Minimum sample number determination and interruption processing method for rolling bearing fitting

Abstract

The invention is suitable for the technical field of bearing processing data processing, and provides a rolling bearing fitting minimum sample number determination and interruption processing method, which comprises the steps of determining a grouping number based on a probability density function of an inner ring and an outer ring of a bearing and an equal probability grouping method, and then determining the number of groups based on the grouping number and the number of storage bins in a waiting area of bearing fitting equipment. According to the method, the matching failure probability of the batch of bearings is calculated, the minimum sample number of bearing matching is calculated by measuring the matching failure probability of the number of material bins in different waiting areas and the number of groups, optimization design is carried out on the bearing matching selection and matching process, and an implementation scheme is provided. When the number of stock bins in the waiting area is fully occupied by different group numbers, and the sleeving process is interrupted, the middle group assemblies in the groups are adopted to conduct cross-combination sleeving under the condition that the optimal clearance is met, and the problem that bearing sleeving selection and matching stop is solved through the method that bearing rolling bodies are different in size deviation; and the rolling bearing fitting process is not stopped under the optimal service clearance and requirement of the bearing.

Description

Technical Field

[0001] The present application relates to the technical field of bearing processing data processing, and in particular to a method for determining a minimum number of samples for rolling bearing assembly and interrupt processing. Background Art

[0002] Bearings, as crucial transmission components in mechanical systems, are widely used in modern industry. In the mass production of rolling bearings, some factories still use manual sorting and assembly, while others employ automated assembly lines.

[0003] At present, in the assembly production process of the automated assembly line, it is easy for the waiting area silo to be filled up due to the inability to find the matching parts, resulting in the interruption and jam of the assembly process. There is a problem of low production efficiency, which needs further improvement. Summary of the Invention

[0004] Based on this, an embodiment of the present application provides a method for determining the minimum number of samples for rolling bearing assembly and interruption processing to solve the problem of low production efficiency in the prior art.

[0005] In a first aspect, an embodiment of the present application provides a method for determining a minimum number of samples for rolling bearing assembly and interrupt processing, the method comprising: Obtain the inner and outer ring size deviation distribution information and the optimal bearing service clearance information corresponding to any production batch of bearings to be assembled; Determining grouping information of the inner and outer ring size deviation ranges of the bearing to be assembled based on the inner and outer ring size deviation distribution information and the bearing service optimal clearance information; Determining the assembly failure probability information corresponding to the bearings to be assembled in the production batch according to the number of silo lanes in the waiting area of ​​the bearing assembly equipment and the grouping information of the inner and outer ring size deviation ranges of the bearings to be assembled; Determine the minimum number of samples based on the number of silo lanes in the waiting area and the inner and outer ring size deviation range grouping information corresponding to each production batch; Based on the minimum sample number information and the bearing fitting failure probability information, the bearing fitting selection process is optimized to generate optimized process information, wherein the optimized process information is used to indicate that when the fitting process is interrupted, the inner and outer ring intermediate group components are selected according to the intermediate group component fitting processing method to give priority to matching excess accessories.

[0006] Compared with the prior art, the beneficial effects are as follows: the method for determining the minimum number of samples and interruption processing for rolling bearing assembly provided in the embodiment of the present application, the terminal device can first obtain the inner and outer ring size deviation distribution information and the bearing service optimal clearance information corresponding to the bearings to be assembled of any production batch, and then quickly determine the inner and outer ring size deviation range grouping information of the bearings to be assembled based on the inner and outer ring size deviation distribution information and the bearing service optimal clearance information. Then, based on the number of waiting area silo lanes of the bearing assembly equipment and the inner and outer ring size deviation range grouping information of the bearings to be assembled, the assembly failure probability information corresponding to the bearings to be assembled in the production batch is accurately determined. Then, based on the number of waiting area silo lanes and the inner and outer ring size deviation range grouping information corresponding to each production batch, the minimum number of samples information is effectively determined. Finally, based on the minimum number of samples information and the assembly failure probability information, the bearing assembly selection process is optimized and optimized process information is generated to prioritize matching excess accessories, thereby avoiding the situation where the waiting area silo is full due to the inability to find suitable accessories, resulting in the assembly process being interrupted or stuck, effectively improving production efficiency and solving the current problem of low production efficiency to a certain extent.

[0007] In a second aspect, an embodiment of the present application provides a system for determining the minimum number of samples for rolling bearing assembly and for processing interruptions, the system comprising: Inner and outer ring size deviation distribution information acquisition module: used to obtain the inner and outer ring size deviation distribution information and the bearing service optimal clearance information corresponding to any production batch of bearings to be assembled; Inner and outer ring size deviation range grouping information determination module: used to determine the inner and outer ring size deviation range grouping information of the bearing to be assembled based on the inner and outer ring size deviation distribution information and the bearing service optimal clearance information; A module for determining the probability of failure of assembly: used to determine the probability of failure of assembly corresponding to the bearings to be assembled in the production batch according to the number of silo lanes in the waiting area of ​​the bearing assembly equipment and the grouping information of the size deviation range of the inner and outer rings of the bearings to be assembled; Minimum sample number information determination module: used to determine the minimum sample number information based on the number of silo lanes in the waiting area corresponding to each production batch and the grouping information of the inner and outer ring size deviation range; Optimization process information generation module: used to optimize the bearing fitting and selection process based on the minimum sample number information and the fitting failure probability information, and generate optimization process information, wherein the optimization process information is used to indicate that when the fitting process is interrupted, the inner and outer ring intermediate group components are selected according to the intermediate group component fitting processing method to give priority to matching excess accessories.

[0008] In a third aspect, an embodiment of the present application provides a terminal device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method of the first aspect described above when executing the computer program.

[0009] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method of the first aspect described above are implemented.

[0010] It can be understood that the beneficial effects of the second to fourth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art.

[0012] Figure 1 This is a flowchart of a method for determining the minimum number of samples and handling interruptions provided in one embodiment of the present application; Figure 2 2 is a flowchart of step S200 in the method for determining the minimum number of samples and handling interruption provided in one embodiment of the present application; Figure 3 This is a flow chart before step S300 in the method for determining the minimum number of samples and handling interruption provided in one embodiment of the present application; Figure 4 This is a schematic diagram of a waiting area provided in one embodiment of the present application; Figure 5 4 is a flowchart of step S400 in the method for determining the minimum number of samples and handling interruption provided in one embodiment of the present application; Figure 6 This is a flowchart after step S500 in the method for determining the minimum number of samples and handling interruption provided in one embodiment of the present application; Figure 7 This is a thermal diagram of the number of sets of different waiting area lanes provided in one embodiment of the present application; Figure 8 This is a schematic diagram comparing the number of different channel sets provided in one embodiment of the present application; Figure 9 (a) is a schematic diagram of the success rate of nesting when the waiting area is 12 tracks according to an embodiment of the present application. Figure 9 (b) is a schematic diagram of the success rate of nesting when the waiting area is 14 lanes, provided in one embodiment of the present application. Figure 9 (c) is a schematic diagram of the success rate of nesting when the waiting area is 13 lanes, provided by an embodiment of the present application; Figure 10 (a) is a schematic diagram showing the number of 13 sets provided in an embodiment of the present application. Figure 10 (b) is a schematic diagram showing a comparison of the number of 12 sets provided in an embodiment of the present application; Figure 11 Schematic diagram of the probability of a shutoff provided by an embodiment of the present application; Figure 12 This is a schematic diagram of the number of sets when the two grouping methods provided in one embodiment of the present application are interrupted; Figure 13 This is a module block diagram of a minimum sample number determination and interrupt processing system provided by an embodiment of the present application; Figure 14 This is a schematic diagram of a terminal device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0013] In the following description, specific details such as specific system structures and techniques are provided for purposes of illustration rather than limitation to facilitate a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obscuring the description of the present application with unnecessary detail.

[0014] In the description of this application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0015] References to "one embodiment" or "some embodiments" in this specification mean that a particular feature, structure, or characteristic described in conjunction with that embodiment is included in one or more embodiments of the present application. Thus, phrases such as "in one embodiment," "in some embodiments," "in other embodiments," and "in other embodiments" appearing in various places in this specification do not necessarily refer to the same embodiment, but rather mean "one or more but not all embodiments," unless otherwise specifically emphasized. The terms "including," "comprising," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0016] In order to illustrate the technical solution described in this application, specific embodiments are provided below.

[0017] See also Figure 1 , Figure 11 is a flow chart of a method for determining the minimum number of samples and handling interruptions for rolling bearing assembly provided in an embodiment of the present application. In this embodiment, the method for determining the minimum number of samples and handling interruptions is performed by a terminal device. It is understood that the types of terminal devices include, but are not limited to, mobile phones, tablet computers, laptop computers, ultra-mobile personal computers (UMPCs), netbooks, personal digital assistants (PDAs), etc., and the embodiments of the present application do not impose any restrictions on the specific types of terminal devices.

[0018] See also Figure 1 The method for determining the minimum number of samples and handling interruption provided in the embodiment of the present application includes but is not limited to the following steps: In S100, the size deviation distribution information of the inner and outer rings and the optimal service clearance information of the bearings corresponding to any production batch to be assembled are obtained.

[0019] Specifically, the terminal device can first obtain the inner and outer ring size deviation distribution information and the optimal service clearance information of the bearings corresponding to any production batch to be assembled.

[0020] For example, the specific inner ring size and the specific outer ring size of the bearing to be assembled can be obtained by measuring with a contact measuring sensor, and the terminal device can determine the inner and outer ring size deviation distribution information based on the specific inner ring size and the specific outer ring size.

[0021] In S200 , the grouping information of the size deviation ranges of the inner and outer rings of the bearing to be assembled is determined based on the size deviation distribution information of the inner and outer rings and the optimal service clearance information of the bearing.

[0022] Specifically, the terminal device can effectively determine the grouping information of the inner and outer ring size deviation ranges of the bearing to be assembled based on the inner and outer ring size deviation distribution information and the bearing service optimal clearance information.

[0023] In a possible implementation, the terminal device may also obtain size deviation distribution information of the rolling element to improve the comprehensiveness of the data.

[0024] In some possible implementations, in order to effectively group the inner and outer ring size deviation range information, please refer to Figure 2 Step S200 includes but is not limited to the following steps: In S210 , a probability density function is constructed based on the inner and outer ring size deviation distribution information.

[0025] For example, the terminal device may construct a probability density function based on the inner and outer ring size deviation distribution information and a statistical distribution model of a normal distribution.

[0026] In S220, based on the information of the optimal bearing service clearance, the probability density function is divided into equal probability groups to generate group information of the inner and outer ring size deviation ranges.

[0027] Specifically, after the terminal device constructs the probability density function, the terminal device can perform equal probability division processing on the probability density function based on the bearing's optimal service clearance information, under the condition of the optimal service clearance, so as to distribute it to different intervals according to the size of the deviation size, and effectively generate inner and outer ring size deviation range grouping information.

[0028] In S300 , the assembly failure probability information corresponding to the bearings to be assembled in the production batch is determined based on the number of silo lanes in the waiting area of ​​the bearing assembly equipment and the grouping information of the size deviation range of the inner and outer rings of the bearings to be assembled.

[0029] Specifically, the terminal device can accurately determine the assembly failure probability information corresponding to the bearings to be assembled in the production batch based on the number of silo lanes in the waiting area of ​​the bearing assembly equipment and the grouping information of the inner and outer ring size deviation range of the bearings to be assembled.

[0030] It should be noted that the bearing assembly failure probability refers to the probability that the inner and outer ring components cannot be matched in the waiting area during deep groove ball bearing assembly, resulting in the inability to complete the assembly. This probability reflects the possibility of sparse or uneven component distribution when there are insufficient lanes or too many groups in the waiting area, leading to matching failure. The ratio of lanes to groups is a key factor influencing the assembly failure probability. When there are sufficient lanes, the distribution is uniform, reducing the failure probability; when there are insufficient lanes, the distribution is sparse, increasing the failure probability.

[0031] In some possible implementations, to determine the number of silo lanes in the waiting area, see Figure 3 Before step S300, the method further includes but is not limited to the following steps: In S301 , the maximum value information of the waiting pairing is obtained.

[0032] Specifically, the terminal device may first obtain the maximum value information of the waiting pairing, wherein the maximum value information of the waiting pairing is used to describe the maximum value of the inner and outer ring accessories of the bearing to be assembled that can be waited for pairing when they are not paired.

[0033] In S302, the maximum waiting pairing value information is determined to be the number of silo lanes in the waiting area.

[0034] Specifically, after the terminal device obtains the maximum waiting pairing value information, the terminal device may determine that the maximum waiting pairing value information is the number of silo lanes in the waiting area.

[0035] In S400, the minimum number of samples is determined based on the number of silo lanes in the waiting area and the grouping information of the inner and outer ring size deviation ranges corresponding to each production batch.

[0036] Specifically, the terminal device can effectively determine the minimum sample number information based on the number of silo lanes in the waiting area and the inner and outer ring size deviation range grouping information corresponding to each production batch.

[0037] It should be noted that in the automated production process of bearing assembly, determining the minimum number of samples is the core link in optimizing the efficiency and stability of the production line. The determination of this parameter is not only related to the rational allocation of equipment resources, but also directly affects the assembly success rate and production continuity. In the automated assembly system, the matching relationship between the number of waiting area lanes (M) and the number of groups (N) determines the density and randomness of the distribution of accessories. When the number of lanes is insufficient, the accessories are sparsely distributed, and the probability of matching within the same group or across groups is significantly reduced, resulting in frequent interruptions; while too many lanes may cause waste of resources and increase system complexity. Therefore, it is necessary to determine the minimum number of lanes (M) that meets the assembly success rate requirements. min ) becomes the key to balancing efficiency and cost.

[0038] In some possible implementations, to determine the minimum number of samples, see Figure 4 Step S400 includes but is not limited to the following steps: In S410, the number of lanes in the waiting area is determined according to the number of lanes in the waiting area, and the number of groups is determined according to the grouping information of the inner and outer ring size deviation ranges.

[0039] Specifically, the terminal device can quickly determine the number of lanes in the waiting area based on the number of silo lanes in the waiting area, and efficiently determine the number of groups based on the grouping information of the inner and outer ring size deviation ranges.

[0040] In S420, the number of silo lanes in the waiting area and the grouping information of the inner and outer ring size deviation ranges are input into a preset fitting success rate calculation function to determine the fitting success rate information.

[0041] Specifically, after the terminal device determines the number of lanes and grouping information in the waiting area, the terminal device can input the number of lanes in the waiting area silo and the grouping information of the inner and outer ring size deviation range into the preset fitting success rate calculation function to accurately determine the fitting success rate information.

[0042] In a possible implementation, the function for calculating the success rate of nesting can be: , Where, Indicates the success rate of the combination. Indicates the failure probability information of the same group, represents the probability of failure across combinations, Indicates the number of groups, Indicates the number of lanes in the waiting area. Indicates the number of combinations, for example is the number of combinations of choosing 2 from 5 elements, is the starting value of the first set, It is the starting value of the second set.

[0043] It should be noted that the numerator in the same-group failure probability information describes all possible situations in which the same group of accessories cannot meet the minimum matching requirements due to insufficient number of channels; the numerator in the cross-group failure probability comprehensively considers the failure situations caused by incompatible dimensional deviations during cross-group adaptation.

[0044] In S430 , the minimum number of samples is determined based on the matching success rate information.

[0045] Specifically, after the terminal device determines the set success rate information, the terminal device can determine the minimum sample number information based on the set success rate information, where the minimum sample number information is used to describe the minimum number of channels required under the condition that the set success rate information is greater than the specified probability; the specific value of the specified probability can be customized.

[0046] Among some possible implementations, the inventors have found from a large number of practical applications that: (1) when the number of tracks is less than twice the number of groups, the average number of groups allocated to each track is small. In the case of a random distribution of groups, the number of group components in some tracks will be too small or even missing, which will reduce the matching success rate and significantly reduce the success rate of fitting. (2) when the number of tracks is equal to twice the number of groups, the components are evenly and densely distributed, the average number of components in each group increases, and the probability of repeated appearance of components with the same group number will increase, which will significantly improve the probability of successful matching and significantly increase the success rate of fitting. (3) when the number of tracks is much larger than the number of groups, such as three times the number of groups or more, its distribution will be more even, and the unevenness caused by randomness can be effectively balanced, so that the chances of all group components participating in matching increase, thereby further improving the efficiency of fitting.

[0047] Therefore, the value of the minimum number of samples information can be at least twice the number of groups information, thereby significantly improving the success rate of the combination and avoiding resource waste and increased system complexity.

[0048] In S500 , based on the minimum sample number information and the bearing assembly failure probability information, the bearing assembly selection process is optimized to generate optimized process information.

[0049] Specifically, the terminal device can optimize the bearing fitting and selection process based on the minimum sample number information and the fitting failure probability information, and generate optimized process information, which is conducive to utilizing redundant space to reduce density, and realize real-time monitoring and allocation, to ensure production continuity and effectively improve production efficiency. Among them, the optimized process information is used to indicate that when the fitting process is interrupted, the inner and outer ring intermediate group components are selected according to the intermediate group component fitting processing method to give priority to matching excess accessories.

[0050] Specifically, the assembly process interruption is used to describe the interruption situation where the assembly process cannot continue because the waiting area of ​​the inner and outer ring parts is full and there are no matching parts with the same group number; For example, see Figure 5 The intermediate group assembly processing method is used to describe the method of cross-group assembly of the target group under the condition of meeting the optimal clearance range, wherein the target group is used to describe the group whose size deviation is close to the mean of the normal distribution. For example, when the size deviation is divided into 8 groups, the 4th and 5th groups are selected as the target groups. In a possible implementation method, the target group can be the group whose size deviation is closest to the mean of the normal distribution.

[0051] It should be noted that due to the smaller size deviation between the inner and outer ring accessories of the target group, it is easier to meet the clearance range specified by production when matching each other; when the number of components in the intermediate group assembly (such as the 5th group) in the outer ring waiting area exceeds the preset threshold, for example, when the number is greater than 2, the terminal device can determine that the density of the group is too high and is prone to congestion, so these excess intermediate group assembly accessories are given priority for matching with other intermediate group components (such as the 4th group), which can reduce the backlog of accessories in a single group and greatly increase the probability of successful matching to the same group.

[0052] In some possible implementations, in order to achieve automatic selection of rolling elements to improve production efficiency, please refer to Figure 6 After step S500, the method further includes but is not limited to the following steps: In S600 , initial clearance information is acquired.

[0053] Without loss of generality, after the intermediate assembly components are matched across the assembly, the initial clearance may not meet production standards due to accumulated dimensional deviations. To address this issue, an automatic adjustment solution for rolling elements can be used to precisely control clearance. Based on the deviation from the initial clearance, the terminal equipment can automatically select rolling elements of different specifications for adjustment, with a variety of rolling element specifications available.

[0054] Specifically, the terminal device may first obtain initial clearance information.

[0055] In S610 , the initial clearance information and the clearance upper limit value information are compared.

[0056] Specifically, after the terminal device obtains the initial clearance information, the terminal device may compare the initial clearance information with the clearance upper limit value information, wherein the clearance upper limit value information may be set to 38 microns.

[0057] In S620 , if the initial clearance information is greater than the clearance upper limit information, the first rolling element is determined to be the pre-selected rolling element.

[0058] Specifically, if the initial clearance information is greater than the clearance upper limit information, the terminal device may determine that the first rolling body is a preliminary selected rolling body, wherein the size of the first rolling body is greater than the size of the current rolling body.

[0059] For example, if the initial clearance is 25 μm (exceeding the upper limit of 23 μm), the terminal device can select slightly larger rolling elements (for example, +4 μm) to reduce the clearance.

[0060] In S630 , the initial clearance information and the clearance lower limit value information are compared.

[0061] Specifically, the terminal device can compare the initial clearance information and the clearance lower limit information at the same time, wherein the clearance lower limit information can be set to 20 microns.

[0062] In S640 , if the initial clearance information is less than the clearance lower limit information, the second rolling element is determined to be the pre-selected rolling element.

[0063] Specifically, if the initial clearance information is smaller than the clearance lower limit information, the terminal device may determine that the second rolling body is a preliminary selected rolling body, wherein the size of the second rolling body is smaller than the size of the current rolling body.

[0064] For example, if the initial clearance is 4 μm (lower than the lower limit of 6 μm), the terminal device may select a slightly smaller rolling element (for example, -4 μm) to increase the clearance.

[0065] In S650, it is determined whether the clearance corresponding to the preliminarily selected rolling element is within the specified fitting range.

[0066] Specifically, the terminal device can determine whether the clearance corresponding to the pre-selected rolling element is within the specified fitting range, where the specified fitting range is 6 microns to 23 microns.

[0067] In S660, if the clearance corresponding to the preselected rolling element is within the specified fitting range, the preselected rolling element is determined to be the fitting rolling element. Otherwise, a rolling element of another specification is re-determined as the preselected rolling element until the clearance corresponding to the preselected rolling element is within the specified fitting range.

[0068] Specifically, if the clearance corresponding to the pre-selected rolling element is within the specified range of the fitting, the terminal device can determine that the pre-selected rolling element is a fitting rolling element. Otherwise, the terminal device can re-determine a rolling element of another specification as the pre-selected rolling element until the clearance corresponding to the pre-selected rolling element is within the specified range of the fitting. In this way, the clearance range after fitting is automatically and repeatedly calculated during the adjustment process until the clearance falls within the range that meets the fitting requirements.

[0069] For example, in order to facilitate those skilled in the art to better understand the technical solution of this application, the following is combined with specific cases and the attached Figures 7 to 12 This technical solution is described in detail again.

[0070] Step 1: The production line utilizes a modular linear layout, integrating core modules such as inner and outer ring loading units, high-precision automatic inspection of inner and outer diameter faces, automatic raceway diameter inspection, dynamic sorting, intelligent automatic closing, and clearance detection (or vibration detection). Except for the loading stage, which requires manual intervention, all other processes utilize an industrial bus for closed-loop control, ensuring synchronization between data collection and process execution.

[0071] Step 2: After the bearing assembly undergoes inner and outer diameter end height testing, it enters the assembly assembly system. Once inside the assembly assembly, the bearing assembly passes through a contact sensor to measure the assembly groove diameter. The contact sensor, based on the principle of inductive displacement detection, uses a constant probe to scan and measure along the groove busbar, enabling real-time acquisition of the inner and outer ring groove diameter dimensions. After the groove diameter values ​​are measured, the inner and outer ring dimensional deviation data is constructed using an independent dual-channel storage architecture to form a data set. After measurement, the components enter the inner and outer ring waiting areas, where they are grouped and matched. After grouping and matching, the inner and outer ring assemblies enter the rolling element loading area. The system adjusts the bearing clearance based on the assembly groove diameter, rolling element specifications, and the specified production clearance to ensure that the bearing clearance is within the specified production clearance range.

[0072] Step 3: Set the number of lanes to be selected in the waiting area and determine the number of groups with equal probability. Fill the waiting area randomly with the inner and outer circle components, and Position start with inner circle Start traversing, when the outer circle The group number and outer circle If the group numbers are the same, the matching operation is executed. Restart with the inner circle Start traversal; when the outer circle With the inner circle If the same group number cannot be found after traversal, the outer circle will start from the next one (i.e. ) and the inner ring Traverse.

[0073] Step 4: After the matching and closing action is executed, the inner and outer ring components are randomly added to make sure that there are no empty spaces in the waiting area. When there is no identical group number to match in the inner and outer ring waiting areas, the traversal stops and the number of inner and outer rings eliminated is recorded.

[0074] Step 5: Set the number of groups to , the number of channels is ,exist In the position, the group number may appear in the following situations: species, in There are also some possible situations where group numbers may appear in the position. Because there are So the total number of combinations is Assume the number of unmatched combinations is , then the probability of unsuccessful combination is: , In the formula, the number of groups is , the number of channels is , round down when the fraction cannot be divided evenly.

[0075] Step 6: While controlling the number of silo channels to 12, 14, and 13 (the number of channels for conventional combined equipment on the market), change the number of groups and perform the traversal described in step 2. When there is no identical group number to match in the inner and outer waiting areas, the traversal stops, and the number of inner and outer circles eliminated is recorded. Different control groups are set up to observe the number of successful combinations and calculate the failure rate of each test group.

[0076] like Figure 9 As shown in (a), when the number of lanes in the waiting area is 12, the assembly success rate gradually decreases from approximately 98% to around 75% as the number of groupings increases from 3 to 8. This indicates that when the number of lanes in the waiting area is three times the number of groupings, the distribution of each group of parts in the waiting area is more even, avoiding the sparse distribution of parts caused by insufficient lanes.

[0077] like Figure 9 As shown in (b), when the number of waiting area lanes is 14, the success rate changes when the number of groupings is 6 to 9, and the overall trend is still downward. When the number of groupings is small (6 to 7), the success rate is at a high level, which shows that when the number of waiting area lanes is twice the number of groupings, the number of waiting area lanes 14 can meet the matching requirements of medium groupings to a certain extent, so that the number of accessories in the same group is relatively sufficient, and the size compatibility of cross-group matching can also be better guaranteed. As the number of groupings further increases to 8 to 9, the success rate gradually drops to around 80% to 85%, indicating that although the number of lanes is relatively high, the success rate is still relatively low. Figure 9(a) in the figure has increased, but facing the ever-increasing number of groups, the probability of successful matching is still decreasing, and the matching efficiency and stability are affected to a certain extent.

[0078] like Figure 9 As shown in (c), when the number of waiting area lanes is 13, the success rate changes from 7 to 10 groups. As the number of groups increases, the success rate gradually decreases from 95% to 83.7%. When the number of waiting area lanes is twice the number of groups, the higher number of waiting area lanes provides more favorable conditions for matching. The number of parts in the same group is relatively abundant, and the incompatibility caused by dimensional deviation during cross-group matching can be alleviated to a certain extent, thus achieving a higher matching success rate. Due to the insufficient number of lanes, the number of combinations of parts in the same group that cannot meet the minimum matching requirements is reduced, thereby reducing the probability of same-group matching failure and improving the overall success rate. However, when the number of groups continues to increase to 9 to 10, the imbalance between the number of lanes and the number of groups becomes increasingly prominent, and the probability of failure in both the same group and cross-group increases, and the matching success rate decreases accordingly.

[0079] Step 7: In the automated assembly system, the matching relationship between the number of waiting area tracks (M) and the number of groups (N) determines the density and randomness of the parts distribution. When the number of tracks is insufficient, the parts are sparsely distributed, and the probability of matching within or across groups is significantly reduced, resulting in frequent interruptions; while too many tracks may cause resource waste and increase system complexity. Therefore, determine the minimum number of tracks ( M min ) becomes the key to balancing efficiency and cost. From the perspective of probability theory, the success rate of matching is affected by two main factors: the probability of failure in matching the same group ( ) means that the number of accessories in the same group of inner and outer rings is insufficient to form an effective pairing; the probability of cross-group matching failure ( ) indicates that different sets of accessories cannot be adapted due to incompatible dimensional deviations. Based on this, the contributions of the two failure scenarios can be quantified and the overall success rate formula can be derived: , When P approaches the threshold of production requirements, the corresponding This is the theoretical optimal solution.

[0080] Then, according to the number of waiting area channels and the required success rate of closing, the minimum sample number calculation formula is established as follows: The calculation formula is: , In the formula, the number of groups is N, and the number of waiting area lanes is , is the number of combinations, for example is the number of combinations of choosing 2 from 5 elements, is the starting value of the first set, is the starting value for the second set, and the numerator describes all possible situations where the same set of accessories cannot meet the minimum matching requirements due to insufficient number of channels; Among them The calculation formula is: , In the formula, the numerator integrates the failures caused by incompatible dimensional deviations during cross-group adaptation; the coefficient 2 represents the bidirectionality of matching between inner and outer rings, and the fraction is rounded down when it cannot be divided evenly.

[0081] from Figure 9 Figures (a), (b), and (c) show a clear relationship between the number of waiting area tracks and the number of groupings. When the number of tracks is insufficient relative to the number of groups, the success rate decreases rapidly as the number of groups increases. A moderate increase in the number of tracks can improve the success rate to a certain extent and slow its downward trend. Once the number of tracks reaches a certain level, while a high success rate can be maintained with a larger number of groupings, the decline in success rate caused by an excessive number of groups cannot be completely avoided. While the success rate of assembly is higher when the number of waiting area tracks is three times the number of groupings, considering cost and system complexity, a higher success rate is achieved when the number of waiting area tracks is twice the number of groupings, achieving a balance between efficiency and cost while maintaining a high assembly success rate.

[0082] A comparison of the number of fits with different numbers of groups and tracks revealed that when the number of tracks is less than twice the number of groups, the average number of groups allocated to each track is small. In the case of a random distribution of groups, the number of group components in some tracks may be too small or even missing, reducing the matching success rate and significantly reducing the fit success rate. When the number of tracks is equal to twice the number of groups, the components are evenly and densely distributed, the average number of components in each group increases, the probability of repeated appearance of components with the same group number increases, the matching success probability is significantly improved, and the fit success rate increases. However, when the number of tracks is close to twice the number of groups (for example, the number of tracks is 13 and the number of groups is 7 or 9), the fit success rate is not as high as when it is twice the corresponding relationship. The reason is that the number of tracks and the number of groups are not integer multiples. As a result, after the inner and outer rings of the bearings that meet the requirements are fit together, there are always fits that cannot be matched. As the number of fits increases, the accumulation increases, resulting in a decrease in the fit success rate. When the number of tracks is much larger than the number of groups (e.g., three times or more the number of groups), the distribution is more even, the unevenness caused by randomness is effectively balanced, the chances of all group components participating in the matching increase, and the efficiency of the matching is further improved.

[0083] Step 8: When the bearing assembly equipment is filled with silo lanes due to different group numbers, the group with size deviation close to the mean of the normal distribution has a smaller deviation and higher matching flexibility, so the group with size deviation close to the mean of the normal distribution is selected as the intermediate group component. When the number of components in the intermediate group components in the outer ring waiting area exceeds the set threshold, the excess accessories are preferentially assembled with other intermediate group components, and the redundant space in the waiting area is used to reduce the density of the intermediate group components to avoid backlog of accessories of a single group. The system monitors the status of each group number in the waiting area in real time and allocates accessories to low-density groups according to priority to ensure matching efficiency and production continuity. When the standard deviation of the group number difference of unmatched components in the inner and outer ring waiting areas exceeds the threshold after multiple consecutive traversals, the interrupt processing mechanism is triggered and the assembly strategy is adjusted.

[0084] Step 9: Identify intermediate components. By statistically analyzing the dimensional deviations of the components, determine the range of intermediate components. For example, the dimensional deviation of the outer ring intermediate component might be [9.4, 14.0] μm, while that of the inner ring intermediate component might be [-19.9, -13.3] μm. These intermediate components are marked in the production system for rapid identification and processing during assembly, expanding the matching range from a single group number to multiple group numbers, significantly reducing interruptions caused by insufficient components from a specific group number.

[0085] Figure 12 The overall number of assembly runs for the traditional and intermediate assembly assembly methods under different grouping numbers is demonstrated. It can be seen that when the number of groups is 7 to 10, the intermediate assembly assembly method achieves a higher overall number of assembly runs than the traditional method. In particular, as the number of groups increases, the intermediate assembly assembly method's advantage in number of assembly runs becomes even more pronounced, further demonstrating its effectiveness. By monitoring the group number status in real time and allocating parts by priority, the assembly sequence can be adjusted promptly to avoid production interruptions caused by congestion in the waiting area and ensure stable operation of the production line. The system dynamically adjusts the assembly strategy through intelligent algorithms to ensure an efficient production rhythm under different operating conditions. The intermediate assembly assembly process is optimized to enable more parts to be assembled within the specified clearance range, improving the overall assembly success rate and, in turn, increasing bearing production efficiency. Experimental data shows that the application of the intermediate assembly assembly method significantly improves the assembly success rate and effectively enhances production efficiency.

[0086] After the intermediate assembly components are matched across groups, the initial clearance may not meet production standards due to accumulated dimensional deviations. To address this issue, rolling element adjustment technology is required to precisely control the clearance. After the assembly is completed, the system measures the actual dimensions of the inner ring, outer ring, and rolling elements, calculates the initial clearance, and selects different rolling element specifications for adjustment based on the deviation from the initial clearance. Rolling elements are typically available in a variety of specifications [-8, -4, -2, 0, 2, 4, 8]. Rolling element adjustment can stably control the optimal clearance range for assembly, thereby reducing interruption frequency, improving production efficiency, and meeting production requirements.

[0087] For the intermediate component closure method, Figure 7 A heat map of the closing efficiency for different numbers of waiting area tracks (M) and groups (N) is shown. It can be seen that when the intermediate closing method is applied to groups of 10 to 14 and waiting area tracks of 12 to 13, closing efficiency is significantly improved, effectively avoiding congestion in the waiting area. Figure 11 A comparison of the interruption frequency between the traditional method and the intermediate assembly method was conducted. The traditional method experienced an interruption frequency of approximately 5.8 times, while the intermediate assembly method reduced this to approximately 2.9 times, a reduction of approximately 50%. This demonstrates that the intermediate assembly method effectively reduces production interruptions.

[0088] Step 10: After the intermediate group components are matched across groups, the initial clearance may not meet the production standards due to the accumulation of dimensional deviations. To solve this problem, it is necessary to accurately control the clearance through rolling element adjustment technology. After the fitting is completed, the system will measure the actual dimensions of the inner ring, outer ring and rolling element, and calculate the initial clearance. According to the deviation of the initial clearance, rolling elements of different specifications are selected for adjustment. Rolling elements are usually available in a variety of specifications [-8, -4, -2, 0, 2, 4, 8]. After rolling element adjustment, the optimal clearance range that meets the fitting can be stably controlled, thereby reducing the interruption frequency, improving production efficiency and meeting production requirements.

[0089] The implementation principle of the method for determining the minimum number of samples and interruption processing for rolling bearing assembly in an embodiment of the present application is as follows: the terminal device first obtains the inner and outer ring size deviation distribution information and the bearing service optimal clearance information corresponding to the bearings to be assembled of any production batch, and then quickly determines the inner and outer ring size deviation range grouping information of the bearings to be assembled based on the inner and outer ring size deviation distribution information and the bearing service optimal clearance information. Then, based on the number of waiting area silo lanes of the bearing assembly equipment and the inner and outer ring size deviation range grouping information of the bearings to be assembled, the assembly failure probability information corresponding to the bearings to be assembled in the production batch is accurately determined. Then, based on the number of waiting area silo lanes and the inner and outer ring size deviation range grouping information corresponding to each production batch, the minimum number of samples information is effectively determined. Finally, based on the minimum number of samples information and the assembly failure probability information, the bearing assembly selection process is optimized to generate optimized process information to prioritize matching excess accessories, thereby avoiding the situation where the waiting area silo is full due to the inability to find suitable accessories, resulting in the interruption or jamming of the assembly process, thereby effectively improving production efficiency.

[0090] It should be noted that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0091] The embodiment of the present application also provides a system for determining the minimum number of samples for rolling bearing assembly and interruption processing. For ease of description, only the parts related to the present application are shown, such as Figure 13 As shown, the system 130 includes: Inner and outer ring size deviation distribution information acquisition module 131: used to obtain the inner and outer ring size deviation distribution information and the bearing service optimal clearance information corresponding to any production batch of bearings to be assembled; Inner and outer ring size deviation range grouping information determination module 132: used to determine the inner and outer ring size deviation range grouping information of the bearing to be assembled based on the inner and outer ring size deviation distribution information and the bearing service optimal clearance information; The assembly failure probability information determination module 133 is used to determine the assembly failure probability information corresponding to the bearings to be assembled in the production batch according to the number of silo lanes in the waiting area of ​​the bearing assembly equipment and the grouping information of the inner and outer ring size deviation ranges of the bearings to be assembled; Minimum sample number information determination module 134: used to determine the minimum sample number information according to the number of silo lanes in the waiting area and the inner and outer ring size deviation range grouping information corresponding to each production batch; Optimization process information generation module 135: is used to optimize the bearing fitting and selection process based on the minimum sample number information and the fitting failure probability information, and generate optimization process information, wherein the optimization process information is used to indicate that when the fitting process is interrupted, the inner and outer ring intermediate group components are selected according to the intermediate group component fitting processing method to give priority to matching excess accessories.

[0092] It should be noted that the information interaction, execution process and other contents between the above modules are based on the same concept as the method embodiment of this application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0093] The present application also provides a terminal device, such as Figure 14 As shown, the terminal device 140 of this embodiment includes: a processor 141, a memory 142, and a computer program 143 stored in the memory 142 and executable on the processor 141. When the processor 141 executes the computer program 143, the steps in the above-mentioned minimum sample number determination and interrupt processing method embodiment are implemented, for example Figure 1 Steps S100 to S500 shown; or, when the processor 141 executes the computer program 143, the functions of each module in the above device are realized, such as Figure 13 Functions of modules 131 to 135 are shown.

[0094] The terminal device 140 can be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The terminal device 140 includes but is not limited to a processor 141 and a memory 142. Those skilled in the art will understand that Figure 14 It is merely an example of the terminal device 140 and does not constitute a limitation on the terminal device 140. The terminal device 140 may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the terminal device 140 may also include input and output devices, network access devices, buses, etc.

[0095] Among them, the processor 141 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.; the general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc.

[0096] The memory 142 can be an internal storage unit of the terminal device 140, such as a hard disk or memory of the terminal device 140, or the memory 142 can be an external storage device of the terminal device 140, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (FlashCard), etc. equipped on the terminal device 140; further, the memory 142 can also include both the internal storage unit of the terminal device 140 and the external storage device, and the memory 142 can also store the computer program 143 and other programs and data required by the terminal device 140, and the memory 142 can also be used to temporarily store data that has been output or is to be output.

[0097] One embodiment of the present application further provides a computer-readable storage medium storing a computer program, which, when executed by a processor, can implement the steps of each of the above-mentioned method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file, or some intermediate form; the computer-readable medium can include: any entity or device capable of carrying computer program code, recording medium, USB flash drive, mobile hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium.

[0098] The above are all preferred embodiments of the present application, and are not intended to limit the scope of protection of the present application. Therefore, any equivalent changes made based on the methods, principles, and structures of the present application should be included in the scope of protection of the present application.

Claims

1. A method for determining the minimum number of samples and interrupting the processing of rolling bearing assembly, characterized in that: The method comprises: Obtain the inner and outer ring size deviation distribution information and the optimal bearing service clearance information corresponding to any production batch of bearings to be assembled; Determining grouping information of the inner and outer ring size deviation ranges of the bearing to be assembled based on the inner and outer ring size deviation distribution information and the bearing service optimal clearance information; Determining the assembly failure probability information corresponding to the bearings to be assembled in the production batch according to the number of silo lanes in the waiting area of ​​the bearing assembly equipment and the grouping information of the inner and outer ring size deviation ranges of the bearings to be assembled; Determine the minimum number of samples based on the number of silo lanes in the waiting area and the inner and outer ring size deviation range grouping information corresponding to each production batch; Based on the minimum sample number information and the bearing fitting failure probability information, the bearing fitting selection process is optimized to generate optimized process information, wherein the optimized process information is used to indicate that when the fitting process is interrupted, the inner and outer ring intermediate group components are selected according to the intermediate group component fitting processing method to give priority to matching excess accessories.

2. The method according to claim 1, characterized in that Determining the grouping information of the inner and outer ring size deviation ranges of the bearing to be assembled based on the inner and outer ring size deviation distribution information and the bearing service optimal clearance information includes: Constructing a probability density function based on the inner and outer ring size deviation distribution information; Based on the bearing's optimal service clearance information, the probability density function is divided into equal probability groups to generate inner and outer ring size deviation range grouping information; Accordingly, before determining the assembly failure probability information corresponding to the bearings to be assembled in the production batch based on the number of silo lanes in the waiting area of ​​the bearing assembly equipment and the grouping information of the inner and outer ring size deviation ranges of the bearings to be assembled, the method further includes: Acquire maximum value information of waiting for pairing, wherein the maximum value information of waiting for pairing is used to describe the maximum value of the inner and outer ring components of the bearing to be assembled that are waiting for pairing when they are not paired; The waiting pairing maximum value information is determined to be the number of silo lanes in the waiting area.

3. The method according to claim 1, characterized in that The assembly process interruption is used to describe the interruption situation where the assembly cannot continue because the inner and outer ring accessories fill the waiting area and there are no matching accessories with the same group number; the intermediate group assembly processing method is used to describe the method of cross-group assembly of the target group under the condition of meeting the optimal clearance range.

4. The method according to claim 1, wherein After optimizing the bearing assembly selection process based on the minimum sample number information and the assembly failure probability information to generate optimized process information, the method further includes: Get initial clearance information; Comparing the initial clearance information with the clearance upper limit information, wherein the clearance upper limit information is 23 microns; If the initial clearance information is greater than the clearance upper limit information, determining the first rolling body as the pre-selected rolling body, wherein the size of the first rolling body is greater than the size of the current rolling body; Comparing the initial clearance information with the clearance lower limit information, wherein the clearance lower limit information is 6 microns; If the initial clearance information is less than the clearance lower limit information, the second rolling body is determined to be the primary rolling body, wherein the size of the second rolling body is smaller than the size of the current rolling body; Determining whether the clearance corresponding to the preliminarily selected rolling element is within a specified fitting range, wherein the specified fitting range is 6 μm to 23 μm; If the clearance corresponding to the preselected rolling element is within the specified range for fitting, the preselected rolling element is determined to be the fitting rolling element. Otherwise, a rolling element of another specification is re-determined as the preselected rolling element until the clearance corresponding to the preselected rolling element is within the specified range for fitting.

5. The method according to claim 1, wherein The minimum number of samples is determined based on the number of silo lanes in the waiting area and the grouping information of the inner and outer ring size deviation ranges corresponding to each production batch, including: According to the number of silo lanes in the waiting area, the number of lanes in the waiting area is determined, and according to the grouping information of the inner and outer ring size deviation range, the number of groups is determined; Input the number of silo lanes in the waiting area and the grouping information of the inner and outer ring size deviation ranges into a preset fitting success rate calculation function to determine the fitting success rate information; Determining minimum sample number information based on the set success rate information, wherein the minimum sample number information is used to describe the minimum number of tracks required under the condition that the set success rate information is greater than a specified probability; The calculation function of the success rate of the nesting is: ， Where, For the success rate information of the combination, is the failure probability information of the same group, is the probability of failure across combinations, is the number of groups, For the waiting area lane number information, is the number of combinations, for example is the number of combinations of choosing 2 from 5 elements, is the starting value of the first set, It is the starting value of the second set.

6. The method according to claim 5, characterized in that The value of the minimum sample number information is at least twice the group number information.

7. A system for determining the minimum number of samples and interrupting the processing of rolling bearing assembly, characterized in that: The system comprises: Inner and outer ring size deviation distribution information acquisition module: used to obtain the inner and outer ring size deviation distribution information and the bearing service optimal clearance information corresponding to any production batch of bearings to be assembled; Inner and outer ring size deviation range grouping information determination module: used to determine the inner and outer ring size deviation range grouping information of the bearing to be assembled based on the inner and outer ring size deviation distribution information and the bearing service optimal clearance information; A module for determining the probability of failure of assembly: used to determine the probability of failure of assembly corresponding to the bearings to be assembled in the production batch according to the number of silo lanes in the waiting area of ​​the bearing assembly equipment and the grouping information of the size deviation range of the inner and outer rings of the bearings to be assembled; Minimum sample number information determination module: used to determine the minimum sample number information based on the number of silo lanes in the waiting area corresponding to each production batch and the grouping information of the inner and outer ring size deviation range; Optimization process information generation module: used to optimize the bearing fitting and selection process based on the minimum sample number information and the fitting failure probability information, and generate optimization process information, wherein the optimization process information is used to indicate that when the fitting process is interrupted, the inner and outer ring intermediate group components are selected according to the intermediate group component fitting processing method to give priority to matching excess accessories.

8. A terminal device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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