing element P2 is searched in R1 and R2, and the elements P1 and P3 matching these elements are combined with these elements to generate the overall optimal assembly matrix R of parts P1, P2 and P3.

[0160] Step 3.9: Output the matching scheme of parts according to the overall optimal assembly matrix. The matching scheme of parts is shown in Table 3:

[0161] Table 3 Parts matching scheme

[0162]

[0163]

[0164] The matching result R between part Pi (i>=0) and part Pj (j=i+1<=n) can be obtained by using the classic Hungarian algorithm. i The maximum number of matches N Ri , then the overall matching quantity range can be calculated as follows:

[0165]

[0166] In this example The total maximum number of matches is 44, and the corresponding assembly success rate is 88%. The assembly success rate obtained by the serial structure parts selection assembly method based on the KM algorithm can reach the theoretical maximum value.

[0167] Comparing the matching results under different numbers of parts as shown in Table 4, it can be seen that the serial structure parts selection and assembly method based on the KM algorithm has a stable solution effect when dealing with the selection and assembly problem of large quantities of parts, and the solution time is roughly proportional to the number of parts, which can well solve the selection and assembly problem of large quantities of parts.

[0168] Table 4 compares the matching results under different numbers of parts

[0169]

[0170] Comparing the matching results under different assembly clearance requirements as shown in Table 5, it can be seen that the serial structure parts selection and assembly method based on the KM algorithm has a stable solution effect when dealing with the selection and assembly problems of parts with different assembly accuracy requirements, and can well solve the selection and assembly problems of parts with different assembly accuracy requirements.

[0171] Table 5 compares the matching results under different assembly clearance requirements

[0172]

[0173] The present invention provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the method for selecting and assembling serial structure parts based on the KM algorithm is implemented.

[0174] The present invention provides an electronic device, comprising:

[0175] Processor; and

[0176] A memory, configured to store executable instructions of the processor;

[0177] Wherein, the processor is configured to execute the above-mentioned serial structure parts selection and assembly method based on the KM algorithm by executing the executable instructions.

[0178] The present invention provides a series structure parts selection and assembly system based on KM algorithm, comprising:

[0179] A data acquisition module is used to obtain a plurality of parts to be selected in a serial assembly structure, wherein the serial assembly structure is sequentially composed of a plurality of parts in series, and each of the parts to be selected includes a plurality of parts;

[0180] Construct a constraint matrix module, which is used to establish a part information matrix of each part in each type of parts to be selected; and establish an assembly relationship constraint matrix between two adjacent parts to be selected based on the part information matrix of each part;

[0181] The optimal assembly module is used to match two adjacent parts in the series structure using the KM algorithm according to the assembly relationship constraint matrix, and obtain the matching result matrices of the two adjacent parts respectively; optimize the matching result matrices of all two adjacent parts to obtain the overall optimal assembly matrix; and output the pairing plan of the parts according to the overall optimal assembly matrix.

[0182] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for selecting and assembling serial structure parts based on KM algorithm, characterized in that: include: Acquire multiple parts to be selected in a serial assembly structure, wherein the serial assembly structure is sequentially composed of multiple parts in series, and each part to be selected includes multiple parts; Establish a parts information matrix for each part in each type of parts to be selected; An assembly relationship constraint matrix between two adjacent parts to be selected is established according to the part information matrix of each part; According to the assembly relationship constraint matrix, the KM algorithm is used to match the two adjacent parts in the series structure, and the matching result matrices of the two adjacent parts are obtained respectively; Optimize and combine the matching result matrices of all two adjacent parts to obtain the overall optimal assembly matrix; Output the pairing scheme of parts according to the overall optimal assembly matrix.

2. The method for selecting and assembling serial structure parts based on the KM algorithm according to claim 1 is characterized in that: Each element in the assembly relationship constraint matrix represents whether the two parts meet the assembly accuracy requirements. If the two parts meet the assembly requirements, the corresponding element is 1, otherwise it is 0.

3. The method for selecting and assembling serial structure parts based on KM algorithm according to claim 1, characterized in that: According to the assembly relationship constraint matrix, the KM algorithm is used to match two adjacent parts in the series structure, including: Step 3.1: According to the assembly relationship constraint matrix, establish the weight matrix between the two parts; Step 3.2: Initialize the top labels of the two part information matrices according to the weight matrix between the two parts; Step 3.3: Perform an augmentation operation on an element in one part information matrix to determine whether an element in another part information matrix and the element meet the assembly accuracy requirement; If the assembly requirements are not met, go to step 3.4; If the assembly requirements are met, go to step 3.5; Step 3.4: record the elements accessed in the two part information matrices during the augmentation operation; update the top marks of the two part information matrices, and return to step 3.3; Step 3.5: performing an augmentation operation on the remaining elements in the one part information matrix, and calculating a matching result matrix between the two parts according to the matching relationship of the elements; Step 3.6: Repeat steps 3.1 to 3.5 to calculate the matching result matrix of two adjacent parts in turn.

4. The method for selecting and assembling serial structure parts based on the KM algorithm according to claim 3 is characterized in that: When establishing the weight matrix between two parts, when the element in the assembly relationship constraint matrix is ​​1, the corresponding weight between the two parts is calculated; when the element in the assembly relationship constraint matrix is ​​0, the corresponding element in the weight matrix is ​​0.

5. The method for selecting and assembling serial structure parts based on KM algorithm according to claim 1, characterized in that: The matching result matrices of all two adjacent parts are optimized and combined to obtain the overall optimal assembly matrix, including: From the matching result matrix of the first part and the second part, and the matching result matrix of the second part and the third part, obtain the elements corresponding to the co-existing second part. Combine the elements corresponding to the second type of parts that exist together with the elements corresponding to the first type of parts and the second type of parts, respectively, to obtain the optimal assembly matrix of the three types of parts in series; Then, the common elements are searched in the optimal assembly matrix of the three parts and the matching result matrix of the third part and the fourth part, and they are combined in sequence until the overall optimal assembly matrix is ​​obtained.

6. The method for selecting and assembling serial structure parts based on KM algorithm according to claim 1, characterized in that: Also includes: An assembly that meets the assembly accuracy requirement is obtained according to the overall optimal assembly, and the assembly success rate is obtained according to the assembly that meets the assembly accuracy requirement.

7. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for selecting and assembling serial structure parts based on the KM algorithm according to any one of claims 1 to 6 is implemented.

8. An electronic device, characterized in that: include: processor; as well as A memory, configured to store executable instructions of the processor; The processor is configured to execute the serial structure parts selection and assembly method based on the KM algorithm according to any one of claims 1 to 6 by executing the executable instructions.

9. A serial structure parts selection and assembly system based on KM algorithm, characterized in that: include: A data acquisition module is used to obtain a plurality of parts to be selected in a serial assembly structure, wherein the serial assembly structure is sequentially composed of a plurality of parts in series, and each of the parts to be selected includes a plurality of parts; Construct a constraint matrix module, which is used to establish a part information matrix of each part in each type of parts to be selected; and establish an assembly relationship constraint matrix between two adjacent parts to be selected based on the part information matrix of each part; The optimal assembly module is used to match two adjacent parts in the series structure using the KM algorithm according to the assembly relationship constraint matrix, and obtain the matching result matrices of the two adjacent parts respectively; optimize the matching result matrices of all two adjacent parts to obtain the overall optimal assembly matrix; and output the pairing plan of the parts according to the overall optimal assembly matrix.

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