CN110598279A - Method and device for planning part machining process route - Google Patents

Method and device for planning part machining process route Download PDF

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CN110598279A
CN110598279A CN201910800482.1A CN201910800482A CN110598279A CN 110598279 A CN110598279 A CN 110598279A CN 201910800482 A CN201910800482 A CN 201910800482A CN 110598279 A CN110598279 A CN 110598279A
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卢杰
潘青姑
徐劲力
胡云锋
刘晓刚
黄丰云
邹琳
吴波
张晓帆
卢佩航
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Wuhan University of Technology WUT
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Abstract

The invention relates to the technical field of part process design, and discloses a part processing process route planning method, which comprises the following steps: acquiring characteristic information of a to-be-machined surface of a target part, and matching a machining method chain according to the characteristic information; decomposing the processing method chain into a plurality of processing elements based on a processing element generation rule; sorting each processing element by adopting an ant colony algorithm based on an elite strategy; and planning a process route according to the sorted processing elements. The invention has the technical effects of accurate chain matching of the processing method and high sorting efficiency of the processed elements.

Description

Method and device for planning part machining process route
Technical Field
The invention relates to the technical field of part process design, in particular to a method and a device for planning a part machining process route.
Background
The process route planning is a set of feature processing primitive combinations that impose a series of constraints on each feature processing chain. For many manufacturing enterprises, an efficient, low-cost, high-quality production mode will have a significant impact on the survival, competition, and development of the enterprise.
Aiming at the research of process route sequencing optimization, many people adopt a method of firstly dividing the characteristics of parts to form a processing chain based on characteristic processing and aiming at the priority of each processing element in the processing chain. Meanwhile, the influence of the transformation of the machine tool and the cutter on the process route scheme is also considered, the process route scheme is taken as an optimization target, and the obtained process route scheme meets the requirement of low processing cost by adopting a relevant algorithm for solving and calculating.
The problems existing in the prior art are as follows: in many researches, when a part process route sequencing decision is considered, in the tool selection of a part feature machining method, one feature machining can be finished once, and the rough machining and the fine machining of some features are not considered and can be finished in different tools; the currently adopted research algorithms are single algorithms, however, each algorithm has certain advantages and disadvantages, and certain limitations exist in solving the process route scheme.
Disclosure of Invention
The invention aims to overcome the technical defects, provides a part processing process route planning method and a part processing process route planning device, and solves the technical problems that in the prior art, part processing is divided according to characteristics, and a matching processing method chain is inaccurate and the sorting efficiency is low due to a single solution of a sorting scheme.
In order to achieve the technical purpose, the technical scheme of the invention provides a part processing process route planning method, which comprises the following steps:
acquiring characteristic information of a to-be-machined surface of a target part, and matching a machining method chain according to the characteristic information;
decomposing the processing method chain into a plurality of processing elements based on a processing element generation rule;
sorting each processing element by adopting an ant colony algorithm based on an elite strategy;
and planning a process route according to the sorted processing elements.
The invention also provides a part machining process route planning device which comprises a processor and a memory, wherein the memory is stored with a computer program, and the computer program is executed by the processor to realize the part machining process route planning method.
Compared with the prior art, the invention has the beneficial effects that: according to the method, firstly, a target part is divided into a plurality of surfaces to be processed, and a processing method chain is matched according to the characteristic information of the surfaces to be processed, wherein the characteristic information of the surfaces to be processed comprises factors such as feed, rough processing and fine processing, so that the matching of the processing method chain is more accurate; meanwhile, the processing element constraint is used for decomposing the processing method chain, the processing elements are sorted by adopting the ant colony algorithm based on the elite strategy, and the processing element sorting method meeting the requirement can be obtained more quickly due to the fact that the elite strategy and the ant colony algorithm are combined, so that the process route planning efficiency is higher.
Drawings
FIG. 1 is a flow chart of one embodiment of a method for planning a part processing process route according to the present invention;
FIG. 2 is a two-dimensional view of a drive gear as a target part;
FIG. 3 is a flowchart of an embodiment of the elite policy based ant colony algorithm provided in the present invention
FIG. 4 is a comparison graph of the ranking results of the existing ant colony algorithm and the ant colony algorithm provided by the present invention;
FIG. 5 is an iterative comparison graph of an existing ant colony algorithm and an ant colony algorithm provided by the present invention;
fig. 6 is a transfer flow chart of an embodiment of ant transfer in the elite policy based ant colony algorithm provided in the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Example 1
As shown in fig. 1, embodiment 1 of the present invention provides a method for planning a route of a part processing process, including the steps of:
s1, acquiring characteristic information of a to-be-machined surface of the target part, and matching a machining method chain according to the characteristic information;
s2, decomposing the processing method chain into a plurality of processing elements based on the processing element generation rule;
s3, sorting the processing elements by adopting an ant colony algorithm based on an elite strategy;
and S4, planning a process route according to the sorted processing elements.
According to the method and the device, the characteristics of a target part are analyzed, the surface to be machined is determined according to the characteristics of the part, and a machining method chain of each surface to be machined of the part is obtained according to the characteristic information of each surface to be machined of the part and based on a process knowledge base and a machining element generation rule. The processing element refers to the most basic processing node in the part processing sequence, and each processing element is a variable of process sequencing. In the processing technology of the parts, each part consists of a plurality of surfaces to be processed, and the generation of each surface to be processed needs to be processed through a plurality of processes or steps. It is therefore necessary to plan the process route for each surface to be processed.
Secondly, decomposing the processing method chain of the surface to be processed based on a processing element generation rule to obtain a corresponding processing element; preferably, after the processing elements are obtained through decomposition, the process personnel recheck the configuration of each processing element and carry out corresponding modification on the configuration based on the resource information in the manufacturing resource library; and then, sequencing the processing elements based on the ant colony algorithm to obtain a primary processing technological process scheme. And planning a process route according to the sorted primary processing process flow, and specifically, adding an auxiliary procedure in the primary processing process flow to form a complete process flow scheme.
According to the invention, target parts are divided based on the surface to be processed, and factors such as feed, rough machining, finish machining and the like are considered, so that the matched processing method chain is more accurate. The processing method chain is decomposed into processing elements, the processing elements are sorted by adopting an ant colony algorithm with an elite strategy, a better sorting scheme can be found more quickly, and the efficiency is higher.
Preferably, the matching processing method chain according to the feature information specifically includes:
matching the characteristic information of the surface to be processed with the characteristic information of the single characteristic of the example part in the process knowledge base to obtain a matched single characteristic matched with the surface to be processed;
and acquiring the processing technology chain matched with the single characteristic as a processing method chain of the surface to be processed.
In order to better explain the present invention, the following description refers to specific components.
And taking a driving gear part of a certain type of the automobile main speed reducer as an example of a target part, and performing processing element sequencing description. A two-dimensional view of the drive gear components is shown in fig. 2. Firstly, the characteristic information of each surface to be machined of the driving gear is obtained, and the main surfaces to be machined and the characteristic information thereof are shown in table 1:
TABLE 1 to-be-machined surface and characteristic information of target part
FT1(center hole), FT2(Waiping)Face) and FT12The three surfaces (central hole) exist when the part is a semi-finished product, further processing is not needed, and the main functions of the three surfaces are positioning reference and clamping surfaces in the further processing.
And determining a processing method chain of the to-be-processed surface, and matching the characteristic processing method chain according to the characteristic information of each to-be-processed surface of the part on the basis of the process knowledge base and the processing element generation rule.
Preferably, the feature information of the surface to be processed is matched with the feature information of the single feature of the example part in the process knowledge base to obtain a matched single feature matched with the surface to be processed, and the specific steps are as follows:
the characteristic information comprises numerical characteristic information and character string characteristic information;
screening out a single feature which is the same as the numerical characteristic information of the surface to be processed from the process knowledge base to obtain a preliminary matching single feature set;
and screening out the single feature with the maximum similarity to the character string type feature information of the surface to be processed as the matching single feature in the preliminary matching single feature set.
Defining characteristic information of each surface to be processed of the target part:
FT＝{FT_PN,FT_FN,FT_V}
wherein, FTCharacteristic information of a certain surface to be machined for the target part, FT_PNPart classification number for target part, FT_FNFor the characteristic classification number of the face to be processed, FT_VThe characteristic attribute value set of the surface to be processed comprises a precision grade FT_V_ITSurface roughness FT_V_RAAnd the like.
Matching the characteristic information of each surface to be processed of the target part with the characteristic information of the example part single characteristic in the process knowledge base:
characteristic information of the example part single characteristics:
FS＝{FS_PN,FS_FN,FS_V}
wherein, FSIs some single characteristic information of the example part, FS_PNPart class number, F, for example partS_FNFeature classification number being a single feature, FS_VA set of feature attribute values for a single feature;
the feature information includes a numerical type and a character string type, for example, in this embodiment, the part classification number and the feature classification number are numerical types, the feature attribute value is a character string type, each single feature in each process knowledge base is determined, and the matching rule in this embodiment is:
IF
{(FT_PN＝FS_PN)AND(FT_FN＝FS_FN)ANDSimF(FT_V,FS_V)≥0.8}
THEN{max(SimF(FT_V,FS_V))}
wherein SimF(FT_V,FS_V) The solution can be performed by using a Jaccard narrow-sense coefficient algorithm.
And if the single features meeting the matching conditions do not exist in the process knowledge base, matching and extracting corresponding single features in the process knowledge base according to the surface feature processing process knowledge to serve as the matching single features.
Preferably, the processing method chain is decomposed into a plurality of processing primitives based on a processing primitive generation rule, specifically:
and according to the attributes of the processing method, the processing tool, the processing clamp, the clamping surface and the surface to be processed, the processing method is divided into a plurality of processing elements.
The acquired to-be-processed surfaces of the target part are decomposed into processing elements according to the processing element generation rule, and the processing elements are decomposed by combining the processing tool processing clamp, the clamping surface and the to-be-processed surface attributes, so that the processing elements inherit information of processing tools, rough processing, fine processing and the like, and the subsequent processing elements are convenient to sort.
In this embodiment, the content expression of the processing primitive is as follows:
ui＝(ui_ni,ui_si,ui_Mi,ui_Ti,ui_Ci,ui_fi,ui_ri)
in the formula ui_niFor processing primitive uiThe characteristic classification number u to which it belongsi_siFor processing primitive uiThe processing method adopted ui_MiFor processing primitive uiMachine tool adopted ui_TiFor processing primitive uiThe adopted cutter ui_CiFor processing primitive uiThe adopted clamp ui_fiFor processing primitive uiClamping surface of ui_riFor processing primitive uiThe center coordinates of the surface to be processed.
The information of each processing element is shown in table 2:
table 2 processing element information table
Preferably, as shown in fig. 3, the ant colony algorithm based on the elite strategy is adopted to order each processing primitive, specifically:
s31, initializing ant colony parameters, wherein the ant colony parameters comprise iteration times, an iteration time threshold, pheromones on each processing element, a taboo table of each ant and a priority matrix;
s32, randomly placing each ant on each processing element;
s33, determining to-be-accessed processing elements capable of being transferred by the ants according to the tabu table and the priority matrix, sequentially selecting the to-be-accessed processing elements by the ants according to a state transfer rule for transfer, and traversing all the processing elements;
s34, respectively calculating the path length of each ant traversing each processing element, obtaining the optimal ant path with the shortest path length, judging whether the optimal ant path length is smaller than the path length of the current optimal path, and if so, updating the current optimal path to be the optimal ant path;
s35, updating pheromones of the processing primitives according to pheromone updating rules;
and S36, judging whether the iteration times is less than the threshold of the generation times, if so, turning to the step S32 to carry out the next iteration, and if not, outputting the current optimal path as the sequence of the processing elements.
Sorting the processing elements by using an ant colony algorithm with an elite strategy:
1) initializing an ant colony algorithm: initializing the iteration times, setting an iteration time counter NC to be 0, and setting an iteration time threshold NCmax(ii) a The pheromones on each path are initialized, tauij(0)＝C，ΔτijC is a constant, and C is preferably selected to be a smaller constant, τ, at initialization timeij(0) Denotes a pheromone transferred from the ith processing element to the jth processing element, Δ τijUpdating a value for the pheromone; tabu is set as the Tabu of each antk(k is 1,2, …, m), m is the number of ants; initializing priority matrix A (a) of process primitiveij)N×NN is the number of processing elements;
2) detecting a priority matrix, determining a plurality of initial processing elements according to the constraint of the priority matrix, randomly placing all ants on the processing elements, and updating a tabu table corresponding to each ant according to the processing element in which each ant is positioned;
3) the ant k starts to search for an optimal path;
4) the ants determine the processing primitives to be accessed which can be transferred according to the tabu table and the priority processing matrix, calculate the probability of transferring the ants to the processing primitives to be accessed according to the state transfer rule, and select the processing primitive u with the maximum probabilityjCarrying out a transfer, after which u isjTabu added with antk(ii) a And will ujIn the priority matrix A (a)ij)N×NChinese character ofAll elements in the corresponding jth column are set as 0, and the priority matrix is updated;
5) j is j + 1; judging whether the ant k completes the traversal transfer of all the processing elements, namely whether j is more than N, if so, turning to (4), otherwise, turning to 6);
6) k is k + 1; judging whether all ants finish the traversal transfer of all processing elements, namely whether k is more than m or not, if so, turning to (3), otherwise, turning to 7);
7) calculating the path length of each ant after traversing each processing element, comparing the path length with the current optimal path, and if an ant path with the length smaller than the optimal path exists, updating the current optimal path;
8) updating pheromones on the path according to the pheromone updating rule;
9) NC is NC + 1; if NC < NCmaxThe taboo list Tabu of all ants is emptiedkInitializing the priority matrix of the processing element and transferring to 2) performing traversal transfer of next ant; otherwise, outputting the current optimal path.
The process ordering objective of the ant colony algorithm based on the elite strategy is to solve the 'shortest distance' of ants after traversing each processing element.
And after processing elements are sorted according to the ant colony algorithm based on the elite strategy, merging the procedures of the obtained sorting results, and generating the procedure of the part processing process.
Fig. 4 (a) shows the ordering result ACO _ short _ Route of the existing ant colony algorithm, and (b) shows the ordering result ASelite _ short _ Route of the ant colony algorithm provided by the present invention. As can be seen from fig. 4, the processing primitive ordering results obtained by using the existing ant colony algorithm and the ant colony algorithm based on the elite strategy provided by the present invention are the same:
u1-u5-u6-u9-u10-u13-u15-u11-u7-u2-u3-u14-u16-u17-u12-u8-u4。
and merging the working procedures of the obtained sequencing results to generate a working procedure of the part machining process.
Although the results of the two algorithms are the same, the convergence rates of the two algorithms are different, fig. 5 (a) shows an iteration process of processing element sorting by using the existing ant colony algorithm, wherein the X axis is the iteration number, the Y axis is the distance, L-best represents the shortest distance found by each ant in each iteration process, and L-ave is the average distance of each ant in each iteration process. Fig. 5 (b) shows an iteration process of processing element ordering by using the ant colony algorithm with elite strategy provided by the present invention, where the X-axis is the number of iterations, the Y-axis is the distance, L-best represents the shortest distance found by each ant in each iteration process, and L-ave is the average distance of each ant in each iteration process. As can be seen from fig. 5 (a): when the 7 th iteration is performed by the existing ant colony algorithm, an ant finds the optimal solution, and the shortest distance is 7.412; ants focus on the optimal solution after proceeding to iteration 71, and the algorithm converges. As shown in fig. 5 (b): in the ant colony algorithm with the elite strategy, the 6 th iteration is carried out, the best solution is found by ants, and the shortest distance is 7.412; ants are all focused on the optimal solution after the 39 th iteration, and the algorithm converges.
By comparison, the existing ant colony algorithm is adopted, so that the convergence rate is low, and the capability of finding out the optimal solution is weak. And the ant system with the elite strategy is adopted, the algorithm convergence speed is high, the capability of finding out the optimal solution is stronger than that of an ant colony in the existing ant colony algorithm, and the ant system is more suitable for the decision of the ordering problem of processing elements.
The time spent using the two algorithms is shown in table 3:
TABLE 3 Algorithm time consuming comparison
As can be seen from table 3, when the existing ant colony algorithm is used to make the sorting decision on 17 processing primitives, the total time and the elapsed time are 25.835s and 10.973s, respectively, which are 1.75 times and 1.71 times of the total time and the elapsed time of the ant colony algorithm with the elite strategy. Compared with the prior art, the ant colony algorithm with the elite strategy is shorter in time-consuming in sequencing decision of the processing elements, is more suitable for solving the sequencing problem of the processing elements, and is beneficial to shortening the process planning time and improving the process design efficiency.
Preferably, initializing the priority matrix specifically includes:
initializing the priority matrix according to the processing technology constraint.
The initialization of the priority matrix is performed according to process constraints, which include: face first, hole second, rough first, fine first, datum first, etc.
A priority matrix between the processing primitives is determined. Priority matrix is represented by A (a)ij)N×NWhere i is 1,2, …, N, j is 1,2, …, N equals the number of processing elements. Element a in the matrix according to the constraint conditions to which the processing elements are subjectedijComprises the following steps:
the constraint number of the processing element is equal to the sum of corresponding row elements of the processing element in the priority matrix; and the constraint number of the processing element on other processing elements is equal to the sum of corresponding column elements of the processing element in the priority matrix. Therefore, in the ant colony algorithm, the premise that the processing primitive is used as the next alternative processing primitive is that the sum of the row elements corresponding to the processing primitive is 0, and when the processing primitive is selected by an ant, the priority matrix is updated, all the column elements corresponding to the processing primitive need to be changed into 0, that is, the constraint of the processing primitive on other primitives is removed.
In this embodiment, initializing the priority matrix is:
preferably, as shown in fig. 6, the S33 specifically includes:
s331, determining processing primitives to be accessed, which can be transferred, by each ant according to the taboo table and the priority matrix;
s332, calculating the probability of ants transferring to each processing element to be accessed according to a state transfer rule, and selecting the processing element to be accessed with the maximum probability for transferring by each ant;
s333, adding the transferred processing primitive to be accessed into the tabu table, and updating the priority matrix;
and S334, judging whether each ant completes traversal transfer of all processing primitives to be accessed, if so, transferring to S34, and otherwise, transferring to S331.
Preferably, the path length of the ants traversing each processing element is calculated, specifically:
acquiring the characteristic attribute of each processing element;
respectively calculating the feature attribute similarity of each feature attribute aiming at the two processing elements;
weighting each characteristic attribute;
calculating a weighted sum of feature attribute similarity of each feature attribute as a distance between the two machining primitives;
and calculating the path length according to the ant path and the distance between the processing elements.
Before calculating the length of the ant path, the distance between each processing element is first determined.
Wherein, the distance between the processing elements is defined as follows:
D(ui,uj)＝ωssim(ui_si,uj_sj)+ωMsim(ui_Mi,uj_Mj)+ωTsim(ui_Ti,uj_Tj) +ωr·d(ui_ri,uj_rj)+(ωC+ωf)·max[sim(ui_Ci,uj_Cj),sim(ui_fi,uj_fj)]
wherein:
D(ui,uj) For processing primitive uiAnd processing element ujThe distance between them;
sim(ui_si,uj_sj) For processing primitive uiAnd processing element ujWith respect to the feature attribute similarity of the feature attribute processing method s, sim (u)i_Mi,uj_Mj) For processing primitive uiAnd processing element ujWith respect to the feature attribute similarity, sim (u) of the feature attribute machine tool Mi_Ti,uj_Tj) For processing primitive uiAnd processing element ujWith respect to the feature attribute similarity sim (u) of the feature attribute tool Ti_Ci,uj_Cj) For processing primitive uiAnd processing element ujWith respect to the feature attribute similarity, sim (u) of the feature attribute holder Ci_fi,uj_fj) For processing primitive uiAnd processing the primitive ujWith respect to the feature attribute similarity of the feature attribute clamping face f, sim (u)i_ri,uj_rj) For processing basic elements uiAnd processing element ujThe feature attribute similarity of the center coordinate r of the surface to be processed with the feature attribute;
ωsweight value, omega, of the processing method s for a characteristic attributeMFor weight values, omega, of machine tools M of characteristic attributesTIs the weight value, omega, of the characteristic attribute tool TCWeight value, ω, for characteristic Attribute Fixture CfClamping the weight value, omega, of the surface f for a characteristic attributerThe weight value of the center coordinate r of the surface to be processed with the characteristic attribute is obtained;
preferably, the calculating the feature attribute similarity specifically includes:
when the characteristic attribute is a numerical type:
wherein sim (u)i_ai,uj_aj) For processing primitive uiAnd processing element ujRegarding the similarity of the feature attributes a, the feature attributes a are numerical types, ui_aiFor processing primitive uiThe attribute value of the characteristic attribute a of (1), uj_ajFor processing primitive ujThe attribute value of the characteristic attribute a of (1);
when the characteristic attribute is a coordinate type:
wherein d (u)i_bi,uj_bj) For processing primitive uiAnd processing element ujRegarding the feature attribute similarity of the feature attribute b, the feature attribute b is a coordinate type, ui_biFor processing primitive uiProperty value of the characteristic property b of (1), uj_bjFor processing primitive ujProperty value of the characteristic property b of (1), ui_bi＝(xi,yi,zi)，uj_bj＝(xj,yj,zj)；
And when two or more characteristic attributes are associated, taking the maximum value in the similarity of the characteristic attributes as the overall characteristic attribute similarity of the characteristic attributes.
For the characteristic attributes of the numerical type, calculating the similarity of the characteristic attributes by adopting a similarity judgment function; for the characteristic attributes of the coordinate types, the distance between the coordinates is used as the characteristic attribute similarity; and when the relevance exists between two or more characteristic attributes, taking the maximum characteristic attribute similarity in the characteristic attribute similarities as the integral characteristic attribute similarity.
For example, when there is a correlation between two feature attributes, the overall feature attribute similarity is:
max[sim(ui_ci,uj_cj),sim(ui_di,uj_dj)]
wherein sim (u)i_ci,uj_cj) For processing primitive uiAnd processing element ujFeature attribute similarity, u, with respect to feature attribute ci_ciFor processing primitive uiThe value of the characteristic attribute c of (1), uj_cjFor processing primitive ujThe value of the characteristic attribute c of (1); sim (u)i_di,uj_dj) For processing primitive uiAnd processing element ujFeature attribute similarity, u, with respect to feature attribute di_diFor processing primitive uiThe value of the characteristic attribute d of (1), uj_djFor processing primitive ujThe value of the characteristic attribute d of
max[sim(ui_ci,uj_cj),sim(ui_di,uj_dj)]The expression simultaneously considers the transformation of the characteristic attribute c or the characteristic attribute d of the processing primitive, and takes the maximum value. For example, the feature attribute c is a jig, the feature attribute d is a clamping surface, and when the jig or the clamping surface of the machining element is changed, the part needs to be clamped again, so when the distance between the two machining elements is considered, the change of the jig or the clamping surface of the machining element needs to be considered at the same time.
The basic element u is processed in this embodiment1And processing element u2Taking the distance between the two nodes as an example, distance calculation is performed, and the weighted values in the formula are respectively: processing method omegas: 0.3 machine tool omegaM: 0.3, cutting tool omegaT: 0.15, clamp omegaC: 0.15, clamping surface omegaf: 0.1, center coordinate omega of the surface to be processedr：0.001。
Processing element u1And processing element u2The distance between them is:
D(u1,u2)＝0.3*1+0.3*1+0.15*1+0.001*0+(0.15+0.1)*max(1,1)。
specifically, the distance between the center coordinates of the surface to be processed is used for selecting the equal distance between the processing elements when the distances between the processing elements obtained by calculation according to other weight values are equal, and the original equal distance between the processing elements generates a slight difference value according to the distance between the center coordinates, so that the leech is producedAnts avoid generating random paths in the algorithm. Therefore, based on the problem of equal distance under other weight values, the center coordinate distance weight value should be small, the influence on the distance between processing primitives should be small, and the distance between some surface center coordinates is 180mm at the maximum, which is a large value, so that the final processing primitive distance calculation is not influenced by multiplying by the small weight value. Weight value ω in this embodimentrThe value 0.0001 is a numerical value defined by the above preconditions.
The distances between other processing elements can be obtained similarly, and are not described in detail herein.
Example 2
Embodiment 2 of the present invention provides a device for planning a route of a machining process of a part, which includes a processor and a memory, where the memory stores a computer program, and when the computer program is executed by the processor, the method for planning a route of a machining process of a part provided in any of the above embodiments is implemented.
The method for planning the part machining process route specifically comprises the following steps:
acquiring characteristic information of a to-be-machined surface of a target part, and matching a machining method chain according to the characteristic information;
decomposing the processing method chain into a plurality of processing primitives based on processing primitive constraints;
sorting each processing element by adopting an ant colony algorithm based on an elite strategy;
and planning a process route according to the sorted processing elements.
The part processing process route planning device provided by the invention is used for realizing the part processing process route planning method, so that the technical effect of the part processing process route planning method is also possessed by the part processing process route planning device, and the details are not repeated herein.
The above-described embodiments of the present invention should not be construed as limiting the scope of the present invention. Any other corresponding changes and modifications made according to the technical idea of the present invention should be included in the scope of the claims of the present invention.

Claims (10)

1. A method for planning a part machining process route is characterized by comprising the following steps:
acquiring characteristic information of a to-be-machined surface of a target part, and matching a machining method chain according to the characteristic information;
decomposing the processing method chain into a plurality of processing elements based on a processing element generation rule;
sorting each processing element by adopting an ant colony algorithm based on an elite strategy;
and planning a process route according to the sorted processing elements.
2. The method for planning a route of a part processing process according to claim 1, wherein a chain of processing methods is matched according to the feature information, specifically:
matching the characteristic information of the surface to be processed with the characteristic information of the single characteristic of the example part in the process knowledge base to obtain a matched single characteristic matched with the surface to be processed;
and acquiring the processing technology chain matched with the single characteristic as a processing method chain of the surface to be processed.
3. The method for planning a processing route of a part according to claim 2, wherein the feature information of the surface to be processed is matched with the feature information of the single feature of the example part in a process knowledge base to obtain a matched single feature matched with the surface to be processed, and specifically, the method comprises the following steps:
the characteristic information comprises numerical characteristic information and character string characteristic information;
screening out a single feature which is the same as the numerical characteristic information of the surface to be processed from the process knowledge base to obtain a preliminary matching single feature set;
and screening out the single feature with the maximum similarity to the character string type feature information of the surface to be processed as the matching single feature in the preliminary matching single feature set.
4. The method for planning a route of a part processing process according to claim 1, wherein the processing method chain is decomposed into a plurality of processing elements based on a processing element generation rule, specifically:
and according to the attributes of the processing method, the processing tool, the processing clamp, the clamping surface and the surface to be processed, the processing method is divided into a plurality of processing elements.
5. The method for planning a route of a part processing process according to claim 1, wherein the processing elements are sorted by using an ant colony algorithm based on an elite strategy, specifically:
s31, initializing ant colony parameters, wherein the ant colony parameters comprise iteration times, an iteration time threshold, pheromones on each processing element, a taboo table of each ant and a priority matrix;
s32, randomly placing each ant on each processing element;
s33, determining processing primitives to be accessed which can be transferred by the ants according to the tabu table and the priority matrix, sequentially selecting the processing primitives to be accessed by the ants according to a state transfer rule for transfer, and traversing all the processing primitives;
s34, respectively calculating the path length of each ant traversing each processing element, obtaining the optimal ant path with the shortest path length, judging whether the optimal ant path length is smaller than the path length of the current optimal path, and if so, updating the current optimal path to be the optimal ant path;
s35, updating pheromones of the processing primitives according to pheromone updating rules;
and S36, judging whether the iteration times is less than the threshold of the generation times, if so, turning to the step S32 to carry out the next iteration, and if not, outputting the current optimal path as the sequence of the processing elements.
6. The method for part processing route planning according to claim 5, wherein the priority matrix is initialized, in particular:
initializing the priority matrix according to the processing technology constraint.
7. The method for planning a route of a part processing technology according to claim 5, wherein the step S33 is specifically as follows:
s331, each ant determines the processing primitive to be accessed which can be transferred according to the tabu list and the priority matrix
S332, calculating the probability of ants transferring to each processing element to be accessed according to a state transfer rule, and selecting the processing element to be accessed with the maximum probability for transferring by each ant;
s333, adding the transferred processing primitive to be accessed into the tabu table, and updating the priority matrix;
and S334, judging whether each ant completes traversal transfer of all processing primitives to be accessed, if so, transferring to S34, and otherwise, transferring to S331.
8. The part processing technology routing method of claim 5, wherein calculating the path length of ants traversing each processing primitive is specifically:
acquiring the characteristic attribute of each processing element;
respectively calculating the feature attribute similarity of each feature attribute aiming at the two processing elements;
weighting each characteristic attribute;
calculating a weighted sum of feature attribute similarity of each feature attribute as a distance between the two machining primitives;
and calculating the path length according to the ant path and the distance between the processing elements.
9. The method for planning a route for a part processing process according to claim 8, wherein the feature attribute similarity is calculated as:
when the characteristic attribute is a numerical type:
wherein sim (u)i_ai,uj_aj) For processing primitive uiAnd processing element ujRegarding the similarity of the characteristic attributes of the characteristic attribute a, the characteristic attribute a is a numerical type, ui_aiFor processing primitive uiThe attribute value of the characteristic attribute a of (1), uj_ajFor processing primitive ujThe attribute value of the characteristic attribute a of (1);
when the characteristic attribute is a coordinate type:
wherein d (u)i_bi,uj_bj) For processing primitive uiAnd processing element ujRegarding the feature attribute similarity of the feature attribute b, the feature attribute b is a coordinate type, ui_biFor processing primitive uiProperty value of the characteristic property b of (1), uj_bjFor processing primitive ujProperty value of the characteristic property b of (1), ui_bi＝(xi,yi,zi)，uj_bj＝(xj,yj,zj)；
And when two or more characteristic attributes are associated, taking the maximum value in the similarity of the characteristic attributes as the overall characteristic attribute similarity of the characteristic attributes.
10. A route planning apparatus for a machining process of a part, comprising a processor and a memory, wherein the memory stores a computer program, and the computer program, when executed by the processor, implements the route planning method for a machining process of a part according to any one of claims 1 to 9.
CN201910800482.1A 2019-08-28 2019-08-28 Method and device for planning part machining process route Pending CN110598279A (en)

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Application publication date: 20191220