Polyethylene buried gas pipeline tracer line construction quality informatization management system

Abstract

The invention relates to the technical field of gas pipeline construction, and discloses a polyethylene buried gas pipeline tracer line construction quality informatization management system. The system comprises a trace line feature extraction module, a topological graph construction module, a resource conflict analysis module, a quality node judgment module and a quality structure generation module. Wherein the feature extraction module obtains a detection signal and constructs an original feature sequence; the topological graph construction module establishes a feature point connection path based on the feature sequence and generates a feature topological graph; the resource conflict analysis module extracts resource allocation paths and screens conflict path combinations; the quality node judgment module collects quality evaluation labels and generates a construction quality label set; and the quality structure generation module counts the quality nodes associated with the labels, establishes an affiliation mapping structure and outputs a classification structure table. According to the system, informatization management of the construction quality of the tracer line is realized, and systematic control of the construction quality is assisted.

Description

Technical Field

[0001] This invention relates to the field of gas pipeline construction technology, specifically to an information management system for the construction quality of polyethylene buried gas pipeline tracer lines. Background Technology

[0002] In urban infrastructure construction, buried polyethylene gas pipelines are widely used due to their advantages such as corrosion resistance and good flexibility. Tracer wires, as a key auxiliary facility ensuring the later maintenance and inspection of pipelines, have their construction quality directly affecting the safety and maintainability of the pipeline throughout its entire life cycle. However, the management of tracer wire construction quality still faces many challenges. Traditional tracer line construction quality control relies heavily on manual inspections and experience-based judgment, resulting in low detection efficiency and high subjectivity. Complex geological conditions in construction areas, soil moisture, and interference from surrounding pipelines can easily distort tracer line detection signals. When manually identifying key feature points in the signal waveform, differences in experience often lead to missed or incorrect judgments. It is also difficult to accurately record the attribute parameters and location information of feature points, resulting in insufficient completeness and accuracy of the original feature data. In terms of construction resource management, there is a lack of systematic correlation analysis in the allocation of resources such as equipment scheduling and personnel distribution across different construction sections. During construction, resource allocation paths for each section are often recorded independently, making it difficult to intuitively present the relationships between paths. When multiple paths have overlapping nodes, it can easily lead to problems such as equipment conflicts and personnel redundancy. Due to the lack of an effective conflict identification mechanism, construction personnel often only make adjustments after problems occur, which not only affects the construction progress but may also lead to quality problems such as deviations in the placement of tracer lines and loose connections due to resource misallocation. In the quality assessment phase, existing methods struggle to establish a precise correlation between the construction quality of the tracer line and specific path nodes. Quality assessment labels are mostly concentrated on the overall construction section, lacking targeted labeling of end nodes, making it difficult to trace the source of quality problems. When quality disputes arise, it is impossible to quickly locate the resource allocation path and characteristic nodes corresponding to the problem, making it difficult to clarify the division of responsibilities and the direction of rectification, thus hindering the formation of a closed loop for quality control. Construction quality data is scattered across various record forms, lacking structured integration and analysis, making it difficult to construct a comprehensive quality classification system. Managers cannot grasp the distribution of each quality node and the paths of related conflicts through intuitive structural tables, resulting in a lack of data support for the formulation of quality control strategies and hindering refined management of construction quality. These problems make it difficult to effectively guarantee the stability and reliability of the construction quality of polyethylene buried gas pipeline tracer lines. Summary of the Invention

[0003] The purpose of this invention is to provide an information management system for the construction quality of polyethylene buried gas pipeline tracer lines, so as to solve the problems mentioned in the background art.

[0004] To achieve the above objectives, the present invention provides an information management system for the construction quality of polyethylene buried gas pipeline tracer lines, the system comprising: The tracer line feature extraction module acquires the tracer line detection signal in the construction area, identifies key feature points in the signal waveform, extracts the attribute parameters of the feature points and records their position information in the signal sequence, and constructs the original feature sequence of the tracer line. The topology map construction module, based on the original feature sequence of the tracer line, hierarchically classifies and sorts the feature points, establishes the feature point connection path from the root node to the leaf node according to the sorting result, collects the association relationship and direction attribute of all nodes in the path, and generates the tracer line feature topology map. The resource conflict analysis module extracts resource allocation paths for different construction sections based on the tracer line feature topology map, compares overlapping nodes between paths and counts the distribution density of terminal nodes, filters path combinations with resource conflicts, and outputs a set of construction resource conflict paths. The quality node determination module collects the quality assessment tags corresponding to the end nodes in the set of construction resource conflict paths, sorts them according to the frequency of tag occurrence, matches the end tags of the paths, and generates a set of construction quality tags. The quality structure generation module, based on the set of construction quality labels, counts the quality nodes of the topology graph associated with each label, assigns conflicting paths to the corresponding quality nodes, establishes the attribution mapping structure between quality nodes and conflicting paths, and outputs a construction quality classification structure table.

[0005] Preferably, the tracer line feature extraction module includes: The feature point recognition submodule acquires the tracer line detection signal of the construction area, segments the signal waveform into independent feature segments, extracts the waveform parameter set of each feature segment, records the temporal position of each parameter in the original signal, identifies the relationship between the first occurrence position of key feature points in the parameter sequence and the number of feature segments, groups them according to the construction area, and obtains the feature point location distribution results. The original sequence construction submodule, based on the distribution results of the feature points, extracts the waveform segments corresponding to the key feature points in the original signal, cuts the waveform according to the position range of the feature points in the signal sequence, constructs a set of feature segments according to the position of each feature point in the cut waveform, and reassembles them in combination with the construction section to which the feature points belong to obtain the original set of key feature points; The feature sequence generation submodule calculates the frequency of occurrence of all key feature points based on the original fragment set of key feature points, arranges the feature points in the temporal order of the original signal, performs temporal reassembly processing on the feature fragment set, splices the original fragments of multiple feature points in the same construction section into a continuous sequence according to the first occurrence time, calculates the feature sequence integration weight value, and classifies and integrates the weight results corresponding to each construction section to obtain the original feature sequence of the tracer line.

[0006] Preferably, the topology map construction module includes: The hierarchical sorting submodule, based on the original feature sequence of the tracer line and combined with the hierarchical attribute values ​​of the feature points, sorts all feature points according to hierarchical priority, reconstructs the feature point sequence in the order from the root node to the leaf node, establishes a hierarchical rearrangement index table, and obtains the feature point sorting index value. The path generation submodule extracts adjacent node pairs from the rearranged sequence of feature points based on the sorted index value of the feature points, labels the connection direction attribute for each pair of adjacent nodes, calculates the connection strength value of the feature path, integrates the directional association information between all nodes in the path, integrates the node connection relationship, and generates a tracer line feature topology map. The node relationship extraction submodule, based on the tracer line feature topology map, collects the node identifiers and adjacent node relationship types in all connected edges, constructs a node relationship mapping table based on the adjacent node relationships, stores the upstream and downstream association attributes between each feature point, and obtains the tracer line feature topology map structure.

[0007] Preferably, the resource conflict analysis module includes: The path extraction submodule, based on the tracer line feature topology map structure, collects the resource allocation path node sequence of different construction sections, establishes the mapping relationship between construction section identifiers and node sequences, records the length attribute value of each path, and obtains the construction resource path node sequence. The overlap analysis submodule selects any two resource path node sequences based on the construction resource path node sequence, performs node set intersection operation, extracts all end node identifiers in the intersection, counts the number of times the node appears in different paths, calculates the path end deviation value, compares it with a preset conflict threshold, filters path combinations with deviation exceeding the threshold, and establishes a resource conflict node set. The conflict path integration submodule, based on the resource conflict node set, queries the original construction section identifier according to the path identifier associated with the conflict node, integrates the construction section identifier and conflict node information, establishes a path conflict relationship table, and generates a construction resource conflict path set.

[0008] Preferably, the quality node determination module includes: The tag acquisition submodule, based on the end nodes in the set of construction resource conflict paths, obtains the quality assessment tag item corresponding to each end node, establishes an index mapping between construction section paths and end quality tags, and generates path end quality tag groups; The frequency sorting submodule, based on the path end quality label group, counts the number of repetitions of all quality evaluation labels, records the frequency of each label in the conflict path set, sorts them from high to low according to the frequency value, and obtains the sorted quality label sequence. The attribution matching submodule performs matching judgment on the label items corresponding to the end nodes in the construction section path according to the sorted quality label sequence, selects the label item with the highest sorted position in each path as the quality attribution category of that path, integrates the attribution labels of all construction section paths, and generates a construction quality label set.

[0009] Preferably, the mass structure generation module includes: The node association submodule extracts the topology map node identifier corresponding to each quality label based on the construction quality label set, records the number of conflict paths associated with each node, determines the matching index between the quality label and the topology node, and obtains the node identifier to which the label belongs. The path division submodule, based on the node identifier of the label, divides the corresponding construction conflict paths to each topology node according to the quality label as the classification basis, establishes a two-way mapping between conflict path identifiers and node identifiers, extracts the path identifier list to which each node belongs, and obtains the number of paths to which each node belongs. The structure output submodule integrates the topology quality nodes and their subordinate conflict path identifiers according to the number of node paths, outputs the quality node index, associated quality tags and total number of paths, determines the affiliation relationship between nodes and conflict paths, and generates a construction quality classification structure table.

[0010] Preferably, the system further includes: The construction environment monitoring module collects environmental parameters in the polyethylene pipeline burial area in real time, identifies soil conditions and groundwater level change characteristics, extracts environmental parameter fluctuation characteristic points, and constructs a construction environment characteristic sequence. The dynamic constraint evaluation module, based on the construction environment feature sequence and the tracer line original feature sequence, compares the spatiotemporal distribution of environmental fluctuation feature points and tracer line feature points, identifies environmental interference periods and abnormal feature point areas, and generates a set of construction environment constraint parameters.

[0011] Preferably, the construction environment monitoring module includes: The environmental parameter acquisition submodule acquires soil moisture distribution data and groundwater flow velocity data in the pipeline burial area, segments the parameter sequence for continuous monitoring periods, extracts the peak points and rate of change features of parameters in each period, records the position of feature points in spatiotemporal coordinates, and obtains the distribution of environmental parameter feature points. The interference feature construction submodule identifies the duration and impact range of parameter mutation points based on the distribution of environmental parameter feature points, clusters the feature points in combination with spatiotemporal coordinates, calculates the interference intensity value of each group of feature points, and generates a construction environment feature sequence.

[0012] Preferably, the dynamic constraint evaluation module includes: The feature matching submodule compares the interference time period feature points in the construction environment feature sequence with the corresponding time period feature points in the original feature sequence of the tracer line, extracts the set of feature points with overlapping spatiotemporal coordinates, and calculates the influence intensity value of environmental interference on the tracer line features. The constraint parameter generation submodule, based on the influence intensity value, calibrates the abnormal regions of the tracer line characteristics and their corresponding construction periods, and, combined with the resource allocation information in the construction resource conflict path set, generates a set of construction environment constraint parameters containing interference periods and abnormal region identifiers.

[0013] Preferably, the mass structure generation module is further used for: The construction environment constraint parameter set and the construction quality classification structure table are integrated. Environmental interference source identifiers are marked in the topology quality nodes. Environmental constraint parameters are mapped to the quality assessment labels of the corresponding conflict paths. The construction quality classification structure table is then updated to include environmental interference factors.

[0014] Compared with the prior art, the beneficial effects of the present invention are: This system provides a systematic solution for the construction quality control of polyethylene buried gas pipeline tracer lines through the collaborative operation of multiple modules. The tracer line feature extraction module accurately acquires detection signals and identifies key feature points, fully records the attribute parameters and location information of the feature points, and constructs an original feature sequence that provides a reliable data foundation for subsequent analysis. This avoids data deviations caused by subjective factors in traditional manual identification, making the collection of feature information more objective and comprehensive.

[0015] The topology map construction module hierarchically categorizes and sorts feature points based on the original feature sequence. The established feature point connection paths clearly present the correlation and directional attributes between each feature point. The generated topology map transforms scattered feature information into a structured relational network. This visualized map format allows managers to intuitively grasp the overall distribution and internal connections of tracer line features, breaking the limitations of isolated information in traditional data records and providing an effective data framework for subsequent resource analysis and quality assessment.

[0016] The resource conflict analysis module extracts resource allocation paths from different construction sections based on the topology map. By comparing the distribution density of overlapping nodes and terminal nodes between paths, it can accurately identify path combinations with resource conflicts. This process does not rely on human experience; instead, it automatically identifies conflicting points in resource allocation through a data-driven approach. This allows construction personnel to promptly identify potential conflicts in equipment scheduling and personnel allocation, making adjustments and optimizations in advance. This avoids the adverse effects of misallocated resources on construction quality and ensures the orderly progress of the construction process.

[0017] The quality node determination module collects quality assessment tags for the end nodes of resource conflict paths. By sorting and matching the end-path tags according to their frequency of occurrence, the generated set of construction quality tags allows quality assessments to focus more on key nodes. Compared to traditional methods of labeling entire sections, this node-based tagging approach makes quality issues more clearly identified, enabling managers to quickly locate potential quality problems and providing clear objectives for targeted rectification, thus making quality control more precise.

[0018] The quality structure generation module statistically analyzes the quality nodes in the topological graph associated with each label, assigning conflict paths to corresponding quality nodes. This established attribution mapping structure forms a clearly structured construction quality classification table. This table integrates the relationships between quality labels, conflict paths, and quality nodes, systematically consolidating scattered quality data. Managers can comprehensively understand the problem distribution and associated paths of each quality node through the table, providing an intuitive reference for the overall assessment and control strategy formulation of construction quality. This promotes the transformation of construction quality control from experience-driven to data-driven, improving the overall effectiveness of tracer line construction quality control. Attached Figure Description

[0019] Figure 1 The flowchart is a process for the polyethylene buried gas pipeline tracer line construction quality information management system described in this invention. Figure 2 This is a schematic diagram illustrating the working principle of the tracer line feature extraction module. Figure 3 This is a schematic diagram illustrating the working principle of the quality node determination module. Figure 4 This is a schematic diagram illustrating the working principle of the construction environment monitoring and dynamic constraint assessment module. Detailed Implementation

[0020] 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.

[0021] Please see Figure 1 This invention provides an information management system for the construction quality of polyethylene buried gas pipeline tracer lines, the system comprising: The tracer line detection signal of the construction area is acquired, key feature points in the signal waveform are identified and attribute parameters are extracted to construct the original feature sequence of the tracer line. Based on this sequence, the feature points are hierarchically classified and sorted, and feature point connection paths from the root node to the leaf node are established to generate a tracer line feature topology map. Subsequently, the resource allocation paths of different construction sections are analyzed, and path combinations with resource conflicts are screened. A set of construction quality labels is generated based on the quality assessment labels of the terminal nodes of conflicting paths. Finally, an attribution mapping structure between quality nodes and conflicting paths is established, and a construction quality classification structure table is output.

[0022] Example 1: See Figure 2 The tracer feature extraction module processes the tracer detection signal by digitally analyzing the received raw detection signal waveform and identifying peak and trough positions based on the waveform amplitude variation. These positions form the initial segmentation boundary, dividing the continuous waveform into discrete feature segment units. Within each feature segment, five waveform parameters are extracted, including maximum amplitude, average energy, duration, rising edge slope, and falling edge slope. The parameter acquisition process simultaneously records the start and end coordinates of these parameters on the complete signal timeline.

[0023] Key feature point identification is based on preset amplitude and slope thresholds. When a specific feature segment simultaneously meets the conditions of amplitude exceeding the set threshold and rising slope exceeding the critical value, it is marked as a positive pulse feature point; when a feature segment meets the conditions of valley depth exceeding the standard and falling slope reaching the negative threshold, it is marked as a negative abrupt change feature point. All identified key feature points record three pieces of information: the point's index number in the original parameter sequence, the number of its corresponding feature segment, and the absolute timestamp of its first appearance. This information is categorized and grouped according to the physical construction section number of the pipeline, forming a matrix-structured location distribution result data.

[0024] The original sequence construction process involves the following steps: Based on the time-series coordinates recorded from the location distribution results, accurately locate the waveform interval corresponding to each key feature point in the original signal. A sliding time window technique is used to extract waveform segments 50 milliseconds before and after each feature point. Waveform segmentation employs a dynamic boundary localization algorithm, selecting different boundary recognition strategies based on the feature point type: zero-crossing detection segmentation is used for pulse feature points, and envelope inflection point segmentation is used for abrupt change feature points. The segmented sets are stored in groups according to construction sections, and segment units within the same section are logically associated based on their first occurrence time.

[0025] Feature sequence generation and temporal reassembly calculation: First, the total occurrence frequency of different types of feature points within each construction section is counted, and the frequency ratio of pulse feature points to abrupt change feature points in that section is calculated. The sequence reassembly weight coefficient is determined based on the frequency ratio. Then, the original fragments of all feature points in that section are sorted by temporal position, arranged in ascending order of time axis coordinates. Whether to merge consecutive feature point fragments of the same type is determined based on the weight coefficient: when the weight coefficient exceeds the merging threshold, waveform superposition is performed on fragments of the same type with an interval of less than 100 milliseconds; otherwise, the original separated state is retained. Finally, each construction section outputs a set of feature point waveform sequences arranged in the actual occurrence time order. Each element in the sequence contains a feature point type code, a waveform parameter vector, and a temporal coordinate value. The feature sequence set of all sections constitutes the original feature sequence of the tracer line.

[0026] The specific method for processing feature sequences during the topology map construction phase is as follows: The hierarchical sorting submodule loads the feature point data from the original feature sequence and assigns a hierarchical attribute value to each feature point. This value is calculated based on the physical location of the feature point in the pipeline network: the main pipeline connection point is set as the highest level (L0), the tee node as the secondary level (L1), and the branch end as the last level (L2). All feature points are arranged in reverse order of their hierarchical values, and nodes at the same level are further sorted according to their original time-series coordinates to form a linear sequence from the main pipeline node to the branch end. During the sorting process, a hierarchical rearrangement index table is generated, recording the mapping relationship between the old and new sequence numbers of each feature point and its hierarchical identifier code.

[0027] The path generation submodule scans the sorted feature point sequence and identifies the spatial relationships between adjacent nodes. A connection path is automatically established for each pair of adjacent nodes, with the path direction attribute determined by the relative spatial positions of the two nodes. When the distance difference between the latitude and longitude coordinates of a subsequent node and the preceding node exceeds the positioning tolerance, the spatial deviation direction is marked. The connection strength calculation formula considers three factors: the actual physical distance between nodes, the density of feature points in the path, and the signal strength attenuation gradient. Path attribute data is organized in a tree structure, with the main pipeline node as the root node, the end of each branch as a leaf node, and intermediate nodes establishing parent-child relationships based on hierarchy. The topology is stored in the form of an adjacency list, with each node entry containing a pointer to its associated parent node, a list of child nodes, and a set of connection edge attributes.

[0028] The node relationship extraction process parses the topological adjacency list data: All connecting edges in the graph are traversed and collected, recording the source node ID and target node ID of each edge, as well as the direction annotation data in the edge attributes. For each feature point node, a doubly linked relationship table is established: the upstream association table records all possible path source points reaching the node, and the downstream association table records all reachable end nodes of the node. The upstream and downstream relationship tables are stored using a cross-linked list structure, with each node entry containing a counter for the number of upstream input paths, a counter for the number of downstream output paths, and a list of pointers to upstream and downstream nodes. This data structure fully represents the transmission path relationship of the tracer line feature points in the pipeline network, forming a traceable topological graph structure system.

[0029] Example 2: See Figure 3 The resource conflict analysis module's complete process for identifying resource path conflicts comprises three technical stages. The path extraction submodule loads the tracer line feature topology map structure data and parses the node path information corresponding to the identifiers of each construction section. The resource allocation path for each construction section is parsed into an ordered sequence of nodes, where each node contains a unique identifier and spatial coordinate data. The module establishes a hash mapping table to store the correspondence between construction section codes and their corresponding node sequences, while also recording the path length value, which is obtained by accumulating the Euclidean distance between adjacent nodes in the sequence. The node sequence data is stored in a four-tuple format: [section identifier, start node, end node, path length], forming a construction resource path node sequence database.

[0030] The overlap analysis phase employs a multi-path cross-detection algorithm. The system randomly selects two sets of node sequence data from different construction sections in the database and performs a set intersection operation. The principle for extracting the intersection result set is: node A is included when it exists in both path sequences and is located at the end of the sequence (position index greater than 70% of the sequence length). The cross-path difference is calculated for each end node. ; Where η represents the offset of the end node position (unit: meters), and L is the path logarithm statistical period. This represents the spatial coordinate vector of a node in the first path. This represents the spatial coordinate vector of the node in the second path. When the value of η exceeds a preset threshold θ (θ is dynamically configured in the range of 0.5-1.2 meters depending on the pipe type), it is determined that there is a resource conflict between the nodes. The algorithm traverses all possible path combinations (totaling...). (where n is the number of construction sections), the accumulated conflict nodes form a resource conflict node set, and each entry in the set records [conflict node ID, associated path pair, η value].

[0031] The conflict path integration process initiates the relationship mapping engine. Based on the node identifiers in the conflict node set, it retrieves the original path definition data from the topology graph in reverse. Using bidirectional pointers, it obtains all construction section identifiers associated with the node. The integration process uses a tree structure to store conflict relationships: the root node is the conflict node ID, and the child nodes are a list of associated construction section identifiers. Each construction section node extends by storing three additional pieces of information: a counter for the number of resource conflict triggers in that section, the timestamp of the last conflict, and a record of the maximum η value. The final path conflict relationship table is encoded in JSON-LD format and includes topological descriptions of conflict nodes, metadata about the resource allocation status of associated construction sections, and spatiotemporal coordinate index information, generating a complete database of construction resource conflict paths.

[0032] The quality node determination module initiates the quality tag processing pipeline. The tag acquisition submodule accesses the construction resource conflict path set database and extracts the identifier set of all conflict path end nodes. Through cross-database connection operations, it accesses the quality assessment tag library to obtain the quality parameters corresponding to each end node. The quality assessment tag contains three basic attributes: material compliance tag (stores material model, production batch, and test report number), construction process tag (records welding parameters, anti-corrosion treatment data, and pressure test results), and environmental adaptability tag (including soil corrosion coefficient and temperature difference adaptability level). The tag system establishes a three-axis tag group for each end node, forming a matrix-style path end quality tag group, whose data structure is: [node ID, material tag code, process tag code, environmental tag code].

[0033] The frequency statistics engine performs a comprehensive analysis of all tags. The system creates a temporary frequency statistics table with fields including [tag type, tag value, frequency of occurrence]. It scans all quality tag groups at the end of each path, incrementing a counter when the same tag value appears repeatedly in different nodes. After completing the global scan, the tags are sorted in descending order of frequency of occurrence, generating a sorted quality tag sequence: the sequence element structure is [sorting number, tag type, tag value, frequency value]. For tags with the same frequency value, an additional sorting rule based on tag type priority is applied: material tags have the highest priority, followed by process tags, and then environmental tags have the lowest priority.

[0034] The attribution matching operation dynamically associates tags with paths. The system loads the sorted quality tag sequence and construction section path data. For each construction section path, it obtains the triaxial tag group corresponding to its end node. This tag group is then matched against the sorted sequence: in the material tag dimension, the highest-ranking match is selected; if no match is found, the process tag dimension is used; finally, the environmental tag dimension is attempted. The matching result is recorded as a path quality attribution triple: [Path ID, Attribution Tag Type, Attribution Tag Value]. After all path matching is completed, the set of paths with the same attribution tag is aggregated, outputting a construction quality tag set. This set uses a fractal storage structure: the first dimension index is the tag type, the second dimension index is the tag value, and the third dimension stores the list of associated path IDs, along with an additional path quantity statistics field. Each path ID is associated with a pointer to a detailed entry in the original set of conflicting construction resource paths, forming a bidirectional traceable data link.

[0035] Example 3: The node association submodule of the quality structure generation module initiates the mapping process between topology map nodes and quality labels. The system loads the construction quality label set data and parses the attribute structure of each quality label item. The label attributes include a type identifier (material / process / environment), specific parameter values, and the number of associated paths. The module accesses the tracer line feature topology map database and performs node search based on label parameter values: for material labels, it matches the pipe specification attributes associated with the node; for process labels, it matches the process parameters in the node's construction record; for environment labels, it matches the environmental monitoring data of the node's burial area. Successfully matched nodes are marked as quality-assigned nodes, and the correspondence between their node IDs and label parameters is recorded.

[0036] The path partitioning submodule handles the topology assignment of conflicting paths. The system establishes a quality node-path association matrix, where row vectors represent nodes to which quality nodes belong and column vectors represent conflicting construction paths. The values ​​of the matrix elements are determined by the topological relationships between paths and nodes.

[0037] in: This represents the attribution value between path j and quality node i (1 for attribution, 0 for no attribution), where i is the quality node index and j is the construction conflict path number. Reachability path determination uses a depth-first search algorithm, traversing the topology graph starting from the quality node and recording the set of all reachable end nodes. When the end node ID of a conflicting path appears in this set, an attribution relationship is determined. The accumulated number of paths under each quality node is calculated by summing the rows of a matrix, forming a node path attribution statistics table.

[0038] The structure output submodule integrates quality classification data. The system reads the node path affiliation statistics table and generates a structured description entry for each quality node. Each entry contains three core pieces of information: basic node attributes (ID, spatial coordinates, level), details of associated quality labels (type, parameter value, confidence level), and a list of subordinate paths (set of path IDs, number of paths). The output processing uses a nested tree format: the root node is the quality classification structure identifier, first-level child nodes are branches for different label types, second-level child nodes are nodes with specific quality parameter values, and third-level nodes are instances of associated construction conflict paths. Each path instance includes a link to the original conflict analysis data, including metadata such as resource conflict type, location, and duration.

[0039] The environmental interference factor integration process expands the quality classification structure. The system loads the construction environmental constraint parameter set and parses the recorded interference time periods and abnormal area data. The spatiotemporal matching of environmental parameters and quality nodes adopts a four-dimensional spatial indexing algorithm: three spatial dimensions (longitude, latitude, and elevation) plus a time dimension constitute the query conditions. When the construction conflict path associated with a quality node overlaps with environmental interference records within the spatiotemporal range, the node is marked with an environmental impact factor identifier. The marking information includes the interference type code (such as groundwater level fluctuation / sudden change in soil pH), interference intensity level (level 1-5), and duration period (start and end timestamps). The final generated construction quality classification structure table adopts an extended JSONSchema format, adding an "environmentalFactors" array field to the original quality node description to store all associated environmental interference parameters.

[0040] The quality structure verification mechanism performs data consistency checks. The system performs triple verification on the generated classification structure table: topology connectivity verification ensures that each quality node has a reachable path to its subordinate paths; label consistency verification checks whether conflicting paths under the same quality node have compatible label parameters; and environmental correlation verification confirms that the marked interference period does indeed include the construction time window of the corresponding path. Anomalies generated during the verification process are written to the correction log, triggering the iterative optimization process of the structure table. The optimized final version of the construction quality classification structure table contains complete version control information, recording the content and timestamp of each correction, forming a traceable quality management data system.

[0041] A dynamic update and maintenance mechanism continuously tracks structural changes. When new construction monitoring data is input into the system, an update trigger initiates a recalculation process for the structural table. New conflict paths are assigned to existing quality nodes or create new nodes using an attribution matching algorithm; changes to environmental interference records trigger updates to the labels of associated nodes; corrections to quality label parameters propagate along the topology path to all relevant nodes. The system maintains version branch management, supports historical structural queries and difference comparisons, ensuring that the quality classification structure dynamically evolves with project progress while preserving a complete change trajectory. Each updated structural snapshot is accompanied by a digital signature and time authentication, forming an immutable chain of evidence for quality management.

[0042] Example 4: See Figure 4 The construction environment monitoring module collects environmental parameters of the polyethylene pipeline burial area through a distributed sensor network. In a specific engineering example, a gas pipeline project in a new urban area was divided into 8 construction sections, with 3 sets of environmental monitoring units deployed in each section. The monitoring units include soil moisture sensors, groundwater level gauges, and temperature probes, collecting raw data at 15-minute intervals. After preprocessing, the raw monitoring data received by the system forms structured environmental parameter records. The data format is shown in Table 1, which provides data from three of the sections.

[0043] Table 1: Environmental Monitoring Parameter Recording Table for Construction Section ; The environmental parameter acquisition submodule performs feature extraction on the raw monitoring data. The system employs a sliding time window analysis method, with a window width of 2 hours and a sliding step size of 15 minutes. Within each analysis window, three key characteristic values ​​are calculated: soil moisture change gradient (the sum of the absolute values ​​of the differences between adjacent sampling points), groundwater level fluctuation amplitude (the difference between the maximum and minimum values), and temperature coefficient of variation (the ratio of standard deviation to mean). When the soil moisture change gradient exceeds 5% / h or the groundwater level fluctuation amplitude is greater than 0.3m within a window, it is marked as a parameter abrupt change point. The system records the start time, duration, and spatial coordinates of the abrupt change points, forming a distribution map of environmental parameter characteristic points.

[0044] In a specific case within section S05, the system detected a sustained anomaly between 09:00 and 11:00 on June 12, 2023: soil moisture surged from 24.3% to 38.6%, while the groundwater level rose by 0.45m. Cross-validation with meteorological data confirmed that heavy rainfall occurred in the area during this period. The system recorded this anomaly as an environmental disturbance event, event number E2023061201, linking it to data from all monitoring equipment in section S05.

[0045] The interference feature construction submodule performs spatial clustering analysis on abnormal events. The system reads the distribution data of environmental parameter feature points and uses a density-based spatial clustering algorithm to group feature points within a 50-meter and 1-hour time range into the same interference group. For each interference group, three characteristic indicators are calculated: average interference intensity (weighted average of the rates of change of each parameter), radius of influence (maximum span of the spatial distribution of feature points), and total duration (time difference between the first and last feature points). In a certain engineering example, on June 15, 2023, section S07 detected three sets of related feature points, which, after clustering, were identified as the same groundwater flow anomaly event, with an influence radius of 82 meters and a duration of 4 hours and 15 minutes.

[0046] The dynamic constraint assessment module correlates environmental disturbance characteristics with construction activities in time and space. The system establishes a construction log database, recording daily work content, construction machinery, and personnel configuration information for each section. When a section conducts pipeline welding or backfilling work during an environmental disturbance period, the system automatically generates a construction environmental constraint alarm. In a real-world case, section S03 conducted pipeline pressure testing from 10:00 to 12:00 on June 18, 2023, and simultaneously detected an environmental disturbance with a 15% decrease in soil resistivity. The system generated constraint parameter entries, recording information such as the test pipe section number, disturbance type, and potential impact dimensions.

[0047] The generation process of environmental constraint parameters involves multi-source data fusion. The system integrates three types of key information: construction machinery operating status data (such as welding current stability and rammed earth machine vibration frequency), environmental monitoring anomaly indicators, and construction quality inspection results (such as X-ray flaw detection reports and airtightness test data). By establishing a spatiotemporal correlation model, the system outputs a set of constraint parameters with engineering guidance value. The constraint parameter records for section S02 of a certain project show that in an acidic environment with a soil pH value below 5.5, the weld qualification rate of pipe joints differs significantly from that under standard working conditions. Based on this, the system automatically adjusts the construction process parameter recommendations for this section.

[0048] The closed-loop feedback mechanism for construction environmental monitoring data and quality management is specifically manifested as follows: the system regularly generates environmental constraint impact analysis reports, summarizing the correlation between environmental disturbance events and corresponding construction quality data for each section. The reports use color coding to indicate risk levels: red indicates confirmed constraints with quality impacts, yellow indicates potential risks requiring continuous monitoring, and green indicates routine fluctuations with no significant impact. Based on the report content, project management personnel can dynamically adjust construction plans or take targeted protective measures to achieve controllable management of environmental factors.

[0049] Example 5: The feature matching submodule of the dynamic constraint evaluation module initiates the spatiotemporal correlation analysis process. The system synchronously loads the database of construction environment feature sequences and tracer line original feature sequences, creating a four-dimensional spatiotemporal index coordinate system. The index dimensions include longitude coordinates, latitude coordinates, elevation data, and precise timestamps. The feature point matching engine performs cross-sequence scanning operations, establishing a correlation when two conditions are met: the spatial coordinates of the environmental feature points and the embedding positions of the tracer line feature points deviate from each other by less than the positioning accuracy threshold, and the difference in their timestamps is within a preset synchronization tolerance window. Successfully matched feature point pairs generate feature correlation records, with the record structure containing four basic data items: environmental feature ID, tracer line feature ID, spatial offset, and time deviation value.

[0050] The impact intensity calculation is based on parameter change analysis of feature point pairs. For each successfully matched feature point pair, the system extracts the soil moisture change rate and groundwater flow velocity increment value from the environmental feature point records, and simultaneously acquires the signal fluctuation amplitude and frequency variation coefficient of the corresponding tracer line feature points. The core data processing mechanism uses a differential algorithm: comparing the tracer line parameter change rates of the same location points before and after the occurrence of environmental disturbance, and calculating the correlation coefficient matrix between parameter changes and environmental disturbance intensity. This matrix generates a numerical impact intensity value, dividing it into five impact level intervals: a change rate below 5% of the baseline value is marked as Level I impact; a change rate of 5%-10% is marked as Level II; 10%-20% is marked as Level III; 20%-30% is marked as Level IV; and exceeding 30% is marked as Level V impact. The intensity value calculation results are written to the extended field of the feature association record.

[0051] The constraint parameter generation submodule performs anomaly region labeling. The system iterates through all feature-related records, filtering records with an impact intensity of Level III or higher. The spatial clustering engine divides regions based on the set of location coordinates in the records: high-impact feature points with a distance of less than 50 meters are clustered into anomaly region units. Each anomaly region generates a list of polygon boundary coordinates and labels the core impact intensity value, taking the weighted average of the impact intensity of all feature points within the region. For time dimension processing, a construction period mapping is established: the earliest and latest feature point timestamps within the anomaly region are extracted, and a 15-minute buffer is extended before and after each time period to form an anomaly period window with labeled start and end times.

[0052] The association mapping mechanism for construction resource conflict paths establishes connections through topological nodes. The system retrieves tracer feature points within the abnormal area and uses these feature points to reverse-locate the resource conflict paths in the topological map. The mapping process employs a tree-structured search algorithm: starting from the feature point, it traces upwards along the topological connection path until the path is found to be recorded in the set of construction resource conflict paths. Successfully associated conflict paths add environmental constraint markers to the original conflict records, and the record structure is expanded to include three new fields: associated abnormal area code, highest impact intensity level, and abnormal time period index number.

[0053] The final integration of environmental constraint parameters adopts a hierarchical data structure. The top layer is the anomaly area summary layer, storing the set of polygon vertex coordinates and the heat map of influence intensity distribution; the middle layer is the construction period mapping layer, recording multiple anomaly time periods corresponding to the area and their intensity fluctuation curves; the bottom layer is the conflict path association layer, listing a list of all construction resource conflict path identifiers affected by the environmental constraint. The data output is a set of construction environmental constraint parameters, encoded in lightweight JSON-LD format, containing machine-readable spatiotemporal semantic annotations and resource conflict path reference pointers. This parameter set is synchronized with the quality management system via a RESTful interface, and each update generates a version hash value as the basis for data integrity verification.

[0054] The dynamic update mechanism for constraint parameters responds to real-time monitoring data streams. The system sets environmental feature sequence change triggers; when new environmental monitoring data triggers feature matching conditions, a dynamic expansion procedure for abnormal areas is initiated: existing abnormal areas have their boundary ranges recalculated, and new high-impact points are added to form independent regional units. The list of associated conflicting paths is adjusted through an incremental update algorithm; newly added paths are added to the association list, and paths that have been decoupled are moved to the historical record database. Each update operation generates a change log, recording key metadata such as the morphological evolution of abnormal areas, trends in impact intensity, and changes in the number of associated paths. The system retains snapshots of historical constraint parameter sets, supporting rollback along a timeline to view the environmental constraint status at any construction stage. All version data is accompanied by digital timestamps and blockchain-based evidence, forming an undeniable chain of responsibility for environmental impact.

[0055] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0056] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An information management system for the construction quality of polyethylene buried gas pipeline tracer lines, characterized in that, The system includes: The tracer line feature extraction module acquires the tracer line detection signal in the construction area, identifies key feature points in the signal waveform, extracts the attribute parameters of the feature points and records their position information in the signal sequence, and constructs the original feature sequence of the tracer line. The topology map construction module, based on the original feature sequence of the tracer line, hierarchically classifies and sorts the feature points, establishes the feature point connection path from the root node to the leaf node according to the sorting result, collects the association relationship and direction attribute of all nodes in the path, and generates the tracer line feature topology map. The resource conflict analysis module extracts resource allocation paths for different construction sections based on the tracer line feature topology map, compares overlapping nodes between paths and counts the distribution density of terminal nodes, filters path combinations with resource conflicts, and outputs a set of construction resource conflict paths. The quality node determination module collects the quality assessment tags corresponding to the end nodes in the set of construction resource conflict paths, sorts them according to the frequency of tag occurrence, matches the end tags of the paths, and generates a set of construction quality tags. The quality structure generation module, based on the set of construction quality labels, counts the quality nodes of the topology graph associated with each label, assigns conflicting paths to the corresponding quality nodes, establishes the attribution mapping structure between quality nodes and conflicting paths, and outputs a construction quality classification structure table.

2. The information management system for construction quality of polyethylene buried gas pipeline tracer wires according to claim 1, characterized in that, The tracer line feature extraction module includes: The feature point recognition submodule acquires the tracer line detection signal of the construction area, segments the signal waveform into independent feature segments, extracts the waveform parameter set of each feature segment, records the temporal position of each parameter in the original signal, identifies the relationship between the first occurrence position of key feature points in the parameter sequence and the number of feature segments, groups them according to the construction area, and obtains the feature point location distribution results. The original sequence construction submodule, based on the distribution results of the feature points, extracts the waveform segments corresponding to the key feature points in the original signal, cuts the waveform according to the position range of the feature points in the signal sequence, constructs a set of feature segments according to the position of each feature point in the cut waveform, and reassembles them in combination with the construction section to which the feature points belong to obtain the original set of key feature points; The feature sequence generation submodule calculates the frequency of occurrence of all key feature points based on the original fragment set of key feature points, arranges the feature points in the temporal order of the original signal, performs temporal reassembly processing on the feature fragment set, splices the original fragments of multiple feature points in the same construction section into a continuous sequence according to the first occurrence time, calculates the feature sequence integration weight value, and classifies and integrates the weight results corresponding to each construction section to obtain the original feature sequence of the tracer line.

3. The information management system for construction quality of polyethylene buried gas pipeline tracer lines according to claim 1, characterized in that, The topology map construction module includes: The hierarchical sorting submodule, based on the original feature sequence of the tracer line and combined with the hierarchical attribute values ​​of the feature points, sorts all feature points according to hierarchical priority, reconstructs the feature point sequence in the order from the root node to the leaf node, establishes a hierarchical rearrangement index table, and obtains the feature point sorting index value. The path generation submodule extracts adjacent node pairs from the rearranged sequence of feature points based on the sorted index value of the feature points, labels the connection direction attribute for each pair of adjacent nodes, calculates the connection strength value of the feature path, integrates the directional association information between all nodes in the path, integrates the node connection relationship, and generates a tracer line feature topology map. The node relationship extraction submodule, based on the tracer line feature topology map, collects the node identifiers and adjacent node relationship types in all connected edges, constructs a node relationship mapping table based on the adjacent node relationships, stores the upstream and downstream association attributes between each feature point, and obtains the tracer line feature topology map structure.

4. The information management system for construction quality of polyethylene buried gas pipeline tracer wires according to claim 1, characterized in that, The resource conflict analysis module includes: The path extraction submodule, based on the tracer line feature topology map structure, collects the resource allocation path node sequence of different construction sections, establishes the mapping relationship between construction section identifiers and node sequences, records the length attribute value of each path, and obtains the construction resource path node sequence. The overlap analysis submodule selects any two resource path node sequences based on the construction resource path node sequence, performs node set intersection operation, extracts all end node identifiers in the intersection, counts the number of times the node appears in different paths, calculates the path end deviation value, compares it with a preset conflict threshold, filters path combinations with deviation exceeding the threshold, and establishes a resource conflict node set. The conflict path integration submodule, based on the resource conflict node set, queries the original construction section identifier according to the path identifier associated with the conflict node, integrates the construction section identifier and conflict node information, establishes a path conflict relationship table, and generates a construction resource conflict path set.

5. The information management system for construction quality of polyethylene buried gas pipeline tracer lines according to claim 1, characterized in that, The quality node determination module includes: The tag acquisition submodule, based on the end nodes in the set of construction resource conflict paths, obtains the quality assessment tag item corresponding to each end node, establishes an index mapping between construction section paths and end quality tags, and generates path end quality tag groups; The frequency sorting submodule, based on the path end quality label group, counts the number of repetitions of all quality evaluation labels, records the frequency of each label in the conflict path set, sorts them from high to low according to the frequency value, and obtains the sorted quality label sequence. The attribution matching submodule performs matching judgment on the label items corresponding to the end nodes in the construction section path according to the sorted quality label sequence, selects the label item with the highest sorted position in each path as the quality attribution category of that path, integrates the attribution labels of all construction section paths, and generates a construction quality label set.

6. The information management system for construction quality of polyethylene buried gas pipeline tracer wires according to claim 1, characterized in that, The mass structure generation module includes: The node association submodule extracts the topology map node identifier corresponding to each quality label based on the construction quality label set, records the number of conflict paths associated with each node, determines the matching index between the quality label and the topology node, and obtains the node identifier to which the label belongs. The path division submodule, based on the node identifier of the label, divides the corresponding construction conflict paths to each topology node according to the quality label as the classification basis, establishes a two-way mapping between conflict path identifiers and node identifiers, extracts the path identifier list to which each node belongs, and obtains the number of paths to which each node belongs. The structure output submodule integrates the topology quality nodes and their subordinate conflict path identifiers according to the number of node paths, outputs the quality node index, associated quality tags and total number of paths, determines the affiliation relationship between nodes and conflict paths, and generates a construction quality classification structure table.

7. The information management system for construction quality of polyethylene buried gas pipeline tracer lines according to claim 1, characterized in that, Also includes: The construction environment monitoring module collects environmental parameters in the polyethylene pipeline burial area in real time, identifies soil conditions and groundwater level change characteristics, extracts environmental parameter fluctuation characteristic points, and constructs a construction environment characteristic sequence. The dynamic constraint evaluation module, based on the construction environment feature sequence and the tracer line original feature sequence, compares the spatiotemporal distribution of environmental fluctuation feature points and tracer line feature points, identifies environmental interference periods and abnormal feature point areas, and generates a set of construction environment constraint parameters.

8. The information management system for construction quality of polyethylene buried gas pipeline tracer wires according to claim 7, characterized in that, The construction environment monitoring module includes: The environmental parameter acquisition submodule acquires soil moisture distribution data and groundwater flow velocity data in the pipeline burial area, segments the parameter sequence for continuous monitoring periods, extracts the peak points and rate of change features of parameters in each period, records the position of feature points in spatiotemporal coordinates, and obtains the distribution of environmental parameter feature points. The interference feature construction submodule identifies the duration and impact range of parameter mutation points based on the distribution of environmental parameter feature points, clusters the feature points in combination with spatiotemporal coordinates, calculates the interference intensity value of each group of feature points, and generates a construction environment feature sequence.

9. The information management system for construction quality of polyethylene buried gas pipeline tracer lines according to claim 7, characterized in that, The dynamic constraint evaluation module includes: The feature matching submodule compares the interference time period feature points in the construction environment feature sequence with the corresponding time period feature points in the original feature sequence of the tracer line, extracts the set of feature points with overlapping spatiotemporal coordinates, and calculates the influence intensity value of environmental interference on the tracer line features. The constraint parameter generation submodule, based on the influence intensity value, calibrates the abnormal regions of the tracer line characteristics and their corresponding construction periods, and, combined with the resource allocation information in the construction resource conflict path set, generates a set of construction environment constraint parameters containing interference periods and abnormal region identifiers.

10. The information management system for construction quality of polyethylene buried gas pipeline tracer wires according to claim 9, characterized in that, The mass structure generation module is also used for: The construction environment constraint parameter set and the construction quality classification structure table are integrated. Environmental interference source identifiers are marked in the topology quality nodes. Environmental constraint parameters are mapped to the quality assessment labels of the corresponding conflict paths. The construction quality classification structure table is then updated to include environmental interference factors.

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