Online assembly test method and system in fixed process

Abstract

The invention discloses an online assembly testing method and system for a fixed process, and relates to the technical field of assembly testing, and the method comprises the steps: obtaining a locking point set and a historical assembly log set of target glass; obtaining a historical locking torque imbalance assembly log set; obtaining a locking point association topology network; arranging torque sensors at the locking points of the locking point set, and performing torque monitoring on the locking point set in a preset monitoring window by using the arranged torque sensor set to obtain a monitoring torque sequence set; and performing assembly collaborative test analysis in combination with the monitoring moment sequence set and the locking point association topology network to obtain an assembly test result. The technical problem that potential torque unbalance is not recognized due to the fact that the correlation influence condition between the locking points in the assembling process cannot be accurately recognized in the prior art is solved, and the technical effect of improving the assembling reliability of the glass lock and the assembling test analysis accuracy is achieved.

Description

Technical Field

[0001] The invention relates to the technical field of assembly testing, and in particular to an online assembly testing method and system for a fixed process. Background Art

[0002] During the glass assembly process, the glass is usually locked by screws, bonding or snaps. In order to ensure that the glass is accurately positioned and evenly stressed, appropriate torque needs to be applied to the locking points. However, traditional assembly methods often rely on manual operation and cannot effectively monitor the torque distribution of each locking point and their relationship, resulting in torque imbalance or uneven locking. This imbalance not only affects the assembly quality, but may also cause glass breakage or fail to achieve the expected assembly effect. Therefore, how to efficiently and accurately monitor and optimize the torque application during the assembly process, especially the interaction between locking points, has become a major challenge in current technology. Summary of the invention

[0003] The present application provides an online assembly test method and system for a fixing process, which is used to solve the technical problem that the prior art cannot accurately identify the correlation influence between locking points in the assembly process, resulting in potential torque imbalance not being identified.

[0004] In view of the above problems, the present application provides an online assembly test method and system for a fixed process.

[0005] In a first aspect of the present application, there is provided an online assembly test method for a fixed process, the method comprising: Get the lock point set and historical assembly log set of the target glass; Performing a locking torque imbalance search on the historical assembly log set to obtain a historical locking torque imbalance assembly log set; Traversing the historical locking torque imbalance assembly log set, constructing an associated network for the locking point set, and obtaining a locking point associated topological network; Deploy torque sensors at the locking points of the locking point set respectively, and use the deployed torque sensor set to perform torque monitoring on the locking point set in a preset monitoring window to obtain a monitoring torque sequence set; The monitoring torque sequence set and the locking point associated topological network are combined to perform assembly collaborative test analysis to obtain assembly test results.

[0006] A second aspect of the present application provides an online assembly test system for a fixed process, the system comprising: A historical assembly log set acquisition module is used to acquire a lock point set and a historical assembly log set of a target glass; An unbalanced assembly log set acquisition module is used to perform a locking torque imbalance search on the historical assembly log set to obtain a historical locking torque imbalance assembly log set; A locking point associated topological network acquisition module is used to traverse the historical locking torque imbalance assembly log set to construct an associated network for the locking point set, and obtain a locking point associated topological network; A monitoring torque sequence set acquisition module is used to respectively deploy torque sensors at the locking points of the locking point set, and use the deployed torque sensor set to perform torque monitoring on the locking point set in a preset monitoring window to obtain a monitoring torque sequence set; The assembly test result acquisition module is used to perform assembly collaborative test analysis in combination with the monitoring torque sequence set and the locking point associated topological network to obtain the assembly test result.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages: The present application obtains the locking point set and historical assembly log set of the target glass, and then retrieves the locking torque imbalance of the historical assembly log set to obtain the historical locking torque imbalance assembly log set, and then traverses the historical locking torque imbalance assembly log set to build an associated network for the locking point set to obtain the locking point associated topological network, and then respectively deploys torque sensors at the locking points of the locking point set, and uses the deployed torque sensor set to monitor the locking point set in a preset monitoring window to obtain a monitoring torque sequence set, and then combines the monitoring torque sequence set and the locking point associated topological network to perform assembly collaborative test analysis to obtain assembly test results. The technical effect of performing assembly test analysis from both overall and local dimensions, identifying torque abnormalities, and improving assembly reliability is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0009] Figure 1 A schematic flow chart of an online assembly test method for a fixed process provided in an embodiment of the present application; Figure 2 A schematic diagram of the structure of an online assembly test system for a fixed process provided in an embodiment of the present application.

[0010] Explanation of the reference numerals: historical assembly log set acquisition module 11, unbalanced assembly log set acquisition module 12, locking point associated topological network acquisition module 13, monitoring torque sequence set acquisition module 14, assembly test result acquisition module 15. DETAILED DESCRIPTION

[0011] The present application provides an online assembly test method and system for a fixed process, which is used to solve the technical problem that the prior art cannot accurately identify the correlation influence between locking points in the assembly process, resulting in potential torque imbalance not being identified.

[0012] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0013] Embodiment 1, as Figure 1 As shown, the present application provides an online assembly test method of a fixed process, the method comprising: S1: Obtain the lock point set and historical assembly log set of the target glass; S2: performing a locking torque imbalance search on the historical assembly log set to obtain a historical locking torque imbalance assembly log set; In a possible embodiment, the target glass refers to a glass piece that is being assembled or tested, and a locking point analysis is required for it in this step. Locking points refer to the points where torque needs to be applied during the glass assembly process. These points are usually where the glass contacts or connects with other components (such as a frame). The locking point set refers to the set of these key points. The historical assembly log set refers to the relevant data log recorded in the historical assembly process, including information such as the applied torque, assembly sequence, and torque changes at each locking point. This log provides basic data for analyzing the torque application during the assembly process.

[0014] First, according to the assembly plan of the target glass, determine the set of locking points to ensure that all points that need to be locked can be identified. Then, obtain the set of historical assembly logs and extract the previous assembly data by consulting these logs. These historical data can provide an important basis for analyzing the torque imbalance problems that may occur during the assembly process. The role of this step is to provide necessary data support and basic information for subsequent imbalance retrieval and assembly testing.

[0015] Locking torque imbalance retrieval refers to filtering out assembly data with uneven or unbalanced torque application in historical assembly logs. Torque imbalance may be manifested as excessive or insufficient torque at a certain locking point, or inconsistent torque at multiple locking points, thus affecting the assembly effect. The historical locking torque imbalance assembly log collection refers to filtering out the relevant log collection with torque imbalance problems in the historical assembly process from the historical assembly log collection. Through this collection, it is possible to analyze which assembly processes have torque distribution problems, providing a reference for subsequent improvements and optimizations.

[0016] Preferably, the historical assembly log collection needs to be scanned and analyzed first. Each log record is retrieved and filtered according to preset standards (such as maximum torque value, minimum torque value, standard deviation, etc.). For example, if the torque value of a certain locking point exceeds the preset standard range, or there is an obvious imbalance in the torque values ​​of multiple locking points, the system will mark it as unbalanced data. During the retrieval process, based on the marks, it is automatically identified which logs contain uneven torque or other abnormal conditions. Finally, the system organizes these identified unbalanced assembly records into a historical locking torque unbalanced assembly log collection for subsequent analysis.

[0017] S3: traversing the historical locking torque unbalanced assembly log set to construct an associated network for the locking point set, and obtaining a locking point associated topological network; Further, the historical locking torque imbalance assembly log set is traversed to construct an associated network for the locking point set to obtain a locking point associated topological network. Step S3 of the embodiment of the present application further includes: Traversing the historical locking torque unbalanced assembly log set to extract unbalanced locking points and obtain an unbalanced locking point combination set; Extracting M locking points with the highest frequencies in the unbalanced locking point combination set as M central locking points, where M is a positive integer; Based on the unbalanced locking point combination set, counting the association frequencies of the M associated locking point sets associated with the M central locking points, to obtain the M associated locking point association frequency sets; Based on the M associated locking point association frequency sets, M associated weight sets are determined, and the locking point association topology network is constructed by combining the M central locking points, the M associated locking point sets and the locking point sets.

[0018] In a possible embodiment, the locking point association topology network is constructed by analyzing the mutual relationship between the locking points. In the locking point association topology network, the locking points are connected to other locking points through an "association" relationship. This network can reflect which locking points have applied torques that affect each other or have relationships. The unbalanced locking point combination set refers to a combination of multiple unbalanced locking points selected from the historical assembly log, which reflects which locking points often have torque imbalances together during the assembly process.

[0019] Preferably, the information of the locking points where torque imbalance has occurred is extracted from the historical locking torque imbalance assembly log set. An unbalanced locking point refers to a locking point where torque application is obviously uneven during the historical assembly process. By extracting these unbalanced points, the system can identify which locking points frequently have abnormalities during the historical assembly process. Then, the first M locking points with a higher frequency of occurrence are extracted from these unbalanced locking points as "central locking points". M is a positive integer, indicating the number of selected locking points.

[0020] Next, based on the set of unbalanced locking point combinations, count the other locking points associated with each center locking point, that is, other locking points that simultaneously cause moment imbalance, and calculate the frequency of these associations. For example, if a center locking point and multiple other locking points frequently co-occur in multiple unbalanced assemblies, the association frequency between them is high. Based on these frequency data, an "association weight" can be assigned to each associated locking point, and the size of the weight reflects the degree of influence between the associated locking point and its corresponding center locking point.

[0021] Finally, combining these association weights and the relationship between the central locking point and the associated locking points, a locking point association topological network is constructed. In this topological network, nodes represent locking points, and connecting edges represent the association between these points. The constructed topological network can not only reveal the association between each locking point, but also provide data support for torque adjustment and assembly strategy optimization in the subsequent assembly process.

[0022] The locking point association topological network constructed in this step can help identify which locking points have close relationships and whose torque application may affect each other, thereby providing a strong basis for subsequent assembly testing and optimization.

[0023] Further, based on the M associated locking point association frequency sets, M associated weight sets are determined, and the locking point association topology network is constructed by combining the M central locking points, the M associated locking point sets and the locking point sets. Step S3 of the embodiment of the present application also includes: The M central locking points are used as M first topological nodes; Obtain a second topological node set, and connect them to the M first topological nodes respectively to obtain M connection edge sets; Using the M association weight sets to identify the M connection edges, to obtain M identified connection edge sets; Based on the M central locking points and the M associated locking point sets, the locking point set is identified as having no associated locking points, so as to obtain a third topological node set; Connecting the third topological node set to the first topological node closest to the M first topological nodes, and marking the connection edges according to the preset position association weights to obtain a third topological node marked connection edge set; A topological network is constructed based on the M first topological nodes, the second topological node set, the M identification connection edge sets, the third topological node set and the third topological node identification connection edge set to obtain the lock point associated topological network.

[0024] Furthermore, a union of the M associated locking point sets is obtained to obtain the second topological node set.

[0025] Further, it is determined whether there are any locking points in the locking point set that do not belong to the M central locking points and the M associated locking point sets. If so, they are added to the third topological node set.

[0026] Further, based on the M associated locking point associated frequency sets, M associated weight sets are determined. In the embodiment of the present application, step S3 further includes: The M association weight sets are obtained by respectively dividing the association frequency of one of the M association lock payment point association frequency sets by the total frequency of the corresponding association lock payment point association frequency sets.

[0027] In one possible embodiment, the first topological node refers to the locking point that serves as the starting node in the construction of the topological network, and is the central locking point where imbalances frequently occur. The second topological node set refers to other locking points that are strongly associated with the central locking point, which constitute the nodes of the second level in the topological network. The relationship between the second topological node set and the central locking point, that is, the corresponding first topological node, is determined by the association weight. Connection edge set: In the topological network, the connection between nodes is represented by edges, and the connection edge set reflects the connection relationship between the first topological node and the second topological node.

[0028] The identified connection edge set is the connection edge obtained after the connection edge is identified by using the associated weight. The identification is used to help distinguish the relationships of different strengths between the first topological node and the second topological node for subsequent analysis. Unassociated locking points refer to those locking points that have no direct relationship with the selected central locking point and the associated locking point set. These locking points are relatively independent in the assembly and may not be affected by the central locking point. The unassociated locking points are aggregated to generate a third topological node set. In other words, the third topological node set is the locking points that are screened out from the locking point set and are not directly associated with any central locking point or associated locking point, and are usually located on the periphery of the topological network.

[0029] The third topological node identification connection edge set refers to the edges connecting the third topological nodes in the third topological node set with the corresponding first topological nodes, and the connection edges are obtained after being identified according to the position association weights preset by technicians in this field.

[0030] In one embodiment, first, M central locking points are used as the first topological nodes of the topological network. Then, the union of the M associated locking point sets is obtained to obtain the second topological node set, and the second topological node set is connected to the corresponding M first topological nodes according to the association relationship between the second topological node set and the first topological node to obtain M connection edge sets. Then, these connection edges are marked using M association weight sets, and the higher the weight, the stronger the association between the two. The marked connection edges help to clarify the influence between different locking points and optimize the construction of the topological network.

[0031] Preferably, the M association weight sets are obtained by respectively dividing the association frequency of one associated lock payment point in the M associated lock payment point association frequency sets by the total frequency of the corresponding associated lock payment point association frequency sets.

[0032] Furthermore, the next step is to identify those lock points that are not associated with any central lock point or associated lock point. These points are classified as "unassociated lock points" and form a third topological node set. By comparing the distance between these unassociated lock points and the first topological node, these nodes are connected to the first topological node that is closest to them. Then, these connection edges are marked according to the preset position association weights to form a third topological node mark connection edge set.

[0033] Finally, based on all topological nodes (including the first topological node, the second topological node and the third topological node) and the connecting edges between them (including the identification connecting edges and the third topological node identification connecting edges), the construction of the entire lock-payment point association topological network is completed.

[0034] By constructing a hierarchical topological network of locking points, the relationship between the central locking point, the associated locking points and the unassociated locking points is clearly displayed, thus providing a clear structural basis for the associated influence of torque during the assembly process. This helps to identify potential torque imbalance risks and achieve more precise assembly control.

[0035] S4: deploying torque sensors at the locking points of the locking point set respectively, and using the deployed torque sensor set to monitor the torque of the locking point set in a preset monitoring window to obtain a monitoring torque sequence set; In one possible embodiment, the torque sensor is a sensor for measuring the rotational force (torque) applied to an object. It can monitor and record the torque changes of each locking point to ensure that the torque applied to each locking point is within an appropriate range. The set of torque sensors that have been deployed refers to the total set of torque sensors installed and configured on each locking point. These sensors are responsible for monitoring the torque state of each locking point. The preset monitoring window refers to the monitoring time range pre-set by a person skilled in the art. During this time period, the torque sensor will continuously record and monitor the torque data of the locking point. The monitoring torque sequence set refers to the torque data set collected from all locking point sensors within the preset monitoring window. This data set will reflect the torque changes of each locking point during the entire monitoring process.

[0036] By installing a torque sensor on each locking point, it is ensured that each locking point can monitor its torque changes in real time, and then the torque sensor is used to continuously record the applied torque size and change trend during the assembly process. In the preset monitoring window, the torque of all locking points is continuously monitored using a set of torque sensors, and the monitored torque data is recorded as a monitoring torque sequence set. The technical effect of providing data support for subsequent assembly collaborative test analysis is achieved.

[0037] S5: performing assembly collaborative test analysis in combination with the monitoring torque sequence set and the locking point associated topological network to obtain assembly test results.

[0038] Further, combining the monitoring torque sequence set and the locking point associated topological network to perform assembly collaborative test analysis to obtain assembly test results, step S5 of the embodiment of the present application further includes: Traversing the monitoring torque sequence set to identify abnormal torque deviation, marking the locking point set as abnormal according to the identification result, and obtaining Q abnormal locking points, where Q is a positive integer; Using the Q abnormal lock-payment points as indexes, performing an associated search on the lock-payment point associated topological network to determine Q abnormal associated lock-payment point sets and Q abnormal identification connection edge sets; In combination with the monitoring torque sequence set, assembly collaborative test analysis is performed on the Q abnormal associated locking point sets and the Q abnormal identification connection edge sets to obtain the assembly test result.

[0039] In a possible embodiment, the monitoring torque sequence set reflects the torque change of the locking point set within a preset monitoring window. The locking point association topological network reflects the association between the locking point sets, providing a basis for subsequent collaborative analysis. Therefore, by discovering abnormal locking points and then combining the locking point association topological network to perform association abnormality analysis, potential torque imbalances in the assembly process can be discovered in a timely manner.

[0040] Preferably, the monitoring torque sequence set is identified for abnormal torque deviation according to the preset locking torque sequence and the preset tolerance threshold to obtain an abnormal locking point. The abnormal locking point refers to a locking point where the difference between the monitoring torque and the preset locking torque exceeds the preset tolerance threshold during the torque monitoring process. The torque state of these points does not meet the standards, which may lead to a decrease in assembly quality or damage to the glass. The preset locking torque sequence is a change in the locking point torque that is preset by a person skilled in the art. The preset tolerance threshold is a torque deviation range that meets the requirements and is preset by a person skilled in the art.

[0041] Then, with the Q abnormal locking points as indexes, the locking point associated topological network is searched for association, and the abnormal associated locking point sets associated with the abnormal locking points and the abnormal identification connection edge sets between them are obtained, thereby obtaining Q abnormal associated locking point sets and Q abnormal identification connection edge sets. Although the locking points in these abnormal associated locking point sets have not deviated from the normal range at present, they may be affected by the abnormal locking points, resulting in torque imbalance or assembly problems. Therefore, monitoring and analysis of these points are crucial.

[0042] Combined with the monitoring torque sequence data, the abnormal associated locking points and their abnormal marked connection edges are subjected to assembly collaborative testing and analysis. Through this collaborative analysis, potential problems in the entire assembly process can be comprehensively evaluated, especially the impact of abnormal locking points on other locking points. In this way, torque imbalance or other abnormalities in the assembly process can be discovered and corrected in a timely manner, thereby improving assembly quality and efficiency. By evaluating the assembly quality from both overall and local aspects, potential assembly risks can be discovered in advance, and glass damage or assembly failure caused by torque imbalance or unevenness can be avoided, thereby improving the reliability and accuracy of the overall assembly.

[0043] Further, in combination with the monitoring torque sequence set, the Q abnormal associated locking point sets and the Q abnormal identification connection edge sets are subjected to assembly collaborative test analysis to obtain the assembly test result. Step S5 of the embodiment of the present application further includes: Extracting Q abnormal associated monitoring moment sequence sets of the Q abnormal associated locking point sets from the monitoring moment sequence set; Based on the preset locking torque sequence, deviation identification is performed on the Q abnormal associated monitoring torque sequence sets to obtain Q abnormal associated monitoring torque deviation degree sets; Combining the weights of the Q abnormal identification connection edge sets, weighted calculation is performed on the Q abnormal association monitoring moment deviation sets to obtain Q abnormal association deviations; It is determined whether the Q abnormal correlation deviations are greater than or equal to a preset abnormal correlation deviation threshold. If so, the corresponding abnormal locking point and the abnormal correlation locking point set are added to the assembly test result.

[0044] Further, based on the preset locking torque sequence, the Q abnormal associated monitoring torque sequence sets are subjected to deviation identification to obtain Q abnormal associated monitoring torque deviation degree sets. Step S5 of the embodiment of the present application further includes: Randomly extracting a first abnormality-associated monitoring moment sequence from the Q abnormality-associated monitoring moment sequence sets; Calculating the deviation between the first abnormality-related monitoring torque sequence and the preset locking torque sequence to obtain a first deviation sequence; Calculating the mean of the first deviation sequence to obtain a first abnormal associated monitoring torque deviation; According to the preset locking torque sequence, deviation identification is performed on the remaining abnormal associated monitoring torque sequences in the Q abnormal associated monitoring torque sequence sets to obtain the Q abnormal associated monitoring torque deviation degree sets.

[0045] In a possible embodiment, firstly, the torque sequence associated with the abnormal locking point is extracted from the monitoring torque sequence set to form an abnormal associated monitoring torque sequence set. These monitoring sequences reflect the possible impact on other locking points associated with the abnormal locking point during the assembly process.

[0046] Then, the first abnormal associated monitoring torque sequence is randomly extracted from the set of Q abnormal associated monitoring torque sequences. The deviation between the first abnormal associated monitoring torque sequence and the preset locking torque sequence is calculated, that is, the difference between the first abnormal associated monitoring torque sequence and the preset locking torque sequence is calculated to obtain a torque deviation value sequence, and then the torque deviation value sequence is compared with the preset locking torque sequence to obtain the first deviation degree sequence. The first deviation degree sequence reflects the degree of deviation of the abnormal associated locking point corresponding to the first abnormal associated monitoring torque sequence from the preset torque on the premise of meeting the torque requirements.

[0047] Then, the mean of the first deviation sequence is calculated to obtain the first abnormal correlation monitoring torque deviation, wherein the first abnormal correlation monitoring torque deviation reflects the general degree of deviation of the abnormal correlation locking point corresponding to the first abnormal correlation monitoring torque sequence from the preset torque under the premise of meeting the torque requirement.

[0048] Based on the same principle as that of obtaining the first abnormal associated monitoring torque deviation, according to the preset locking torque sequence, deviation identification is performed on the remaining abnormal associated monitoring torque sequences in the set of Q abnormal associated monitoring torque sequences to obtain the set of Q abnormal associated monitoring torque deviations.

[0049] Combined with the weights in the abnormal identification connection edge set (i.e., the connection edges representing the relative importance of the locking points), a weighted calculation is performed on each abnormal associated monitoring torque deviation to obtain the abnormal associated deviation. This calculation takes into account the relative importance of different locking points, so that important locking points (e.g., key bearing points) have a greater influence on the final assembly result.

[0050] Finally, by judging whether the abnormal correlation deviation exceeds the preset abnormal correlation deviation threshold, it can be decided whether to include the abnormal locking point and its associated points in the assembly test results. If the deviation exceeds the threshold, it means that there may be problems with the assembly of these points and further correction is required. The preset abnormal correlation deviation threshold is the maximum deviation allowed by the technicians in this field.

[0051] Through precise torque monitoring and deviation analysis, possible anomalies and unevenness in the assembly process can be identified, and the assembly process can be optimized according to the degree of influence of each locking point. Through weighted calculation and deviation analysis, the key factors affecting assembly quality can be more effectively identified, thereby improving the accuracy and reliability of assembly.

[0052] In summary, the online assembly test method of a fixed process provided by the present invention has the following technical effects: The present application obtains the locking point set and historical assembly log set of the target glass, and then retrieves the locking torque imbalance of the historical assembly log set to obtain the historical locking torque imbalance assembly log set, and then traverses the historical locking torque imbalance assembly log set to build an associated network for the locking point set to obtain the locking point associated topological network, and then respectively deploys torque sensors at the locking points of the locking point set, and uses the deployed torque sensor set to monitor the locking point set in a preset monitoring window to obtain a monitoring torque sequence set, and then combines the monitoring torque sequence set and the locking point associated topological network to perform assembly collaborative test analysis to obtain assembly test results. The technical effect of performing assembly test analysis from both overall and local dimensions, identifying torque abnormalities, and improving assembly reliability is achieved.

[0053] Embodiment 2, based on the same inventive concept as the online assembly test method of a fixed process in the above embodiment, Figure 2 As shown, the present application provides an online assembly test system for a fixed process, and the system and method embodiments in the present application are based on the same inventive concept. The system includes: A historical assembly log set acquisition module 11 is used to acquire a locking point set and a historical assembly log set of a target glass; An unbalanced assembly log set obtaining module 12 is used to perform a locking torque unbalance search on the historical assembly log set to obtain a historical locking torque unbalanced assembly log set; A locking point associated topological network acquisition module 13 is used to traverse the historical locking torque imbalance assembly log set to construct an associated network for the locking point set, and obtain a locking point associated topological network; A monitoring torque sequence set acquisition module 14 is used to respectively deploy torque sensors at the locking points of the locking point set, and use the deployed torque sensor set to perform torque monitoring on the locking point set in a preset monitoring window to obtain a monitoring torque sequence set; The assembly test result acquisition module 15 is used to perform assembly collaborative test analysis in combination with the monitoring torque sequence set and the locking point associated topological network to obtain the assembly test result.

[0054] Furthermore, the lock-payment point associated topological network obtaining module 13 is used to perform the following steps: Traversing the historical locking torque unbalanced assembly log set to extract unbalanced locking points and obtain an unbalanced locking point combination set; Extracting M locking points with the highest frequencies in the unbalanced locking point combination set as M central locking points, where M is a positive integer; Based on the unbalanced locking point combination set, counting the association frequencies of the M associated locking point sets associated with the M central locking points, to obtain the M associated locking point association frequency sets; Based on the M associated locking point association frequency sets, M associated weight sets are determined, and the locking point association topology network is constructed by combining the M central locking points, the M associated locking point sets and the locking point sets.

[0055] Furthermore, the lock-payment point associated topological network obtaining module 13 is used to perform the following steps: The M central locking points are used as M first topological nodes; Obtain a second topological node set, and connect them to the M first topological nodes respectively to obtain M connection edge sets; Using the M association weight sets to identify the M connection edges, to obtain M identified connection edge sets; Based on the M central locking points and the M associated locking point sets, the locking point set is identified as having no associated locking points, so as to obtain a third topological node set; Connecting the third topological node set to the first topological node closest to the M first topological nodes, and marking the connection edges according to the preset position association weights to obtain a third topological node marked connection edge set; A topological network is constructed based on the M first topological nodes, the second topological node set, the M identification connection edge sets, the third topological node set and the third topological node identification connection edge set to obtain the lock point associated topological network.

[0056] Furthermore, a union of the M associated locking point sets is obtained to obtain the second topological node set.

[0057] Further, it is determined whether there are any locking points in the locking point set that do not belong to the M central locking points and the M associated locking point sets. If so, they are added to the third topological node set.

[0058] Furthermore, the lock-payment point associated topological network obtaining module 13 is used to perform the following steps: The M association weight sets are obtained by respectively dividing the association frequency of one of the M association lock payment point association frequency sets by the total frequency of the corresponding association lock payment point association frequency sets.

[0059] Furthermore, the assembly test result obtaining module 15 is used to perform the following steps: Traversing the monitoring torque sequence set to identify abnormal torque deviation, marking the locking point set as abnormal according to the identification result, and obtaining Q abnormal locking points, where Q is a positive integer; Using the Q abnormal lock-payment points as indexes, performing an associated search on the lock-payment point associated topological network to determine Q abnormal associated lock-payment point sets and Q abnormal identification connection edge sets; In combination with the monitoring torque sequence set, assembly collaborative test analysis is performed on the Q abnormal associated locking point sets and the Q abnormal identification connection edge sets to obtain the assembly test result.

[0060] Furthermore, the assembly test result obtaining module 15 is used to perform the following steps: Extracting Q abnormal associated monitoring moment sequence sets of the Q abnormal associated locking point sets from the monitoring moment sequence set; Based on the preset locking torque sequence, deviation identification is performed on the Q abnormal associated monitoring torque sequence sets to obtain Q abnormal associated monitoring torque deviation degree sets; Combining the weights of the Q abnormal identification connection edge sets, weighted calculation is performed on the Q abnormal association monitoring moment deviation sets to obtain Q abnormal association deviations; It is determined whether the Q abnormal correlation deviations are greater than or equal to a preset abnormal correlation deviation threshold. If so, the corresponding abnormal locking point and the abnormal correlation locking point set are added to the assembly test result.

[0061] Furthermore, the assembly test result obtaining module 15 is used to perform the following steps: Randomly extracting a first abnormality-associated monitoring moment sequence from the Q abnormality-associated monitoring moment sequence sets; Calculating the deviation between the first abnormality-related monitoring torque sequence and the preset locking torque sequence to obtain a first deviation sequence; Calculating the mean of the first deviation sequence to obtain a first abnormal associated monitoring torque deviation; According to the preset locking torque sequence, deviation identification is performed on the remaining abnormal associated monitoring torque sequences in the Q abnormal associated monitoring torque sequence sets to obtain the Q abnormal associated monitoring torque deviation degree sets.

[0062] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0063] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

[0064] This specification and the drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. An online assembly test method for a fixed process, characterized in that: The method comprises: Get the lock point set and historical assembly log set of the target glass; Performing a locking torque imbalance search on the historical assembly log set to obtain a historical locking torque imbalance assembly log set; Traversing the historical locking torque imbalance assembly log set, constructing an associated network for the locking point set, and obtaining a locking point associated topological network; Deploy torque sensors at the locking points of the locking point set respectively, and use the deployed torque sensor set to monitor the torque of the locking point set in a preset monitoring window to obtain a monitoring torque sequence set; The monitoring torque sequence set and the locking point associated topological network are combined to perform assembly collaborative test analysis to obtain assembly test results.

2. The online assembly test method of a fixing process as claimed in claim 1, characterized in that: Traversing the historical locking torque imbalance assembly log set, constructing an associated network for the locking point set, and obtaining a locking point associated topological network, including: Traversing the historical locking torque unbalanced assembly log set to extract unbalanced locking points and obtain an unbalanced locking point combination set; Extracting M locking points with the highest frequencies in the unbalanced locking point combination set as M central locking points, where M is a positive integer; Based on the unbalanced locking point combination set, counting the association frequencies of the M associated locking point sets associated with the M central locking points, to obtain the M associated locking point association frequency sets; Based on the M associated locking point association frequency sets, M associated weight sets are determined, and the locking point association topology network is constructed by combining the M central locking points, the M associated locking point sets and the locking point sets.

3. The online assembly test method of a fixing process as claimed in claim 2, characterized in that: Based on the M associated locking point association frequency sets, M associated weight sets are determined, and the locking point association topology network is constructed by combining the M central locking points, the M associated locking point sets and the locking point sets, including: The M central locking points are used as M first topological nodes; Obtain a second topological node set, and connect them to the M first topological nodes respectively to obtain M connection edge sets; Using the M association weight sets to identify the M connection edges, to obtain M identified connection edge sets; Based on the M central locking points and the M associated locking point sets, the locking point set is identified as having no associated locking points, so as to obtain a third topological node set; Connecting the third topological node set to the first topological node closest to the M first topological nodes, and marking the connection edges according to the preset position association weights to obtain a third topological node marked connection edge set; A topological network is constructed based on the M first topological nodes, the second topological node set, the M identification connection edge sets, the third topological node set and the third topological node identification connection edge set to obtain the lock point associated topological network.

4. The online assembly test method of a fixing process as claimed in claim 3, characterized in that: The M associated locking point sets are unioned to obtain the second topological node set.

5. The online assembly test method of a fixing process as claimed in claim 3, characterized in that: Determine whether there are any locking points in the locking point set that do not belong to the M central locking points and the M associated locking point sets. If so, add them to the third topological node set.

6. The online assembly test method of a fixing process as claimed in claim 2, characterized in that: Determining M association weight sets based on the M association lock point association frequency sets includes: The M association weight sets are obtained by respectively dividing the association frequency of one of the M association lock payment point association frequency sets by the total frequency of the corresponding association lock payment point association frequency sets.

7. The online assembly test method of a fixing process as claimed in claim 1, characterized in that: Combining the monitoring torque sequence set and the locking point associated topological network to perform assembly collaborative test analysis, obtaining assembly test results, including: Traversing the monitoring torque sequence set to identify abnormal torque deviation, marking the locking point set as abnormal according to the identification result, and obtaining Q abnormal locking points, where Q is a positive integer; Using the Q abnormal lock-payment points as indexes, performing an associated search on the lock-payment point associated topological network to determine Q abnormal associated lock-payment point sets and Q abnormal identification connection edge sets; In combination with the monitoring torque sequence set, assembly collaborative test analysis is performed on the Q abnormal associated locking point sets and the Q abnormal identification connection edge sets to obtain the assembly test result.

8. The online assembly test method of a fixing process as claimed in claim 7, characterized in that: In combination with the monitoring torque sequence set, the assembly collaborative test analysis is performed on the Q abnormal associated locking point sets and the Q abnormal identification connection edge sets to obtain the assembly test result, including: Extracting Q abnormal associated monitoring moment sequence sets of the Q abnormal associated locking point sets from the monitoring moment sequence set; Based on the preset locking torque sequence, deviation identification is performed on the Q abnormal associated monitoring torque sequence sets to obtain Q abnormal associated monitoring torque deviation degree sets; Combining the weights of the Q abnormal identification connection edge sets, weighted calculation is performed on the Q abnormal association monitoring moment deviation sets to obtain Q abnormal association deviations; It is determined whether the Q abnormal correlation deviations are greater than or equal to a preset abnormal correlation deviation threshold. If so, the corresponding abnormal locking point and the abnormal correlation locking point set are added to the assembly test result.

9. An online assembly test method for a fixing process as claimed in claim 8, characterized in that: Based on the preset locking torque sequence, deviation identification is performed on the Q abnormal associated monitoring torque sequence sets to obtain Q abnormal associated monitoring torque deviation degree sets, including: Randomly extracting a first abnormality-associated monitoring moment sequence from the Q abnormality-associated monitoring moment sequence sets; Calculating the deviation between the first abnormality-related monitoring torque sequence and the preset locking torque sequence to obtain a first deviation sequence; Calculating the mean of the first deviation sequence to obtain a first abnormal associated monitoring torque deviation; According to the preset locking torque sequence, deviation identification is performed on the remaining abnormal associated monitoring torque sequences in the Q abnormal associated monitoring torque sequence sets to obtain the Q abnormal associated monitoring torque deviation degree sets.

10. An online assembly test system for a fixed process, characterized in that: include: A historical assembly log set acquisition module is used to acquire a lock point set and a historical assembly log set of a target glass; An unbalanced assembly log set acquisition module is used to perform a locking torque imbalance search on the historical assembly log set to obtain a historical locking torque imbalance assembly log set; A locking point associated topological network acquisition module is used to traverse the historical locking torque imbalance assembly log set to construct an associated network for the locking point set, and obtain a locking point associated topological network; A monitoring torque sequence set acquisition module is used to respectively deploy torque sensors at the locking points of the locking point set, and use the deployed torque sensor set to perform torque monitoring on the locking point set in a preset monitoring window to obtain a monitoring torque sequence set; The assembly test result acquisition module is used to perform assembly collaborative test analysis in combination with the monitoring torque sequence set and the locking point associated topological network to obtain the assembly test result.

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