Method, device and system for checking a dimension chain

Abstract

The application provides a size chain checking method, a checking device and a size chain checking system. The method comprises the following steps: dividing component rings in a size chain into a plurality of statistical rings and at least one extreme ring; calculating checking tolerances of all the statistical rings by using a statistical method to obtain first checking tolerances; calculating checking tolerances of all the extreme rings by using an extreme method to obtain second checking tolerances; and performing size chain checking by using third checking tolerances, wherein the third checking tolerances are the sum of the first checking tolerances and the second checking tolerances. The method calculates the checking tolerances of part of the component rings by using the limit method and calculates the checking tolerances of the other part of the component rings by using the statistical method, the sum of the two checking tolerances is used as the checking tolerance for the size chain checking, the size precision requirement of the part is not high, and the size deviation of the part does not need to strictly conform to the normal distribution, and the problem that the size chain checking method in the prior art cannot meet the actual production requirement is solved.

Description

Technical Field

[0001] This application relates to the field of dimensional chain verification technology, and more specifically, to a dimensional chain verification method, verification device, computer-readable storage medium, processor, and dimensional chain verification system. Background Technology

[0002] Dimension chain calculation is a fundamental verification method in the machinery industry. Reasonable dimensional chain verification in the early stages of design can avoid many risks. Traditional dimensional chain verification methods mainly include two types: extreme value method and statistical method. Both methods have certain drawbacks. The extreme value method is too conservative in its calculation results, directly adding up each tolerance, resulting in an overly large target result. This requires products with high precision to meet the requirements, leading to higher costs. On the other hand, the statistical method is too idealistic, requiring each dimensional deviation to conform to a normal distribution. While the actual dimensional deviation distribution of manufactured parts tends to be normal, it is not a perfect normal distribution. Therefore, the calculated result is too small, and actual production cannot achieve such perfection, often resulting in assembly problems.

[0003] The information disclosed in the background section is only intended to enhance the understanding of the background art of the art described herein. Therefore, the background art may contain information that does not constitute prior art known to those skilled in the art in this country. Summary of the Invention

[0004] The main objective of this application is to provide a dimensional chain verification method, verification device, computer-readable storage medium, processor, and dimensional chain verification system to solve the problem that existing dimensional chain verification methods cannot meet the needs of actual production.

[0005] According to one aspect of the present invention, a method for verifying a dimensional chain is provided, comprising: dividing the constituent loops in the dimensional chain into a plurality of statistical loops and at least one extreme loop; calculating the verification tolerance of all the statistical loops using a statistical method to obtain a first verification tolerance; calculating the verification tolerance of all the extreme loops using an extreme value method to obtain a second verification tolerance; and verifying the dimensional chain using a third verification tolerance, wherein the third verification tolerance is the sum of the first verification tolerance and the second verification tolerance.

[0006] Optionally, the component loops in the dimensional chain are divided into multiple statistical loops and at least one extreme loop, including: calculating the verification tolerance of all the component loops using the statistical method to obtain a fourth verification tolerance; calculating the contribution rate of each component loop to obtain multiple contribution rates, wherein the contribution rate is the percentage of the square of the tolerance of the component loop to the square of the fourth verification tolerance, and the contribution rate corresponds one-to-one with the component loop; identifying the component loop whose sum of the contribution rates is greater than or equal to a predetermined value as the statistical loop, and identifying the component loops other than the statistical loops as the extreme loops, wherein the contribution rate of any statistical loop is greater than or equal to the contribution rate of any extreme loop.

[0007] Optionally, the verification tolerance of all the statistical loops is calculated using a statistical method to obtain a first verification tolerance, including: calculating the sum of squares of the tolerances of each of the statistical loops to obtain a first tolerance sum of squares; and calculating the square root of the first tolerance sum of squares to obtain the first verification tolerance.

[0008] Optionally, the component loops in the dimensional chain are divided into multiple statistical loops and at least one extreme loop, including: defining the component loops whose dimensional deviations are distributed in a normal or uniform manner as the statistical loops, wherein the normal distribution means that the dimensional deviations of the component loops conform to a normal distribution, and the uniform distribution means that the dimensional deviations of the component loops are evenly distributed within the tolerance allowable range of the component loops; and defining the component loops whose tolerances are distributed in an extreme value manner as the extreme loops, wherein the extreme value distribution means that the dimensional deviations of the component loops are equal to one endpoint of the tolerance allowable range of the component loops.

[0009] Optionally, a statistical method is used to calculate the verification tolerance of all the statistical loops to obtain a first verification tolerance, including: calculating the sum of squares of the tolerances of each first statistical loop to obtain a second sum of squares of tolerances, wherein the first statistical loops are the component loops in which the distribution of the dimensional deviations is the normal distribution; calculating the product of the sum of squares of the tolerances of each second statistical loop and a correction factor to obtain a third sum of squares of tolerances, wherein the second statistical loops are the component loops in which the distribution of the dimensional deviations is the uniform distribution, and the correction factor is a constant greater than 1; calculating the sum of the second sum of squares of tolerances and the third sum of squares of tolerances to obtain a fourth sum of squares of tolerances; and calculating the square root of the fourth sum of squares of tolerances to obtain the first verification tolerance.

[0010] Optionally, the extreme value method is used to calculate the verification tolerance of all the extreme value loops to obtain the second verification tolerance, including: calculating the sum of the tolerances of each extreme value loop to obtain the second verification tolerance.

[0011] According to another aspect of the present invention, a dimensional chain verification device is also provided, comprising: a classification unit for dividing the constituent loops in the dimensional chain into a plurality of statistical loops and at least one extreme loop; a first calculation unit for calculating the verification tolerance of the statistical loops using a statistical method to obtain a first verification tolerance; a second calculation unit for calculating the verification tolerance of the extreme loops using an extreme value method to obtain a second verification tolerance; and a verification unit for performing dimensional chain verification using a third verification tolerance, wherein the third verification tolerance is the sum of the first verification tolerance and the second verification tolerance.

[0012] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored program, wherein the program executes any one of the methods described.

[0013] According to another aspect of the present invention, a processor is also provided, the processor being configured to run a program, wherein the program, when running, executes any of the methods described.

[0014] According to another aspect of the present invention, a dimensional chain verification system is also provided, comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include methods for performing any one of the methods described.

[0015] In this embodiment of the invention, the above-mentioned dimensional chain verification method uses either the extreme value method or the statistical method for dimensional chain verification. The extreme value method uses the sum of all tolerances as the verification tolerance, requiring each tolerance to be small to meet verification requirements, necessitating high dimensional accuracy, which is difficult to achieve in actual production or is costly. The statistical method uses the square root of the sum of the squares of all tolerances as the verification tolerance, resulting in a much smaller verification tolerance compared to the extreme value method, with lower dimensional accuracy requirements. However, it cannot guarantee that the dimensional deviations of the components in each link strictly conform to a normal distribution. Any deviation may prevent the properly assembled parts that have passed verification. This application uses the limit method to calculate the verification tolerance for some components and the statistical method for others, using the sum of the two verification tolerances as the dimensional chain verification tolerance. This reduces the dimensional accuracy requirements of the parts and eliminates the requirement for strict conformity of dimensional deviations to a normal distribution, thus solving the problem that the dimensional chain verification method in the prior art cannot meet the needs of actual production. Attached Figure Description

[0016] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0017] Figure 1 A flowchart of a dimensional chain verification method according to an embodiment of this application is shown;

[0018] Figure 2 A schematic diagram of a dimensional chain verification device according to an embodiment of this application is shown. Detailed Implementation

[0019] It should be noted that the following detailed descriptions are illustrative and intended to provide further explanation of this application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0020] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this application. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0021] It should be understood that when an element (such as a layer, film, region, or substrate) is described as being "on" another element, the element may be directly on the other element, or there may be an intermediate element present. Furthermore, in the specification and claims, when an element is described as being "connected" to another element, the element may be "directly connected" to the other element, or "connected" to the other element via a third element.

[0022] For ease of description, the following explains some of the nouns or terms used in the embodiments of this application:

[0023] Statistical method: The dimensional deviations of each component link in the dimensional chain follow a normal distribution. The check tolerance is the square root of the sum of the squares of the tolerances of each component link. For example, if the tolerances of each component link in the dimensional chain are T1, T2, T3, T4, and T5, then the check tolerance is... The tolerances need to be checked to ensure they meet the requirements.

[0024] Extreme value method: The dimensional deviation of each component link in the dimensional chain is taken as the maximum value. The check tolerance is the sum of the tolerances of each component link. For example, if the tolerances of each component link in the dimensional chain are T1, T2, T3, T4, and T5, then the check tolerance T0 = T1 + T2 + T3 + T4 + T5. The check tolerance needs to meet the check requirements.

[0025] As mentioned in the background section, existing dimensional chain verification methods cannot meet the needs of actual production. In order to solve the above problems, in a typical embodiment of this application, a dimensional chain verification method, verification device, computer-readable storage medium, processor, and dimensional chain verification system are provided.

[0026] According to an embodiment of this application, a method for verifying dimensional chains is provided.

[0027] Figure 1 This is a flowchart of a dimensional chain verification method according to an embodiment of this application. Figure 1 As shown, the method includes the following steps:

[0028] Step S101: Divide the constituent loops in the size chain into multiple statistical loops and at least one extreme loop;

[0029] Optionally, the present invention does not limit the specific process of dividing the constituent loops in the size chain into multiple statistical loops and at least one extreme loop; any feasible method is within the protection scope of the present invention.

[0030] For example, in an optional implementation, step S101 above includes:

[0031] Step S1011: Calculate the check tolerances of all the above-mentioned component rings using the above statistical method to obtain the fourth check tolerance;

[0032] Step S1012: Calculate the contribution rate of each of the above-mentioned component rings to obtain multiple contribution rates. The contribution rate is the percentage of the ratio of the square of the tolerance of the above-mentioned component ring to the square of the fourth verification tolerance. The contribution rate corresponds one-to-one with the above-mentioned component rings.

[0033] Step S1013: The constituent rings whose sum of contribution rates is greater than or equal to a predetermined value are defined as the statistical rings, and the constituent rings other than the statistical rings are defined as the extreme value rings, wherein the contribution rate of any statistical ring is greater than or equal to the contribution rate of any extreme value ring.

[0034] In the above embodiments, the tolerances of each component link in the dimension chain are T1, T2, T3, T4, and T5, respectively. The verification tolerance of all the above component links, i.e., the fourth verification tolerance, is calculated using the above statistical method. Contribution rate of the above constituent rings Where n = 1, 2, ... 5, for example, C1≥C3>C5≥C2≥C4, C1+C3+C5≥90%, then the component rings corresponding to C1, C3 and C5 are determined to be statistical rings, and the component rings corresponding to C2 and C4 are determined to be extreme value rings. The statistical rings have a larger proportion, and the extreme value rings have a smaller proportion. This further ensures that the size deviation of the component rings does not need to strictly conform to the normal distribution, and the size accuracy requirements of the component rings are not high.

[0035] For example, in another alternative implementation, step S101 further includes:

[0036] Step S1014: The above-mentioned component rings whose size deviations are distributed in the form of normal distribution and uniform distribution are determined as the above-mentioned statistical rings. The above-mentioned normal distribution means that the size deviations of the above-mentioned component rings conform to a normal distribution, and the above-mentioned uniform distribution means that the size deviations of the above-mentioned component rings are evenly distributed within the tolerance range of the above-mentioned component rings.

[0037] Step S1015: The above-mentioned component loop whose tolerance distribution is an extreme value distribution is determined as the above-mentioned extreme value loop, wherein the above-mentioned extreme value distribution is an endpoint of the range in which the dimensional deviation of the above-mentioned component loop is equal to the allowable tolerance of the above-mentioned component loop.

[0038] In the above embodiments, during actual assembly, the common distributions of dimensional deviations in the dimensional chain links are normal distribution, extreme value distribution, and uniform distribution. For example, the dimensional deviations during part processing conform to a normal distribution. During assembly, the part is biased to one side of the hole due to the force (gravity), causing the dimensional deviation to conform to an extreme value distribution. During assembly, the part is positioned arbitrarily in the hole without force, causing the dimensional deviation to conform to a uniform distribution. The above-mentioned component loops of normal and uniform distributions are identified as the above-mentioned statistical loops, and the above-mentioned component loops of extreme value distributions are identified as the above-mentioned extreme value loops, thus completing the classification.

[0039] Step S102: Calculate the verification tolerance of all the above statistical loops using statistical methods to obtain the first verification tolerance;

[0040] Optionally, the present invention does not limit the specific process of calculating the verification tolerance of all the above-mentioned statistical loops using statistical methods to obtain the first verification tolerance, and any feasible method is within the protection scope of the present invention.

[0041] For example, in an optional implementation, step S102 above includes:

[0042] Step S1021: Calculate the sum of squares of the tolerances of each of the above statistical loops to obtain the first sum of squares of tolerances;

[0043] Step S1022: Calculate the square root of the sum of squares of the first tolerance to obtain the first verification tolerance.

[0044] In the above embodiment, the tolerances of each component link in the dimension chain are T1, T2, T3, T4, and T5, respectively. The component links corresponding to T1, T3, and T5 are statistical links. The verification tolerance of all the above component links, i.e., the first verification tolerance, is calculated using the above statistical method.

[0045] For example, in another alternative implementation, step S102 further includes:

[0046] Step S1023: Calculate the sum of squares of the tolerances of each first statistical ring to obtain the sum of squares of the second tolerances. The first statistical ring is the component ring in which the distribution of the dimensional deviation is the normal distribution.

[0047] Step S1024: Calculate the product of the sum of squares of the tolerances of each second statistical ring and the correction coefficient to obtain the third sum of squares of the tolerances. The second statistical ring is the component ring in which the distribution of the dimensional deviations is uniformly distributed. The correction coefficient is a constant greater than 1.

[0048] Step S1025: Calculate the sum of the second and third tolerance sums of squares to obtain the fourth tolerance sum of squares;

[0049] Step S1026: Calculate the square root of the sum of squares of the fourth tolerance to obtain the first verification tolerance.

[0050] In the above embodiments, since uniformly distributed dimensional deviations are generally larger than normally distributed dimensional deviations, calculating the tolerance using statistical methods is not entirely consistent with actual production. The tolerances of each component in the dimensional chain are T1, T2, T3, T4, and T5. For example, the component links corresponding to T1, T3, and T5 are statistical links, and the dimensional deviation of the component link corresponding to T1 conforms to an average distribution, the dimensional deviations of the component links corresponding to T3 and T5 conform to a normal distribution, and the dimensional deviations of the component links corresponding to T2 and T4 conform to an extreme value distribution. The aforementioned first verification tolerance... Wherein, 3 is a correction factor, which can be adjusted by those skilled in the art according to the actual situation.

[0051] Step S103: Calculate the verification tolerance of all the above extreme value loops using the extreme value method to obtain the second verification tolerance;

[0052] Optionally, the present invention does not limit the specific process of calculating the verification tolerance of all the above-mentioned extreme value loops using the extreme value method to obtain the second verification tolerance, and any feasible method is within the protection scope of the present invention.

[0053] For example, in an optional implementation, step S103 above includes:

[0054] Step S1031: Calculate the sum of the tolerances of each of the above extreme value loops to obtain the above second verification tolerance.

[0055] In the above embodiments, the tolerances of each component loop in the dimensional chain are T1, T2, T3, T4, and T5, respectively. For example, the component loops corresponding to T2 and T4 are extreme value loops, and the second verification tolerance T is... z =T2+T4.

[0056] Step S104: Perform dimensional chain verification using a third verification tolerance, where the third verification tolerance is the sum of the first verification tolerance and the second verification tolerance.

[0057] It should be noted that using the sum of the first and second verification tolerances as the verification tolerance for dimensional chain verification combines the calculation results of traditional statistical methods and limit methods, which can ensure that the dimensional chain tolerance design is reasonable while also ensuring that the product accuracy is appropriate and not too stringent.

[0058] In the aforementioned dimensional chain verification methods, existing technologies employ extreme value methods or statistical methods. The extreme value method uses the sum of all tolerances as the verification tolerance, requiring each tolerance to be small to meet verification requirements, necessitating high dimensional accuracy, which is difficult to achieve in actual production or is costly. The statistical method uses the square root of the sum of the squares of all tolerances as the verification tolerance, resulting in a much smaller tolerance compared to the extreme value method, with lower dimensional accuracy requirements. However, it cannot guarantee that the dimensional deviations of the components strictly conform to a normal distribution; any deviation may prevent properly assembled parts that have passed verification. This application uses the limit method to calculate the verification tolerance for some components and the statistical method for others, summing the two tolerances as the verification tolerance for the dimensional chain verification. This reduces the dimensional accuracy requirements of the parts and eliminates the requirement for strict conformity of dimensional deviations to a normal distribution, thus solving the problem that existing dimensional chain verification methods cannot meet the needs of actual production.

[0059] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0060] This application also provides a dimensional chain verification device. It should be noted that the dimensional chain verification device of this application can be used to execute the dimensional chain verification method provided in this application. The dimensional chain verification device provided in this application is described below.

[0061] Figure 2 This is a schematic diagram of a dimensional chain verification device according to an embodiment of this application. Figure 2 As shown, the device includes:

[0062] Classification unit 10 is used to divide the constituent loops in the size chain into multiple statistical loops and at least one extreme loop;

[0063] Optionally, the present invention does not limit the specific process of dividing the constituent loops in the size chain into multiple statistical loops and at least one extreme loop; any feasible method is within the protection scope of the present invention.

[0064] For example, in one alternative implementation, the classification unit includes:

[0065] The first calculation module is used to calculate the verification tolerance of all the above-mentioned component rings using the above statistical method, and obtain the fourth verification tolerance;

[0066] The second calculation module is used to calculate the contribution rate of each of the above-mentioned component rings, and obtain multiple contribution rates. The contribution rate is the percentage of the ratio of the square of the tolerance of the above-mentioned component ring to the square of the fourth verification tolerance. The contribution rate corresponds one-to-one with the above-mentioned component ring.

[0067] The first determining module is used to determine the constituent rings whose sum of contribution rates is greater than or equal to a predetermined value as the statistical rings, and to determine the constituent rings other than the statistical rings as the extreme value rings, wherein the contribution rate of any statistical ring is greater than or equal to the contribution rate of any extreme value ring.

[0068] In the above embodiments, the tolerances of each component link in the dimension chain are T1, T2, T3, T4, and T5, respectively. The verification tolerance of all the above component links, i.e., the fourth verification tolerance, is calculated using the above statistical method. Contribution rate of the above constituent rings Where n = 1, 2, ... 5, for example, C1≥C3>C5≥C2≥C4, C1+C3+C5≥90%, then the component rings corresponding to C1, C3 and C5 are determined to be statistical rings, and the component rings corresponding to C2 and C4 are determined to be extreme value rings. The statistical rings have a larger proportion, and the extreme value rings have a smaller proportion. This further ensures that the size deviation of the component rings does not need to strictly conform to the normal distribution, and the size accuracy requirements of the component rings are not high.

[0069] For example, in another alternative implementation, the classification unit further includes:

[0070] The second determining module is used to determine the above-mentioned component rings whose size deviations are distributed in the form of normal distribution and uniform distribution as the above-mentioned statistical rings. The above-mentioned normal distribution means that the size deviations of the above-mentioned component rings conform to a normal distribution, and the above-mentioned uniform distribution means that the size deviations of the above-mentioned component rings are uniformly distributed within the tolerance range of the above-mentioned component rings.

[0071] The third determining module is used to determine the above-mentioned component loop whose tolerance distribution is an extreme value distribution as the above-mentioned extreme value loop, wherein the above-mentioned extreme value distribution is an endpoint of the interval in which the dimensional deviation of the above-mentioned component loop is equal to the allowable tolerance of the above-mentioned component loop.

[0072] In the above embodiments, during actual assembly, the common distributions of dimensional deviations in the dimensional chain links are normal distribution, extreme value distribution, and uniform distribution. For example, the dimensional deviations during part processing conform to a normal distribution. During assembly, the part is biased to one side of the hole due to the force (gravity), causing the dimensional deviation to conform to an extreme value distribution. During assembly, the part is positioned arbitrarily in the hole without force, causing the dimensional deviation to conform to a uniform distribution. The above-mentioned component loops of normal and uniform distributions are identified as the above-mentioned statistical loops, and the above-mentioned component loops of extreme value distributions are identified as the above-mentioned extreme value loops, thus completing the classification.

[0073] The first calculation unit 20 is used to calculate the verification tolerance of all the above-mentioned statistical loops using statistical methods to obtain the first verification tolerance;

[0074] Optionally, the present invention does not limit the specific process of calculating the verification tolerance of all the above-mentioned statistical loops using statistical methods to obtain the first verification tolerance, and any feasible method is within the protection scope of the present invention.

[0075] For example, in one alternative implementation, the first computing unit includes:

[0076] The third calculation module is used to calculate the sum of squares of the tolerances of each of the above statistical loops, and obtain the first sum of squares of the tolerances;

[0077] The fourth calculation module is used to calculate the square root of the sum of squares of the first tolerance mentioned above, and to obtain the first verification tolerance mentioned above.

[0078] In the above embodiment, the tolerances of each component link in the dimension chain are T1, T2, T3, T4, and T5, respectively. The component links corresponding to T1, T3, and T5 are statistical links. The verification tolerance of all the above component links, i.e., the first verification tolerance, is calculated using the above statistical method.

[0079] For example, in another alternative implementation, the first computing unit further includes:

[0080] The fifth calculation module is used to calculate the sum of squares of the tolerances of each first statistical ring to obtain the sum of squares of the second tolerance. The first statistical ring is the component ring in which the distribution of the dimensional deviation is the normal distribution.

[0081] The sixth calculation module is used to calculate the product of the sum of squares of the tolerances of each second statistical ring and the correction coefficient to obtain the sum of squares of the third tolerance. The second statistical ring is the component ring in which the distribution of the dimensional deviation is uniformly distributed. The correction coefficient is a constant greater than 1.

[0082] The seventh calculation module is used to calculate the sum of the second and third tolerance sums of squares to obtain the fourth tolerance sum of squares;

[0083] The eighth calculation module is used to calculate the square root of the sum of squares of the fourth tolerance mentioned above, and to obtain the first verification tolerance mentioned above.

[0084] In the above embodiments, since uniformly distributed dimensional deviations are generally larger than normally distributed dimensional deviations, calculating the tolerance using statistical methods is not entirely consistent with actual production. The tolerances of each component in the dimensional chain are T1, T2, T3, T4, and T5. For example, the component links corresponding to T1, T3, and T5 are statistical links, and the dimensional deviation of the component link corresponding to T1 conforms to an average distribution, the dimensional deviations of the component links corresponding to T3 and T5 conform to a normal distribution, and the dimensional deviations of the component links corresponding to T2 and T4 conform to an extreme value distribution. The aforementioned first verification tolerance... Wherein, 3 is a correction factor, which can be adjusted by those skilled in the art according to the actual situation.

[0085] The second calculation unit 30 is used to calculate the verification tolerance of all the above-mentioned extreme value loops using the extreme value method, and obtain the second verification tolerance;

[0086] Optionally, the present invention does not limit the specific process of calculating the verification tolerance of all the above-mentioned extreme value loops using the extreme value method to obtain the second verification tolerance, and any feasible method is within the protection scope of the present invention.

[0087] For example, in one alternative implementation, the second computing unit includes:

[0088] The ninth calculation module is used to calculate the sum of the tolerances of each of the above extreme value loops to obtain the second verification tolerance.

[0089] In the above embodiments, the tolerances of each component loop in the dimensional chain are T1, T2, T3, T4, and T5, respectively. For example, the component loops corresponding to T2 and T4 are extreme value loops, and the second verification tolerance T is... z =T2+T4.

[0090] The verification unit 40 is used to perform dimensional chain verification using a third verification tolerance, wherein the third verification tolerance is the sum of the first verification tolerance and the second verification tolerance.

[0091] It should be noted that using the sum of the first and second verification tolerances as the verification tolerance for dimensional chain verification combines the calculation results of traditional statistical methods and limit methods, which can ensure that the dimensional chain tolerance design is reasonable while also ensuring that the product accuracy is appropriate and not too stringent.

[0092] In the aforementioned dimensional chain verification device, existing technologies employ extreme value methods or statistical methods for dimensional chain verification. The extreme value method uses the sum of all tolerances as the verification tolerance, requiring each tolerance to be small to meet verification requirements, necessitating high dimensional accuracy, which is difficult to achieve in actual production or is costly. The statistical method uses the square root of the sum of the squares of all tolerances as the verification tolerance, resulting in a much smaller tolerance compared to the extreme value method, with lower dimensional accuracy requirements. However, it cannot guarantee that the dimensional deviations of the components in each link strictly conform to a normal distribution; any deviation may prevent the properly assembled parts that have passed verification. This application uses the limit method to calculate the verification tolerance for some components and the statistical method for others, summing the two verification tolerances as the dimensional chain verification tolerance. This reduces the dimensional accuracy requirements of the parts and eliminates the requirement for strict conformity of dimensional deviations to a normal distribution, thus solving the problem that existing dimensional chain verification methods cannot meet the needs of actual production.

[0093] This application also provides a dimensional chain verification system, including: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include methods for performing any of the above-described methods.

[0094] In the aforementioned dimensional chain verification system, existing technologies employ extreme value methods or statistical methods for dimensional chain verification. The extreme value method uses the sum of all tolerances as the verification tolerance, requiring each tolerance to be small to meet verification requirements, necessitating high dimensional accuracy, which is difficult to achieve in actual production or is costly. The statistical method uses the square root of the sum of the squares of all tolerances as the verification tolerance, resulting in a much smaller tolerance compared to the extreme value method, with lower dimensional accuracy requirements. However, it cannot guarantee that the dimensional deviations of the components strictly conform to a normal distribution; any deviation may prevent properly assembled parts that have passed verification. This application uses the limit method to calculate the verification tolerance for some components and the statistical method for others, summing the two verification tolerances as the dimensional chain verification tolerance. This reduces the dimensional accuracy requirements of the parts and eliminates the requirement for strict conformity of dimensional deviations to a normal distribution, thus solving the problem that existing dimensional chain verification methods cannot meet the needs of actual production.

[0095] The aforementioned size chain verification device includes a processor and a memory. The classification unit, the first calculation unit, the second calculation unit, and the verification unit are all stored in the memory as program units. The processor executes the aforementioned program units stored in the memory to achieve the corresponding functions.

[0096] The processor contains a kernel, which retrieves the corresponding program units from memory. One or more kernels can be configured, and adjusting kernel parameters can address the problem that existing dimensional chain verification methods cannot meet the needs of actual production.

[0097] The memory may include non-permanent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0098] This invention provides a computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the above-described method.

[0099] This invention provides a processor for running a program, wherein the program executes the method described above when it runs.

[0100] This invention provides a device including a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, it performs at least the following steps:

[0101] Step S101: Divide the constituent loops in the size chain into multiple statistical loops and at least one extreme loop;

[0102] Step S102: Calculate the verification tolerance of all the above statistical loops using statistical methods to obtain the first verification tolerance;

[0103] Step S103: Calculate the verification tolerance of all the above extreme value loops using the extreme value method to obtain the second verification tolerance;

[0104] Step S104: Perform dimensional chain verification using a third verification tolerance, where the third verification tolerance is the sum of the first verification tolerance and the second verification tolerance.

[0105] The devices mentioned in this article can be servers, PCs, tablets, mobile phones, etc.

[0106] This application also provides a computer program product, which, when executed on a data processing device, is suitable for executing an initialization program having at least the following method steps:

[0107] Step S101: Divide the constituent loops in the size chain into multiple statistical loops and at least one extreme loop;

[0108] Step S102: Calculate the verification tolerance of all the above statistical loops using statistical methods to obtain the first verification tolerance;

[0109] Step S103: Calculate the verification tolerance of all the above extreme value loops using the extreme value method to obtain the second verification tolerance;

[0110] Step S104: Perform dimensional chain verification using a third verification tolerance, where the third verification tolerance is the sum of the first verification tolerance and the second verification tolerance.

[0111] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0112] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units described above can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between units or modules, and may be electrical or other forms.

[0113] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0114] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0115] If the aforementioned integrated units are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a computer-readable storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned computer-readable storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0116] As can be seen from the above description, the embodiments of this application achieve the following technical effects:

[0117] 1) In the dimensional chain verification method of this application, the existing technology uses the extreme value method or the statistical method for dimensional chain verification. The extreme value method uses the sum of all tolerances as the verification tolerance. In order to meet the verification requirements, each tolerance must be small, requiring high dimensional accuracy, which is difficult to achieve in actual production or is costly. The statistical method uses the square root of the sum of the squares of all tolerances as the verification tolerance. The calculated verification tolerance is much smaller than that of the extreme value method, and the dimensional accuracy requirement is not high. However, it cannot guarantee that the dimensional deviation of each component link strictly conforms to the normal distribution. Once there is a deviation, it may cause the parts that have passed the verification to be unable to be assembled normally. This application uses the limit method to calculate the verification tolerance of some component links and the statistical method to calculate the verification tolerance of other component links. The sum of the two verification tolerances is used as the verification tolerance for dimensional chain verification. This makes the dimensional accuracy requirement of the parts not high and does not require the dimensional deviation of the parts to strictly conform to the normal distribution. This solves the problem that the dimensional chain verification method in the existing technology cannot meet the needs of actual production.

[0118] 2) In the dimensional chain verification device of this application, the existing technology uses extreme value method or statistical method for dimensional chain verification. The extreme value method uses the sum of all tolerances as the verification tolerance. In order to meet the verification requirements, each tolerance must be small, requiring high dimensional accuracy, which is difficult to achieve in actual production or is costly. The statistical method uses the square root of the sum of the squares of all tolerances as the verification tolerance. The calculated verification tolerance is much smaller than that of the extreme value method, and the dimensional accuracy requirement is not high. However, it cannot guarantee that the dimensional deviation of each component link strictly conforms to the normal distribution. Once there is a deviation, it may cause the parts that have passed the verification to be unable to be assembled normally. This application uses the limit method to calculate the verification tolerance of some component links and the statistical method to calculate the verification tolerance of other component links. The sum of the two verification tolerances is used as the verification tolerance for dimensional chain verification. This makes the dimensional accuracy requirement of the parts not high and does not require the dimensional deviation of the parts to strictly conform to the normal distribution. This solves the problem that the dimensional chain verification method in the existing technology cannot meet the needs of actual production.

[0119] 3) In the dimensional chain verification system of this application, the existing technology uses extreme value method or statistical method for dimensional chain verification. The extreme value method uses the sum of all tolerances as the verification tolerance. In order to meet the verification requirements, each tolerance must be small, requiring high dimensional accuracy, which is difficult to achieve in actual production or is costly. The statistical method uses the square root of the sum of the squares of all tolerances as the verification tolerance. The calculated verification tolerance is much smaller than that of the extreme value method, and the dimensional accuracy requirement is not high. However, it cannot guarantee that the dimensional deviation of each component link strictly conforms to a normal distribution. Once there is a deviation, it may cause the parts that have passed the verification to be unable to be assembled normally. This application uses the limit method to calculate the verification tolerance of some component links and the statistical method to calculate the verification tolerance of other component links. The sum of the two verification tolerances is used as the verification tolerance for dimensional chain verification. This makes the dimensional accuracy requirement of the parts not high and does not require the dimensional deviation of the parts to strictly conform to a normal distribution. This solves the problem that the dimensional chain verification method in the existing technology cannot meet the needs of actual production.

[0120] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for verifying dimensional chains, characterized in that, include: The constituent loops in the size chain are divided into multiple statistical loops and at least one extreme value loop; The first verification tolerance is obtained by calculating the verification tolerance of all the statistical loops using a statistical method. The verification tolerances of all the extreme value loops are calculated using the extreme value method to obtain the second verification tolerance; The dimensional chain is checked using a third verification tolerance, which is the sum of the first verification tolerance and the second verification tolerance. Dividing the component loops in the size chain into multiple statistical loops and at least one extreme loop includes: calculating the check tolerances of all the component loops using the statistical method to obtain a fourth check tolerance; The contribution rate of each component loop is calculated to obtain multiple contribution rates. The contribution rate is the percentage of the square of the tolerance of the component loop to the square of the fourth verification tolerance. Each contribution rate corresponds to a component loop. The component loop whose sum of contribution rates is greater than or equal to a predetermined value is determined as the statistical loop. The component loops other than the statistical loops are determined as the extreme value loops. The contribution rate of any statistical loop is greater than or equal to the contribution rate of any extreme value loop.

2. The method according to claim 1, characterized in that, The check tolerances for all the statistical loops are calculated using statistical methods to obtain the first check tolerance, which includes: Calculate the sum of squares of the tolerances of each of the statistical loops to obtain the first sum of squares of tolerances; Calculate the square root of the sum of squares of the first tolerance to obtain the first verification tolerance.

3. The method according to claim 1, characterized in that, The component loops in the size chain are divided into multiple statistical loops and at least one extreme loop, including: The component loop whose size deviation is distributed in a normal or uniform manner is defined as the statistical loop. The normal distribution means that the size deviation of the component loop conforms to a normal distribution, and the uniform distribution means that the size deviation of the component loop is evenly distributed within the tolerance range of the component loop. The component loop whose tolerance distribution is an extreme value distribution is defined as the extreme value loop, where the extreme value distribution is an endpoint of the range in which the dimensional deviation of the component loop is equal to the allowable tolerance of the component loop.

4. The method according to claim 3, characterized in that, The check tolerances for all the statistical loops are calculated using statistical methods to obtain the first check tolerance, which includes: Calculate the sum of squares of the tolerances of each first statistical ring to obtain the sum of squares of the second tolerances. The first statistical rings are the constituent rings whose size deviations are distributed in the form of the normal distribution. The product of the sum of squares of the tolerances of each second statistical ring and the correction factor is calculated to obtain the sum of squares of the third tolerance. The second statistical ring is the component ring in which the distribution of the size deviation is uniformly distributed. The correction factor is a constant greater than 1. Calculate the sum of the second and third tolerance sums of squares to obtain the fourth tolerance sum of squares; Calculate the square root of the sum of squares of the fourth tolerance to obtain the first verification tolerance.

5. The method according to any one of claims 1 to 4, characterized in that, The verification tolerances for all the extreme value loops are calculated using the extreme value method to obtain the second verification tolerance, which includes: The sum of the tolerances of each extreme value loop is calculated to obtain the second verification tolerance.

6. A dimensional chain verification device, characterized in that, include: A classification unit is used to divide the constituent loops in the size chain into multiple statistical loops and at least one extreme loop; The first calculation unit is used to calculate the verification tolerance of the statistical loop using a statistical method to obtain the first verification tolerance; The second calculation unit is used to calculate the verification tolerance of the extreme value loop using the extreme value method, and obtain the second verification tolerance; The verification unit is used to perform dimensional chain verification using a third verification tolerance, wherein the third verification tolerance is the sum of the first verification tolerance and the second verification tolerance; The classification unit includes: a first calculation module, used to calculate the verification tolerance of all the component loops using the statistical method to obtain a fourth verification tolerance; a second calculation module, used to calculate the contribution rate of each component loop to obtain multiple contribution rates, wherein the contribution rate is the percentage of the square of the tolerance of the component loop to the square of the fourth verification tolerance, and the contribution rate corresponds one-to-one with the component loop; and a first determination module, used to determine the component loops whose sum of contribution rates is greater than or equal to a predetermined value as the statistical loops, and to determine the component loops other than the statistical loops as the extreme value loops, wherein the contribution rate of any statistical loop is greater than or equal to the contribution rate of any extreme value loop.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein the program performs the method according to any one of claims 1 to 5.

8. A processor, characterized in that, The processor is used to run a program, wherein the program executes the method according to any one of claims 1 to 5 when it runs.

9. A dimensional chain verification system, characterized in that, include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs comprising methods for performing any one of claims 1 to 5.

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