A monitoring management method for tunnel support construction

Abstract

The present application relates to the technical field of construction management, in particular to a monitoring and management method for tunnel support construction, comprising the following steps: setting a unique operation ID for single-shot grouting operation and single-anchor rod installation operation, associating the operation ID with construction time, operation team, equipment number, material batch number and design parameters, collecting all operation data and establishing a tunnel support full-cycle construction information database. The present application sets a unique operation ID for each grouting operation and single-anchor rod installation operation, and binds the ID with construction time, operation team, equipment number, material batch number and design parameters, etc. to form a traceable data basis, making the construction behavior have full-process traceability. After an abnormal signal is triggered at a monitoring point, the associated operation information is retrieved in reverse order of the process sequence, a quality problem traceability chain is constructed, and precise defect positioning and responsibility path restoration are achieved.

Description

Technical Field

[0001] This invention relates to the field of construction management technology, and in particular to a monitoring and management method for tunnel support construction. Background Technology

[0002] The field of construction management technology is a key component of the engineering construction and project execution control system, mainly involving multiple aspects such as planning, resource allocation, progress control, quality monitoring, safety management, cost accounting, and collaborative scheduling during the construction process.

[0003] In current construction management, fragmented information leads to unclear delineation of responsibility for defects, especially in multi-party collaborative environments. Responsibility determination often relies on manual experience or fragmented records, lacking unified data standards and reducing the objectivity of quality assessments. For example, when quality issues arise in support work, it's difficult to reconstruct the specific batches of anchor bolt installations, the materials used, and the routes taken by construction personnel. Only post-event assessments based on the outcome level can be conducted, delaying defect handling and amplifying construction costs and safety risks. Furthermore, current technologies fail to effectively link supplier material performance with construction results, making it difficult to simultaneously assess material-related risks. Therefore, improvements are needed. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of existing technologies by proposing a monitoring and management method for tunnel support construction.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a monitoring and management method for tunnel support construction, comprising the following steps:

[0006] A unique operation ID is assigned to each shotcrete operation and each anchor bolt installation operation. The operation ID is associated with the construction time, operating team, equipment number, material batch number and design parameters. All operation data is collected to establish a tunnel support full-cycle construction information database.

[0007] Based on the tunnel support full-cycle construction information database, the sequence logic of drilling, hole cleaning, and grouting in anchor bolt construction is preset. When an abnormal signal of the target monitoring point ID is received, the data bound to the monitoring point ID in the tunnel support full-cycle construction information database is traversed in reverse to obtain the defect-related operation ID sequence. All associated operation IDs and all bound information are extracted according to the sequence logic. Combined with the defect-related operation ID sequence, a quality problem traceability chain is formed.

[0008] Based on the quality problem traceability chain, the associated material suppliers are extracted, the indicator data of each supplier are collected, and the material supply chain logistics stability index is calculated.

[0009] Based on the quality problem traceability chain, the frequency of each construction team and anchor bolt material supplier appearing in multiple quality problem traceability chains is counted, and a multi-source subject-related quality problem frequency table is established. The multi-source subject-related quality problem frequency table is then combined with the supplier's material supply chain logistics stability index to generate a comprehensive construction quality responsibility result.

[0010] Preferably, the steps for obtaining the tunnel support full-cycle construction information database are as follows:

[0011] The construction time is analyzed for each shotcrete operation and each anchor bolt installation operation. The operation team is extracted, the equipment number is read, the material batch number is retrieved, and the design parameters are imported. The data is then spliced ​​and compared according to a fixed field order to check for duplicate records and obtain a unique operation ID.

[0012] Based on the unique job ID, the construction time, operation team, equipment number, material batch number and design parameters are called to establish a one-to-one binding relationship between the unique job ID and the parameters, and a time and operation identifier are generated for each binding relationship record to generate a unique job ID binding record;

[0013] Based on the unique job ID binding records, all job entries are aggregated one by one. A retrieval index is established according to the unique job ID, a sorting index is established according to the construction time, and an auxiliary index is established according to the operation team and material batch number to form a structured storage, thus obtaining a tunnel support full-cycle construction information database.

[0014] Preferably, the step of obtaining the defect-associated job ID sequence is as follows:

[0015] Based on the tunnel support full-cycle construction information database, the drilling record field, hole cleaning record field and grouting record field are extracted, and the process labels, process sequence codes and pre- and post-constraints are marked. The parallel allowance flag and timeout processing flag are fixed, and the mapping relationship between process labels and process sequence codes is established to obtain the anchor bolt construction process sequence logic.

[0016] According to the logic of the anchor bolt construction sequence, the abnormal signal of the target monitoring point ID is received, and the operation ID, timestamp, construction time, operation team, equipment number, material batch number and design parameters bound to the target monitoring point ID are retrieved from the tunnel support full-cycle construction information database. The operation ID is traced back in reverse order of timestamp and the positions of adjacent operations and the intervals between operations are recorded to generate a defect-related operation ID sequence.

[0017] Preferably, the steps for obtaining the quality problem traceability chain are as follows:

[0018] Based on the defect-associated operation ID sequence, the operation IDs are compared with adjacent operations and cross-operation missing verification is performed according to the logic of the anchor bolt construction procedure. The construction time, operation team, equipment number, material batch number and design parameters bound to the operation ID are aggregated and organized into a traceable node chain according to the defect-associated operation ID sequence, forming a quality problem traceability chain.

[0019] Preferably, the step of obtaining the material supply chain logistics stability index is as follows:

[0020] Based on the quality issue traceability chain, read the material batch number field, supplier name field, and supplier code field bound to the defect-related job ID, verify the consistency of supplier name and supplier code one by one and remove duplicates, and record the job ID, corresponding timestamp, and material batch number to generate a list of related material suppliers.

[0021] Based on the aforementioned list of related material suppliers, the on-time delivery rate is obtained by comparing the delivery records of each supplier with the planned delivery records. The batch quality pass rate is calculated by extracting inspection records. The supply quantity satisfaction and transit damage rate are obtained by comparing the purchase records with the shipping records. The price fluctuation coefficient is calculated by extracting price records. The emergency replenishment response time is calculated by extracting emergency replenishment records. All indicators are normalized by interval and positive and negative ideal values ​​are determined, generating a set of standardized indicators and a set of positive and negative ideal solutions.

[0022] The material supply chain logistics stability index is calculated based on the normalized index set and the positive and negative ideal solution set.

[0023] Preferably, the steps for obtaining the multi-source subject association quality problem frequency table are as follows:

[0024] Based on the quality issue traceability chain, pairing keys are established according to the construction team name and the anchor bolt material supplier name. The number of occurrences of each pairing key is accumulated, and the number of operations of the construction team, the list of associated operation IDs, the first time stamp and the last time stamp are accumulated simultaneously. Duplicate pairing keys are merged and the consistency of fields is checked to generate a multi-source subject-related quality issue frequency table.

[0025] Preferably, the steps for obtaining the comprehensive responsibility result for construction quality are as follows: calculate the bilateral joint responsibility index based on the frequency table of quality problems associated with multiple sources.

[0026] Preferably, the steps for obtaining the comprehensive responsibility results for construction quality further include: sorting the bilateral joint responsibility indices in descending order by the construction team name and the anchor bolt material supplier name, extracting the bilateral joint responsibility index, first timestamp, last timestamp and associated operation ID list for each pair, and forming the comprehensive responsibility results for construction quality.

[0027] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0028] This invention assigns a unique operation ID to each shotcrete operation and single anchor bolt installation, binding this ID with information such as construction time, operating team, equipment number, material batch number, and design parameters to form a traceable data foundation. This enables full-process traceability of construction activities. After an abnormal signal is triggered at a monitoring point, the associated operation information is retrieved in reverse using the process sequence logic to construct a quality problem traceability chain. This achieves precise defect location and responsibility path reconstruction. Furthermore, the material suppliers involved in the traceability chain are extracted, and a logistics stability index is constructed based on the stability of supply indicators. Combining the frequency of the construction team's appearance in multiple traceability chains, a joint responsibility evaluation model for the construction team and material suppliers is established. Statistical frequency and stability index are used for quantitative fusion. The granular control of the operation ID enhances the precision of the basic data, the embedding of process logic improves the contextual accuracy of information extraction, and the joint evaluation of supply chain and construction responsibility enhances the horizontal collaborative identification capability. This improves the response efficiency to abnormal quality problems and the accuracy of responsibility pointing, ensuring control over the construction process in complex engineering scenarios. Attached Figure Description

[0029] Figure 1 This is a schematic diagram of the steps of the present invention. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0031] Please see Figure 1 This invention provides a technical solution, a monitoring and management method for tunnel support construction, comprising the following steps:

[0032] A unique operation ID is assigned to each shotcrete operation and each anchor bolt installation operation. The operation ID is associated with the construction time, operating team, equipment number, material batch number and design parameters. All operation data is collected to establish a tunnel support full-cycle construction information database.

[0033] Based on the tunnel support full-cycle construction information database, the sequence logic of drilling, hole cleaning and grouting in anchor bolt construction is preset. When an abnormal signal of the target monitoring point ID is received, the data bound to the monitoring point ID in the tunnel support full-cycle construction information database is traversed in reverse to obtain the defect-related operation ID sequence. Based on the sequence logic, all related operation IDs and all bound information are extracted. Combined with the defect-related operation ID sequence, a quality problem traceability chain is formed.

[0034] Based on the quality issue traceability chain, the associated material suppliers are extracted, the indicator data of each supplier are collected, and the material supply chain logistics stability index is calculated.

[0035] Based on the quality issue traceability chain, the frequency of each construction team and anchor bolt material supplier appearing in multiple quality issue traceability chains is counted, and a multi-source entity related quality issue frequency table is established. The multi-source entity related quality issue frequency table is then combined with the supplier's material supply chain logistics stability index to generate a comprehensive construction quality responsibility result.

[0036] The steps for obtaining the tunnel support full-cycle construction information database are as follows:

[0037] The construction time is analyzed for each shotcrete operation and each anchor bolt installation operation. The operation team is extracted, the equipment number is read, the material batch number is retrieved, and the design parameters are imported. The data is then spliced ​​and compared according to a fixed field order to check for duplicate records and obtain a unique operation ID.

[0038] Based on the unique job ID, the construction time, operation team, equipment number, material batch number and design parameters are called to establish a one-to-one binding relationship between the unique job ID and the parameters, and a time and operation identifier are generated for each binding relationship record, generating a unique job ID binding record;

[0039] Based on the unique job ID binding records, all job entries are aggregated one by one. A retrieval index is established according to the unique job ID, a sorting index is established according to the construction time, and an auxiliary index is established according to the operation team and material batch number to form a structured storage, thus obtaining a tunnel support full-cycle construction information database.

[0040] Specifically, the construction time is analyzed separately for a single shotcrete operation and a single anchor bolt installation operation. First, the raw data stream is obtained from the industrial control computer or data acquisition terminal on the equipment. This data stream contains timestamps, equipment status codes, and operation parameters. For the construction time field, it is analyzed according to ISO standards. The 8601 standard format, "YYYY-MM-DDTHH:mm:ss.sssZ", is parsed and uniformly converted to Coordinated Universal Time (UTC) timestamps. When extracting work team information, an interface with the construction scheduling management system is used for correlation querying. The work team identifier at that time is matched using the construction timestamp. The equipment number is directly extracted from the preset fields of the data stream to obtain the unique equipment asset code. Retrieving the material batch number requires calling the records of the material management system. Based on the operation time and the equipment used, the material batch information allocated to the equipment within that time period is retrieved in reverse. At the same time, when importing design parameters, the corresponding support design requirements, such as shotcrete thickness, anchor bolt length, and anchor bolt spacing, are retrieved from the Building Information Model (BIM) or design parameter database based on the tunnel mileage location where the operation occurred. Subsequently, the strings are concatenated according to the fixed field order of "tunnel mileage_operation type_equipment number_work team ID_material batch number" to generate an original identifier character. To generate a compact and unique ID, the SHA-256 hash algorithm is used to calculate the hash of the concatenated original identifier string, and the first 32 hexadecimal characters are extracted as candidate unique job IDs. Before formal confirmation, duplicate records are checked. This check mechanism sets a time window threshold, which is calculated based on historical job data. Specifically, the average time interval between all two adjacent jobs is calculated, and one-quarter of the average is used as the judgment standard. For example, if the average job interval is 20 minutes, the threshold is 5 minutes. When a new candidate unique job ID is generated, the database is searched to see if there is a record with the same timestamp that falls within the aforementioned 5-minute window. If it exists, the current record is marked as potential duplicate data, and a manual review process is triggered. If it does not exist, the candidate ID is confirmed as a valid unique job ID. In this way, each independent construction activity is given a reliable and conflict-free identity, ultimately resulting in a unique job ID.

[0041] Based on the unique job ID generated in the previous step, the system immediately retrieves the complete set of associated parameters, including the parsed construction time, the matched work team identifier, the retrieved equipment number, the retrieved material batch number, and the design parameters imported from the design library. To establish a one-to-one binding relationship between the unique job ID and these parameters, a key-value pair data structure is used for encapsulation. The key is the unique job ID, and the value is a structured object containing all associated parameters, such as a JSON object. This object clearly divides information into five dimensions: time, personnel, equipment, materials, and design, ensuring data integrity and ease of subsequent retrieval. Simultaneously, two additional metadata fields are added to each record: time and operation identifier. The timestamp is a server system timestamp recording the current binding operation, used to trace the exact moment the data was entered into the database. The operation identifier is a predefined code used to indicate the record's status; for example, '10' represents "created," '20' represents "updated," and '30' represents "archived." When the binding relationship is initially established, this identifier is uniformly set to '10'. This process is completed through an atomic database transaction; that is, the generation of the unique job ID and its binding with parameters are committed as an indivisible unit of operation, ensuring data consistency and preventing "orphan" data with only an ID but no corresponding parameters. The resulting binding record is represented at the data level as a complete record with metadata tags, for example, { The sequence of operations, "Job ID": "a1b2c3d4e5f6...", "Associated Data": { "Construction Time": "2023-11-01T10:30:00Z", "Operating Team": "CZ-01", "Equipment Number": "SGJ-05", "Material Batch Number": "SN-20231028-003", "Design Parameters": { "Spraying Thickness": "25cm", "Initial Setting Time": "8min"}}, "Record Generation Time": "2023-11-01T10:30:05.123Z", "Operation Identifier": "10"}, generates a uniquely bound record with a well-structured and complete set of job IDs.

[0042] Based on the series of unique job ID binding records generated in the previous steps, these records are aggregated and stored in a central database to construct the entity of the information repository. This process is not a simple accumulation, but is accompanied by the establishment of indexes and the optimization of the storage structure. At the data storage level, a relational database management system is selected, and a core data table named "Support Operation Information Table" is designed. Each row of the table corresponds to a unique job ID binding record, and the columns of the table correspond to the unique job ID, construction time, operation team, equipment number, material batch number, and a JSONB or TEXT type field for storing design parameters. In order to achieve efficient data retrieval and analysis, multiple indexes are created according to the preset indexing strategy while the data is being written. First, the unique job ID field... The primary key index is a unique, non-null clustered index that ensures the highest performance when querying by job ID. Secondly, a B-tree sorted index is created for the construction time field. This index supports fast data filtering by time range and time sorting of results. Secondary indexes are also created for the operation team and material batch number fields. These non-clustered indexes accelerate the query speed for all jobs related to a specific team or batch of materials, reducing the overhead of full table scans. Through this multi-index parallel strategy, the originally discrete job entries are organized into a highly structured data set, forming a logically clear and easily accessible structured storage, ultimately resulting in a tunnel support full-cycle construction information database that supports multi-dimensional, high-performance queries.

[0043] The steps to obtain the defect-associated job ID sequence are as follows:

[0044] Based on the tunnel support full-cycle construction information database, the drilling record field, hole cleaning record field and grouting record field are extracted, and the process labels, process sequence codes and pre- and post-constraints are marked. The parallel allowance flag and timeout processing flag are fixed, and the mapping relationship between process labels and process sequence codes is established to obtain the anchor bolt construction process sequence logic.

[0045] Based on the sequence logic of anchor bolt construction procedures, the abnormal signal of the target monitoring point ID is received. The operation ID, timestamp, construction time, operation team, equipment number, material batch number and design parameters bound to the target monitoring point ID are retrieved from the tunnel support full-cycle construction information database. The operation ID is traced back in reverse order of timestamp and the positions of adjacent procedures and the intervals between procedures are recorded to generate a defect-related operation ID sequence.

[0046] Specifically, based on the tunnel support full-cycle construction information database, the process first involves setting filtering conditions for work types, such as querying records with the work type field being 'anchor drilling', 'anchor cleaning', or 'anchor grouting'. This extracts all drilling, cleaning, and grouting record fields related to anchor installation from the database. Then, these three types of work records are standardized and labeled. Specifically, 'anchor drilling' records are assigned the process label 'DRILL' and process sequence code '1', 'anchor cleaning' records are assigned the process label 'CLEAN' and process sequence code '2', and 'anchor grouting' records are assigned the process label 'GROUT' and process sequence code '3'. Next, preconditions and postconditions are defined, explicitly stipulating that work with process sequence code '2' must be completed before the completion of precondition '1', and work with process sequence code '3' must be completed before the completion of precondition '2'. The premise is that, for the linear process of anchor bolt construction, a fixed parallel operation flag is set as 'FALSE', indicating that these three processes cannot be performed simultaneously on the same anchor bolt. Then, a timeout flag is set, which is a specific time threshold used to determine whether the interval between adjacent processes is too long. This threshold is set based on historical data analysis. Specifically, at least 5000 complete anchor bolt construction records are randomly selected from the tunnel support full-cycle construction information database. The time difference between the completion time of 'drilling' and the start time of 'hole cleaning', and the time difference between the completion time of 'hole cleaning' and the start time of 'grouting' are calculated for each record, forming two time difference datasets. The mean and standard deviation of each dataset are calculated. The timeout threshold is set to the mean plus 1.5 times the standard deviation. For example, if the average interval between 'hole cleaning' and 'grouting' is 45 minutes and the standard deviation is 10 minutes, then the timeout threshold is 45 minutes. + 1.5 * 10 = 60 minutes. Finally, organize all the information defined above, including process labels, process sequence codes, pre- and post-constraints, parallel flags, and calculated timeout thresholds, into a structured configuration table or mapping set, establish the mapping relationship between process labels and process sequence codes, and obtain the logic of the anchor bolt construction process sequence.

[0047] Based on the sequence logic of anchor bolt construction, when an abnormal signal is received from the on-site automated monitoring system containing the target monitoring point ID (typically 'MP_K10+500_R'), the timestamp of the abnormality, and the type of abnormality (e.g., 'displacement exceeding limits'), this information is immediately used as input to search the tunnel support full-cycle construction information database. The search scope is not global, but rather a localized query based on space and time. Spatially, based on the mileage location information contained in the target monitoring point ID, all anchor bolt installation records within a preset radius (e.g., 2 meters) of that location in three-dimensional space are selected from the database. Temporally, the search scope is limited to operations completed within 72 hours prior to the timestamp of the abnormality. Through this spatiotemporal joint filtering, the set of operations most likely related to the abnormality is precisely identified, and the IDs, timestamps, construction times, operating teams, equipment numbers, material batch numbers, and design parameters of these operations are obtained. Then, this filtering... The generated task set is sorted in descending order by timestamp. Starting from the most recent task, it backtracks backwards one by one. During the backtracking process, the logical relationship between the current task and the previous task (i.e., the earlier one in terms of time) is recorded. For example, if the current task's sequence code is '3' and the previous one's is '2', it is recorded as an adjacent task, and the difference between their timestamps is calculated as the cross-task interval. This interval is compared with the corresponding timeout threshold in the anchor bolt construction task sequence logic. If the interval is greater than the threshold, the task ID is marked as 'timeout'. If the current task's sequence code is '3' and the previous one's is '1', it is determined to be a cross-task, and the current task ID is marked as 'missing step'. This backtracking process continues until a complete 'GROUT'-'CLEAN'-'DRILL' task chain is found, or all the filtered task records are traversed. Finally, all the task IDs recorded during the backtracking process are arranged in reverse order to form a defect-related task ID sequence.

[0048] The steps to obtain the quality issue traceability chain are as follows:

[0049] Based on the defect-related operation ID sequence, the operation IDs are compared with adjacent operations and cross-operation missing verification is performed according to the logic of the anchor bolt construction process. The construction time, operation team, equipment number, material batch number and design parameters bound to the operation ID are aggregated and organized into a traceable node chain according to the defect-related operation ID sequence, forming a quality problem traceability chain.

[0050] Specifically, based on the defect-related job ID sequence generated in the previous step, a verification and data aggregation process is initiated. First, the job IDs in the sequence are re-verified according to the anchor bolt construction procedure order logic. Specifically, starting from the first job ID in the sequence (the latest job in terms of time), the process sequence code is read, and then the process sequence code of the next job ID in the sequence is read. Adjacent processes are compared according to the pre- and post-constraint rules in the anchor bolt construction procedure order logic to verify whether the sequence codes of the two are continuously decreasing. For example, if the current one is '3', the next one should be '2'. If this is not satisfied, it is confirmed that there is a cross-process missing, and a 'logical break' marker is added to the connection between the two IDs. At the same time, the timestamps corresponding to the two IDs are extracted, the difference is calculated, and compared with the timeout threshold set in the anchor bolt construction procedure order logic to confirm whether there is a timeout. After completing the verification of the entire sequence, each job ID in the sequence is then checked. Data aggregation is performed on each job ID. This involves using each job ID as an index to initiate a precise query to the tunnel support full-cycle construction information database. All detailed information bound one-to-one with that ID, including construction time, work team, equipment number, material batch number, and design parameters such as anchor bolt length, diameter, and angle, is extracted completely. Finally, these job records, with all aggregated information, are organized strictly according to the original order of the defect-related job ID sequence, constructing a chain-like data structure. Each node represents a specific job, storing all information about that job and status indicators generated during verification (such as 'normal,' 'timeout,' 'missing preceding sequence'). Nodes are linked in reverse chronological order via pointers or indexes, forming a complete and logically clear traceable node chain from the quality problem manifestation (abnormal signal) to the construction source, ultimately forming a quality problem traceability chain.

[0051] The steps to obtain the material supply chain logistics stability index are as follows:

[0052] Based on the quality issue traceability chain, read the material batch number field, supplier name field, and supplier code field bound to the defect-related job ID, verify the consistency of supplier name and supplier code one by one and remove duplicates, and record the job ID, corresponding timestamp, and material batch number to generate a list of related material suppliers.

[0053] Based on the list of related material suppliers, the on-time delivery rate is obtained by comparing the delivery records of each supplier with the planned delivery records. The batch quality pass rate is calculated by extracting inspection records. The supply quantity satisfaction and transit damage rate are obtained by comparing the purchase records with the shipping records. The price fluctuation coefficient is calculated by extracting price records. The emergency replenishment response time is calculated by extracting emergency replenishment records. All indicators are normalized by interval and the positive and negative ideal values ​​are determined, generating a set of standardized indicators and a set of positive and negative ideal solutions.

[0054] Based on the normalized index set and the positive and negative ideal solution set, the material supply chain logistics stability index is calculated using the following formula:

[0055] ;

[0056] in, For the first The material supply chain logistics stability index of each supplier. For the first The supplier in the first The value of a standardized indicator. For the first The positive ideal value of a normalized indicator. For the first The negative ideal value of a normalized indicator. The total number of standardized indicators. For the supplier's serial number, For the serial number of the standardized indicator, For the first The historical instability coefficient of a normalized indicator is derived from the relative volatility of the historical series of the normalized indicator. For the first The criticality coefficient of the correlation between a standardized indicator and the current quality problem traceability chain.

[0057] Specifically, based on the quality issue traceability chain, each traceable node in the chain is traversed, and for each node's associated unique job ID, a query is initiated to the tunnel support full-cycle construction information database to retrieve the bound material batch number field, obtaining batch number information such as "SN20231101A". Then, using this material batch number, a related query is performed in the material management system to extract the corresponding supplier name field, such as "XX Special Building Materials Co., Ltd.", and the supplier code field, such as "GS0087". Subsequently, a data consistency check is performed, combining the retrieved supplier name and supplier code with a pre-set qualified supplier master data table. This master data table is entered at project initiation and periodically reviewed and updated, containing the official full names of all cooperating suppliers and their unique internal codes. If no exact match is found in the data table, the job ID and its associated supplier information are marked as "pending verification," and a data cleaning task is generated. After verification, to construct a list of suppliers without duplicates, the supplier code is used as a unique identifier. All relevant supplier information is aggregated and deduplicated. Specifically, a hash table structure is used, with the supplier code as the key. When a new supplier code is encountered, a new entry is created in the hash table, and the current job ID, corresponding timestamp, and material batch number are stored as initial information in the entry. If the encountered supplier code already exists in the hash table, only the new job ID, timestamp, and material batch number are appended to the information list of the corresponding entry. Through this series of data extraction, verification, and aggregation operations, a list of associated material suppliers is finally generated.

[0058] Based on the related material supplier list generated in the previous step, for each supplier on the list, a series of logistical support capability indicators are calculated by calling data from different modules in the Enterprise Resource Planning (ERP) system. First, to calculate the on-time delivery rate, all delivery records and corresponding planned delivery records of the supplier within the past six months are extracted from the procurement and logistics module. The actual delivery date is compared with the planned delivery date, and a 24-hour grace period is set. That is, the actual delivery date is considered on time if it is not later than the planned delivery date plus 24 hours. The formula for calculating the on-time delivery rate is: On-time delivery rate = (Number of on-time deliveries / Total number of deliveries) X First, to calculate the batch quality pass rate, the incoming inspection records of all material batches are retrieved from the quality management module. The batch quality pass rate equals the number of batches with an inspection result of "pass" divided by the total number of inspected batches, multiplied by 100%. Second, to obtain the supply quantity fulfillment rate and transit damage rate, the purchase order records in the procurement module are compared with the actual warehousing records in the warehousing module. The supply quantity fulfillment rate is the cumulative actual warehousing quantity of all orders divided by the cumulative order requirement quantity. The transit damage rate is the difference between the cumulative shipped quantity and the cumulative warehousing quantity divided by the cumulative shipped quantity. Finally, to calculate the price fluctuation coefficient, the data for the same standard anchor bolt is extracted from the financial module. The price records of materials at each purchase are used to calculate the standard deviation of these prices, which is then divided by the average price to obtain the price volatility coefficient. Finally, to calculate the emergency replenishment response time, orders marked as "urgent" or "emergency" in the purchase records are selected, and the average time from order placement to final material receipt is calculated to obtain the emergency replenishment response time. After obtaining these six raw indicators (on-time delivery rate, batch quality pass rate, supply quantity satisfaction, transit damage rate, price volatility coefficient, and emergency replenishment response time), they are subjected to interval normalization, transforming all indicator values ​​to the range of 0 to 1. For positive indicators such as on-time delivery rate, the normalization formula is as follows: For negative indicators such as transit loss rate, then use ,in and It is the maximum and minimum values ​​of all suppliers for this indicator over the past year. By using this method, the positive ideal value of all indicators is determined to be 1, and the negative ideal value is determined to be 0. Finally, a standardized set of indicators and a unified set of positive and negative ideal solutions are generated for each supplier.

[0059] The material supply chain logistics stability index calculation formula uses a dynamically weighted improved TOPSIS method to assess the supply chain logistics stability of a specific supplier under the current quality problem context. The formula introduces a historical instability coefficient. Keyness coefficient related to the current problem Dynamic weighting factors constituted together This weighting system can adaptively adjust the influence of each evaluation indicator in the comprehensive assessment based on the historical performance stability of the indicators and their relevance to current specific quality issues. This makes the assessment results more targeted and objective. Furthermore, by calculating the Euclidean distance between the weighted sample points (suppliers) and the positive and negative ideal solutions, and using relative proximity to quantify their merits, the denominator is the sum of the weighted distances to the positive and negative ideal solutions, and the numerator is the weighted distance to the negative ideal solution. This results in... If the value falls within the range of [0, 1], the closer the value is to 1, the closer the supplier is to the ideal state and the higher the stability.

[0060] The steps to obtain this parameter are as follows: The supplier in the first The values ​​for each standardized indicator are derived from a generated set of standardized indicators. This set quantifies and unifies the supplier's performance across multiple dimensions, such as on-time delivery rate and batch quality pass rate, into the range [0, 1]. In this example, the evaluation of supplier A (i.e., ), which involves 6 standardized indicators (i.e. The value is: On-time delivery rate. Batch quality pass rate Supply quantity satisfaction Loss rate (After normalization, a higher value indicates less loss along the way), price volatility coefficient (After normalization, a higher value indicates more stable prices), emergency replenishment response time (After normalization, a higher value indicates a faster response.)

[0061] The steps to obtain this parameter are as follows: After positive normalization and interval normalization, the optimal performance of all standardized indicators corresponds to the value 1. Therefore, for all six indicators in this example, their optimal positive value is 1. .

[0062] The steps to obtain this parameter are as follows: The negative ideal value of each normalized indicator corresponds to its positive ideal value. After normalization, the worst performance of all indicators corresponds to the value 0. Therefore, for all 6 indicators in this example, their negative ideal values ​​are all 0. .

[0063] The steps to obtain this parameter are as follows: the total number of standardized indicators is determined by the evaluation system design. In this method, six core indicators are selected to evaluate the stability of the supply chain. .

[0064] The steps to obtain this parameter are as follows: The historical instability coefficient of a standardized indicator is obtained by calculating the relative volatility (i.e., coefficient of variation) of the indicator's historical data series. Specifically, it involves collecting raw data for the indicator over the past 24 months and calculating the ratio of its standard deviation to its mean. For example, for indicator 1 (on-time delivery rate), 24 data points were collected, and the calculated mean is 91% with a standard deviation of 4.55%. Therefore, its instability coefficient is... Similarly, the instability coefficients of other indicators were calculated as follows: , , , , .

[0065] The steps to obtain this parameter are as follows: The correlation criticality coefficients between standardized indicators and the current quality problem traceability chain were formulated by domain experts based on historical experience. Different types of quality defects and the correlation strength between each supply chain indicator were defined, with correlation strength divided into three levels: low (1), medium (2), and high (3). The defect revealed in this quality problem traceability chain was due to "the batch strength of the anchor bolt material not meeting the standard." Looking at the correlation matrix, the correlation between this defect and the "batch quality pass rate" indicator was "high," the correlation with the "price fluctuation coefficient" (which may reflect sacrificing quality for the sake of low prices) was "medium," and the correlation with other indicators was "low." Therefore, the correlation criticality coefficients for each indicator were set as follows: , , , , , .

[0066] Calculations based on parameters:

[0067] First, calculate the dynamic weights of each indicator. :

[0068] ;

[0069] ;

[0070] ;

[0071] ;

[0072] ;

[0073] ;

[0074] Next, the weighted distance from supplier A to the negative ideal solution is calculated. :

[0075] ;

[0076] ;

[0077] ;

[0078] Then, calculate the weighted distance from supplier A to the ideal solution. :

[0079] ;

[0080] ;

[0081] ;

[0082] Finally, calculate the material supply chain logistics stability index. :

[0083] ;

[0084] The results indicate that Supplier A's material supply chain logistics stability index is 0.884, which is very close to 1. This means that after comprehensively considering the correlation between historical stability and current quality issues, the supplier's overall performance is very close to the ideal state, and the stability of its logistics supply chain is very high. Although the quality issue was traced back to the supplier's materials, from a multi-dimensional and long-term comprehensive evaluation perspective, the supplier is still a highly reliable partner.

[0085] The steps to obtain the frequency table of quality problems associated with multiple sources are as follows:

[0086] Based on the quality issue traceability chain, pairing keys are established according to the construction team name and the anchor bolt material supplier name. The number of occurrences of each pairing key is accumulated, and the number of operations of the construction team, the list of associated operation IDs, the first time stamp and the last time stamp are accumulated simultaneously. Duplicate pairing keys are merged and the consistency of fields is checked to generate a multi-source subject-related quality issue frequency table.

[0087] Specifically, based on the quality issue traceability chain, each work node in the chain is traversed. The operation team name and material batch number fields are extracted from the node data. Then, based on the material batch number, the corresponding anchor bolt material supplier name field is obtained by querying the material management system database. Subsequently, the "operation team name" and "anchor bolt material supplier name" are concatenated using a specific separator (e.g., "|") to form a unique pairing key, such as "CZ-01 team | XXX Special Building Materials Co., Ltd." Next, a hash table structure is initialized for dynamic statistics, using the pairing key as the key and a composite object containing multiple statistical items, including: the number of times the pairing key appears, the total number of operations by the construction team, a list of associated operation IDs, and the first and last timestamps. When processing each node in the traceability chain, the corresponding pairing key is generated, and the hash table is updated accordingly. If the key is appearing for the first time, a new entry is created, the occurrence count is set to 1, and the current job ID and timestamp are recorded. If the key already exists, the occurrence count is incremented by 1, the new job ID is appended to the associated job ID list, and the last timestamp is compared and updated. While processing the paired keys, the construction information database is queried asynchronously to count the total number of operations performed by the construction team since the start of the project, and this value is updated in the composite object of the corresponding paired key. After traversing all quality problem traceability chains, a merge verification procedure is executed. This procedure merges duplicate paired keys with the same content but different names according to a preset alias mapping table (e.g., mapping "Team 1" and "Construction Team 1" to "CZ-01 Team"), and accumulates their statistical data. Finally, all entries in the hash table are converted into a table to generate a multi-source subject-related quality problem frequency table.

[0088] The steps for obtaining the comprehensive responsibility results for construction quality are as follows:

[0089] Based on the frequency table of quality issues related to multiple stakeholders, the bilateral joint responsibility index is calculated using the following formula:

[0090] ;

[0091] in, For construction teams With anchor bolt material suppliers Bilateral Joint Responsibility Index For construction teams With anchor bolt material suppliers The ratio of the number of occurrences of a pair in the frequency table of quality problems associated with multiple sources to the sum of the total number of occurrences of all pairs. For construction teams The historical defect index is equal to that of the construction team. Number of associated quality issues divided by construction team The value obtained after interval normalization following the number of operations. Anchor bolt material supplier The material supply chain logistics stability index. This is the serial number of the construction team. This refers to the serial number of the anchor bolt material supplier;

[0092] The bilateral joint responsibility indices are sorted in descending order by construction team name and anchor bolt material supplier name. The bilateral joint responsibility index, first timestamp, last timestamp and associated operation ID list of each pair are extracted to form the comprehensive responsibility result for construction quality.

[0093] Specifically, the formula: The above formula aims to establish a quantitative model that can comprehensively measure the shared responsibility of construction teams and material suppliers in specific quality issues. The formula contains... The term, as the basic weight, directly reflects the frequency of a specific "team-supplier" combination in the currently analyzed quality problem sample, demonstrating its direct correlation with the problem. The product term within the square root... The historical shortcomings and tendencies of the construction team Potential instability with suppliers (as indicated by the stability index) Combining the results obtained by negation, the potential risks of a historically underperforming work team collaborating with a supplier with poor stability are amplified multiplicatively. Finally, using square root extraction to address this compounded risk can moderately smooth out the impact of extreme values, resulting in a more favorable final responsibility index. This will prevent an overemphasis on the outcome due to the extreme poor performance of one party, thus allowing for a more equitable assessment of the joint responsibility of both parties.

[0094] The steps to obtain this parameter are as follows: This parameter represents the construction team. With anchor bolt material suppliers The frequency percentage of pairings is derived from statistical analysis of the generated multi-source subject association quality problem frequency table, and the calculation formula is: ,in The specific "work group" was obtained from the frequency table. -supplier "The number of times the pairings occur, and This is the sum of the occurrences of all pairs recorded in the table. For example, in an analysis batch containing 10 quality issue traceability chains, a total of 50 "team-supplier" pairing records were generated. Among them, the pairing of "CZ-01 team" and "XX special building materials" appeared 15 times. Then, the frequency percentage of this combination is... .

[0095] The steps to obtain this parameter are as follows: the parameter is obtained by the construction team. The historical defect index reflects the long-term construction quality level of the work team. Its calculation involves two steps: first, calculating the original defect rate. The formula is ,in It is the sum of all occurrences of the work group in the multi-source subject-related quality problem frequency table (e.g., the sum of the number of times it is paired with all suppliers). This refers to the total number of operations recorded by the work team in the tunnel support full-cycle construction information database; secondly, it refers to the original defect rate of all work teams. Max-min normalization is performed to eliminate the influence of dimensions and map it to the interval [0, 1]. The normalization formula is as follows: ,in and These are the maximum and minimum original defect rates for all construction teams in the current project. For example, team "CZ-01" has 20 associated quality issues, with a total of 500 operations, and the original defect rate is... If all work groups If the value range is [0.01, 0.08], then the historical defect index of this work group is... .

[0096] The steps to obtain this parameter are as follows: the parameter is obtained from the anchor bolt material supplier. The material supply chain logistics stability index is obtained through the aforementioned material supply chain logistics stability index calculation steps. It is a comprehensive score between [0, 1], directly calling the calculation results of the previous steps. For example, the stability index of supplier "XX Special Building Materials" is calculated as follows: .

[0097] Calculations based on parameters:

[0098] Calculate the bilateral joint responsibility index between "CZ-01 Team" and "XX Special Building Materials". .

[0099] Known parameters:

[0100] ;

[0101] ;

[0102] ;

[0103] Substitute into the formula:

[0104] ;

[0105] ;

[0106] ;

[0107] ;

[0108] ;

[0109] The result indicates that the bilateral joint responsibility index of the "CZ-01 Team" and "XX Special Building Materials" combination is approximately 0.06689. This value will serve as the basis for subsequent responsibility ranking and division. After calculating the responsibility indices of all relevant combinations, by comparing the magnitude of these indices, the high-risk combination that contributes the most to the quality problem can be clearly identified. For example, if the index of another combination is 0.15, then its responsibility is much greater than that of the current combination.

[0110] Based on the bilateral joint responsibility index calculated for each "construction team-anchor bolt material supplier" pairing in the previous step, this data is integrated and presented. First, a result set is created, where each record contains the construction team name, anchor bolt material supplier name, and corresponding bilateral joint responsibility index. Next, the result set is sorted in descending order using the bilateral joint responsibility index as the primary sort key, placing the pairing with the highest responsibility index at the top of the list to prioritize it. After sorting, the information in each record is further enriched. By using the construction team name and supplier name as the joint primary key, a multi-source subject-related quality problem frequency table is retrieved to extract additional diagnostic information related to the pairing. This includes the timestamp of the first time the pairing was associated with a quality problem, the timestamp of the most recent association, and a detailed list containing all unique job IDs related to this pairing. By binding the sorted responsibility index with this detailed time and job information, a structured and comprehensive construction quality responsibility result is finally formed, quantifying and ranking the responsibilities of each party.

[0111] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A monitoring and management method for tunnel support construction, characterized in that, Includes the following steps: A unique operation ID is assigned to each shotcrete operation and each anchor bolt installation operation. The operation ID is associated with the construction time, operating team, equipment number, material batch number and design parameters. All operation data is collected to establish a tunnel support full-cycle construction information database. Based on the tunnel support full-cycle construction information database, the sequence logic of drilling, hole cleaning, and grouting in anchor bolt construction is preset. When an abnormal signal of the target monitoring point ID is received, the data bound to the monitoring point ID in the tunnel support full-cycle construction information database is traversed in reverse to obtain the defect-related operation ID sequence. All associated operation IDs and all bound information are extracted according to the sequence logic. Combined with the defect-related operation ID sequence, a quality problem traceability chain is formed. Based on the quality problem traceability chain, the associated material suppliers are extracted, the indicator data of each supplier are collected, and the material supply chain logistics stability index is calculated. Based on the quality problem traceability chain, the frequency of each construction team and anchor bolt material supplier appearing in multiple quality problem traceability chains is counted, and a multi-source subject-related quality problem frequency table is established. The multi-source subject-related quality problem frequency table is jointly configured with the supplier's material supply chain logistics stability index to generate a comprehensive construction quality responsibility result. The steps for obtaining the material supply chain logistics stability index are as follows: Based on the quality issue traceability chain, read the material batch number field, supplier name field, and supplier code field bound to the defect-related job ID, verify the consistency of supplier name and supplier code one by one and remove duplicates, and record the job ID, corresponding timestamp, and material batch number to generate a list of related material suppliers. Based on the aforementioned list of related material suppliers, the on-time delivery rate is obtained by comparing the delivery records of each supplier with the planned delivery records. The batch quality pass rate is calculated by extracting inspection records. The supply quantity satisfaction and transit damage rate are obtained by comparing the purchase records with the shipping records. The price fluctuation coefficient is calculated by extracting price records. The emergency replenishment response time is calculated by extracting emergency replenishment records. All indicators are normalized by interval and positive and negative ideal values ​​are determined, generating a set of standardized indicators and a set of positive and negative ideal solutions. The material supply chain logistics stability index is calculated based on the normalized index set and the positive and negative ideal solution set.

2. The monitoring and management method for tunnel support construction according to claim 1, characterized in that, The steps for obtaining the tunnel support full-cycle construction information database are as follows: The construction time is analyzed for each shotcrete operation and each anchor bolt installation operation. The operation team is extracted, the equipment number is read, the material batch number is retrieved, and the design parameters are imported. The data is then spliced ​​and compared according to a fixed field order to check for duplicate records and obtain a unique operation ID. Based on the unique job ID, the construction time, operation team, equipment number, material batch number and design parameters are called to establish a one-to-one binding relationship between the unique job ID and the parameters, and a time and operation identifier are generated for each binding relationship record to generate a unique job ID binding record; Based on the unique job ID binding records, all job entries are aggregated one by one. A retrieval index is established according to the unique job ID, a sorting index is established according to the construction time, and an auxiliary index is established according to the operation team and material batch number to form a structured storage, thus obtaining a tunnel support full-cycle construction information database.

3. The monitoring and management method for tunnel support construction according to claim 1, characterized in that, The steps for obtaining the defect-associated job ID sequence are as follows: Based on the tunnel support full-cycle construction information database, the drilling record field, hole cleaning record field and grouting record field are extracted, and the process labels, process sequence codes and pre- and post-constraints are marked. The parallel allowance flag and timeout processing flag are fixed, and the mapping relationship between process labels and process sequence codes is established to obtain the anchor bolt construction process sequence logic. According to the logic of the anchor bolt construction sequence, the abnormal signal of the target monitoring point ID is received, and the operation ID, timestamp, construction time, operation team, equipment number, material batch number and design parameters bound to the target monitoring point ID are retrieved from the tunnel support full-cycle construction information database. The operation ID is traced back in reverse order of timestamp and the positions of adjacent operations and the intervals between operations are recorded to generate a defect-related operation ID sequence.

4. The monitoring and management method for tunnel support construction according to claim 1, characterized in that, The steps for obtaining the quality problem traceability chain are as follows: Based on the defect-associated operation ID sequence, the operation IDs are compared with adjacent operations and cross-operation missing verification is performed according to the logic of the anchor bolt construction procedure. The construction time, operation team, equipment number, material batch number and design parameters bound to the operation ID are aggregated and organized into a traceable node chain according to the defect-associated operation ID sequence, forming a quality problem traceability chain.

5. The monitoring and management method for tunnel support construction according to claim 1, characterized in that, The steps for obtaining the multi-source subject-related quality problem frequency table are as follows: Based on the quality issue traceability chain, pairing keys are established according to the construction team name and the anchor bolt material supplier name. The number of occurrences of each pairing key is accumulated, and the number of operations of the construction team, the list of associated operation IDs, the first time stamp and the last time stamp are accumulated simultaneously. Duplicate pairing keys are merged and the consistency of fields is checked to generate a multi-source subject-related quality issue frequency table.

6. The monitoring and management method for tunnel support construction according to claim 1, characterized in that, The steps for obtaining the comprehensive responsibility result for construction quality are as follows: calculate the bilateral joint responsibility index based on the frequency table of quality problems associated with multiple sources.

7. The monitoring and management method for tunnel support construction according to claim 6, characterized in that, The steps for obtaining the comprehensive responsibility results for construction quality also include: sorting the bilateral joint responsibility index in descending order by construction team name and anchor bolt material supplier name, extracting the bilateral joint responsibility index, first timestamp, last timestamp and associated operation ID list for each pair, and forming the comprehensive responsibility results for construction quality.

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