An intelligent management system and method based on the whole process of engineering detection projects

Abstract

This invention discloses a full-process intelligent management system and method for engineering testing projects, belonging to the field of engineering project management technology. The invention obtains testing projects, testing objects, and testing processes from the engineering project management system; breaks down testing projects into independent testing items and analyzes and establishes a set of related relationships; collects testing data and preliminary testing results, identifies abnormal testing items, and determines the scope of affected related testing items based on the set of related relationships; classifies and filters all independent testing items, distinguishing them into independent flow testing items and related controlled testing items; allows qualified testing items among the independent flow testing items to enter subsequent review; for related controlled testing items, analyzes the re-inspection priority and generates a re-inspection sequence, matches testing personnel to generate re-inspection task dispatch orders, and pushes them to the corresponding terminals.

Description

Technical Field

[0001] This invention relates to the field of engineering project management technology, specifically to an intelligent management system and method for the entire process of engineering testing projects. Background Technology

[0002] Current engineering testing project management systems generally adopt an integrated and linear process management model. A testing project can only proceed to the review, report preparation and document archiving stages after all testing content, data entry and preliminary inspection are completed. This approach, which requires all stages to be completed before proceeding, is inefficient in practice. If a test has abnormal data that needs to be rectified or retested, other completed and qualified tests cannot enter the subsequent processes in advance. They can only wait for the problem to be rectified, which unnecessarily delays the normal process and lengthens the overall project cycle.

[0003] On the other hand, the various tests within an engineering testing project are not entirely unrelated; they often have inherent connections. For example, test results for the same location, the same batch of materials, or the same construction procedure can affect each other, and an anomaly in a single test may indicate potential quality risks in related projects. However, existing management systems do not clearly identify and distinguish these relationships, making it impossible to determine which tests can be carried out independently and which require inter-related control. This results in inefficiencies caused by overall waiting during the execution of the entire engineering testing project, and also makes it difficult to effectively avoid incomplete test assessments and inaccurate conclusions due to neglecting interrelated risks. Summary of the Invention

[0004] The purpose of this invention is to provide a full-process intelligent management system and method for engineering testing projects, so as to solve the problems mentioned in the background art.

[0005] To address the aforementioned technical problems, this invention provides the following technical solution: a method for intelligent management of the entire process of engineering testing projects, comprising: Step S10: Obtain the testing project information, testing object information, testing process information, and testing task information for each engineering project from the engineering project management system; break down the testing project into multiple independent testing items, analyze and determine the relationship between each independent testing item, and establish a set of testing item relationship. Step S20: Collect the detection data and preliminary inspection results of each independent detection item, and identify abnormal detection items; based on the abnormal detection items, and combined with the set of correlation relationships of detection items, analyze and determine the range of related detection items affected by the abnormal detection items; Step S30: Classify and screen all independent detection items to determine whether they are within the scope of abnormal influence, and classify independent detection items into independent flow detection item category and associated controlled detection item category; Step S40: For independent inspection items that have passed the inspection in the independent flow inspection item category, allow them to enter the subsequent review stage; for related controlled inspection item categories, analyze the re-inspection priority of each independent inspection item, generate a re-inspection sequence according to the priority from high to low, match the inspection personnel, generate a re-inspection task dispatch form and push it to the corresponding terminal.

[0006] Step S10 includes: Step S11: Establish a communication connection with the engineering project management system through a preset data interface to receive structured data of the engineering project in real time. The structured data includes inspection project information, inspection object information, inspection process information, and inspection task information. Among them, the inspection project information includes a unique project identifier, project name, engineering type, inspection scope, planned start time, and planned end time; the inspection object information includes the spatial location code, object type identifier, object quantity, and group identifier of each inspection object; the inspection process information includes a list of inspection work procedures and a list of prerequisite procedures for each procedure, wherein the list of prerequisite procedures records the immediate preceding procedures that must be completed before each procedure is executed; the inspection task information includes the specific work content, job requirements, planned completion time, and list of required instruments and equipment for each inspection task. Step S12: Split each detection task into the smallest independent execution unit. If a detection task contains multiple detection objects, split the detection task into an independent detection item for each detection object; if a detection task contains multiple detection parameters, split the detection task into an independent detection item for each detection parameter; if a detection task contains multiple procedures, split the detection task into an independent detection item for each procedure; assign a globally unique independent detection item number to each independent detection item, and record the task identifier from which each independent detection item originates, the original execution order index, and the identifier of the planned executor.

[0007] Step S13: Extract three associated attribute values ​​for each independent inspection item to form an associated attribute triplet, including structural affiliation attribute, object classification attribute, and process sequence attribute; wherein, the structural affiliation attribute is determined based on the spatial location code of the inspection object corresponding to the independent inspection item, and the value is the structural unit identifier represented by the spatial location code. If the independent inspection item is not attached to any spatial location, the structural affiliation attribute is empty; the object classification attribute is determined based on the type identifier and batch number of the inspection object corresponding to the independent inspection item, and the value is a combination string of the type identifier and batch number. If the independent inspection item does not involve the batch classification of materials or components, the object classification attribute is empty; the process sequence attribute is determined based on the process list in the inspection process information, and the value is the sequence number of the process corresponding to the independent inspection item. At the same time, the set of preceding process numbers and the set of succeeding process numbers are recorded. If the independent inspection item does not belong to any process, the process sequence attribute is empty; Step S14: Traverse all independent inspection items and perform association relationship determination for each pair of independent inspection items. Let the association attribute triplet of independent inspection item A be (SA, OA, PA), and the association attribute triplet of independent inspection item B be (SB, OB, PB); where S represents the structural affiliation attribute, O represents the object classification attribute, and P represents the process sequence attribute; count the number of common association attributes between independent inspection items A and B, and use the ratio obtained by dividing the number of common attributes by the total number of attributes as the association strength value between the two inspection items, and record the specific common attribute association type combination; if the number of common attributes is greater than 0, then establish an association record between independent inspection items A and B, and the association record includes the independent inspection item A number, the independent inspection item B number, the association type combination, and the association strength value; summarize all established association records to form an inspection item association relationship set.

[0008] Step S20 includes: Step S21: Collect the original test data of each independent test item and the preliminary inspection results entered by the inspector. Compare the preliminary inspection results of each independent test item with the preset quality judgment standard item by item. If the preliminary inspection results do not meet the requirements of the quality judgment standard, mark the independent test item as an abnormal test item and update its status flag to abnormal status. Step S22: Starting with the anomaly detection item, retrieve all associated records containing the anomaly detection item number from the detection item association set. Extract the number of another independent detection item paired with the anomaly detection item in each associated record, as well as the corresponding association strength value and association type combination. After deduplicating the paired independent detection item numbers, form the initial influence set.

[0009] Step S23: Traverse each independent detection item number in the initial impact set and perform a secondary search. For the currently traversed independent detection item number, search the detection item association set for a record that simultaneously contains the current independent detection item number and another abnormal detection item number. The other abnormal detection item refers to any abnormal detection item other than those marked in step S21. If such an association record exists, mark the independent detection item corresponding to the current independent detection item number as a composite association controlled item and record all associated abnormal detection item numbers. If no such record exists, mark the current independent detection item as a single-source association controlled item and record its associated abnormal detection item numbers. Record all independent detection item numbers marked as composite association controlled items or single-source association controlled items, along with their respective association type combinations, association strength values, and associated abnormal detection item numbers in the impact range list. The impact range list is a data table, and each record contains at least: the affected independent detection item number, association type combination, association strength value, and one or more abnormal detection item numbers associated with the current independent detection item.

[0010] Step S30 includes: Step S31: Traverse all independent detection items and classify all independent detection items that appear in the scope of influence list into the associated controlled detection item category; if the independent detection item number does not appear in the scope of influence list, classify it into the independent flow detection item category. Step S32: For each independent detection item classified into the associated controlled detection item category, read the corresponding abnormal detection item number, association type combination, and association strength value from the impact range list. At the same time, update the corresponding status flag to the association locked status, record the lock timestamp and lock reason field, fill in the associated abnormal detection item number in the lock reason field, set the closed review submission entry for this independent detection item, and prohibit it from entering the subsequent review and report preparation stages.

[0011] Step S40 includes: Step S41: Check whether the original test data in all independent flow test items meet the preset pass / fail criteria; if they do, update the corresponding status flag to pending review status and allow entry into the subsequent review process; if they do not meet, maintain the original status and do not perform any operation. Step S42: In the category of associated controlled detection items, set the association strength value between single-source associated controlled items and associated abnormal detection items to r1, and the number of association types corresponding to single-source associated controlled items to k1, where k1 takes the value of 1, 2, or 3; calculate the re-inspection priority index P1, and the calculation formula is: P1 = r1 × k1; Set the number of anomaly detection items associated with the composite associated controlled item to m, obtain the maximum value of the association strength between the composite associated controlled item and all associated anomaly detection items, and denote it as r2; the number of association types corresponding to the composite associated controlled item is k2, and k2 takes the value of 1, 2, or 3; calculate the re-inspection priority index P2 of the composite associated controlled item, and the calculation formula is: P2 = r2 × k2 × m; Step S43: Sort the re-inspection priority index P1 of the single-source associated controlled item and the re-inspection priority index P2 of the composite associated controlled item from high to low to generate a re-inspection sequence; when the priority indices of multiple associated controlled inspection items are equal, they are sorted in a second sorting order according to the original execution order index value set in the project management system from small to large, with the smaller the original execution order index value, the earlier the sorting order. Step S44: Obtain the personnel number and current task load value of each inspector in the inspector information table. The current task load value is the number of inspection tasks that the inspector is currently executing. Count the number of inspection task entries with the status of "in progress" for each inspector from the task allocation table. For each single-source associated controlled item or composite associated controlled item in the re-inspection sequence, select the personnel with the smallest current task load value from the inspector information table as the dispatch target. If there are multiple personnel with the same current task load value, select the one with the smallest personnel number. Step S45: Generate a re-inspection task dispatch order according to the re-inspection sequence from high priority to low priority. The dispatch order includes the number of the single-source associated controlled item or the number of the compound associated controlled item, the name of the single-source associated controlled item or the name of the compound associated controlled item, the number of the associated anomaly detection item and its association strength value and association type combination, the re-inspection priority index, and the personnel number of the dispatched personnel; push the dispatch order to the mobile terminal of the dispatched personnel, and increment the current task load value of the dispatched personnel by one after successful push; summarize all the generated re-inspection task dispatch orders to form a re-inspection task list and store it in the database.

[0012] A full-process intelligent management system based on engineering testing projects includes a testing project data acquisition module, a testing item correlation analysis module, an abnormal testing item identification module, and a re-inspection task dispatch module; The testing project data acquisition module obtains testing project information, testing object information, testing process information, and testing task information for each engineering project from the engineering project management system; it breaks down the testing project into multiple independent testing items, analyzes and determines the relationship between each independent testing item, and establishes a set of testing item relationship. The detection item correlation analysis module collects the detection data and preliminary inspection results of each independent detection item to identify abnormal detection items; based on the abnormal detection items, and combined with the detection item correlation relationship set, it analyzes and determines the range of related detection items affected by the abnormal detection items. The anomaly detection item identification module classifies and filters all independent detection items to determine whether they are within the scope of anomaly influence, and distinguishes independent detection items into independent flow detection items and associated controlled detection items. The re-inspection task dispatch module allows qualified independent inspection items from the independent flow inspection items to enter the subsequent review stage; for associated controlled inspection items, it analyzes the re-inspection priority of each independent inspection item, generates a re-inspection sequence according to the priority from high to low, matches the inspection personnel, generates a re-inspection task dispatch form, and pushes it to the corresponding terminal.

[0013] Compared with the prior art, the beneficial effects achieved by the present invention are: This invention establishes a set of relationships between independent testing items, enabling automatic identification of abnormal testing items and accurate determination of their impact range. When an independent testing item becomes abnormal, it can automatically classify the unaffected and qualified independent testing items into an independent transfer category, allowing them to independently enter the subsequent review and report preparation stages. This avoids the problem of the overall project cycle being lengthened due to the rectification of some testing items, and significantly improves the execution efficiency of engineering testing projects. This invention distinguishes between single-source associated controlled detection items and composite associated controlled detection items, and calculates a re-inspection priority index based on association strength value, number of association types, and number of abnormal detection items. This enables differentiated re-inspection scheduling for detection items affected by anomalies, automatically generating re-inspection sequences according to priority, and intelligently matching dispatch objects based on the current workload of testing personnel, ensuring efficient execution of re-inspection tasks. Simultaneously, locking the execution status of associated controlled detection items and closing the review entry point effectively prevents incomplete judgments and inaccurate conclusions due to neglecting association risks, achieving intelligent process control while ensuring testing quality. Attached Figure Description

[0014] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a flowchart of a method for intelligent management of the entire process of engineering testing projects. Detailed Implementation

[0015] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0016] Please see Figure 1The present invention provides a technical solution: a full-process intelligent management system based on engineering testing projects, including a testing project data acquisition module, a testing item correlation analysis module, an abnormal testing item identification module, and a re-inspection task dispatch module; The testing project data acquisition module obtains testing project information, testing object information, testing process information, and testing task information for each engineering project from the engineering project management system; it breaks down the testing project into multiple independent testing items, analyzes and determines the relationship between each independent testing item, and establishes a set of testing item relationship. The detection item correlation analysis module collects the detection data and preliminary inspection results of each independent detection item to identify abnormal detection items; based on the abnormal detection items, and combined with the detection item correlation relationship set, it analyzes and determines the range of related detection items affected by the abnormal detection items. The anomaly detection item identification module classifies and filters all independent detection items to determine whether they are within the scope of anomaly influence, and distinguishes independent detection items into independent flow detection items and associated controlled detection items. The re-inspection task dispatch module allows qualified independent inspection items from the independent flow inspection items to enter the subsequent review stage; for associated controlled inspection items, it analyzes the re-inspection priority of each independent inspection item, generates a re-inspection sequence according to the priority from high to low, matches the inspection personnel, generates a re-inspection task dispatch form, and pushes it to the corresponding terminal.

[0017] A method for intelligent management of the entire process of engineering testing projects includes: Step S10: Obtain the testing project information, testing object information, testing process information, and testing task information for each engineering project from the engineering project management system; break down the testing project into multiple independent testing items, analyze and determine the relationship between each independent testing item, and establish a set of testing item relationship. Step S20: Collect the detection data and preliminary inspection results of each independent detection item, and identify abnormal detection items; based on the abnormal detection items, and combined with the set of correlation relationships of detection items, analyze and determine the range of related detection items affected by the abnormal detection items; Step S30: Classify and screen all independent detection items to determine whether they are within the scope of abnormal influence, and classify independent detection items into independent flow detection item category and associated controlled detection item category; Step S40: For independent inspection items that have passed the inspection in the independent flow inspection item category, allow them to enter the subsequent review stage; for related controlled inspection item categories, analyze the re-inspection priority of each independent inspection item, generate a re-inspection sequence according to the priority from high to low, match the inspection personnel, generate a re-inspection task dispatch form and push it to the corresponding terminal.

[0018] Step S10 includes: Step S11: Establish a communication connection with the engineering project management system through a preset data interface to receive structured data of the engineering project in real time. The structured data includes inspection project information, inspection object information, inspection process information, and inspection task information. Among them, the inspection project information includes a unique project identifier, project name, engineering type, inspection scope, planned start time, and planned end time; the inspection object information includes the spatial location code, object type identifier, object quantity, and group identifier of each inspection object; the inspection process information includes a list of inspection work procedures and a list of prerequisite procedures for each procedure, wherein the list of prerequisite procedures records the immediate preceding procedures that must be completed before each procedure is executed; the inspection task information includes the specific work content, job requirements, planned completion time, and list of required instruments and equipment for each inspection task. Step S12: Split each detection task into the smallest independent execution unit. If a detection task contains multiple detection objects, split the detection task into an independent detection item for each detection object; if a detection task contains multiple detection parameters, split the detection task into an independent detection item for each detection parameter; if a detection task contains multiple procedures, split the detection task into an independent detection item for each procedure; assign a globally unique independent detection item number to each independent detection item, and record the task identifier from which each independent detection item originates, the original execution order index, and the identifier of the planned executor.

[0019] Step S13: Extract three associated attribute values ​​for each independent inspection item to form an associated attribute triplet, including structural affiliation attribute, object classification attribute, and process sequence attribute; wherein, the structural affiliation attribute is determined based on the spatial location code of the inspection object corresponding to the independent inspection item, and the value is the structural unit identifier represented by the spatial location code. If the independent inspection item is not attached to any spatial location, the structural affiliation attribute is empty; the object classification attribute is determined based on the type identifier and batch number of the inspection object corresponding to the independent inspection item, and the value is a combination string of the type identifier and batch number. If the independent inspection item does not involve the batch classification of materials or components, the object classification attribute is empty; the process sequence attribute is determined based on the process list in the inspection process information, and the value is the sequence number of the process corresponding to the independent inspection item. At the same time, the set of preceding process numbers and the set of succeeding process numbers are recorded. If the independent inspection item does not belong to any process, the process sequence attribute is empty; Step S14: Traverse all independent inspection items and perform association relationship determination for each pair of independent inspection items. Let the association attribute triplet of independent inspection item A be (SA, OA, PA), and the association attribute triplet of independent inspection item B be (SB, OB, PB); where S represents the structural affiliation attribute, O represents the object classification attribute, and P represents the process sequence attribute; count the number of common association attributes between independent inspection items A and B, and use the ratio obtained by dividing the number of common attributes by the total number of attributes as the association strength value between the two inspection items, and record the specific common attribute association type combination; if the number of common attributes is greater than 0, then establish an association record between independent inspection items A and B, and the association record includes the independent inspection item A number, the independent inspection item B number, the association type combination, and the association strength value; summarize all established association records to form an inspection item association relationship set.

[0020] Step S20 includes: Step S21: Collect the original test data of each independent test item and the preliminary inspection results entered by the inspector. Compare the preliminary inspection results of each independent test item with the preset quality judgment standard item by item. If the preliminary inspection results do not meet the requirements of the quality judgment standard, mark the independent test item as an abnormal test item and update its status flag to abnormal status. Step S22: Starting with the anomaly detection item, retrieve all associated records containing the anomaly detection item number from the detection item association set. Extract the number of another independent detection item paired with the anomaly detection item in each associated record, as well as the corresponding association strength value and association type combination. After deduplicating the paired independent detection item numbers, form the initial influence set.

[0021] Step S23: Traverse each independent detection item number in the initial impact set and perform a secondary search. For the currently traversed independent detection item number, search the detection item association set for a record that simultaneously contains the current independent detection item number and another abnormal detection item number. The other abnormal detection item refers to any abnormal detection item other than those marked in step S21. If such an association record exists, mark the independent detection item corresponding to the current independent detection item number as a composite association controlled item and record all associated abnormal detection item numbers. If no such record exists, mark the current independent detection item as a single-source association controlled item and record its associated abnormal detection item numbers. Record all independent detection item numbers marked as composite association controlled items or single-source association controlled items, along with their respective association type combinations, association strength values, and associated abnormal detection item numbers in the impact range list. The impact range list is a data table, and each record contains at least: the affected independent detection item number, association type combination, association strength value, and one or more abnormal detection item numbers associated with the current independent detection item.

[0022] Step S30 includes: Step S31: Traverse all independent detection items and classify all independent detection items that appear in the scope of influence list into the associated controlled detection item category; if the independent detection item number does not appear in the scope of influence list, classify it into the independent flow detection item category. Step S32: For each independent detection item classified into the associated controlled detection item category, read the corresponding abnormal detection item number, association type combination, and association strength value from the impact range list. At the same time, update the corresponding status flag to the association locked status, record the lock timestamp and lock reason field, fill in the associated abnormal detection item number in the lock reason field, set the closed review submission entry for this independent detection item, and prohibit it from entering the subsequent review and report preparation stages.

[0023] Step S40 includes: Step S41: Check whether the original test data in all independent flow test items meet the preset pass / fail criteria; if they do, update the corresponding status flag to pending review status and allow entry into the subsequent review process; if they do not meet, maintain the original status and do not perform any operation. Step S42: In the category of associated controlled detection items, set the association strength value between single-source associated controlled items and associated abnormal detection items to r1, and the number of association types corresponding to single-source associated controlled items to k1, where k1 takes the value of 1, 2, or 3; calculate the re-inspection priority index P1, and the calculation formula is: P1 = r1 × k1; Set the number of anomaly detection items associated with the composite associated controlled item to m, obtain the maximum value of the association strength between the composite associated controlled item and all associated anomaly detection items, and denote it as r2; the number of association types corresponding to the composite associated controlled item is k2, and k2 takes the value of 1, 2, or 3; calculate the re-inspection priority index P2 of the composite associated controlled item, and the calculation formula is: P2 = r2 × k2 × m; Step S43: Sort the re-inspection priority index P1 of the single-source associated controlled item and the re-inspection priority index P2 of the composite associated controlled item from high to low to generate a re-inspection sequence; when the priority indices of multiple associated controlled inspection items are equal, they are sorted in a second sorting order according to the original execution order index value set in the project management system from small to large, with the smaller the original execution order index value, the earlier the sorting order. Step S44: Obtain the personnel number and current task load value of each inspector in the inspector information table. The current task load value is the number of inspection tasks that the inspector is currently executing. Count the number of inspection task entries with the status of "in progress" for each inspector from the task allocation table. For each single-source associated controlled item or composite associated controlled item in the re-inspection sequence, select the personnel with the smallest current task load value from the inspector information table as the dispatch target. If there are multiple personnel with the same current task load value, select the one with the smallest personnel number. Step S45: Generate a re-inspection task dispatch order according to the re-inspection sequence from high priority to low priority. The dispatch order includes the number of the single-source associated controlled item or the number of the compound associated controlled item, the name of the single-source associated controlled item or the name of the compound associated controlled item, the number of the associated anomaly detection item and its association strength value and association type combination, the re-inspection priority index, and the personnel number of the dispatched personnel; push the dispatch order to the mobile terminal of the dispatched personnel, and increment the current task load value of the dispatched personnel by one after successful push; summarize all the generated re-inspection task dispatch orders to form a re-inspection task list and store it in the database.

[0024] This embodiment is applied to a structural building engineering project. First, the project management system is used to obtain information on the main structure inspection project, beam, slab and column inspection objects, structural inspection process, and inspection tasks. The overall inspection task is divided into multiple independent inspection items according to the smallest execution unit, including 32 independent inspection items such as concrete strength inspection, rebar cover thickness inspection, floor slab thickness inspection, and component verticality inspection. Each independent inspection item is assigned a unique number from JC1 to JC32. For each independent inspection item, three types of association attributes are extracted: structural affiliation, object classification, and process sequence, forming association attribute triplet. All inspection item pairs are traversed and the association strength value is calculated. When the number of identical attributes is 2, the association strength value is 0.67, and when the number of identical attributes is 1, the association strength value is 0.33. Finally, a set of inspection item association relationships containing 48 association records is established. The original test data of each independent test item and the preliminary inspection results entered by the inspectors were collected and compared with the preset quality standards. The measured concrete strength of the 3rd floor frame beam corresponding to test item JC8 was 22.6 MPa, which did not meet the design strength requirements. It was marked as an abnormal test item and set to an abnormal state. Based on this abnormal test item, three related test items JC9, JC12 and JC15 were retrieved from the test item association set, forming the initial influence set. Further secondary search revealed that JC9 is also associated with another abnormal test item JC18. Therefore, JC9 was marked as a composite associated controlled item. JC12 and JC15 are only associated with JC8 and are marked as single-source associated controlled items. The test item numbers, association strengths, association types and corresponding abnormal test item numbers of the above test items were uniformly recorded in the influence range list. Iterate through all 32 independent inspection items and categorize them according to whether they are in the impact range list. JC9, JC12, and JC15 are classified into the associated controlled inspection item category, their review submission entry is closed, their status is updated to associated locked status, and the lock timestamp and anomaly source number are recorded. The remaining 28 independent inspection items that are not affected by the anomaly are classified into the independent flow inspection item category, and their review submission entry remains open. Among them, 25 independent flow inspection items have qualified inspection results, and the system automatically updates their status to pending review, allowing them to enter the subsequent review and report preparation stages. The 3 independent flow inspection items with unqualified results maintain their original status and do not enter the next process. For each associated controlled detection item, a re-inspection priority index is calculated. For the single-source associated controlled item JC12, the association strength r1 is 0.67 and the number of association types k1 is 2, resulting in a priority index P1 = 1.34. For the composite associated controlled item JC9, the number of associated abnormal detection items m is 2, the maximum association strength r2 is 0.73, and the number of association types k2 is 2, resulting in a priority index P2 = 2.92. A re-inspection sequence is generated by sorting the items by priority index from high to low. If the priorities are the same, they are sorted again by the original execution order index. Intelligent task assignment is performed based on the current task load of the inspectors. Inspector A is currently executing 1 inspection task, which is the minimum load. Re-inspection task assignment orders are generated for the inspection items in the re-inspection sequence and pushed to their mobile terminal. After the push is completed, their task load is updated, and all re-inspection task lists are stored in the database for archiving.

[0025] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A method for intelligent management of the entire process of engineering testing projects, characterized in that: The method includes: Step S10: Obtain the testing project information, testing object information, testing process information, and testing task information for each engineering project from the engineering project management system; break down the testing project into multiple independent testing items, analyze and determine the relationship between each independent testing item, and establish a set of testing item relationship. Step S20: Collect the detection data and preliminary inspection results of each independent detection item, and identify abnormal detection items; based on the abnormal detection items, and combined with the set of correlation relationships of detection items, analyze and determine the range of related detection items affected by the abnormal detection items; Step S30: Classify and screen all independent detection items to determine whether they are within the scope of abnormal influence, and classify independent detection items into independent flow detection item category and associated controlled detection item category; Step S40: For independent inspection items that have passed the inspection in the independent flow inspection item category, allow them to enter the subsequent review stage; for related controlled inspection item categories, analyze the re-inspection priority of each independent inspection item, generate a re-inspection sequence according to the priority from high to low, match the inspection personnel, generate a re-inspection task dispatch form and push it to the corresponding terminal.

2. The intelligent management method for the entire process of engineering testing projects according to claim 1, characterized in that: Step S10 includes: Step S11: Establish a communication connection with the engineering project management system through a preset data interface to receive structured data of the engineering project in real time. The structured data includes inspection project information, inspection object information, inspection process information, and inspection task information. Among them, the inspection project information includes a unique project identifier, project name, engineering type, inspection scope, planned start time, and planned end time; the inspection object information includes the spatial location code, object type identifier, object quantity, and group identifier of each inspection object; the inspection process information includes a list of inspection work procedures and a list of prerequisite procedures for each procedure, wherein the list of prerequisite procedures records the immediate preceding procedures that must be completed before each procedure is executed; the inspection task information includes the specific work content, job requirements, planned completion time, and list of required instruments and equipment for each inspection task. Step S12: Split each detection task into the smallest independent execution unit. If a detection task contains multiple detection objects, split the detection task into an independent detection item for each detection object; if a detection task contains multiple detection parameters, split the detection task into an independent detection item for each detection parameter; if a detection task contains multiple procedures, split the detection task into an independent detection item for each procedure; assign a globally unique independent detection item number to each independent detection item, and record the task identifier from which each independent detection item originates, the original execution order index, and the identifier of the planned executor.

3. The intelligent management method for the entire process of engineering testing projects according to claim 2, characterized in that: Step S10 further includes: Step S13: Extract three associated attribute values ​​for each independent inspection item to form an associated attribute triplet, including structural affiliation attribute, object classification attribute, and process sequence attribute; wherein, the structural affiliation attribute is determined based on the spatial location code of the inspection object corresponding to the independent inspection item, and the value is the structural unit identifier represented by the spatial location code. If the independent inspection item is not attached to any spatial location, the structural affiliation attribute is empty; the object classification attribute is determined based on the type identifier and batch number of the inspection object corresponding to the independent inspection item, and the value is a combination string of the type identifier and batch number. If the independent inspection item does not involve the batch classification of materials or components, the object classification attribute is empty; the process sequence attribute is determined based on the process list in the inspection process information, and the value is the sequence number of the process corresponding to the independent inspection item. At the same time, the set of preceding process numbers and the set of succeeding process numbers are recorded. If the independent inspection item does not belong to any process, the process sequence attribute is empty; Step S14: Traverse all independent inspection items and perform association relationship determination for each pair of independent inspection items. Let the association attribute triplet of independent inspection item A be (SA, OA, PA), and the association attribute triplet of independent inspection item B be (SB, OB, PB); where S represents the structural affiliation attribute, O represents the object classification attribute, and P represents the process sequence attribute; count the number of common association attributes between independent inspection items A and B, and use the ratio obtained by dividing the number of common attributes by the total number of attributes as the association strength value between the two inspection items, and record the specific common attribute association type combination; if the number of common attributes is greater than 0, then establish an association record between independent inspection items A and B, and the association record includes the independent inspection item A number, the independent inspection item B number, the association type combination, and the association strength value; summarize all established association records to form an inspection item association relationship set.

4. The intelligent management method for the entire process of engineering testing projects according to claim 1, characterized in that: Step S20 includes: Step S21: Collect the original test data of each independent test item and the preliminary inspection results entered by the inspector. Compare the preliminary inspection results of each independent test item with the preset quality judgment standard item by item. If the preliminary inspection results do not meet the requirements of the quality judgment standard, mark the independent test item as an abnormal test item and update its status flag to abnormal status. Step S22: Starting with the anomaly detection item, retrieve all associated records containing the anomaly detection item number from the detection item association set. Extract the number of another independent detection item paired with the anomaly detection item in each associated record, as well as the corresponding association strength value and association type combination. After deduplicating the paired independent detection item numbers, form the initial influence set.

5. The intelligent management method for the entire process of engineering testing projects according to claim 4, characterized in that: Step S20 includes: Step S23: Traverse each independent detection item number in the initial impact set and perform a secondary search. For the currently traversed independent detection item number, search the detection item association set for a record that simultaneously contains the current independent detection item number and another abnormal detection item number. The other abnormal detection item refers to any abnormal detection item other than those marked in step S21. If such an association record exists, mark the independent detection item corresponding to the current independent detection item number as a composite association controlled item and record all associated abnormal detection item numbers. If no such record exists, mark the current independent detection item as a single-source association controlled item and record its associated abnormal detection item numbers. Record all independent detection item numbers marked as composite association controlled items or single-source association controlled items, along with their respective association type combinations, association strength values, and associated abnormal detection item numbers in the impact range list. The impact range list is a data table, and each record contains at least: the affected independent detection item number, association type combination, association strength value, and one or more abnormal detection item numbers associated with the current independent detection item.

6. The intelligent management method for the entire process of engineering testing projects according to claim 5, characterized in that: Step S30 includes: Step S31: Traverse all independent detection items and classify all independent detection items that appear in the scope of influence list into the associated controlled detection item category; if the independent detection item number does not appear in the scope of influence list, classify it into the independent flow detection item category. Step S32: For each independent detection item classified into the associated controlled detection item category, read the corresponding abnormal detection item number, association type combination, and association strength value from the impact range list. At the same time, update the corresponding status flag to the association locked status, record the lock timestamp and lock reason field, fill in the associated abnormal detection item number in the lock reason field, set the closed review submission entry for this independent detection item, and prohibit it from entering the subsequent review and report preparation stages.

7. The intelligent management method for the entire process of engineering testing projects according to claim 6, characterized in that: Step S40 includes: Step S41: Check whether the original test data in all independent flow test items meet the preset pass / fail criteria; if they do, update the corresponding status flag to pending review status and allow entry into the subsequent review process; if they do not meet, maintain the original status and do not perform any operation. Step S42: In the category of associated controlled detection items, set the association strength value between single-source associated controlled items and associated abnormal detection items to r1, and the number of association types corresponding to single-source associated controlled items to k1, where k1 takes the value of 1, 2, or 3; calculate the re-inspection priority index P1, and the calculation formula is: P1 = r1 × k1; Set the number of anomaly detection items associated with the composite associated controlled item to m, obtain the maximum value of the association strength between the composite associated controlled item and all associated anomaly detection items, and denote it as r2; the number of association types corresponding to the composite associated controlled item is k2, and k2 takes the value of 1, 2, or 3; calculate the re-inspection priority index P2 of the composite associated controlled item, and the calculation formula is: P2 = r2 × k2 × m; Step S43: Sort the re-inspection priority index P1 of the single-source associated controlled item and the re-inspection priority index P2 of the composite associated controlled item from high to low to generate a re-inspection sequence; when the priority indices of multiple associated controlled inspection items are equal, they are sorted in a second sorting order according to the original execution order index value set in the project management system from small to large, with the smaller the original execution order index value, the earlier the sorting order. Step S44: Obtain the personnel number and current task load value of each inspector in the inspector information table. The current task load value is the number of inspection tasks that the inspector is currently executing. Count the number of inspection task entries with the status of "in progress" for each inspector from the task allocation table. For each single-source associated controlled item or composite associated controlled item in the re-inspection sequence, select the personnel with the smallest current task load value from the inspector information table as the dispatch target. If there are multiple personnel with the same current task load value, select the one with the smallest personnel number. Step S45: Generate a re-inspection task dispatch order according to the re-inspection sequence from high priority to low priority. The dispatch order includes the number of the single-source associated controlled item or the number of the compound associated controlled item, the name of the single-source associated controlled item or the name of the compound associated controlled item, the number of the associated anomaly detection item and its association strength value and association type combination, the re-inspection priority index, and the personnel number of the dispatched personnel; push the dispatch order to the mobile terminal of the dispatched personnel, and increment the current task load value of the dispatched personnel by one after successful push; summarize all the generated re-inspection task dispatch orders to form a re-inspection task list and store it in the database.

8. A full-process intelligent management system based on engineering testing projects, characterized in that: The system includes a test item data acquisition module, a test item correlation analysis module, an abnormal test item identification module, and a re-inspection task dispatch module; The data acquisition module for the testing items obtains information on testing items, testing objects, testing processes, and testing tasks for each engineering project from the engineering project management system; it breaks down the testing items into multiple independent testing items, analyzes and determines the relationships between each independent testing item, and establishes a set of relationships between testing items. The detection item correlation analysis module collects the detection data and preliminary inspection results of each independent detection item to identify abnormal detection items; based on the abnormal detection items, and combined with the detection item correlation relationship set, it analyzes and determines the range of related detection items affected by the abnormal detection items. The anomaly detection item identification module classifies and filters all independent detection items to determine whether they are within the scope of anomaly influence, and distinguishes independent detection items into independent flow detection items and associated controlled detection items. The re-inspection task dispatch module allows qualified independent inspection items from the independent flow inspection items to enter the subsequent review stage; for associated controlled inspection items, it analyzes the re-inspection priority of each independent inspection item, generates a re-inspection sequence from high to low priority, matches the inspection personnel, generates a re-inspection task dispatch form, and pushes it to the corresponding terminal.

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