Mechanical precision specification evaluation method, system, device, apparatus, and storage medium

Abstract

The application discloses a mechanical precision specification evaluation method, system, device, equipment and a storage medium. The mechanical precision specification evaluation method comprises the following steps: determining a first mechanical type and a first precision type to be evaluated; acquiring precision specification parameters to be evaluated according to the first mechanical type and the first precision type; inputting the precision specification parameters to be evaluated into a pre-constructed precision distribution model to obtain a precision specification evaluation result. The application solves the problem that the automatic mechanical precision specification evaluation process is time-consuming and long, and can quickly complete the evaluation of the automatic mechanical precision specification.

Description

Technical Field

[0001] This application relates to the field of automation control technology, and in particular to a method, system, device, equipment, and storage medium for evaluating mechanical precision specifications. Background Technology

[0002] When determining and judging the precision specifications of automated machinery, the issue of their rationality often arises. When the precision specification value is too high, poorly accurate items cannot be filtered out, failing to meet usage requirements; when the value is too low, too many items will fail to pass, thus affecting the pass rate.

[0003] There are generally two ways to determine and judge accuracy specifications. One approach is to determine them based on the accuracy specifications of other manufacturers or the accuracy specifications required by customers. However, in reality, since each manufacturer has different capabilities in material handling, processing, assembly, and modeling control, the standards for judging accuracy specifications are not uniform and therefore cannot be directly referenced. The other approach is to determine them based on historical data and experience values. This approach requires the prior collection and statistical analysis of a large amount of relevant information, followed by summarization, and usually involves a long decision-making and adjustment cycle.

[0004] Therefore, it is necessary to propose a solution for rapidly evaluating accuracy specifications. Summary of the Invention

[0005] The main objective of this application is to provide a method, system, device, equipment, and storage medium for evaluating mechanical precision specifications, aiming to solve the problem of long time consumption in the automated mechanical precision specification evaluation process and to complete the evaluation of automated mechanical precision specifications quickly.

[0006] To achieve the above objectives, this application provides a method for evaluating mechanical precision specifications, the method comprising:

[0007] Determine the first mechanical type and the first precision type to be evaluated;

[0008] Based on the first machine type and the first precision type, obtain the precision specification parameters to be evaluated;

[0009] The accuracy specification parameters to be evaluated are input into a pre-built accuracy distribution model to obtain the accuracy specification evaluation results.

[0010] Optionally, the accuracy specification evaluation result includes the pass rate of the evaluation, and after the step of obtaining the accuracy specification parameters to be evaluated, the method further includes:

[0011] Determine the type of the accuracy specification parameter;

[0012] If the type of the accuracy specification parameter is an accuracy specification line, then the accuracy specification line to be evaluated is input into the pre-built accuracy distribution model to obtain the pass rate of the evaluation.

[0013] Optionally, the accuracy specification evaluation result further includes the evaluated specification line, and after the step of determining the type of the accuracy specification parameter, it further includes:

[0014] If the type of the accuracy specification parameter is pass rate, then the pass rate to be evaluated is input into the pre-built accuracy distribution model to obtain the specification line to be evaluated.

[0015] Optionally, before the step of determining the first machine type and the first precision type to be evaluated, the method further includes:

[0016] Constructing the precision distribution model specifically includes:

[0017] Determine the second mechanical type and the second precision type to be constructed;

[0018] Based on the second machine type and the second precision type, establish a precision model;

[0019] The influencing variables are determined based on the accuracy model.

[0020] The precision distribution model is constructed based on the influencing variables.

[0021] Optionally, the step of constructing the precision distribution model based on the influencing variables includes:

[0022] Determine the error distribution model and interval based on the aforementioned influencing variables;

[0023] Random numbers are generated based on the error distribution model and interval, and then a random array is formed.

[0024] The error is calculated by inputting the random array into the accuracy model;

[0025] The error is segmented and summarized based on the Euclidean distance to obtain a precision histogram;

[0026] The accuracy histogram is fitted to the corresponding error distribution curve to obtain the accuracy distribution model.

[0027] Optionally, after the step of inputting the accuracy specification parameters to be evaluated into a pre-built accuracy distribution model to obtain the accuracy specification evaluation result, the method further includes:

[0028] The decision result of obtaining the accuracy specification evaluation result includes meeting the requirements and not meeting the requirements;

[0029] If the decision result meets the requirements, the evaluation of mechanical precision specifications ends;

[0030] If the decision result does not meet the requirements, then the error distribution of the influencing variables is controlled.

[0031] Execution steps: Determine the error distribution model and interval based on the influencing variables.

[0032] This application also proposes a mechanical precision specification evaluation system, which includes at least one of the following: a parameter distribution model, a precision model, a precision bar chart, and a precision distribution model;

[0033] The parameter distribution model is used to determine the error distribution model and interval based on the influence variables of the accuracy model; and to generate random numbers based on the error distribution model and interval, forming a random array.

[0034] The accuracy model is used to calculate the error by inputting the random array into the accuracy model; the error is then segmented and summarized according to the Euclidean distance to obtain the accuracy histogram.

[0035] The precision histogram is used to fit the precision histogram to the corresponding error distribution curve to obtain the precision distribution model;

[0036] The accuracy distribution model is used to input the accuracy specification parameters to be evaluated into the accuracy distribution model to obtain the accuracy specification evaluation results.

[0037] This application also proposes a mechanical precision specification evaluation device, which includes:

[0038] The type determination module is used to determine the first mechanical type and the first precision type to be evaluated.

[0039] The parameter acquisition module is used to acquire the accuracy specification parameters to be evaluated based on the first machine type and the first accuracy type.

[0040] The accuracy evaluation module is used to input the accuracy specification parameters to be evaluated into a pre-built accuracy distribution model to obtain the accuracy specification evaluation results.

[0041] This application also proposes an apparatus comprising a memory, a processor, and a mechanical precision specification evaluation program stored in the memory and executable on the processor. When executed by the processor, the mechanical precision specification evaluation program implements the steps of the mechanical precision specification evaluation method as described above.

[0042] This application also proposes a computer-readable storage medium storing a mechanical precision specification evaluation program, which, when executed by a processor, implements the steps of the mechanical precision specification evaluation method as described above.

[0043] The mechanical precision specification evaluation method, system, device, equipment, and storage medium proposed in this application determine a first mechanical type and a first precision type to be evaluated; obtain precision specification parameters to be evaluated based on the first mechanical type and the first precision type; and input the precision specification parameters to be evaluated into a pre-constructed precision distribution model to obtain the precision specification evaluation result. Based on this application's solution, there is no need to construct a precision distribution model using actual production and historical data. By evaluating the precision specification parameters to be evaluated using the constructed precision distribution model, intuitive and data-driven precision specification evaluation results can be quickly obtained, solving the problem of long evaluation cycles in the automated mechanical precision specification evaluation process and enabling rapid completion of the automated mechanical precision specification evaluation. Attached Figure Description

[0044] Figure 1 This is a schematic diagram of the functional modules of the equipment to which the mechanical precision specification evaluation device of this application belongs;

[0045] Figure 2 This is a flowchart illustrating a first exemplary embodiment of the mechanical precision specification evaluation method of this application;

[0046] Figure 3 This is a flowchart illustrating a second exemplary embodiment of the mechanical precision specification evaluation method of this application;

[0047] Figure 4 This is a flowchart illustrating a third exemplary embodiment of the mechanical precision specification evaluation method of this application;

[0048] Figure 5 This is a schematic diagram of the process for constructing the precision distribution model involved in the third exemplary embodiment of the mechanical precision specification evaluation method of this application;

[0049] Figure 6 This is a schematic diagram of the process for constructing the accuracy distribution model based on the influencing variables, as described in the third exemplary embodiment of the mechanical accuracy specification evaluation method of this application.

[0050] Figure 7 This is a flowchart illustrating the fourth exemplary embodiment of the mechanical precision specification evaluation method of this application;

[0051] Figure 8 This is a flowchart illustrating the fifth exemplary embodiment of the mechanical precision specification evaluation method of this application.

[0052] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0053] It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit this application.

[0054] The main solution of this application embodiment is to construct a precision distribution model, specifically including: determining the second machine type and the second precision type to be constructed; establishing a precision model based on the second machine type and the second precision type; determining influencing variables based on the precision model; constructing the precision distribution model based on the influencing variables; after completing the construction of the precision distribution model, determining the first machine type and the first precision type to be evaluated; obtaining the precision specification parameters to be evaluated based on the first machine type and the first precision type; and inputting the precision specification parameters to be evaluated into the pre-constructed precision distribution model to obtain the precision specification evaluation result. Based on this application solution, there is no need to construct a precision distribution model using actual production and historical data. By evaluating the precision specification parameters to be evaluated using the constructed precision distribution model, intuitive and data-driven precision specification evaluation results can be obtained quickly, solving the problem of long evaluation cycles in the precision specification evaluation process of automated machinery, and enabling the rapid completion of the precision specification evaluation of automated machinery.

[0055] Specifically, refer to Figure 1 , Figure 1 This is a functional module diagram of the equipment to which the mechanical precision specification evaluation device of this application belongs. The mechanical precision specification evaluation device can be an independent device capable of evaluating mechanical precision specifications and building models, and it can be carried on the equipment in the form of hardware or software. The equipment can be a smart mobile terminal with data processing capabilities, such as a mobile phone or tablet, or a fixed terminal device or server with data processing capabilities.

[0056] In this embodiment, the equipment to which the mechanical precision specification evaluation device belongs includes at least an output module 110, a processor 120, a memory 130, and a communication module 140.

[0057] The memory 130 stores the operating system and the mechanical precision specification evaluation program. The mechanical precision specification evaluation device can store information such as the first mechanical type and first precision type to be evaluated, the precision specification parameters to be evaluated, the pre-constructed precision distribution model, the obtained precision specification evaluation results, the second mechanical type and second precision type to be constructed, the established precision model, the precision distribution model constructed based on the influencing variables determined by the precision model, the error distribution model and interval determined based on the influencing variables, the generated random numbers and random arrays, the precision histogram obtained by segmenting and summarizing the errors according to the Euclidean distance, and the obtained decision results in the memory 130. The output module 110 can be a display screen, etc. The communication module 140 can include a WIFI module, a mobile communication module, and a Bluetooth module, etc., and communicates with external devices or servers through the communication module 140.

[0058] The mechanical precision specification evaluation program in memory 130, when executed by the processor, performs the following steps:

[0059] Determine the first mechanical type and the first precision type to be evaluated;

[0060] Based on the first machine type and the first precision type, obtain the precision specification parameters to be evaluated;

[0061] The accuracy specification parameters to be evaluated are input into a pre-built accuracy distribution model to obtain the accuracy specification evaluation results.

[0062] Furthermore, when the mechanical precision specification evaluation program in memory 130 is executed by the processor, it also performs the following steps:

[0063] Determine the type of the accuracy specification parameter;

[0064] If the type of the accuracy specification parameter is an accuracy specification line, then the accuracy specification line to be evaluated is input into the pre-built accuracy distribution model to obtain the pass rate of the evaluation.

[0065] Furthermore, when the mechanical precision specification evaluation program in memory 130 is executed by the processor, it also performs the following steps:

[0066] If the type of the accuracy specification parameter is pass rate, then the pass rate to be evaluated is input into the pre-built accuracy distribution model to obtain the specification line to be evaluated.

[0067] Furthermore, when the mechanical precision specification evaluation program in memory 130 is executed by the processor, it also performs the following steps:

[0068] Constructing the precision distribution model specifically includes:

[0069] Determine the second mechanical type and the second precision type to be constructed;

[0070] Based on the second machine type and the second precision type, establish a precision model;

[0071] The influencing variables are determined based on the accuracy model.

[0072] The precision distribution model is constructed based on the influencing variables.

[0073] Furthermore, when the mechanical precision specification evaluation program in memory 130 is executed by the processor, it also performs the following steps:

[0074] Determine the error distribution model and interval based on the aforementioned influencing variables;

[0075] Random numbers are generated based on the error distribution model and interval, and then a random array is formed.

[0076] The error is calculated by inputting the random array into the accuracy model;

[0077] The error is segmented and summarized based on the Euclidean distance to obtain a precision histogram;

[0078] The accuracy histogram is fitted to the corresponding error distribution curve to obtain the accuracy distribution model.

[0079] Furthermore, when the mechanical precision specification evaluation program in memory 130 is executed by the processor, it also performs the following steps:

[0080] The decision result of obtaining the accuracy specification evaluation result includes meeting the requirements and not meeting the requirements;

[0081] If the decision result meets the requirements, the evaluation of mechanical precision specifications ends;

[0082] If the decision result does not meet the requirements, then the error distribution of the influencing variables is controlled.

[0083] Execution steps: Determine the error distribution model and interval based on the influencing variables.

[0084] This embodiment, through the above-described scheme, specifically determines the first machine type and the first precision type to be evaluated; obtains the precision specification parameters to be evaluated based on the first machine type and the first precision type; and inputs the precision specification parameters to be evaluated into a pre-constructed precision distribution model to obtain the precision specification evaluation result. Based on this application's scheme, there is no need to construct a precision distribution model using actual production and historical data. By evaluating the precision specification parameters to be evaluated using the constructed precision distribution model, intuitive and data-driven precision specification evaluation results can be quickly obtained, solving the problem of long evaluation cycles in the precision specification evaluation process of automated machinery and enabling rapid completion of the precision specification evaluation of automated machinery.

[0085] Based on, but not limited to, the above-described device architecture, this application proposes method embodiments.

[0086] First Embodiment

[0087] Reference Figure 2 , Figure 2 This is a flowchart illustrating a first exemplary embodiment of the mechanical precision specification evaluation method of this application. The executing entity of this embodiment can be a mechanical precision specification evaluation device, a mechanical precision specification evaluation equipment, or a server. This embodiment uses a mechanical precision specification evaluation device as an example, which can be integrated into a device with data processing capabilities. The mechanical precision specification evaluation method includes:

[0088] Step S101: Determine the first mechanical type and the first precision type to be evaluated.

[0089] In this embodiment, the type of automated machinery to be evaluated is determined, denoted as a first machinery type. For example, the machinery type may include: a specific model of SCARA robot, a specific model of XYZAC 5-axis robot, etc. Then, the type of accuracy to be evaluated is determined, denoted as a first accuracy type. Optionally, the accuracy type may include, but is not limited to: absolute position accuracy, repeatability accuracy, and trajectory accuracy, etc.

[0090] Step S102: Obtain the accuracy specification parameters to be evaluated based on the first machine type and the first accuracy type.

[0091] In this embodiment, based on the determined first machine type and first precision type, the precision specification parameters to be evaluated corresponding to that type are obtained. Optionally, the precision specification parameters refer to index parameters used to measure the precision specifications of automated machinery, which may include, but are not limited to, the precision specification line and pass rate of the machinery.

[0092] Step S103: Input the accuracy specification parameters to be evaluated into the pre-built accuracy distribution model to obtain the accuracy specification evaluation results.

[0093] In this embodiment, a pre-built accuracy distribution model can be used to evaluate the input accuracy specification parameters to be evaluated, and output the corresponding accuracy specification evaluation results. Optionally, the accuracy specification evaluation results may include, but are not limited to, the pass rate of the evaluation, the evaluated accuracy specification line, or the evaluation results on whether the accuracy specification line is reasonable.

[0094] This embodiment, through the above-described scheme, specifically determines the first machine type and the first precision type to be evaluated; obtains the precision specification parameters to be evaluated based on the first machine type and the first precision type; and inputs the precision specification parameters to be evaluated into a pre-constructed precision distribution model to obtain the precision specification evaluation result. Based on this application's scheme, there is no need to construct a precision distribution model using actual production and historical data. By evaluating the precision specification parameters to be evaluated using the constructed precision distribution model, intuitive and data-driven precision specification evaluation results can be quickly obtained, solving the problem of long evaluation cycles in the precision specification evaluation process of automated machinery and enabling rapid completion of the precision specification evaluation of automated machinery.

[0095] Second Embodiment

[0096] Based on the first embodiment described above, this embodiment further discloses a method implemented after the step of obtaining the accuracy specification parameters to be evaluated. (See reference...) Figure 3 , Figure 3 This is a flowchart illustrating a second exemplary embodiment of the mechanical precision specification evaluation method of this application. In this embodiment, the precision specification evaluation result may include the pass rate of the evaluation. After obtaining the precision specification parameters to be evaluated based on the first machine type and the first precision type in step S102, the method may further include:

[0097] Step S1021: Determine the type of the accuracy specification parameter.

[0098] In this embodiment, after obtaining the accuracy specification parameters to be evaluated, the type of the accuracy specification parameters is determined. Optionally, the type of the accuracy specification parameters may include, but is not limited to, accuracy specification lines and pass rates.

[0099] Optionally, if the type of the accuracy specification parameter is an accuracy specification line, then step S1031 is executed, inputting the accuracy specification line to be evaluated into the pre-built accuracy distribution model to obtain the pass rate of the evaluation. The pre-built accuracy distribution model can be used to evaluate the input accuracy specification line to be evaluated and obtain the corresponding pass rate.

[0100] Optionally, this embodiment also discloses another method implemented after the step of determining the type of the accuracy specification parameter. In this embodiment, the accuracy specification evaluation result may further include the evaluated specification line, and after step S1021 above, which determines the type of the accuracy specification parameter, it may further include:

[0101] Step S1032: If the type of the accuracy specification parameter is pass rate, then the pass rate to be evaluated is input into the pre-built accuracy distribution model to obtain the specification line to be evaluated.

[0102] In this embodiment, if the type of the accuracy specification parameter is pass rate, the input pass rate to be evaluated is evaluated through a pre-built accuracy distribution model, and the corresponding evaluation specification line is output in reverse.

[0103] This embodiment, through the above-described scheme, specifically determines the type of the precision specification parameter; if the type of the precision specification parameter is a precision specification line, the precision specification line to be evaluated is input into the pre-built precision distribution model to obtain the evaluation pass rate; if the type of the precision specification parameter is a pass rate, the pass rate to be evaluated is input into the pre-built precision distribution model to obtain the evaluated specification line. Based on this application's scheme, no actual production and historical data are required to construct the precision distribution model. The constructed precision distribution model can not only evaluate the precision specification line to be evaluated, but also perform reverse evaluation of the pass rate to be evaluated, meeting the bidirectional evaluation requirements of precision specifications in automated machinery.

[0104] Third Embodiment

[0105] Based on the first embodiment described above, this embodiment further discloses a method for constructing the accuracy distribution model. (Refer to...) Figure 4 , Figure 4 This is a flowchart illustrating a third exemplary embodiment of the mechanical precision specification evaluation method of this application. Before step S101 above, which determines the first mechanical type and the first precision type to be predicted and evaluated, the method may further include:

[0106] Step S100: Construct the accuracy distribution model. In this embodiment, step S100 is implemented before step S101. In other embodiments, step S100 may also be implemented between step S101 and step S103.

[0107] Compared to the above Figure 2 The embodiment shown also includes a scheme for constructing the accuracy distribution model, as described above. Figure 5 , Figure 5 This is a schematic diagram of the process for constructing the accuracy distribution model involved in the third exemplary embodiment of the mechanical accuracy specification evaluation method of this application. Specific steps may include:

[0108] Step S110: Determine the second mechanical type and the second precision type to be constructed;

[0109] Step S120: Establish a precision model based on the second machine type and the second precision type;

[0110] Step S130: Determine the influencing variables based on the accuracy model;

[0111] Step S140: Construct the precision distribution model based on the influencing variables.

[0112] In this embodiment, the type of machinery and the precision type to be constructed are first determined, and are represented by the second machinery type and the second precision type, respectively.

[0113] Then, based on the determined second mechanical type and second precision type, a corresponding function expression is established, and a precision model is built based on the function expression. Optionally, the precision model may include, but is not limited to, an absolute pose model, a repetitive pose model, and a trajectory precision model. Optionally, the variables of the precision model may include, but are not limited to, structural parameter variables, joint parameter variables, and assembly parameter variables. The numerical distribution of the variables of the precision model is represented by a parameter distribution model, that is, the independent variables in the precision model are the relevant parameters in the parameter distribution model. Optionally, the parameter distribution model may be provided by the suppliers and manufacturers of each component, or it may be obtained through measurement and statistical analysis. It should be noted that the parameters in the corresponding parameter distribution models of different precision models may not be the same.

[0114] Then, based on the established accuracy model, the functional expressions within the model are analyzed to determine their influencing variables. Optionally, during simplification, only a subset of parameters are selected as the main influencing variables. Afterward, a corresponding accuracy distribution model is constructed based on the determined influencing variables.

[0115] Furthermore, this embodiment also discloses a method for constructing the accuracy distribution model based on the influencing variables. (Refer to...) Figure 6 , Figure 6 This is a schematic flowchart illustrating the process of constructing the accuracy distribution model based on the influencing variables, as described in the third exemplary embodiment of the mechanical accuracy specification evaluation method of this application. Step S140 above, constructing the accuracy distribution model based on the influencing variables, may include:

[0116] Step S141: Determine the error distribution model and interval based on the influencing variables.

[0117] In this embodiment, a measurement area or group of measurement points is selected within the workspace of the automated machinery as the main influencing variable. Based on the influencing variable, the error distribution model and interval for each influencing variable are determined. Optionally, the error distribution model and interval for each influencing variable are determined based on data provided by the component supplier or manufacturer and / or experimental measurement data.

[0118] Step S142: Generate random numbers based on the error distribution model and interval, and form a random array.

[0119] In this embodiment, random numbers are generated for the error distribution model and interval of the selected influencing variables. The random numbers for each influencing variable are the same, and the random numbers are combined into a random array of size N (N is a natural number, usually greater than 1000).

[0120] Step S143: Input the random array into the accuracy model to calculate the error.

[0121] In this embodiment, the generated random array is input into the constructed accuracy model for calculation to obtain the corresponding error.

[0122] Step S144: Segment and summarize the error according to the Euclidean distance to obtain an accuracy histogram.

[0123] In this embodiment, the Euclidean distance of the error is segmented and summarized according to the data size to form a bar chart of error segments and frequencies, i.e., a precision bar chart. Optionally, the Euclidean distance of the error may include, but is not limited to, the Euclidean distance of position error, the Euclidean distance of attitude error, and the Euclidean distance of joint angle error.

[0124] Step S145: Fit the accuracy histogram to the corresponding error distribution curve to obtain the accuracy distribution model.

[0125] Finally, based on the obtained accuracy histogram, it is fitted to the corresponding error distribution curve to obtain the final accuracy distribution model. Optionally, the accuracy distribution model may include, but is not limited to, a normal distribution.

[0126] This embodiment, through the above-described scheme, specifically determines the first machine type and the first precision type to be predicted and evaluated; based on the first machine type and the first precision type, obtains the precision specification line to be predicted and / or the pass rate to be evaluated; inputs the precision specification line to be predicted into a pre-constructed precision distribution model to obtain the predicted pass rate, and / or inputs the pass rate to be evaluated into the precision distribution model to obtain the specification line evaluation result. Based on this application's scheme, without the need for actual production and historical data, a precision distribution model is constructed. By using the constructed precision distribution model to predict the precision specification line to be predicted and / or to evaluate the pass rate to be evaluated, intuitive and data-driven prediction and evaluation results can be quickly obtained. This solves the problem of long cycles in the precision prediction and evaluation process, achieving rapid prediction and evaluation of precision specifications and pass rates.

[0127] Fourth embodiment

[0128] Based on the first and third embodiments described above, this embodiment further discloses a method implemented after the step of inputting the accuracy specification parameters to be evaluated into a pre-constructed accuracy distribution model to obtain the accuracy specification evaluation result. (Refer to...) Figure 7 , Figure 7 This is a flowchart illustrating a fourth exemplary embodiment of the mechanical precision specification evaluation method of this application. After step S103, in which the precision specification parameters to be evaluated are input into a pre-constructed precision distribution model to obtain the precision specification evaluation result, the method may further include:

[0129] Step S104: Obtain the decision result of the accuracy specification evaluation result, wherein the decision result includes meeting the requirements and not meeting the requirements.

[0130] In this embodiment, a decision is made based on the obtained accuracy specification evaluation results to determine whether the accuracy specification evaluation results meet the requirements, and a decision result is given. Optionally, the decision result may include meeting the requirements and not meeting the requirements. After giving the decision result of the accuracy specification evaluation results, the decision result is obtained.

[0131] Optionally, if the decision result meets the requirements, then step S1051 is executed to end the evaluation of mechanical precision specifications.

[0132] In this embodiment, if the obtained decision result meets the requirements, the evaluation of the precision specifications of the automated machinery ends, and the positive decision-making process of the precision specification evaluation result is completed.

[0133] Optionally, if the decision result does not meet the requirements, then step S1052 is executed to control the error distribution of the influencing variables.

[0134] Then, return to step S141 to determine the error distribution model and interval based on the influencing variables.

[0135] In this embodiment, if the obtained decision result does not meet the requirements, the error distribution of the influencing variables is controlled. Optionally, the error distribution of certain influencing variables is reduced or increased. Then, the process returns to step S141, whereby an error distribution model and interval are determined based on the influencing variables; random numbers are generated based on the error distribution model and interval, and a random array is formed; the random array is input into the accuracy model to calculate the error; the error is segmented and summarized based on the Euclidean distance to obtain an accuracy histogram; and then, the accuracy histogram is fitted to the corresponding error distribution curve to obtain the accuracy distribution model.

[0136] This embodiment, through the above-described scheme, specifically determines whether the accuracy specification evaluation results meet the requirements; if they do, the mechanical accuracy specification evaluation ends; if they do not, the error of the influencing variables is controlled. The execution steps include: determining the error distribution model and interval of the influencing variables, which provides intuitive and data-driven results, offering a quantitative basis for the final decision. This scheme not only allows for forward decision-making regarding whether specifications and pass rates meet requirements, but also enables reverse tracing of improvement factors and indicators, providing direction and indicators for improvement measures.

[0137] Fifth embodiment

[0138] Based on the first, second, third, and fourth embodiments described above, this embodiment discloses a method for evaluating mechanical precision specifications based on an automated mechanical precision prediction and evaluation system. (Reference) Figure 8 , Figure 8 This is a flowchart illustrating a fifth exemplary embodiment of the mechanical precision specification evaluation method of this application. The mechanical precision specification evaluation method may further include:

[0139] Step S1: Determine the type of machinery to be evaluated.

[0140] Step S2: Determine the type of accuracy to be evaluated.

[0141] Step S3: Establish a precision model based on the machine type and the precision type.

[0142] Step S4: Determine the influencing variables based on the accuracy model.

[0143] Step S5: Determine the error distribution model and interval based on the influencing variables.

[0144] Step S6: Generate random numbers based on the error distribution model and interval, and form a random array.

[0145] Step S7: Input the random array into the accuracy model to calculate the error; summarize the error in segments according to the Euclidean distance to obtain an accuracy histogram.

[0146] Step S8: Fit the accuracy histogram to the corresponding error distribution curve to obtain the accuracy distribution model.

[0147] Step S9: Obtain the accuracy specification parameters to be evaluated; input the accuracy specification parameters to be evaluated into the pre-built accuracy distribution model to obtain the accuracy specification evaluation results.

[0148] Step S10: Make a decision based on the accuracy specification evaluation result, decide whether the accuracy specification evaluation result meets the requirements, and give a decision result; obtain the decision result of the accuracy specification evaluation result, wherein the decision result includes meeting the requirements and not meeting the requirements.

[0149] Step S11: If the decision result does not meet the requirements, then control the error distribution of the influencing variables; return to step S5 to determine the error distribution model and interval based on the influencing variables.

[0150] Step S12: If the decision result meets the requirements, the evaluation of mechanical precision specifications ends.

[0151] Optionally, the mechanical precision specification evaluation method may include, but is not limited to: the type of automated machinery, the type and model of precision for prediction and evaluation, the type and number of influencing variables of the precision model, the error distribution model of each influencing variable, the precision distribution model of random number type and bar chart fitting, etc.

[0152] This embodiment, through the above-described scheme, specifically determines the type of machinery and the precision type to be evaluated; obtains the precision specification parameters to be evaluated based on the machinery type and the precision type; and inputs the precision specification parameters to be evaluated into a pre-constructed precision distribution model to obtain the precision specification evaluation result. Based on this application's scheme, there is no need to construct a precision distribution model using actual production and historical data. By evaluating the precision specification parameters to be evaluated using the constructed precision distribution model, intuitive and data-driven precision specification evaluation results can be obtained quickly, solving the problem of long evaluation cycles in the precision specification evaluation process for automated machinery. This allows for the rapid completion of precision specification evaluation for automated machinery. Furthermore, the intuitive and data-driven results provide a quantitative basis for final decision-making. It not only allows for positive decision-making regarding whether specifications and pass rates meet requirements, but also allows for reverse tracing of improvement factors and indicators, providing direction and indicators for improvement measures.

[0153] Furthermore, this application also proposes a mechanical precision specification evaluation system, which includes at least one of the following: a parameter distribution model, a precision model, a precision bar chart, and a precision distribution model;

[0154] The parameter distribution model is used to determine the error distribution model and interval based on the influence variables of the accuracy model; and to generate random numbers based on the error distribution model and interval, forming a random array.

[0155] The accuracy model is used to calculate the error by inputting the random array into the accuracy model; the error is then segmented and summarized according to the Euclidean distance to obtain the accuracy histogram.

[0156] The precision histogram is used to fit the precision histogram to the corresponding error distribution curve to obtain the precision distribution model;

[0157] The accuracy distribution model is used to input the accuracy specification parameters to be evaluated into the accuracy distribution model to obtain the accuracy specification evaluation results.

[0158] The principle and implementation process of this embodiment for evaluating mechanical precision specifications are described in the above embodiments and will not be repeated here.

[0159] Furthermore, this application also proposes a mechanical precision specification evaluation device, which includes:

[0160] The type determination module is used to determine the first mechanical type and the first precision type to be evaluated.

[0161] The parameter acquisition module is used to acquire the accuracy specification parameters to be evaluated based on the first machine type and the first accuracy type.

[0162] The accuracy evaluation module is used to input the accuracy specification parameters to be evaluated into a pre-built accuracy distribution model to obtain the accuracy specification evaluation results.

[0163] Furthermore, the mechanical precision specification evaluation device also includes:

[0164] The model building module is used to build the accuracy distribution model.

[0165] The principle and implementation process of this embodiment for evaluating mechanical precision specifications are described in the above embodiments and will not be repeated here.

[0166] Furthermore, this application also proposes an apparatus comprising a memory, a processor, and a mechanical precision specification evaluation program stored in the memory and executable on the processor. When executed by the processor, the mechanical precision specification evaluation program implements the steps of the mechanical precision specification evaluation method as described above.

[0167] Since this mechanical precision specification evaluation program adopts all the technical solutions of all the aforementioned embodiments when it is executed by the processor, it has at least all the beneficial effects brought about by all the technical solutions of all the aforementioned embodiments, which will not be repeated here.

[0168] Furthermore, embodiments of this application also propose a computer-readable storage medium storing a mechanical precision specification evaluation program, which, when executed by a processor, implements the steps of the mechanical precision specification evaluation method as described above.

[0169] Since this mechanical precision specification evaluation program adopts all the technical solutions of all the aforementioned embodiments when it is executed by the processor, it has at least all the beneficial effects brought about by all the technical solutions of all the aforementioned embodiments, which will not be repeated here.

[0170] Compared to existing technologies, the mechanical precision specification evaluation method, system, device, equipment, and storage medium proposed in this application determine a first mechanical type and a first precision type to be evaluated; obtain precision specification parameters to be evaluated based on the first mechanical type and the first precision type; and input the precision specification parameters to be evaluated into a pre-constructed precision distribution model to obtain the precision specification evaluation result. Based on this application's solution, there is no need to construct a precision distribution model using actual production and historical data. By evaluating the precision specification parameters to be evaluated using the constructed precision distribution model, intuitive and data-driven precision specification evaluation results can be obtained quickly, solving the problem of long evaluation cycles in the automated mechanical precision specification evaluation process and enabling rapid completion of the automated mechanical precision specification evaluation.

[0171] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0172] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0173] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a device (which may be a mobile phone, computer, server, controlled terminal, or network device, etc.) to execute the methods of each embodiment of this application.

[0174] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A method for evaluating mechanical precision specifications, characterized in that, The mechanical precision specification evaluation method includes: Determine the first mechanical type and the first precision type to be evaluated; Based on the first machine type and the first precision type, obtain the precision specification parameters to be evaluated; The accuracy specification parameters to be evaluated are input into a pre-built accuracy distribution model to obtain the accuracy specification evaluation results; Before the step of determining the first mechanical type and the first precision type to be evaluated, the method further includes: Constructing the precision distribution model specifically includes: Determine the second mechanical type and the second precision type to be constructed; Based on the second machine type and the second precision type, establish a precision model; The influencing variables are determined based on the accuracy model, and the influencing variables include some parameters of the accuracy model. Determine the error distribution model and interval based on the aforementioned influencing variables; Random numbers are generated based on the error distribution model and interval, and then a random array is formed. The error is calculated by inputting the random array into the accuracy model; The error is segmented and summarized based on the Euclidean distance to obtain a precision histogram; The accuracy histogram is fitted to the corresponding error distribution curve to obtain the accuracy distribution model.

2. The mechanical precision specification evaluation method as described in claim 1, characterized in that, The accuracy specification evaluation result includes the pass rate of the evaluation. After the step of obtaining the accuracy specification parameters to be evaluated, the method further includes: Determine the type of the accuracy specification parameter; If the type of the accuracy specification parameter is an accuracy specification line, then the accuracy specification line to be evaluated is input into the pre-built accuracy distribution model to obtain the pass rate of the evaluation.

3. The mechanical precision specification evaluation method as described in claim 2, characterized in that, The accuracy specification evaluation result also includes the evaluated specification line. After the step of determining the type of the accuracy specification parameter, the following is also included: If the type of the accuracy specification parameter is pass rate, then the pass rate to be evaluated is input into the pre-built accuracy distribution model to obtain the specification line to be evaluated.

4. The mechanical precision specification evaluation method as described in claim 3, characterized in that, After the step of inputting the accuracy specification parameters to be evaluated into a pre-built accuracy distribution model to obtain the accuracy specification evaluation results, the method further includes: The decision result of obtaining the accuracy specification evaluation result includes meeting the requirements and not meeting the requirements; If the decision result meets the requirements, the evaluation of mechanical precision specifications ends; If the decision result does not meet the requirements, then the error distribution of the influencing variables is controlled. Execution steps: Determine the error distribution model and interval based on the influencing variables.

5. A mechanical precision specification evaluation system, characterized in that, The mechanical precision specification evaluation system, applicable to any one of claims 1 to 4, comprises at least one of the following: a parameter distribution model, a precision model, a precision bar chart, and a precision distribution model; The parameter distribution model is used to determine the error distribution model and interval based on the influence variables of the accuracy model; and to generate random numbers based on the error distribution model and interval, forming a random array. The accuracy model is used to calculate the error by inputting the random array into the accuracy model; the error is then segmented and summarized according to the Euclidean distance to obtain the accuracy histogram. The precision histogram is used to fit the precision histogram to the corresponding error distribution curve to obtain the precision distribution model; The accuracy distribution model is used to input the accuracy specification parameters to be evaluated into the accuracy distribution model to obtain the accuracy specification evaluation results.

6. A mechanical precision specification evaluation device, characterized in that, The mechanical precision specification evaluation device includes: The type determination module is used to determine the first mechanical type and the first precision type to be evaluated. The parameter acquisition module is used to acquire the accuracy specification parameters to be evaluated based on the first machine type and the first accuracy type. The accuracy evaluation module is used to input the accuracy specification parameters to be evaluated into a pre-built accuracy distribution model to obtain the accuracy specification evaluation results; Before the step of determining the first mechanical type and the first precision type to be evaluated, the method further includes: The model building module, used to build the accuracy distribution model, specifically includes: Determine the second mechanical type and the second precision type to be constructed; Based on the second machine type and the second precision type, establish a precision model; The influencing variables are determined based on the accuracy model, and the influencing variables include some parameters of the accuracy model. Determine the error distribution model and interval based on the aforementioned influencing variables; Random numbers are generated based on the error distribution model and interval, and then a random array is formed. The error is calculated by inputting the random array into the accuracy model; The error is segmented and summarized based on the Euclidean distance to obtain a precision histogram; The accuracy histogram is fitted to the corresponding error distribution curve to obtain the accuracy distribution model.

7. A mechanical precision specification evaluation device, characterized in that, The mechanical precision specification evaluation device includes a memory, a processor, and a mechanical precision specification evaluation program stored in the memory and executable on the processor. When the mechanical precision specification evaluation program is executed by the processor, it implements the steps of the mechanical precision specification evaluation method as described in any one of claims 1-4.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a mechanical precision specification evaluation program, which, when executed by a processor, implements the steps of the mechanical precision specification evaluation method as described in any one of claims 1-4.

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