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CN-115758617-B - Firearm assembly precision control method and system supporting large number of interchangeable assemblies

CN115758617BCN 115758617 BCN115758617 BCN 115758617BCN-115758617-B

Abstract

The invention discloses a firearm assembly precision control method and system supporting a large number of interchangeable assemblies, the method comprises the steps of firstly defining position points of geometric elements in an assembly model, deducing a calculation formula of a target dimensional tolerance through accumulation and decomposition of confidence regions, then optimizing the dimensional tolerance, calculating a theoretical confidence region of position coordinates of the target geometric elements, calculating a process capability index and a qualification rate of the target geometric element by the actual dimensions of sampled parts, calculating an actual confidence region of position coordinates of the target geometric elements, and predicting and monitoring whether the qualification rate of the assembly precision meets requirements through comparison of the theoretical confidence region and the actual confidence region.

Inventors

  • FANG JUN
  • Ruan Baojun

Assignees

  • 南京理工大学

Dates

Publication Date
20260512
Application Date
20221129

Claims (5)

  1. 1. The firearm assembly precision control method supporting the large number of interchangeable assemblies is characterized by comprising the following steps of: Step 1, defining position points and coordinate system origins of geometric elements in an assembly model, and representing the position coordinates of the geometric elements corresponding to the endpoints of each component ring by adopting n-element normal distribution; step 2, deducing a calculation formula of the target size tolerance through accumulation and decomposition of a theoretical confidence region; Step 3, setting the distribution of the sizes of all the component rings as normal distribution, adopting an optimization design method to obtain the size tolerance of each component ring, wherein an optimization variable is the standard deviation of the sizes of the component rings, an optimization target is the maximum area or volume of each confidence region, and constraint conditions are the variation range and tolerance requirements of the sizes of the component rings and the closed rings; calculating a theoretical confidence region of the position coordinates of the target geometric elements and the dimensional tolerance of the closed loop; Step 5, calculating a processing process capability index and a qualification rate according to the actual size of the sampled part, stopping production and adjusting the processing of the unqualified part if the qualification rate of the actual size of the part or the process capability index of the part is not in accordance with the requirements; step 6, calculating an actual confidence region of the position coordinates of the target geometric elements according to the actual size of the sampled parts, and calculating the actual confidence region of the position coordinates of the target geometric elements by adopting a multi-element normal distribution accumulation method according to the actual size of the sampled parts, wherein the method specifically comprises the following steps: According to the actual size of the sampled part, calculating an actual confidence region of the position coordinates of the target geometric element by adopting a multi-element normal distribution accumulation method, wherein the method for calculating the actual confidence region is as follows: (1) In the case of part sampling, the covariance matrix of the whole body of the part size is unknown, the covariance matrix sigma of the sample is used for replacing the covariance matrix of the whole body when the multivariate normal distribution of the geometric element positions is represented, and the mean value of the sample is used Replacing the mean mu of normal distribution, and replacing the standard deviation of normal distribution with the standard deviation of a sample; (2) The coordinates of the related dimensions are used for counting the related coefficients among the parts according to the numerical value of the actual dimensions of the sampled parts; (3) Let point a n be used to represent the position of the target geometric element, the confidence region for the multivariate normal distribution of point a n with confidence level 1- α is calculated using the following equation: where T α is the T distribution with a significance level of alpha, M is the number of samples for sampling inspection, n is the number of degrees of freedom of the part, P represents the probability that point a n falls in this confidence region as 1-alpha, For an F distribution with a significance level of alpha, A vector representing the origin of o and the end of a n , the vector The confidence region of the actual coordinates of the point a n is still an ellipse with the center of the ellipse as the point p, the direction and the length of the ellipse axis are determined by the covariance matrix sigma of the sample, and the vector with o as the origin p is represented as the end point; step 7, predicting and monitoring whether the qualification rate of the assembly precision meets the requirement or not through comparison of a theoretical confidence region and an actual confidence region; judging whether the actual confidence region of the position coordinate point a n of the target geometric element is positioned in the range of the theoretical confidence region, if the actual confidence region exceeds the range of the theoretical confidence region, calculating the error variation range of the actual confidence region in the target direction or position, comparing the actual confidence region with the tolerance design requirement of the assembly precision, predicting and monitoring whether the qualification rate of the assembly precision meets the requirement according to the comparison result, and giving corresponding adjustment suggestion.
  2. 2. The firearm assembly accuracy control method supporting a large number of interchangeable assemblies according to claim 1, wherein step 1 specifically comprises the steps of: Step 1.1, establishing a two-dimensional or three-dimensional dimension chain diagram, wherein the chain diagram comprises a closed loop and a component loop; Step 1.2, determining a target geometric element and a coordinate origin of a coordinate system in an assembly model of the part, wherein the geometric element corresponding to one end point of the closed loop is the target geometric element; Step 1.3, the size value of each part is set to be a random number which is compliant with normal distribution, the position of any geometric element on the part is set to be represented by coordinates in an n-dimensional coordinate system, and the position coordinates of the geometric elements corresponding to the endpoints of each component ring are represented by n-element normal distribution from the origin of coordinates.
  3. 3. The firearm assembly accuracy control method supporting a large number of interchangeable assemblies according to claim 1, wherein step2 specifically comprises the steps of: step 2.1, a multi-element normal distribution accumulation method is adopted to obtain multi-element normal distribution of the position coordinates of the target geometric elements relative to the origin; 2.2, decomposing a confidence region representing the multi-element normal distribution of the position coordinate point a n of the target geometric element into a maximum error variation range in a certain direction or position according to the design requirement of the target dimensional tolerance; The confidence region for point a n with a confidence level of 1- α is calculated using the following equation: Wherein T represents the transpose, Chi-square distribution χ 2 with degree of freedom n and significance level alpha, P represents that the probability of a n point falling in the confidence region is 1-alpha, C is the overall covariance matrix, The vector which takes o as an origin and a n as an end point is expressed, and n is respectively 2 or 3 for the two-dimensional or three-dimensional coordinate problem; The calculation formula of the target dimensional tolerance is a calculation formula of the maximum error variation range of the a n point in a certain direction or position, when the direction of the error variation range of the a n point is known, the error variation range of the a n point in the direction or the certain position of the direction is obtained by calculating the conditional probability distribution of the multi-element normal distribution of the a n point, and when the direction of the error variation range of the a n point is uncertain, the error variation range of the a n point in the direction or the certain position of the direction is obtained by adopting the minimum circumscribed rectangle or the side length of the cuboid of the confidence region of the a n point.
  4. 4. The firearm assembly accuracy control method supporting a large number of interchangeable assemblies according to claim 1, wherein when the theoretical confidence region is compared with the actual confidence region in step 7, two cases are divided: (1) When the theoretical confidence region of the a n point can completely contain the actual confidence region, receiving the assumption that the assembly accuracy qualification rate is more than 1-alpha, outputting a signal which is continuously produced, wherein alpha is a significance level; (2) When the actual confidence region of the a n point exceeds the theoretical confidence region, calculating the error variation range of the actual confidence region in the target direction or position, wherein the error variation range comprises the following two cases: (a) If the error variation range of the actual confidence area in the target direction or position exceeds the tolerance design requirement of the closed loop, the actual assembly precision cannot meet the requirement under the confidence level of 1-alpha, so that signals for stopping production are output, and the statistical mean value, the process capability index C p and the value C pk of each part are checked when adjustment suggestions are given, wherein if the value C p of a certain size of the part is smaller, the random error is large; if the value of C p meets the requirement, but the value of C pk or the predicted overall qualification rate is smaller, which indicates that the deviation of the statistical average value of the dimension from the center of the tolerance zone is larger, the dimension is the cause of generating a systematic error, and the relative position between the cutter and the processed part should be considered to be adjusted, so that the statistical average value of the actual dimension is close to the center of the tolerance zone, namely, close to the average value of theoretical normal distribution; (b) If the error variance of the actual confidence area in a certain direction or position is within the tolerance design requirement of the closed loop, it is indicated that the actual assembly accuracy will meet the tolerance design requirement of the closed loop in that direction or position, but the position of the target geometric element may exceed the theoretical design range in other directions or positions, so that production can continue, but a warning signal is output, giving a suggestion to increase or decrease the size of the larger system error to be close to the center of the tolerance zone.
  5. 5. The firearm assembly accuracy control method design supporting a large number of interchangeable assemblies of claim 1, comprising: the geometric element position point definition module is used for assisting a user in determining a coordinate system origin point in an assembly drawing and position points of geometric elements in a man-machine interaction mode, assisting the user in establishing a dimension chain drawing and establishing a necessary data model for tolerance optimization design and assembly precision prediction and monitoring; The dimensional tolerance optimization design module performs dimensional tolerance optimization design according to the established geometric element position coordinate model, can optimize according to the closed ring tolerance design requirement and the lowest tolerance grade design requirement of each component ring given by a user by using the optimization method of the step 3, converts each tolerance into the nearest standard tolerance value after searching a standard tolerance database, and adopts the method of the step 4 to test the standardized tolerance and output the optimized and standardized dimensional tolerance; The assembly precision prediction and monitoring module calculates the statistical mean value, the process capability index and the predicted overall qualification rate of each component ring size according to the actual measurement data of the part sizes and the tolerance design requirement, calculates the actual confidence region of the position coordinates of the geometric elements according to the method of the step 6 to generate a theoretical and actual confidence region diagram, and checks whether the theoretical confidence region of the position coordinates of the target geometric elements contains the actual confidence region according to the tolerance optimization result and the method of the step 7 so as to judge whether the actual sizes of the parts meet the requirement of the assembly precision qualification rate and give suggestions of early warning and adjustment modes for possibly occurring unqualified conditions.

Description

Firearm assembly precision control method and system supporting large number of interchangeable assemblies Technical Field The invention belongs to the field of assembly precision control, and particularly relates to a firearm assembly precision control method and system supporting a large number of interchangeable assemblies. Background Assembly accuracy control refers to ensuring assembly accuracy of a product during product design stages and part machining assembly processes. In the method for ensuring the assembly precision of mechanical products, a large number of exchange methods are generally used in the case of higher assembly precision requirements and more component rings. Compared with a complete exchange method, the method has the advantages that under the same assembly precision requirement, the tolerance of parts designed according to the large number exchange method is larger, and the economy is better. Most of the existing researches on assembly precision control technology mainly focus on tolerance modeling and tolerance analysis optimization technology in a design stage. In the assembly tolerance analysis, distribution or optimization by the large number interchange method, it is assumed that the geometric parameters of each part or the mathematical transformation amounts thereof obey a certain probability distribution, and each component ring (or geometric component) is independent from each other. In order to realize the large number exchange assembly of parts, statistical tolerance analysis methods which can be adopted in the design of assembly precision mainly comprise a root mean square method (RSS), a Croft method, an extended Taylor series approximation method, a Hasofer-Lind index method, a numerical integration or product approximation method, a field opening method, a Monte Carlo simulation method, a nuclear density estimation method and the like. In the process of part processing and assembly production, the existing quality control method of assembly precision is mainly divided into two types, namely (1) an assembly precision monitoring and predicting method based on assembly precision measurement data and (2) an assembly precision control method based on part processing quality detection data. The first type of method utilizes the actually measured assembly precision data in the assembly process to establish a relation model between the assembly characteristic parameters and the assembly precision targets through methods such as machine learning, data mining, state space models and the like. The second type of method based on the quality detection data of the parts can be applied to the interchange assembly mode, in the production practice, a sampling inspection method is generally adopted, a batch of parts are extracted from the finished parts, the mean value and standard deviation of geometric parameters of the parts are counted, the process capability index (also called as process capability index) of the parts is predicted, or the overall qualification rate of the parts is predicted according to a probability distribution function. The common measurement index parameters of the process capability index are Cp and Cpk, and the method is applicable to the conditions of not considering mean deviation and considering mean deviation respectively. When the process capability index is larger or the predicted overall qualification rate is larger, the geometric parameters of the processed parts are considered to meet the assembly precision requirement of the large-number exchange method, and then the assembly precision is deduced to meet the design requirement. Firearms are a typical type of mechanical product. The assembly precision design of the firearm product is generally characterized in that the assembly precision requirement of dimensional tolerance is high, but the number of component rings of related parts is more. The assembly structure of many parts in the firearm has the characteristic of symmetry about a central plane, and the assembly precision control method commonly used in the production of firearm products at present is a measurement inspection and manual repair and frustration assembly method during two-dimensional dimension chain design and assembly. In order to ensure the economy of parts processing, the commonly adopted firearm assembly precision design method generally designs the size of a certain part into a repair ring, converts a part of geometric tolerance zone into a 'ring' in a size chain, and reduces the processing precision requirement of other matched parts, and a great amount of repair work is inevitably required when firearm products are assembled. The existing assembly accuracy control method has the following technical problems: (1) A prerequisite for successful application of the assembly accuracy monitoring prediction method based on the assembly accuracy measurement data is that there is a large amount of assembly measurement history data as