Bridge swivel visual monitoring method and system based on BIM

Abstract

This invention provides a BIM-based visual monitoring method and system for bridge rotation. It acquires structural deformation monitoring data from various monitoring points during the bridge rotation process in real time, retrieves a pre-constructed full-element BIM model of the corresponding bridge, establishes a unique mapping relationship between each component and the corresponding time-period structural deformation monitoring data, obtains a component-monitoring data mapping relationship set, extracts the preset geometric boundaries and inherent attribute entries of the corresponding components in the full-element BIM model of the bridge, locates abnormal collected values ​​in the structural deformation monitoring data and performs calibration processing, obtains a calibrated set of component deformation collected values, matches them to the corresponding component attribute configuration nodes in the full-element BIM model of the bridge, synchronously adjusts the spatial connection relationship between components according to the change amplitude of the calibrated component deformation collected values, obtains an iteratively updated bridge BIM model, extracts a dynamic visualization carrier, and generates dynamic visual monitoring results of the bridge rotation process. This invention improves the intuitiveness and reliability of rotation monitoring.

Description

Technical Field

[0001] This invention relates to the field of data processing, and more specifically, to a BIM-based method and system for visual monitoring of bridge rotation. Background Technology

[0002] With the development of bridge construction technology, real-time monitoring and visualization of bridge structural status can provide a basis for the safe progress of bridge rotation construction. Currently, monitoring points are typically set up on the bridge to obtain deformation data, while a general BIM model is used as the visualization basis. In existing technologies, the binding of monitoring data and the BIM model relies on fixed, preset correspondences between monitoring points and components, which cannot adapt to the dynamic displacement of components during the rotation process. This easily leads to spatiotemporal misalignment between data and components, resulting in insufficient data matching accuracy. It also easily leads to misjudgment or omission of abnormal data, affecting the accuracy of deformation data. In addition, existing technologies do not consider the changes in the connection state between components simultaneously, making it impossible for the BIM model to accurately reflect the overall structural state of the bridge during the rotation process. This results in a deviation between the visualized monitoring results and the actual rotation state, making it difficult to provide reliable support for the safe progress of bridge rotation construction. Summary of the Invention

[0003] This invention provides a BIM-based method and system for visual monitoring of bridge rotation.

[0004] In a first aspect, embodiments of the present invention provide a BIM-based visual monitoring method for bridge rotation, comprising: acquiring in real time structural deformation monitoring data at each monitoring point during bridge rotation, and retrieving a pre-constructed corresponding full-element BIM model of the bridge, wherein the structural deformation monitoring data includes the point deformation collection values ​​at each time period of bridge rotation, and the full-element BIM model of the bridge includes the spatial location codes, preset geometric boundaries, and inherent attribute entries of each component of the bridge; based on the spatial location codes of each component in the full-element BIM model of the bridge, mapping and associating the structural deformation monitoring data with the corresponding components one by one, establishing a unique correspondence mapping relationship between each component and the structural deformation monitoring data at the corresponding time period, and obtaining a component-monitoring data mapping relationship set; and based on the component-monitoring data... The mapping relationship set is used to extract the preset geometric boundaries and inherent attribute entries of the corresponding components in the full-element BIM model of the bridge. Using the preset geometric boundaries as a reference, abnormal values ​​in the structural deformation monitoring data are located and calibrated to obtain a calibrated set of component deformation data. This calibrated set of component deformation data is then matched to the corresponding component attribute configuration nodes in the full-element BIM model of the bridge. The spatial connection relationships between components are adjusted synchronously according to the change amplitude of the calibrated component deformation data, resulting in an iteratively updated bridge BIM model. Based on the iteratively updated bridge BIM model, the deformation degree, spatial posture, and connection status between components of the corresponding components during the bridge rotation process are extracted and integrated to obtain a dynamic visualization carrier, generating dynamic visual monitoring results of the bridge rotation process.

[0005] Secondly, embodiments of the present invention provide a computer system, including: a memory storing a computer program; and a processor for loading the computer program to implement the above-mentioned BIM-based bridge rotation visual monitoring method.

[0006] This invention deeply binds a customized full-element BIM model of the bridge with real-time monitoring data, constructing a unique mapping relationship based on the characteristics of dynamic displacement of components during the rotation process. This effectively solves the problem of spatiotemporal misalignment between monitoring data and components in rotation scenarios, improving the accuracy of data-component matching. Simultaneously, it calibrates abnormal collected values ​​based on the pre-defined geometric boundaries of the components themselves, replacing general outlier filtering rules, reducing the probability of misjudging abnormal data, and improving the accuracy of deformation data. Furthermore, it synchronously adjusts the spatial connection relationships between components, enabling the iteratively updated BIM model to reflect the overall structural state of the bridge during the rotation process in real time, rather than just updating isolated parameters of individual components. This strengthens the model's adaptability to the dynamic rotation process. Finally, by integrating multi-dimensional rotation status to generate visual monitoring results, it comprehensively presents the structural changes during the rotation process to monitoring personnel, improving the intuitiveness and reliability of rotation monitoring and providing strong support for the safe advancement of rotation construction. Attached Figure Description

[0007] Figure 1 This is a flowchart of a BIM-based visual monitoring method for bridge rotation provided in an embodiment of the present invention.

[0008] Figure 2 This is a schematic diagram of the composition of a computer system provided in an embodiment of the present invention. Detailed Implementation

[0009] Please see Figure 1 This is a flowchart of a BIM-based visual monitoring method for bridge rotation, provided by an embodiment of the present invention. The method can be executed by a computer system and may include the following steps:

[0010] Step S100: Acquire the structural deformation monitoring data of each monitoring point during the bridge rotation process in real time, and retrieve the pre-built corresponding bridge full-element BIM model. The structural deformation monitoring data includes the point deformation collection values ​​at each time period of the bridge rotation, and the bridge full-element BIM model includes the spatial location code, preset geometric boundary and inherent attribute entries of each bridge component.

[0011] Structural deformation monitoring data is a collection of information used to describe the deformation of a bridge structure during rotation. Point-based deformation data are specific deformation values ​​collected at designated monitoring points during different rotation periods. These values ​​directly reflect the degree of deformation at that point. To obtain structural deformation monitoring data, various sensors can be installed at key locations on the bridge. For example, strain sensors can be installed at critical stress points of the piers. These sensors operate based on the resistance strain effect; when the pier deforms, the resistance of the strain gauge changes. By measuring this change in resistance and applying appropriate conversion algorithms, the strain data of the pier can be obtained, and the stress changes can be calculated. For the beam, displacement sensors, such as laser displacement sensors, can be installed. These sensors utilize the principle of laser reflection, emitting a laser beam onto the beam surface and calculating the beam's displacement by measuring the time it takes for the laser to reflect back. These sensors automatically collect data at regular time intervals and transmit the collected data to a data acquisition system for storage and processing.

[0012] A full-element BIM model of a bridge is a digital 3D model integrating detailed information on all bridge components. Spatial location coding is a unique identifier assigned to each component to accurately determine its position in 3D space. This coding can be done in a hierarchical manner, for example, first dividing the bridge according to different structural layers, and then further subdividing the coding within each structural layer according to regions. Preset geometric boundaries clearly define the spatial range and shape of the components, determined through precise measurements and calculations based on the bridge's design drawings and actual construction conditions. Inherent attribute entries contain various characteristics of the components, such as material type, strength grade, and modulus of elasticity. This attribute information is entered during model construction according to design documents and relevant standards. When retrieving this model, specialized BIM model management software can be used to quickly locate and retrieve the corresponding full-element BIM model of the bridge by entering the bridge's project name, number, and other information.

[0013] Step S200: Based on the spatial location coding of each component in the bridge full-element BIM model, the structural deformation monitoring data is mapped and associated with the corresponding components one by one, and a unique mapping relationship between each component and the structural deformation monitoring data of the corresponding time period is established to obtain the component-monitoring data mapping relationship set.

[0014] In one implementation, step S200 may specifically include the following steps S210 to S260:

[0015] Step S210: Embed the deformation acquisition value of each point in the structural deformation monitoring data with the rotation time stamp, and match the acquisition time of each point deformation acquisition value with the time period division node of the bridge rotation to generate a time period embedded deformation acquisition value set with a unique identifier of the rotation time period.

[0016] The time stamp embedding during bridge rotation is to add a time dimension identifier to the deformation data collected at each point, enabling it to accurately correspond to different time periods during the bridge rotation. The time period division nodes are pre-set time nodes based on the planned process of bridge rotation, such as dividing the rotation process into the initial stage, acceleration stage, constant speed stage, deceleration stage, and final stage, with each stage corresponding to a specific time range.

[0017] When embedding time stamps for rotation periods, the acquisition time information of the deformation data collected at each point is first obtained, which can be directly obtained from the sensor's recorded data. Then, the acquisition time is compared with pre-defined time period division nodes to determine the rotation period to which the acquired value belongs. The comparison process can be performed using a time range judgment method, i.e., determining whether the acquisition time falls within the time range corresponding to a certain time period division node. For example, if the acquisition time of a deformation data collected at a point falls within the time range of the acceleration phase, then the acquired value is marked as belonging to the acceleration phase. To ensure the uniqueness of the identifier, numerical codes or letter combinations can be used to represent different rotation periods. Finally, the deformation data collected at points with rotation period identifiers are organized to form a time period embedded deformation data collection set, in which each acquired value clearly identifies its corresponding rotation period.

[0018] Step S220: Extend the spatial location codes of each component in the full-element BIM model of the bridge to the time period dimension. Add the time period code suffix corresponding to the rotation time period to the original spatial location codes to generate an extended spatial location code set with the time period dimension, and complete the deep binding between the component location codes and the rotation time period.

[0019] The time-period dimension extension is designed to enable spatial location codes to simultaneously reflect the spatial location and temporal information of components, thus better matching them with the time-period embedded deformation data set. Adding a time-period code suffix to the original spatial location code is achieved by combining the pre-defined time-period code with the spatial location code. For example, suppose the original spatial location code represents a specific component of the bridge, and the code for a certain rotation period is a predefined identifier. The extended spatial location code is the original code plus the time-period code suffix, representing the component's code for that specific rotation period. When adding the time-period code suffix, it is necessary to ensure that each component has a unique extended spatial location code for each rotation period. This can be achieved by writing a program that iterates through all components in the bridge's full-element BIM model and automatically generates extended spatial location codes based on their corresponding rotation periods. Specifically, this can be implemented by reading data from a database storing component and rotation period information, and then combining it according to coding rules to generate new codes. Finally, all generated extended spatial location codes are organized to form an extended spatial location code set with a time-period dimension, completing the deep binding between component location codes and rotation periods.

[0020] Step S230: Perform time-space dual-dimensional matching between the time period embedded deformation acquisition value set and the extended spatial location code set. According to the correspondence between the time period identifier and the time period code suffix, bind each acquisition value to the component extended location code of the corresponding time period to generate a preliminary binding relationship entry.

[0021] In one implementation, step S230 may specifically include the following steps S231 to S236:

[0022] Step S231: Perform format standardization processing on each time period identifier in the time period embedded deformation acquisition value set, convert the time period identifier into a format consistent with the time period code suffix in the extended spatial location code set, and generate a standardized time period identifier set with a unified format.

[0023] Format standardization aims to eliminate format differences between time period identifiers and time period code suffixes, ensuring accurate matching. Since time period identifiers and time period code suffixes may use different encoding methods or data formats—for example, a time period identifier might be a text description while the time period code suffix is ​​a numerical number—format conversion is necessary. During format standardization, the standard format for time period code suffixes in the extended spatial location code set is first determined, such as using a unified numerical number or letter combination. Then, conversion rules and procedures are written to convert each time period identifier in the time period embedded deformation data set according to the standard format. The specific conversion process can be implemented by establishing a mapping table, mapping different time period identifiers one-to-one with their corresponding standard formats. For example, if a time period identifier is a text description while the standard format is a numerical number, the text description is converted to the corresponding numerical number using the mapping table. Finally, all converted time period identifiers are compiled to form a standardized time period identifier set with a unified format.

[0024] Step S232: Perform time period range parsing on each time period code suffix in the extended spatial location code set, determine the start and end times of the rotation time period corresponding to each time period code suffix, and generate a time period range parsing result set.

[0025] Time period range analysis is used to clarify the specific time range represented by each time period code suffix, so as to determine whether the sampling time of the point deformation data is within the time period range. By analyzing the start and end times of the rotation time period corresponding to the time period code suffix, a correspondence in the time dimension can be established.

[0026] When performing time period range analysis, a mapping table is first established based on the bridge rotation plan, mapping time period code suffixes to the start and end times of the rotation period. This mapping table can be stored in a database for convenient subsequent query operations. Then, each time period code suffix in the extended spatial location code set is traversed, and its corresponding start and end times are found according to the mapping table. For example, if a time period code suffix is ​​a specific identifier, the mapping table shows that its corresponding rotation period is from one specific time to another. During the analysis process, the accuracy and completeness of the mapping table must be ensured to avoid overlapping or omissions in time period ranges. Finally, the start and end times corresponding to all time period code suffixes are compiled to form the time period range analysis result set.

[0027] Step S233: Match the standardized time period identifier set with the time period range parsing result set to determine whether the collection time corresponding to each time period identifier is within the time period range of the corresponding time period code suffix, and generate the time period range matching result.

[0028] Time period range matching is used to filter out deformation data collected from points that meet the time dimension requirements, ensuring that the collection time matches the corresponding rotation time period. By comparing the standardized time period identifier set with the time period range parsing result set, it can be determined whether each collected value is within the correct time period.

[0029] When performing time period range matching, the standardized time period identifier set is first associated with the extended spatial location code set, so that each time period identifier can correspond to a specific time period code suffix. Then, for each time period identifier, its corresponding collection time information is obtained and compared with the time period range corresponding to the time period code suffix in the time period range parsing result set. Specifically, the comparison process determines whether the collection time is greater than or equal to the start time of the time period and less than or equal to the end time of the time period. For example, if the collection time corresponding to a certain time period identifier is within the time period range represented by its corresponding time period code suffix, it is considered a successful match. This judgment is performed for each collection value, and finally all judgment results are sorted together to form the time period range matching result, which clarifies the matching status of each collection value in the time dimension.

[0030] Step S234: For the successfully matched entries in the time period range matching results, extract the corresponding collected values ​​and perform code prefix matching with the component extended spatial location code, determine whether the monitoring point of the collected value is within the spatial coverage range of the component, and generate code prefix matching results.

[0031] In one implementation, step S234 may specifically include the following steps S2341 to S2346:

[0032] Step S2341: Extract the preset geometric boundaries of the corresponding components from the full-element BIM model of the bridge, convert the preset geometric boundaries into quantifiable spatial coordinate ranges, and generate a set of component spatial coordinate ranges.

[0033] Preset geometric boundaries are the spatial shapes and extents of components defined in the full-element BIM model of a bridge, usually existing in the form of graphical or textual descriptions. Converting them into quantifiable spatial coordinate ranges facilitates subsequent comparison with the coordinates of monitoring points.

[0034] When extracting preset geometric boundaries, the query function of BIM model management software can be used to locate the corresponding component based on its spatial location code or other identification information, and obtain its preset geometric boundary information. Then, based on the specific description of the preset geometric boundaries, they are converted into spatial coordinate ranges. For simple geometric shapes, such as rectangles and circles, the coordinate range can be calculated directly from their geometric parameters. For complex geometric shapes, a polygon approximation algorithm can be used to approximate them into multiple simple polygons, and then the coordinate range of each polygon is calculated separately. Finally, these coordinate ranges are combined to obtain the spatial coordinate range of the entire component. During the conversion process, it is necessary to ensure the accuracy and completeness of the coordinate ranges, so as to accurately reflect the actual spatial range of the component. Finally, the spatial coordinate ranges of all components are organized to form a set of component spatial coordinate ranges.

[0035] Step S2342: Extract the coordinates of the monitoring points corresponding to the data collected from the time period embedded deformation data collection set, convert the coordinates of the monitoring points into a coordinate format consistent with the spatial coordinate range set of the component, and generate a standardized monitoring point coordinate set.

[0036] The coordinates of a monitoring point are the spatial location information of that point recorded when collecting deformation data. The coordinate format may be inconsistent with the format of the component's spatial coordinate range set, so conversion is required.

[0037] When extracting monitoring point coordinates, the coordinate information of each collected value can be directly obtained from the time-period embedded deformation data set. Then, based on the coordinate system and format used by the component spatial coordinate range set, a conversion program or algorithm is written to convert the monitoring point coordinates. If the component spatial coordinate range set uses a geodetic coordinate system while the monitoring point coordinates use a local coordinate system, coordinate transformation is required. This transformation can be achieved through operations such as coordinate translation, rotation, and scaling; the specific transformation parameters can be determined based on the relative relationship between the two coordinate systems. During the transformation process, it is necessary to ensure the accuracy and precision of the transformation to avoid coordinate deviations or information loss. Finally, all the transformed monitoring point coordinates are organized to form a standardized monitoring point coordinate set.

[0038] Step S2343: Compare the coordinate positions of the standardized monitoring point coordinate set with the component spatial coordinate range set, determine whether the coordinates of each monitoring point fall within the spatial coordinate range of the corresponding component, and generate the coordinate position comparison result.

[0039] Coordinate position comparison is used to determine whether each monitoring point is within the spatial coverage area of ​​the corresponding component. By comparing the standardized monitoring point coordinates with the component's spatial coordinate range, a clear judgment result can be obtained. During coordinate position comparison, the coordinates of each monitoring point in the standardized monitoring point coordinate set are traversed and compared with the corresponding component spatial coordinate range in the component spatial coordinate range set. Specifically, the comparison process involves sequentially determining whether each coordinate component of the monitoring point is within the corresponding component interval of the component spatial coordinate range. For example, for a three-dimensional coordinate monitoring point, it is determined whether its X-coordinate is within the interval of the X component of the component spatial coordinate range, its Y-coordinate is within the interval of the Y component, and its Z-coordinate is within the interval of the Z component. Only when all coordinate components are within their corresponding intervals is the monitoring point determined to be within the component's spatial coordinate range. This judgment is performed for each monitoring point coordinate, and all judgment results are finally compiled to form a coordinate position comparison result, which clarifies the spatial matching status of each monitoring point with the component.

[0040] Step S2344: For entries falling within the range in the coordinate position comparison results, extract the extended spatial position code prefix of the corresponding component, verify the consistency with the area code of the monitoring point corresponding to the collected value, and generate the code prefix verification result.

[0041] After successful coordinate location matching, the coding prefix verification is performed to further ensure the accurate correspondence between the collected values ​​and the components. By verifying the consistency between the extended spatial location coding prefix and the regional coding of the monitoring point, the accuracy of matching can be improved.

[0042] For entries falling within the range in the coordinate location comparison results, the extended spatial location code prefix of the corresponding component is first extracted. The extended spatial location code prefix typically contains the component's spatial location and regional information. Then, the region code of the corresponding monitoring point is obtained from the collected values. The two are compared to determine if they match. This comparison can be achieved through string comparison; if the two codes are identical, the verification is considered successful. During verification, the accuracy and consistency of the codes must be ensured to avoid errors or confusion. Finally, all verification results are compiled to form the code prefix verification result, which clarifies the matching status of each entry at the code level.

[0043] Step S2345: For entries that pass the verification in the encoding prefix verification result, mark them as encoding prefix matching successful; for entries that fail the verification, mark them as encoding prefix matching failed, and generate a matching status mark set.

[0044] The matching status tag set is used to visually represent the success or failure status of each entry during the encoding prefix matching process, facilitating subsequent statistical analysis of the matching results. When generating the matching status tag set, each entry in the encoding prefix verification results is traversed and marked according to its verification result. For entries that pass verification, the encoding prefix matching is marked as successful, using a predefined symbol or text, such as "success" or a predefined identifier. For entries that fail verification, the encoding prefix matching fails, marked with "failure" or another identifier. During the marking process, it is necessary to ensure the accuracy and consistency of the markings to avoid errors or omissions. Finally, all marked entries are compiled to form the matching status tag set.

[0045] Step S2346: Integrate the coordinate position comparison results, the encoding prefix verification results, and the matching status mark set to generate the encoding prefix matching results, so as to determine the matching status and basis of each entry.

[0046] The encoding prefix matching result is a comprehensive presentation of the entire encoding prefix matching process. By integrating the coordinate position comparison results, encoding prefix verification results, and matching status marker sets, a complete understanding of the matching status and basis for each entry can be obtained. During integration, the coordinate position comparison results, encoding prefix verification results, and matching status marker sets are first arranged in the same order as the entries. Then, the coordinate position comparison results, encoding prefix verification results, and matching status markers for each entry are combined to form a comprehensive information record. For example, for an entry whose coordinate position comparison result is "falls within range," encoding prefix verification result is "verification passed," and matching status marker is "successful," this information is integrated into a complete record. During the integration process, it is necessary to ensure the accuracy and completeness of the information to avoid information loss or errors. Finally, all integrated records are organized to form the encoding prefix matching result, which not only clarifies the matching status of each entry but also provides the basis for the matching.

[0047] Step S235: For entries that successfully match in the coding prefix matching results, bind the collected values ​​with the component extended spatial location codes to generate a single binding relationship entry, so that each entry is compliant in both time period and spatial matching.

[0048] Based on successful prefix matching, binding the collected values ​​with the component extended spatial location code is to establish an accurate correspondence between data and components, ensuring that each collected value can be accurately associated with the corresponding component and rotation period.

[0049] For entries that successfully match in the prefix matching results, the corresponding collected values ​​and component extended spatial location codes are first extracted. Then, relevant information of the collected values, such as the specific values ​​of the point deformation collected values ​​and the collection time, is combined with the component extended spatial location codes to form a single binding relationship entry. During the binding process, it is necessary to ensure compliance with both time period and spatial matching. That is, the collection time of the collected value must be consistent with the rotation time period corresponding to the time period code suffix in the component extended spatial location code, and the monitoring point of the collected value must be within the spatial coverage area of ​​the component. The specific checking process is to double-check whether the collection time is within the corresponding time period range and whether the coordinates of the monitoring point are within the spatial coordinate range of the component. If both requirements are met, the binding relationship meets the requirement of dual compliance of time period and spatial matching. Finally, all single binding relationship entries that meet the requirements are organized.

[0050] Step S236: Summarize all compliant single binding relationship entries, arrange them in the order of rotation time period and component expansion space location code, and generate preliminary binding relationship entries.

[0051] Summarizing and arranging individual binding relationship entries makes the bound data more organized and easier to manage, facilitating subsequent analysis and use.

[0052] When aggregating individual binding relationship entries, all entries that meet both time period and spatial matching compliance requirements are collected into a single set. Then, they are arranged according to the rotation time period and the component extended spatial location code. First, entries are sorted by rotation time period, grouping entries within the same rotation time period together. Within the same rotation time period, they are then sorted again according to the component extended spatial location code, ensuring data order. The sorting process can employ sorting algorithms, such as quicksort, comparing and swapping entries based on the size relationship between the rotation time period and the component extended spatial location code until all entries are arranged as required. During the sorting process, the accuracy and stability of the sorting must be ensured to avoid sorting errors or data loss. Finally, all sorted entries are organized to generate preliminary binding relationship entries.

[0053] Step S240: Perform a duplicate binding check on the initial binding relationship entries within the same time period. Traverse all initial binding relationship entries under the same rotation time period, identify duplicate binding situations where multiple collected values ​​correspond to the same component, and record the index of the duplicate binding entries.

[0054] The purpose of checking for duplicate bindings within a time period is to eliminate potential duplicate binding issues in the initial binding relationship entries and ensure that each component corresponds to only one valid collection value within the same rotation time period.

[0055] During the investigation, the initial binding relationships were first grouped according to the rotation period, with all entries within the same rotation period grouped together. Then, the entries within each rotation period were traversed, and for each component, it was checked whether multiple collected values ​​corresponded to it. Specifically, this was done by comparing the component's extended spatial location code; if multiple entries had the same extended spatial location code, it was considered a duplicate binding. To record duplicate bindings, the indices of these duplicate binding entries were recorded. The entry index could be the entry's sequence number or other unique identifier, facilitating subsequent processing of duplicate binding entries. For example, a list could be used to store the indices of duplicate binding entries. During the traversal, it was crucial to ensure a comprehensive check of each rotation period and each component to avoid overlooking duplicate bindings. Finally, all recorded duplicate binding entry indices were compiled.

[0056] Step S250: For the index of duplicate bound entries, extract the deformation collection values ​​of multiple points in the corresponding time period to determine the homogeneity within the time period. Merge the duplicate collection values ​​collected from the same monitoring point and retain the collection value at the most recent time. Add new component binding entries to the collection values ​​that are not homogeneous.

[0057] The purpose of homogeneity discrimination within a time period is to handle duplicate data collection. By determining whether the data collection comes from the same monitoring point, different processing methods are adopted to ensure the accuracy and validity of the data.

[0058] For duplicate bound entry indexes, firstly, extract deformation data from multiple points within the corresponding time period based on the index. Then, perform source identification on these data. Determining whether data points originate from the same monitoring point can be done by comparing the monitoring point coordinates or other unique identifiers. If the monitoring point coordinates of the data points are exactly the same, they are considered to be from the same source. For data points from the same source, since they reflect the deformation at the same monitoring point, to avoid data redundancy, these data points are merged, retaining only the most recent data point. This is because the most recent data point better reflects the current deformation state. Specifically, the merging process can retain all information from the most recent data point while ignoring other data points from the same source. For data points from different sources, indicating they originate from different monitoring points and reflect deformation at different locations, additional component binding entries need to be added to bind these data points to the corresponding components. During processing, it is necessary to ensure the accuracy of source identification and the rationality of the processing method to avoid misjudgments or improper processing. Finally, the processed data points and binding entries are organized, and the initial binding relationship entries are updated.

[0059] Step S260: Organize and sort all the binding relationship entries after investigation and resolution, arrange the entries according to the rotation time period and component spatial location code, and generate a structurally regular component-monitoring data mapping relationship set.

[0060] After the preceding duplicate binding checks and homology identification, the binding relationship entries may change. Organizing and sorting these entries is crucial for creating a more standardized and orderly final component-monitoring data mapping set, facilitating subsequent use and analysis. The sorting process begins by collecting all processed binding relationship entries. Then, they are arranged according to the rotation period and component spatial location code. First, entries are grouped by rotation period, placing entries from the same rotation period together. Within the same rotation period, they are then sorted according to the component spatial location code. A sorting algorithm, such as merge sort, can be used to compare and swap positions based on the size relationship between the rotation period and the component spatial location code, ensuring the stability and efficiency of the sorting. During the sorting process, data integrity and accuracy must be ensured to avoid data loss or sorting errors. Finally, all sorted entries are organized to form a structurally regular component-monitoring data mapping set. This set clearly identifies the unique and valid structural deformation monitoring data corresponding to each component at different rotation periods.

[0061] Step S300: Based on the component-monitoring data mapping relationship set, extract the preset geometric boundaries and inherent attribute entries of the corresponding components in the bridge full-element BIM model, locate the abnormal acquisition values ​​in the structural deformation monitoring data with the preset geometric boundaries as the reference, and perform calibration processing to obtain the calibrated component deformation acquisition value set.

[0062] In one implementation, step S300 may specifically include the following steps S310 to S360:

[0063] Step S310: Based on the component-monitoring data mapping relationship set, extract the preset geometric boundary and inherent attribute entries corresponding to each component from the bridge full-element BIM model, convert the preset geometric boundary into a quantifiable spatial range description, and generate a component spatial range-attribute association set.

[0064] The component-monitoring data mapping set clearly defines the structural deformation monitoring data corresponding to each component. Based on this, the preset geometric boundaries and inherent attribute entries of the corresponding components can be accurately extracted from the bridge's full-element BIM model. The preset geometric boundaries usually exist in the form of graphical or textual descriptions. Converting them into quantifiable spatial range descriptions facilitates subsequent comparison with the collected values.

[0065] When extracting preset geometric boundaries and inherent attribute entries, the correspondence in the component-monitoring data mapping relationship set is utilized. Through the query function of the BIM model management software, each component is located, and its preset geometric boundaries and inherent attribute entry information are obtained. Then, based on the specific description of the preset geometric boundaries, appropriate mathematical methods are used to convert them into spatial extent descriptions. For simple geometric shapes, such as cuboids, the value range on each coordinate axis can be directly determined based on its length, width, and height. For complex geometric shapes, a discretization method may be needed to divide it into multiple small regions, then determine the coordinate range of each small region, and finally merge them to obtain the spatial extent description of the entire component. The converted spatial extent description is then associated with the corresponding inherent attribute entries to form a component spatial extent-attribute association set. For example, the spatial extent description of a component can be bound to inherent attribute entries such as the component's material type and strength grade. During the association process, data structures, such as dictionaries or objects, can be used to store the spatial extent description and inherent attribute entries as key-value pairs. Finally, the spatial extent-attribute association information of all components is organized to form a component spatial extent-attribute association set.

[0066] Step S320: Compare the spatial location of the structural deformation monitoring data for each time period in the component-monitoring data mapping relationship set with the corresponding component spatial range in the component spatial range-attribute association set, determine whether the monitoring point corresponding to the collected value exceeds the spatial range description of the component, and generate the spatial location comparison result.

[0067] Spatial location comparison aims to identify collected values ​​in structural deformation monitoring data that exceed the normal spatial range of structural components. By comparing the monitoring point of the collected value with the spatial range of the component, it can be determined whether the collected value is abnormal. For structural deformation monitoring data of each time period in the component-monitoring data mapping set, the coordinates of the corresponding monitoring point are first extracted. Then, based on the correspondence in the component-monitoring data mapping set, the spatial range description of the component corresponding to the collected value in the component spatial range-attribute association set is found. The coordinates of the monitoring point are compared with the spatial range description of the component. Specifically, the comparison process involves sequentially determining whether each coordinate component of the monitoring point is within the corresponding component interval of the component spatial range description. For example, for a three-dimensional coordinate monitoring point, it is determined whether its X coordinate is within the interval of the X component of the component spatial range description, whether its Y coordinate is within the interval of the Y component, and whether its Z coordinate is within the interval of the Z component. If any coordinate component exceeds the corresponding interval, the monitoring point corresponding to the collected value is considered to be outside the spatial range description of the component. This comparison is performed for each collected value, and finally, all comparison results are compiled to form the spatial location comparison result. The results can be stored as a list or other data structure, where each element represents the comparison result of a collected value, such as "out of range" or "not out of range".

[0068] Step S330: Identify continuous deviations in the spatial position comparison results over time periods. Mark cases where the collected values ​​of multiple consecutive rotation periods of the same component exceed the spatial range description, record the start and end times of the continuous deviation, and determine the continuous characteristics of the deviation.

[0069] In one implementation, step S330 may specifically include the following steps S331 to S336:

[0070] Step S331: Extract all rotation time period deviation states of each component from the spatial location comparison results, combine them with the inherent attribute entries of the corresponding components in the bridge full-element BIM model, filter out the components whose inherent attributes contain rotation deformation sensitive annotations, and organize all time period deviation states of these components into a preliminary set of component time period deviations.

[0071] From the spatial location comparison results, the deviation states of each component are categorized and organized to obtain the deviation state of each component across all rotation periods. The deviation state can be represented as "out of range" or "not out of range." Then, the inherent attribute entries of the corresponding components are extracted from the bridge's full-element BIM model. These entries contain various characteristic information of the components, which may include rotation deformation sensitive annotations. Rotation deformation sensitive annotations are indicators of the component's sensitivity to deformation during rotation, such as "high sensitivity," "medium sensitivity," and "low sensitivity." Components with rotation deformation sensitive annotations in their inherent attributes are selected, and the deviation states of these components across all time periods are organized to form an initial set of component time-period deviations. During this process, data structures, such as dictionaries, can be used, storing the component identifier as the key and its corresponding time-period deviation states as the values. Ultimately, this step narrows the scope of subsequent analysis, focusing on components sensitive to rotation deformation, thus improving the efficiency and relevance of the analysis.

[0072] Step S332: For each component item in the component time period deviation from the initial screening set, match the point deformation acquisition value in the structural deformation monitoring data of the corresponding time period, bind the deviation status of each time period with the acquisition environment label of the corresponding acquisition value, generate a time period acquisition value association set, so that the time period and the acquisition value correspond one-to-one.

[0073] For each component entry whose time period deviates from the initial screening set, the corresponding point deformation acquisition value is matched from the structural deformation monitoring data based on the rotation time period information. The acquisition environment annotation is relevant environmental information recorded when acquiring point deformation values, such as temperature, humidity, and wind speed; this information may affect the acquired values. The deviation status of each time period is bound to the acquisition environment annotation of the corresponding acquisition value, generating a time period acquisition value association set. A data structure, such as a list nested dictionary, can be used, where each list element represents a time period, and the dictionary contains information such as the deviation status, point deformation acquisition value, and acquisition environment annotation. This binding method achieves a one-to-one correspondence between time periods and acquisition values.

[0074] Step S333: Traverse the associated set of time period collected values, calculate the consistency of the deviation state of adjacent time periods for each component's continuous time period entries, mark the entries with continuous deviation states that exceed the spatial range description as suspected continuous deviation sequences, and generate the time period deviation continuity discrimination result.

[0075] As one implementation method, step S333 generates the time period deviation continuity discrimination result, which may specifically include the following steps S3331~S3336:

[0076] Step S3331: Split the time period collection value association set by component, extract all rotation time period entries of each component separately, strictly sort them according to the rotation time sequence, and generate the component time period sequence splitting result.

[0077] The time-segment data collection set contains relevant information for multiple components during different rotation periods. To facilitate subsequent analysis of continuous time periods for each component, it needs to be split into components. During splitting, the identifier information of each component is identified from the time-segment data collection set, and all rotation period entries belonging to the same component are extracted based on this identifier. For example, if the time-segment data collection set is stored in a database table, the entries corresponding to each component can be filtered using an SQL query with the component identifier as the filtering condition. Then, these entries are strictly sorted according to the rotation time sequence. Sorting can be based on the rotation time field recorded in the entries, using a sorting algorithm such as merge sort to ensure the stability and accuracy of the sorting. This allows the rotation period entries for each component to be arranged in chronological order, facilitating subsequent analysis of deviations between adjacent time periods. Finally, the split and sorted time period entries for each component are organized into a component time period sequence splitting result, which is stored in the form of a data structure, such as nested lists. Each element of the outer list represents a component, and the inner list contains all time period entries for that component sorted by time.

[0078] Step S3332: For each component time period sequence in the component time period sequence splitting result, extract the deviation state of adjacent time periods in pairs, form a deviation state pair by combining the deviation state of the previous time period with the deviation state of the next time period, and generate a set of adjacent time period deviation pairs, covering all consecutive adjacent time periods.

[0079] For each component's time-segment sequence in the component time-segment sequence splitting result, the deviation state relationship between adjacent time segments is further analyzed. By traversing the time-segment sequence of each component, the deviation state of adjacent time segments is extracted pairwise. During extraction, starting from the first entry of the time-segment sequence, the deviation states of the current entry and the next entry are sequentially combined into a deviation state pair. For example, if a component's time-segment sequence has 5 entries, namely entry 1, entry 2, entry 3, entry 4, and entry 5, then 4 deviation state pairs will be generated: (deviation state of entry 1, deviation state of entry 2), (deviation state of entry 2, deviation state of entry 3), (deviation state of entry 3, deviation state of entry 4), and (deviation state of entry 4, deviation state of entry 5). This ensures that all consecutive adjacent time segments in the component's time-segment sequence are covered. Finally, the deviation state pairs generated for all components are summarized into an adjacent time-segment deviation pair set, which is also stored using a suitable data structure, such as a list nested tuples, where each tuple represents a deviation state pair.

[0080] Step S3333: For each deviation state pair in the adjacent time period deviation pair set, determine the consistency degree. If the deviation state of the preceding and following time periods is both described as exceeding the spatial range, mark it as a consistent pair; otherwise, mark it as a non-consistent pair. Calculate the proportion of consistent pairs in the time period sequence of each component and generate the deviation state consistency degree result.

[0081] To determine the consistency of deviation states between adjacent time periods, each deviation state pair in the set of adjacent time period deviation pairs needs to be judged. During the judgment, the deviation states of the preceding and following time periods in each deviation state pair are checked. If the deviation states of both preceding and following time periods are outside the spatial range description, the deviation state pair is marked as a consistent pair; if the deviation states of preceding and following time periods are not entirely outside the spatial range description (e.g., one is outside the range and the other is not), or both are not outside the range, they are marked as inconsistent pairs. The marking process can be implemented using conditional statements. Next, for each component's time period sequence, the number of consistent pairs is counted, and the proportion of consistent pairs in all deviation state pairs for that component is calculated. The proportion is calculated by dividing the number of consistent pairs by the total number of deviation state pairs for that component. Finally, the proportion of consistent pairs for each component is compiled into a deviation state consistency result, which can be stored in dictionary form, with the component identifier as the key and the corresponding consistent pair proportion as the value.

[0082] Step S3334: For continuous time segments in the deviation state consistency results where the proportion of consistent pairs reaches 100%, extract the complete segment from the start time of the first consistent pair to the end time of the last consistent pair, mark these segments as continuous deviation candidate sequences, and generate a continuous deviation candidate sequence set.

[0083] After obtaining the deviation consistency results, continuous time segment segments with a 100% consistency ratio are selected. This means that within these continuous time segments, the deviation states of adjacent time segments remain consistent and are all outside the spatial range description. During the selection process, the deviation consistency results are traversed to find component time segment sequences with a 100% consistency ratio. For segments that meet the criteria, the complete time range from the start time of the first consistency pair to the end time of the last consistency pair is extracted. These extracted complete segments are marked as continuous deviation candidate sequences. Finally, all marked candidate sequences are aggregated into a continuous deviation candidate sequence set, which is stored using a suitable data structure, such as a list nested dictionary, where each dictionary contains information such as the start time, end time, and component identifier of the candidate sequence.

[0084] Step S3335: For each candidate sequence in the continuous deviation candidate sequence set, combine the inherent attribute entries of the corresponding component in the bridge full-element BIM model to verify the matching of the component's rotation action type in the corresponding time period with the deviation sequence, filter out the matching candidate sequences, and generate candidate sequence verification results.

[0085] The candidate sequences in the continuous deviation candidate sequence set are only preliminary screening of time period sequences that may have continuous deviations. Further verification of their matching with the component rotation action type is needed. For each candidate sequence in the continuous deviation candidate sequence set, the inherent attribute entries of the corresponding component are obtained from the bridge's full-element BIM model. These inherent attribute entries contain relevant characteristic information of the component under different rotation action types. Then, based on the time period corresponding to the candidate sequence and the bridge rotation plan, the rotation action type of the component within that time period is determined. Next, it is analyzed whether this rotation action type matches the deviation presented by the candidate sequence. For example, if a component theoretically should not exhibit a long-term continuous deviation beyond the spatial range description under a certain rotation action type, but the candidate sequence shows continuous deviation within that time period, then the candidate sequence may not match. Each candidate sequence is verified in this way to filter out matching candidate sequences. Finally, the filtered matching candidate sequences are compiled into a candidate sequence verification result, which is stored in a suitable data structure, such as a list nested dictionary, where each dictionary contains detailed information about the matching candidate sequence.

[0086] Step S3336: For the matching candidate sequences in the candidate sequence verification results, check the number of time periods covered by the sequence, mark the candidate sequences that cover three or more time periods as suspected continuous deviation sequences, organize all marked sequences and corresponding component information, and generate time period deviation continuity discrimination results.

[0087] After obtaining the candidate sequence verification results, it is necessary to further determine which matching candidate sequences can be marked as suspected continuous deviation sequences. Examine the number of time periods covered by each matching candidate sequence in the verification results, and set a threshold, such as three time periods. If a matching candidate sequence covers three or more time periods, it is marked as a suspected continuous deviation sequence. The marking process can be implemented by adding a marking field to the candidate sequence information. Then, all marked suspected continuous deviation sequences and their corresponding component information are organized to form the time period deviation continuity discrimination result. This result is stored in the form of a data structure, such as a list nested dictionary, where each dictionary contains the start time period, end time period, component identifier, marking information, etc., of the suspected continuous deviation sequence.

[0088] Step S334: For the suspected continuous deviation sequence in the time period deviation continuity discrimination results, extract the monitoring point coordinates of the corresponding time period collection values, and perform a secondary coordinate comparison with the preset geometric boundary of the corresponding component in the bridge full-element BIM model to verify the accuracy of the deviation state and generate a deviation time period boundary verification set.

[0089] For suspected continuous deviation sequences in the time-period deviation continuity judgment results, a secondary coordinate comparison is required to ensure the accuracy of the deviation status. First, the coordinates of the monitoring points corresponding to the time periods collected in the structural deformation monitoring data are extracted. These monitoring point coordinates record the spatial location information of the monitoring points within the corresponding time periods. Then, the preset geometric boundary information of the corresponding components is obtained from the bridge's full-element BIM model and converted into a quantifiable spatial coordinate range. During the secondary coordinate comparison, the monitoring point coordinates are compared in detail with the spatial coordinate range corresponding to the preset geometric boundaries of the components. The comparison process is similar to the previous coordinate position comparison, determining whether the monitoring point coordinates fall within the spatial coordinate range of the components. For each suspected continuous deviation sequence, the comparison result is recorded, such as whether the monitoring point coordinates exceed the preset geometric boundaries. Finally, the comparison results of all suspected continuous deviation sequences are compiled into a deviation time period boundary verification set. This set is stored using a suitable data structure, such as a list nested dictionary, where each dictionary contains relevant information about the suspected continuous deviation sequence and the comparison results.

[0090] Step S335: Select continuous time periods from the deviation time period boundary verification set that are still outside the spatial range description after secondary alignment, mark the first time period of each continuous sequence as the continuous deviation start time period and the last time period as the continuous deviation end time period, and generate continuous deviation time period labeling results.

[0091] After obtaining the deviation time period boundary verification set, further filtering is performed to identify time period sequences that truly exhibit continuous deviations. From the deviation time period boundary verification set, continuous time periods whose secondary comparison results still exceed the spatial range description are selected. The filtering process involves traversing the deviation time period boundary verification set and checking the comparison results of each suspected continuous deviation sequence. If the monitoring point coordinates of the sequence still exceed the preset geometric boundary of the component in the secondary comparison, the sequence is considered to meet the requirements. For the selected continuous time period sequences, the first time period is marked as the continuous deviation start time period, and the last time period is marked as the continuous deviation end time period. The marking process can be implemented by adding corresponding fields to the data structure. Finally, all marked continuous time period sequences and related information are compiled into continuous deviation time period marking results. This result is stored in a suitable data structure, such as a list nested dictionary, where each dictionary contains information such as the continuous deviation start time period, end time period, and component identifier.

[0092] Step S336: For each continuous deviation sequence in the continuous deviation time period marking results, calculate the difference in the number of time periods between the start time period and the end time period, and combine it with the deformation sensitivity attribute annotation of the corresponding component to generate a deviation persistence feature description set containing time period length and deformation sensitivity association description, and determine the persistence feature of the deviation.

[0093] For each consecutive deviation sequence in the consecutive deviation time period marking results, its deviation persistence characteristics need to be determined. First, calculate the difference in the number of time periods between the start and end periods of each consecutive deviation sequence. This difference represents the time period length of the consecutive deviation sequence. To calculate the difference, subtract the start period number from the end period number and add 1. Then, combine this with the deformation sensitivity attribute annotations of the corresponding components in the bridge's full-element BIM model. These annotations reflect the component's sensitivity to deformation, such as high sensitivity, medium sensitivity, or low sensitivity. Based on the time period length and deformation sensitivity attribute annotations, generate a deviation persistence characteristic description that includes the time period length and deformation sensitivity association description. For example, if a component's deformation sensitivity attribute is labeled as high sensitivity and the consecutive deviation time period is long, it can be described as "This component, due to its high sensitivity characteristics, continues to deviate over a long period, which may indicate a serious problem." Organize the deviation persistence characteristic descriptions of each consecutive deviation sequence into a deviation persistence characteristic description set. This set is stored using a suitable data structure, such as a list nested dictionary. Each dictionary contains information such as the component identifier, time period length, and deformation sensitivity association description of the consecutive deviation sequence.

[0094] Step S340: For the continuously deviating marking results, extract the inherent attribute entries of the corresponding components, analyze the intrinsic relationship between the inherent attribute entries and the deviation, and combine the changing trend of the collected values ​​over a continuous period to generate a preliminary judgment result of the cause of the deviation.

[0095] The marking results of continuous deviations clearly identify the components and time periods exhibiting continuous deviations. To determine the causes of these deviations, further analysis of the inherent attribute entries of the corresponding components is needed. Inherent attribute entries for the corresponding components are extracted from the bridge's full-element BIM model based on the continuous deviation marking results. These inherent attribute entries contain information such as the component's material properties, mechanical performance, and design parameters. The intrinsic correlation between these inherent attribute entries and the deviations is analyzed. Simultaneously, the trend of collected values ​​over consecutive time periods is observed to determine whether the values ​​are increasing, decreasing, or fluctuating. If the collected values ​​show an increasing trend and consistently exceed the range, it may indicate a deteriorating stress condition in the component. By comprehensively analyzing the inherent attribute entries and the trend of collected value changes, a preliminary judgment result for the cause of the deviation is generated. This preliminary judgment result can be presented in the form of a text description, such as "Due to insufficient strength of the component material, during the continuous rotation period, as the stress increases, the collected values ​​continuously exceed the range, leading to continuous deviations." Finally, the preliminary judgment results for each continuous deviation are compiled into a set.

[0096] Step S350: Based on the preliminary judgment result of the deviation cause, interpolate and correct the continuously deviating collected values ​​within the time period. With other normal collected values ​​of the same component in the same time period as a reference, adjust the values ​​of the deviating collected values ​​to generate the corrected deformation collected values.

[0097] After obtaining the preliminary judgment results of the deviation causes, the continuously deviating collected values ​​are corrected. Other normal collected values ​​for the same component within the same time period are used as a reference. Normal collected values ​​refer to those that do not show deviations within that time period and reflect the deformation of the component under normal conditions. An interpolation correction method within the time period is used to adjust the values ​​of the deviating collected values. The principle of interpolation correction is to infer the reasonable value of the deviating collected values ​​based on the distribution pattern of normal collected values. For example, if there are multiple normal collected values ​​for the same component within the same time period, and these collected values ​​exhibit a certain linear trend, the corrected value of the deviating collected values ​​can be calculated using linear interpolation, based on the position of the deviating collected values ​​within the time period and the variation pattern of the normal collected values. During the adjustment process, it is necessary to ensure that the corrected collected values ​​conform to the actual physical characteristics and mechanical laws of the component. Finally, all the continuously deviating collected values ​​are compiled into a set of corrected deformation collected values. This set is stored in a suitable data structure, such as a list, where each element is a corrected deformation collected value.

[0098] Step S360: Integrate the corrected deformation acquisition values ​​with the acquisition values ​​not marked as deviations, arrange them according to the rotation time period and the order of components, and generate a set of calibrated component deformation acquisition values ​​so that the deformation acquisition values ​​of each component conform to its spatial range constraints.

[0099] After obtaining the corrected deformation acquisition values, they are integrated with the acquisition values ​​not marked as deviations. Acquisition values ​​not marked as deviations refer to those that were not judged as abnormal deviations throughout the process and are themselves valid data conforming to the component's spatial range constraints. The corrected deformation acquisition values ​​and the acquisition values ​​not marked as deviations are merged into a single set. Then, this set is arranged according to the rotation period and the order of the components. During arrangement, the data is first grouped by rotation period, placing acquisition values ​​from the same rotation period together. Within the same rotation period, the data is then sorted by component. The sorting process can be implemented using a sorting algorithm to ensure the data's orderliness. Finally, the arranged acquisition value set is organized into a calibrated component deformation acquisition value set. The deformation acquisition values ​​of each component in this set have been corrected and organized to conform to its spatial range constraints.

[0100] Step S400: Match the calibrated component deformation acquisition value set to the corresponding component attribute configuration node of the bridge full-element BIM model, and synchronously adjust the spatial connection relationship between components according to the change amplitude of the calibrated component deformation acquisition value to obtain the iteratively updated bridge BIM model.

[0101] In one implementation, step S400 may specifically include the following steps S410 to S460:

[0102] Step S410: Extract the deformation acquisition value corresponding to each component from the calibrated component deformation acquisition value set, perform node positioning matching with the attribute configuration node of the corresponding component in the bridge full-element BIM model, determine the attribute configuration node path corresponding to the deformation acquisition value of each component, and generate an attribute node-acquisition value correspondence table.

[0103] The calibrated component deformation acquisition value set contains the calibrated deformation acquisition values ​​of each component. To accurately match these acquisition values ​​to the bridge's full-element BIM model, node location matching is performed. The deformation acquisition value corresponding to each component is extracted from the calibrated component deformation acquisition value set; each acquisition value represents the deformation of the component during the corresponding rotation period. Then, the attribute configuration node of the corresponding component is located in the bridge's full-element BIM model. Attribute configuration nodes are nodes in the model used to store various attribute information of components. During node location matching, the corresponding node is found in the model's attribute configuration node tree based on the component's identification information, such as the component's name and number. The path of the attribute configuration node corresponding to each component's deformation acquisition value is determined. The path can be represented as a series of node names or numbers from the root node to the target attribute configuration node. For example, by traversing the model's attribute configuration node tree, the corresponding node is found based on the component identification, and the path from the root node to that node is recorded. Associate the attribute configuration node path of each component with the corresponding deformation acquisition value to generate an attribute node-acquisition value mapping table. This table is stored in a suitable data structure, such as a dictionary, with the attribute configuration node path as the key and the corresponding deformation acquisition value as the value.

[0104] Step S420: Write each deformation acquisition value in the calibrated component deformation acquisition value set into the attribute configuration node of the corresponding component, overwrite the preset deformation information in the original node, generate an attribute configuration node set with real-time deformation acquisition values, and complete the initial binding of acquisition values ​​with BIM model.

[0105] Based on the attribute node-collected value mapping table, each deformation collected value from the calibrated component deformation collected value set is written into the corresponding component's attribute configuration node in the bridge's full-element BIM model. During the writing process, the collected values ​​are assigned to the corresponding attribute configuration nodes using the interfaces or methods provided by the model management software. The preset deformation information in the original nodes is deformation data pre-set during model construction. To ensure the model reflects the latest actual situation, the new deformation collected values ​​overwrite the original information. For example, if the preset deformation value stored in the attribute configuration node of a component was a fixed value, the calibrated deformation collected value is now written into that node, replacing the original value. After performing this update operation on the attribute configuration nodes of all components, an attribute configuration node set with real-time deformation collected values ​​is generated. This set contains the attribute configuration nodes of all components in the model, and each node stores the latest deformation collected value, completing the initial binding of the collected values ​​to the BIM model.

[0106] Step S430: Extract the deformation acquisition value of each component from the attribute configuration node set with real-time deformation acquisition value, analyze the spatial position change of the component corresponding to the deformation acquisition value, generate a description set of component spatial position change, and determine the position change of each component.

[0107] The attribute configuration node set with real-time deformation acquisition values ​​stores the latest deformation information for each component. To understand the spatial position changes of the components, these deformation acquisition values ​​need to be extracted and analyzed. The deformation acquisition values ​​for each component are extracted from the attribute configuration node set; these values ​​reflect the degree of deformation during the component's rotation. Based on the structural characteristics and mechanical principles of the components, the relationship between the deformation acquisition values ​​and the spatial position changes of the components is analyzed. For example, if the deformation acquisition value of a beam component represents its tension or compression in a certain direction, then based on the beam's geometry and mechanical properties, the displacement changes at both ends of the beam in that direction can be calculated, thereby determining the beam's spatial position changes. A detailed description of the spatial position changes of each component is then generated, forming a component spatial position change description set. This description set can be stored in the form of text or a data structure, such as a list nested with dictionaries. Each dictionary contains information such as the component identifier, the direction of the spatial position change, and the magnitude of the change, clearly defining the positional changes of each component.

[0108] Step S440: Combining the component spatial position change description set with the spatial connection relationship between components in the bridge full-element BIM model, calculate the degree of influence of each component position change on the spatial connection of adjacent components, generate a component connection influence degree description set, and quantify the influence range.

[0109] In one implementation, step S440 may specifically include the following steps S441 to S446:

[0110] Step S441: Extract the list of adjacent components for each component from the full-element BIM model of the bridge, determine the direct adjacent components of each component, and generate a list set of component adjacency relationships.

[0111] The full-element BIM model of a bridge contains information on the spatial connections between components. To calculate the impact of changes in component position on adjacent components, it is necessary to first determine the direct adjacent components of each component. The list of adjacent components for each component is extracted from the full-element BIM model of the bridge. In the model, the adjacency relationships between components can be recorded through connection information, spatial positional relationships, etc. For example, if two components have a physical connection, such as a bolted connection or welding, or are spatially close and interact with each other, then they are considered adjacent components. By traversing the component information and connection information in the model, the direct adjacent components of each component are determined. Each component and its corresponding list of adjacent components are then organized to generate a set of component adjacency relationships. This set is stored in a suitable data structure, such as a dictionary, where the key is the component identifier and the value is the corresponding list of adjacent components.

[0112] Step S442: Extract the spatial position change of each component from the component spatial position change description set, convert the spatial position change to a unit format consistent with the spatial coordinates of adjacent components, and generate a standardized position change set.

[0113] The component spatial position change description set records the spatial position changes of each component. To accurately calculate the impact on adjacent components, it is necessary to extract the spatial position change quantities and convert them to the correct unit format. The spatial position change quantities for each component are extracted from the description set; these quantities can be represented by physical quantities such as displacement and angular changes. Since different components may use different unit formats for their spatial coordinates (e.g., meters, millimeters, degrees), the spatial position change quantities are converted to a unit format consistent with the spatial coordinates of adjacent components to ensure a unified calculation standard.

[0114] Step S443: For each adjacent component of each component, extract the spatial connection constraints between the adjacent component and the component, determine the type of connection constraint and the allowable range of positional changes, and generate a connection constraint description set.

[0115] In one implementation, step S443 may specifically include the following steps S4431 to S4436:

[0116] Step S4431: Extract the original spatial connection relationships between components from the full-element BIM model of the bridge, and match the rotation action planning information of the corresponding rotation period. Bind the original spatial connection relationships with the rotation action planning of the corresponding period, mark the rotation action type corresponding to each connection relationship, and generate a time-related connection relationship set.

[0117] The full-element BIM model of the bridge stores the original spatial connection relationships between components, which describe the connection methods and relative positions of the components. To more accurately analyze the connection constraints of components during the rotation process, it is necessary to combine the rotation action planning information for the corresponding rotation period. The original spatial connection relationships between components are extracted from the full-element BIM model of the bridge; these relationships can be reflected through the connection information and constraints in the model. Simultaneously, the rotation action planning information for the corresponding rotation period is obtained, including parameters such as rotation speed, angle, and direction. The original spatial connection relationships are bound to the corresponding rotation action planning for each period, i.e., each connection relationship is labeled with a corresponding rotation action type. For example, if the connection relationship between components is under uniform rotation during a certain rotation period, then the rotation action type corresponding to that connection relationship is labeled as "uniform rotation". All the bound connection relationship information is organized into a time-related connection relationship set, which is stored using a suitable data structure, such as a list nested dictionary. Each dictionary contains information such as component identifier, adjacent component identifier, connection relationship description, and rotation action type.

[0118] Step S4432: Decompose the constraint dimensions of the time period association connection set, decompose each connection relationship into three independent dimensions: spatial position constraint, relative angle constraint, and load transfer constraint, extract the initial constraint content under each dimension, record the rotation action adaptation requirements corresponding to each dimension, and generate the connection constraint dimension decomposition result.

[0119] The time-segmented connection relationship set contains the connection relationships between components under different rotation time periods and rotation action types. To analyze the connection constraints in more detail, the constraint dimensions are decomposed. Each connection relationship is decomposed into three independent dimensions: spatial position constraint, relative angle constraint, and load transfer constraint. Spatial position constraint specifies the position range of the component in space, relative angle constraint restricts the relative rotation angle between components, and load transfer constraint involves the force and energy transfer restrictions between components. The initial constraint content for each dimension is extracted. The initial constraint content can be specific numerical ranges, conditional restrictions, etc. For example, spatial position constraint may specify the maximum and minimum distance between two components; relative angle constraint may specify the allowable rotation angle range; and load transfer constraint may specify the maximum load type and size that can be transferred. At the same time, the rotation action adaptation requirements corresponding to each dimension are recorded, that is, the constraint conditions of this dimension may be different under different rotation action types. For example, under rapid rotation action, the spatial position constraint may be more stringent. The constraints and rotation action adaptation requirements of each dimension after decomposition are organized into the connection constraint dimension decomposition results. These results are stored in a suitable data structure, such as a list nested dictionary. Each dictionary contains information such as component identifier, adjacent component identifier, constraint dimension, initial constraint content, and rotation action adaptation requirements.

[0120] Step S4433: For the spatial position constraint dimension in the connection constraint dimension decomposition result, extract the allowable displacement range of the corresponding component during the rotation period, and perform standardized conversion in combination with the coordinate unit of the component spatial position change description set to convert the allowable displacement range into a coordinate format consistent with the position change amount, and generate a standardized position constraint range set.

[0121] In the decomposition results of the connection constraint dimension, the spatial position constraint dimension specifies the allowable displacement range of the component during the rotation period. The allowable displacement range of the corresponding component during the rotation period is extracted from the constraint content of this dimension. The allowable displacement range can be represented by a coordinate interval, such as the maximum and minimum displacement values ​​on a certain coordinate axis. Since the component spatial position change description set and the allowable displacement range may use different coordinate units, a standardization conversion is performed based on the coordinate units of the component spatial position change description set to facilitate subsequent comparison and calculation. The standardized allowable displacement ranges of all components are organized into a standardized position constraint range set, which is stored in a suitable data structure, such as a list nested dictionary. Each dictionary contains information such as component identifier, adjacent component identifiers, and the standardized allowable displacement range of the spatial position constraint dimension.

[0122] Step S4434: For the relative angle constraint dimension in the connection constraint dimension decomposition result, extract the allowable rotation angle range of the corresponding component during the rotation period, and perform standardization conversion in combination with the angle unit of the component spatial position change description set to convert the allowable rotation angle range into an angle format consistent with the angle change amount, and generate a standardized angle constraint range set.

[0123] For the relative angle constraint dimension in the decomposition results of the connection constraint dimension, it is necessary to extract the allowable rotation angle range of the corresponding component during the rotation period. The allowable rotation angle range specifies the maximum and minimum angles of relative rotation between components. This range is obtained from the constraint content of the relative angle constraint dimension. Since the angle change and allowable rotation angle range in the component spatial position change description set may use different angle units, such as degrees and radians, a standardization conversion is performed based on the angle unit in the component spatial position change description set to unify the calculation standard. The standardized allowable rotation angle ranges of all components are organized into a standardized angle constraint range set, which is stored in a suitable data structure, such as a list nested dictionary. Each dictionary contains information such as component identifier, adjacent component identifier, and standardized allowable rotation angle range of the relative angle constraint dimension.

[0124] Step S4435: For the load transfer constraint dimension in the connection constraint dimension decomposition result, extract the allowable load transfer type of the corresponding component during the rotation period, match the load tolerance information in the inherent attribute entries of the corresponding component in the bridge full-element BIM model, verify the compatibility between the allowable load transfer type and the component load tolerance capacity, and generate load constraint matching results.

[0125] In the load transfer constraint dimension of the connection constraint dimension decomposition results, the allowable load transfer type of the corresponding component during the rotation period is extracted. The allowable load transfer type can include tension, compression, torque, etc. The inherent attribute entries of the corresponding component are obtained from the bridge's full-element BIM model. These inherent attribute entries contain the component's load tolerance information, such as maximum tensile force and maximum compressive force. The compatibility between the allowable load transfer type and the component's load tolerance capacity is verified, i.e., checking whether the allowable load type and magnitude are within the component's load tolerance range. For example, if the allowable load transfer type is tension, and the component's inherent attribute entry shows its maximum tensile force as a certain value, it is checked whether the allowable tensile force exceeds that value. The verification results are organized into load constraint matching results, which are stored in a suitable data structure, such as a list nested dictionary. Each dictionary contains information such as component identifier, adjacent component identifier, allowable load transfer type, load tolerance information, and compatibility verification results.

[0126] Step S4436: Align and integrate the standardized position constraint range set, standardized angle constraint range set, and load constraint matching results by time period, arrange the multi-dimensional information of each connection constraint in the order of component, adjacent component, and rotation time period, mark the adaptation status of each constraint dimension, and generate a connection constraint description set containing multi-dimensional constraint content.

[0127] To comprehensively consider the multi-dimensional information of inter-component connection constraints, it is necessary to integrate the standardized set of positional constraint ranges, the standardized set of angle constraint ranges, and the load constraint matching results. First, time period alignment is performed to ensure that the constraint information of each component and its adjacent components corresponds within the same rotation time period. Then, the multi-dimensional information of each connection constraint is arranged sequentially in the order of component, adjacent component, and rotation time period. For each connection constraint, the adaptation status of each constraint dimension is marked, which can be categorized as "fitted" or "out of range." For example, if the spatial position change of a component is within the range specified by the standardized set of positional constraint ranges, the adaptation status of the spatial position constraint dimension is marked as "fitted"; if it exceeds the range, it is marked as "out of range." The integrated multi-dimensional constraint information is then organized into a connection constraint description set containing multi-dimensional constraint content. This set is stored using a suitable data structure, such as a list nested dictionary. Each dictionary contains information such as component identifier, adjacent component identifier, rotation time period, spatial position constraint dimension information and adaptation status, relative angle constraint dimension information and adaptation status, and load transfer constraint dimension information and adaptation status.

[0128] Step S444: Perform constraint matching between the standardized set of positional changes and the set of connection constraint descriptions, determine whether the positional changes of the components exceed the allowable range of the connection constraints of adjacent components, and generate constraint matching results.

[0129] The standardized set of positional changes is matched with a set of connection constraint descriptions containing multi-dimensional constraints. For each component's positional change in the standardized set, the multi-dimensional constraint information of its adjacent components in the connection constraint description set is used to determine whether the component's positional change exceeds the allowable range of the adjacent components' connection constraints. The judgment is made separately for three dimensions: spatial position constraints, relative angle constraints, and load transfer constraints. For spatial position constraints, the component's positional change is compared with the allowable displacement range specified in the standardized set of positional constraints; for relative angle constraints, the component's angle change is compared with the allowable rotation angle range specified in the standardized set of angle constraints; for load transfer constraints, the load transfer type and magnitude are determined based on the load constraint matching results. If the constraint range is exceeded in any dimension, the component's positional change is considered to exceed the allowable range of the connection constraints of adjacent components. The constraint matching results of each component with its adjacent components are compiled into a constraint matching result, which is stored in a suitable data structure, such as a list nested dictionary. Each dictionary contains a component identifier, adjacent component identifiers, constraint matching status (out of range or not out of range), and specific dimensional information of the exceeded constraint.

[0130] Step S445: For cases where the constraint matching results exceed the allowable range, calculate the magnitude of the component position change exceeding the constraint range and quantify it as an impact value. For cases where the range is not exceeded, mark the impact value as zero.

[0131] Based on the constraint matching results, for cases exceeding the allowable range, it is necessary to calculate the magnitude of the component position change exceeding the constraint range. For the spatial position constraint dimension, if the component's position change exceeds the allowable displacement range specified by the standardized position constraint range set, the excess distance is calculated. For the relative angle constraint dimension, if the component's angle change exceeds the allowable rotation angle range specified by the standardized angle constraint range set, the excess angle is calculated. For the load transfer constraint dimension, if the allowable load transfer type and magnitude are exceeded, the excess load amount is calculated. These excess magnitudes are quantified into impact values. For example, they can be converted into a numerical value based on the magnitude of the excess distance, angle, or load amount; a larger value indicates a more severe impact. For cases not exceeding the range, the impact value is marked as zero. The impact values ​​of each component and its adjacent components are compiled into a set, stored using a suitable data structure, such as a list nested with dictionaries. Each dictionary contains information such as component identifier, adjacent component identifier, and impact value.

[0132] Step S446: Organize the influence degree values ​​of each component on its adjacent components, arrange them in the order of components and adjacent components, generate a set of component connection influence degree descriptions, and quantify the influence range.

[0133] The influence values ​​of each component on its adjacent components are organized and arranged according to the order of the components and their adjacent components. First, they are sorted by component identifier; within the same component, they are then sorted by the identifiers of adjacent components. This makes the data more organized and easier to view and analyze. The organized influence value information is then compiled into a description set of the influence of component connections. This set is stored using a suitable data structure, such as a list nested with dictionaries, where each dictionary contains information such as component identifier, adjacent component identifier, and influence value. Through this description set, the degree of influence of each component's positional change on its adjacent components can be clearly seen, quantifying the scope of the impact of positional changes between components.

[0134] Step S450: Based on the component connection influence description set, the spatial position of adjacent components is adjusted synchronously. The adjustment range is proportional to the change of the deformation acquisition value of the corresponding component, so that the spatial connection relationship between components meets the position requirements after deformation.

[0135] The component connection influence description set clarifies the degree of impact of each component's positional change on adjacent components, and based on this, the spatial positions of adjacent components are adjusted synchronously. For each component and its adjacent components, the spatial position adjustment range of adjacent components is determined according to the influence degree value in the component connection influence description set and the corresponding component's deformation acquisition value change. The adjustment range is proportional to the corresponding component's deformation acquisition value change; that is, the greater the deformation acquisition value change, the greater the adjustment range of adjacent components. When adjusting the spatial positions of adjacent components, the connection method and mechanical relationship between components must be considered to ensure that the adjusted spatial positions conform to physical laws and actual conditions. According to the calculated adjustment range, the spatial positions of adjacent components are modified so that the spatial connection relationship between components conforms to the positional requirements after deformation, ensuring the stability and safety of the bridge structure during rotation.

[0136] Step S460: Synchronize the adjusted spatial positions and spatial connections of the components to the bridge full-element BIM model, update the spatial coordinates and connection constraint information of the components in the model, and generate an iteratively updated bridge BIM model.

[0137] After adjusting the spatial positions of adjacent components, the adjusted component spatial positions and spatial connections are synchronized to the bridge's full-element BIM model. Using the interface or methods provided by the model management software, the adjusted component spatial coordinate information is updated to the corresponding component attribute configuration nodes in the model. Simultaneously, the connection constraint information in the model is updated, as adjustments to component positions may cause changes in connection constraints. For example, if the distance between two components changes, their spatial position constraints and relative angle constraints may need to be adjusted accordingly. The updated model information is saved, generating an iteratively updated bridge BIM model. The iteratively updated bridge BIM model reflects the latest component spatial positions and connection relationships during the bridge's rotation process.

[0138] Step S500: Based on the iteratively updated bridge BIM model, extract the deformation degree, spatial posture and connection status between components during the bridge rotation process, integrate them to obtain a dynamic visualization carrier, and generate dynamic visual monitoring results of the bridge rotation process.

[0139] In one implementation, step S500 may specifically include the following steps S510-S560:

[0140] Step S510: Extract the spatial location information of each component from the iteratively updated bridge BIM model, synchronously match the action trigger nodes during the bridge rotation process, label the spatial location information of each time period with the corresponding action trigger mark, and generate a temporal sequence of component spatial locations with action marks.

[0141] Spatial location information for each component is extracted from the iteratively updated bridge BIM model. This spatial location information can be represented by three-dimensional coordinates, reflecting the component's specific position in space. Simultaneously, action trigger nodes during the bridge's rotation process are acquired. These trigger nodes are pre-defined actions that are triggered at specific moments or under predetermined conditions during the rotation, such as acceleration, deceleration, and turning. The spatial location information of each time period is synchronously matched with the action trigger nodes to determine the corresponding action triggering situation for each time period. A corresponding action trigger marker is added to the spatial location information for each time period; this marker can be a specific action name or number. The spatial location information of the components with action trigger markers is arranged chronologically to generate a temporal sequence of component spatial locations with action trigger markers. This sequence is stored using a suitable data structure, such as a list nested with dictionaries, where each dictionary contains information such as time period number, component identifier, spatial location information, and action trigger marker.

[0142] Step S520: Extract the spatial orientation information of each component from the iteratively updated bridge BIM model, combine it with the action trigger markers of the corresponding time period, mark the action adaptation description of the spatial orientation information of each time period, generate the component spatial orientation time sequence with action descriptions, and keep the time period aligned with the component spatial position time sequence with action markers.

[0143] Spatial orientation information for each component is extracted from the iteratively updated bridge BIM model. This spatial orientation information can be represented by a direction vector or angle, describing the component's orientation in space. Combined with the action trigger markers in the component spatial position time series with action tags for the corresponding time period, action adaptation descriptions are added to the spatial orientation information for each time period. These action adaptation descriptions explain the reasons and characteristics of the changes in the component's spatial orientation under the triggered action. The component spatial orientation information with action adaptation descriptions is arranged chronologically to generate a component spatial orientation time series with action descriptions. This series is ensured to be time-aligned with the component spatial position time series with action tags, meaning that the information for the same time period in both series corresponds to each other. This ensures that the spatial position and spatial orientation information of the components can be accurately associated during visualization, reflecting the true state of the components under different rotational actions. This series is stored using a suitable data structure, such as a list nested dictionary, where each dictionary contains information such as time period number, component identifier, spatial orientation information, and action adaptation description.

[0144] Step S530: Extract the spatial connection status information between each component and its adjacent components from the iteratively updated bridge BIM model, match the action trigger markers for the corresponding time period, label the connection status information for each time period with action impact descriptions, generate a time sequence of connection status between components with impact descriptions, and keep the time period synchronized with the previous two time sequences.

[0145] The spatial connection status information of each component and its adjacent components is extracted from the iteratively updated bridge BIM model. This information includes the connection method, connection strength, and relative positional relationship between components. Action trigger markers in the spatial position time sequence of components with action markers are matched to the corresponding time period, and an action impact description is added to the connection status information for each time period. The action impact description explains the changes in the connection status between components under the triggering action. The connection status information of components with action impact descriptions is arranged chronologically to generate a time sequence of connection status between components with impact descriptions. This sequence is ensured to be synchronized with the time sequence of component spatial position with action markers and the time sequence of component spatial orientation with action descriptions, meaning that the information for the same time period in the three sequences corresponds to each other. This allows for a comprehensive visualization of the changes in the spatial position, spatial orientation, and connection status of components during bridge rotation. This sequence is stored using a suitable data structure, such as a list nested dictionary, where each dictionary contains time period number, component identifier, adjacent component identifier, spatial connection status information, and action impact description.

[0146] Step S540: Calculate the time-period correlation degree for the component spatial position time sequence with action markers, the component spatial orientation time sequence with action descriptions, and the component connection state time sequence with influence descriptions. Weight and integrate the state information of each time period according to the correlation degree value to generate a time-period weighted multi-dimensional rotation state time sequence set.

[0147] The time-series correlation of component spatial positions marked with action markers, component spatial orientations marked with action descriptions, and component connection states marked with influence descriptions is calculated. Time-series correlation reflects the relevance and importance of information within the same time period. Multiple factors can be considered when calculating time-series correlation, such as the consistency of action trigger markers and the degree of mutual influence of component state changes. For example, if in a certain time period, the action trigger markers in all three time series indicate the same action, and the changes in component spatial position, spatial orientation, and connection state are closely related, then the correlation of that time period is high. Based on the calculated correlation values, the state information of each time period is weighted and integrated. Time periods with high correlation are given higher weights, meaning that the information in that time period has a greater impact on the overall rotation state; time periods with low correlation are given lower weights. During weighted integration, the information in the same time period within each time series is comprehensively calculated according to weights, for example, by weighting the component spatial position, spatial orientation, and connection state information. The weighted and integrated multi-dimensional rotation status information for each time period is arranged in chronological order to generate a time-weighted multi-dimensional rotation status time series set. This set is stored in a suitable data structure, such as a list nested dictionary, where each dictionary contains the time period number, comprehensive multi-dimensional rotation status information, etc.

[0148] Step S550: Convert the time-weighted multi-dimensional rotating state time series into a dynamically visualized frame sequence, adjust the generation density of the frames according to the correlation, and generate a dynamically density-adjusted frame sequence.

[0149] In one implementation, step S550 may specifically include the following steps S551 to S556:

[0150] Step S551: Perform time-segment clustering on the multi-dimensional rotation state time series set weighted by time period. Divide the rotation time period into multiple cluster groups according to the type of action trigger mark. Each cluster group corresponds to the same type of rotation action, and generate action type clustering results.

[0151] The purpose of time-weighted multi-dimensional rotation state time series is to perform time-segment clustering to group rotation time series with the same action trigger marker type into one category. The time-segment weighted multi-dimensional rotation state time series is traversed, and rotation time series are classified according to their action trigger marker types. Each cluster group corresponds to the same type of rotation action, thus dividing the rotation process according to different action types, facilitating the design of visualization templates for different action types. The classified cluster group information is then organized into action type clustering results, which are stored in a suitable data structure, such as a dictionary, where the key is the action trigger marker type and the value is a list of time series numbers containing that type of action trigger marker.

[0152] Step S552: For each action type cluster, extract the multi-dimensional state features of the time period within the group, and generate a visualization template adapted to the action type. The template includes differentiated settings for component display priority, connection status display position, and orientation mark style.

[0153] For each cluster in the action type clustering results, multi-dimensional state features of the time period within the group are extracted. These features include information such as the spatial location, orientation, and connection status of components. Based on these features, a visualization template adapted to the action type is generated. The template is customized with different settings for component display priority, connection status display position, and orientation marker style. For component display priority, components are ranked according to their importance and influence within the action type, with higher-importance components displayed first. For example, in the "turn" action, components near the turning center may have a higher display priority. For connection status display position, the appropriate location for displaying connection status information on the visualization interface is determined based on the characteristics and changes in the connection relationships between components. For orientation marker style, different marker styles are designed based on the spatial orientation changes of components, such as arrow length, color, and shape, to more intuitively display the orientation changes of components. The generated visualization templates for each action type are compiled into a set, stored using a suitable data structure, such as a dictionary, where the key is the action trigger marker type and the value is the corresponding visualization template information.

[0154] Step S553: ​​Map the state information of each time period in the time-weighted multi-dimensional rotation state time sequence set to the visualization display template of the corresponding action type cluster group, fill in the spatial position, orientation and connection state information of the component according to the template setting requirements, and generate the single time period template filling result.

[0155] In one implementation, step S553 may specifically include the following steps S5531 to S5536:

[0156] Step S5531: Perform coordinate standardization processing on the state information of each time period in the time-weighted multi-dimensional rotating state time series set, convert the component spatial position information into a canvas coordinate format consistent with the visualization display template, and generate standardized component spatial position information.

[0157] The state information of each time period in the time-weighted multi-dimensional rotating state time series is standardized using coordinates. Since the spatial location information of components in the time-weighted multi-dimensional rotating state time series may use different coordinate systems and unit formats, while the visualization template has a set canvas coordinate format, coordinate transformation is required to ensure compatibility. The spatial location information of components is converted from its original coordinate system and unit format to a canvas coordinate format consistent with the visualization template. For example, if the original spatial location information uses a geodetic coordinate system, while the canvas coordinate format of the visualization template is pixel coordinates, then the geodetic coordinates need to be converted to pixel coordinates using a coordinate transformation formula. During the transformation process, factors such as the position of the coordinate origin, the direction of the coordinate axes, and the scale relationship must be considered. The standardized spatial location information of the components is then organized into a set, which is stored using a suitable data structure, such as a list nested with dictionaries. Each dictionary contains a time period number, component identifier, and standardized spatial location information.

[0158] Step S5532: Divide the standardized component spatial location information into component hierarchical levels. According to the role of the component in the rotation movement, divide the component into core components and auxiliary components, and generate the component hierarchical division result.

[0159] The spatial location information of standardized components is used to classify them into hierarchical levels. Based on their role in the rotation process, components are divided into core components and auxiliary components. Core components play a crucial role in the rotation process and significantly impact its stability and safety, such as the main structural beams and piers of a bridge. Auxiliary components provide support, connection, or auxiliary functions to the core components, such as connectors and supporting structures. When classifying component levels, bridge design drawings and mechanical analysis results can be referenced, combined with the characteristics of the rotation process. For example, in a rotation process, components directly involved in the rotation may be classified as core components, while components providing fixation and support are classified as auxiliary components. The resulting component level information is organized into a component level classification result, which is stored using a suitable data structure, such as a dictionary, where the key is the component identifier and the value is the component level (core component or auxiliary component).

[0160] Step S5533: For the core component display area in the visualization template, fill in the standardized component spatial location information and component spatial orientation information with action descriptions for the corresponding time period, and draw the core component graphics and orientation labels according to the style specified in the template.

[0161] For the core component display area in the visualization template, standardized component spatial location information and component spatial orientation information with action descriptions for the corresponding time period are filled into this area. Based on the component hierarchy, the identifier of the core component is determined. The spatial location information of the corresponding core component is obtained from the standardized component spatial location information set, and the spatial orientation information of the corresponding core component is obtained from the temporal sequence of component spatial orientations with action descriptions. The core component graphics and orientation labels are drawn according to the style specified in the visualization template. The style specified in the visualization template includes the shape, color, and size of the graphics, and the orientation labels can be arrows, symbols, etc. For example, for a core component, a graphic of the corresponding shape and size is drawn in the core component display area based on its spatial location information, and an arrow with a set direction and style is drawn to indicate its orientation based on its spatial orientation information. In this way, the spatial location and orientation of the core component during the specified time period are intuitively displayed on the visualization interface.

[0162] Step S5534: For the auxiliary component display area in the visualization template, fill in the standardized component spatial location information and component spatial orientation information with action descriptions for the corresponding time period, and draw auxiliary component graphics and orientation labels according to the style specified in the template.

[0163] For the auxiliary component display area in the visualization template, similar operations are performed as for the core components. Based on the component hierarchy, the identifiers of the auxiliary components are determined. The spatial position information of the corresponding auxiliary components is obtained from the standardized component spatial position information set, and the spatial orientation information of the corresponding auxiliary components is obtained from the component spatial orientation time sequence with action descriptions. The auxiliary component graphics and orientation labels are drawn according to the style specified in the visualization template. The style and size of the auxiliary component graphics may differ from those of the core components to reflect their auxiliary role. For example, the auxiliary component graphics can be drawn relatively small and in lighter colors. The orientation labels are also drawn based on the spatial orientation information to show the changes in the spatial orientation of the auxiliary components. By filling and drawing information in the auxiliary component display area, the spatial position and orientation of all bridge components during that time period are fully presented.

[0164] Step S5535: For the connection status display position in the visualization display template, fill in the connection status information between components with the corresponding time period and the impact description, draw the connection line between components according to the style specified in the template, and mark the status change description caused by the action.

[0165] For the connection status display positions in the visualization template, the connection status information between components for the corresponding time period is obtained from the time sequence of connection status between components with impact descriptions. This information is then filled into the connection status display positions, and connection lines between components are drawn according to the style specified in the visualization template. The style of the connection lines can be designed according to different connection statuses, such as line thickness, color, and solid / dashed lines. Simultaneously, descriptions of status changes caused by actions are added. These descriptions are textual descriptions generated based on action trigger markers and changes in connection status, such as "Due to acceleration, the tension at this connection point increases." By drawing connection lines and adding descriptions of status changes, the connection status between components and the impact of actions on the connection status are visually displayed on the visualization interface.

[0166] Step S5536: Perform inter-layer alignment verification on the completed core component graphics, auxiliary component graphics, and connecting lines. Check the position of different component graphics and the correspondence of the endpoints of the connecting lines, adjust the graphic elements with alignment deviations, and generate the single-time template filling result.

[0167] After completing the drawing of the core component graphics, auxiliary component graphics, and connecting lines, inter-layer alignment verification is performed. This involves checking whether the positions of different component graphics accurately correspond, and whether the endpoints of the connecting lines match the positions of their respective component graphics. For example, it checks whether the endpoints of the connecting lines accurately connect to their corresponding component graphics, and whether the relative positions between different component graphics conform to the actual situation. If any graphic elements with alignment deviations are found, such as a component graphic being offset or the endpoints of connecting lines being inaccurate, adjustments are made accordingly. During adjustment, the coordinates of the graphic elements can be modified according to the magnitude and direction of the deviation. The adjusted graphic element information is then organized into a single-time-period template filling result. This result is stored using a suitable data structure, such as a dictionary containing information on graphic element coordinates, styles, and status descriptions, providing accurate single-time-period visualization information for the subsequent generation of dynamic visualization frame sequences.

[0168] Step S554: For the single-period template filling result, match the action impact description of the corresponding period. If the status information indicates an action impact causing status change, add an anomaly marker at the corresponding position in the template to generate a single-period display result with an anomaly marker.

[0169] For the single-period template filling results, the action impact descriptions for the corresponding time periods are matched from the time sequence of the connection states between components with impact descriptions. The connection state information is checked for any state anomalies caused by action impacts, such as increased tension at the connection or loosening of the connection. If state anomalies exist, an anomaly marker is added to the corresponding position in the visualization template of the single-period template filling results. The anomaly marker can be a special symbol, color change, or flashing effect to attract the user's attention. For example, if a connection is marked with the state anomaly description "Connection loosened due to turning action," a flashing red exclamation mark is added to the visualization display position of that connection as an anomaly marker. The single-period display results after adding anomaly markers are then organized to generate single-period display results with anomaly markers. This result is stored in an appropriate data structure, such as a dictionary containing graphic element information and anomaly marker information, enhancing the alertness and readability of the visualization display.

[0170] Step S555: Perform time period density adaptation on the single-time period display results with anomaly markers. For time periods with correlation greater than a preset threshold, extract key nodes of state change from the single-time period display results, supplement and generate intermediate state display results, increase the number of frames in that time period, and generate a density-adapted single-time period frame set.

[0171] For single-period display results with anomaly indicators, time-period density adaptation is performed. A preset threshold is set to determine the correlation between time periods. Correlation reflects the importance and degree of change of the time period during the rotation process. For time periods with a correlation greater than the preset threshold, it indicates that the rotation state changes significantly during that time period, requiring a more detailed display of the process. Key nodes of state change are extracted from the single-period display results. Key nodes refer to moments within that time period when the spatial position, spatial orientation, or connection state of the components undergoes significant changes. Based on the information from the key nodes, intermediate state display results are supplemented and generated. For example, intermediate states between key nodes are estimated through interpolation calculations or physical simulations, and then corresponding display results are generated according to the visualization display template. The number of frames in that time period is increased, and the supplemented intermediate state display results are inserted into the original single-period display results to form a density-adapted single-period frame set. This frame set is stored using a suitable data structure, such as a list containing multiple single-period display results, with each display result representing a frame, providing richer frame information for dynamic visualization and making the rotation process display smoother and more detailed.

[0172] Step S556: Arrange all density-adapted single-time frame sets according to the rotation time sequence to generate a frame sequence with dynamic density adjustment.

[0173] All density-adapted single-time frame sets, after time-period density adaptation processing, are arranged according to the rotation time period. Following the chronological order of the rotation time periods, the frame sets of each time period are sequentially connected to form a continuous frame sequence. During the arrangement process, the frame order must be ensured to guarantee the correct temporal sequence for dynamic visualization. The arranged frame sequence is then organized into a dynamically density-adjusted frame sequence, stored using a suitable data structure, such as a list containing multiple single-time frame sets, each containing multiple frame information for that time period. The dynamically density-adjusted frame sequence adjusts the frame generation density based on the correlation and state changes of different time periods during the rotation process, more effectively displaying the dynamic changes of the bridge rotation process and providing complete frame data for the final generation of dynamic visual monitoring results of the bridge rotation process.

[0174] Step S560: Perform time-smooth transition processing on the frame sequence with dynamic density adjustment, supplement intermediate frames for state transition between adjacent frames, encapsulate the processed frame sequence into a dynamic visualization carrier, and generate dynamic visual monitoring results of the bridge rotation process based on the dynamic visualization carrier.

[0175] The frame sequence with dynamically adjusted density undergoes time-smooth transition processing to make state changes between adjacent frames more natural and fluid. Intermediate frames are added between adjacent frames to facilitate this transition. These intermediate frames can be generated using interpolation algorithms. Based on information such as the spatial position, orientation, and connection status of components in adjacent frames, the state information at intermediate moments is calculated, and then the intermediate frames are generated according to a visualization template. For example, if the spatial position of a component changes between two adjacent frames, the spatial position of that component at the intermediate moment is calculated using linear interpolation, and the corresponding visualization result is then generated as an intermediate frame. The frame sequence after adding intermediate frames is encapsulated into a dynamic visualization carrier, which can be in the form of a video file, animation file, or interactive visualization interface. Based on this dynamic visualization carrier, dynamic visual monitoring results of the bridge rotation process are generated. These results can intuitively and dynamically display the deformation degree, spatial orientation, and changes in the connection status between components during the bridge rotation process.

[0176] Please see Figure 2 , Figure 2This is a schematic diagram of a computer system provided in an embodiment of the present invention. The computer system 100 includes at least a processor 101, a communication interface 102, and a memory 103. The processor 101, communication interface 102, and memory 103 can be connected via a bus or other means. The processor 101 (or Central Processing Unit, CPU) is the computing and control core of the computer system, capable of parsing various instructions and processing various data within the computer system. The communication interface 102 may optionally include standard wired interfaces or wireless interfaces (such as Wi-Fi, mobile communication interfaces, etc.), and can be used for sending and receiving data under the control of the processor 101; the communication interface 102 can also be used for data transmission and interaction within the computer system. The memory 103 is a memory device in the computer system used to store programs and data. It is understood that the memory 103 here can include the computer system's built-in memory, or it can include extended memory supported by the computer system. The memory 103 provides storage space, which stores the computer system's operating system; this invention does not limit this.

[0177] In one embodiment, the processor 101 executes the BIM-based bridge rotation visual monitoring method provided above in the embodiments of the present invention by running a computer program in the memory 103.

Claims

1. A BIM-based visual monitoring method for bridge rotation, characterized in that, The method includes: The system acquires structural deformation monitoring data at each monitoring point during the bridge rotation process in real time and retrieves the pre-built corresponding full-element BIM model of the bridge. The structural deformation monitoring data includes the point deformation collection values ​​at each time period of the bridge rotation, and the full-element BIM model of the bridge includes the spatial location code, preset geometric boundary and inherent attribute entries of each component of the bridge. Based on the spatial location coding of each component in the full-element BIM model of the bridge, the structural deformation monitoring data is mapped and associated with the corresponding components one by one, and a unique mapping relationship between each component and the structural deformation monitoring data of the corresponding time period is established to obtain the component-monitoring data mapping relationship set. Based on the component-monitoring data mapping relationship set, the preset geometric boundary and the inherent attribute entries of the corresponding components in the bridge full-element BIM model are extracted. The abnormal collection values ​​in the structural deformation monitoring data are located and calibrated using the preset geometric boundary as a reference, so as to obtain the calibrated component deformation collection value set. The calibrated component deformation acquisition value set is matched to the corresponding component attribute configuration node of the bridge full-element BIM model, and the spatial connection relationship between components is synchronously adjusted according to the change amplitude of the calibrated component deformation acquisition value to obtain the iteratively updated bridge BIM model. Based on the iteratively updated bridge BIM model, the deformation degree, spatial posture, and connection status between components of the corresponding components during the bridge rotation process are extracted, and integrated to obtain a dynamic visualization carrier, generating dynamic visual monitoring results of the bridge rotation process.

2. The method of claim 1, wherein, Based on the spatial location coding of each component in the full-element BIM model of the bridge, the structural deformation monitoring data is mapped and associated with the corresponding components one by one to establish a unique mapping relationship between each component and the structural deformation monitoring data of the corresponding time period, resulting in a component-monitoring data mapping relationship set, including: For each deformation acquisition value at a given point in the structural deformation monitoring data, a rotation time stamp is embedded, and the acquisition time of each deformation acquisition value at a given point is correlated with the time period division node of the bridge rotation, thereby generating a time period embedded deformation acquisition value set with a unique identifier for the rotation time period. The spatial location codes of each component in the full-element BIM model of the bridge are extended with a time period dimension. A time period code suffix corresponding to the rotation time period is added to the original spatial location codes to generate an extended spatial location code set with a time period dimension, thus completing the deep binding between the component location code and the rotation time period. The time period embedded deformation acquisition value set and the extended spatial location code set are matched in a time period-space dual dimension. According to the correspondence between the time period identifier and the time period code suffix, each acquisition value is bound to the component extended location code of the corresponding time period to generate a preliminary binding relationship entry. The initial binding relationship entries are checked for duplicate binding within a time period. All initial binding relationship entries under the same rotation time period are traversed to identify duplicate binding situations where multiple collected values ​​correspond to the same component, and the index of the duplicate binding entries is recorded. For the index of the duplicated entries, extract the deformation collection values ​​of multiple points in the corresponding time period and determine the homogeneity within the time period. Merge the duplicate collection values ​​collected from the same monitoring point and retain the collection value at the most recent time. The collection values ​​that are not homogeneous are used to supplement the newly added component binding entries. All binding relationship entries that have been investigated and resolved are sorted and arranged according to the rotation period and the spatial location code of the component, generating a structurally regular set of component-monitoring data mapping relationships.

3. The method of claim 2, wherein, The step involves performing a time-space dual-dimensional matching between the embedded deformation data set and the extended spatial location code set, and binding each data set to the corresponding extended location code of the component within the same time period according to the correspondence between the time period identifier and the time period code suffix, thereby generating an initial binding relationship entry, including: The format of each time period identifier in the time period embedded deformation acquisition value set is standardized, and the time period identifier is converted into a format consistent with the time period code suffix in the extended spatial location code set, thereby generating a standardized time period identifier set with a unified format. Perform time period range parsing on each time period code suffix in the extended spatial location code set to determine the start and end times of the rotation time period corresponding to each time period code suffix, and generate a time period range parsing result set; The standardized time period identifier set is matched with the time period range parsing result set to determine whether the collection time corresponding to each time period identifier is within the time period range of the corresponding time period code suffix, and a time period range matching result is generated. For the successfully matched entries in the time period range matching results, extract the corresponding collected values ​​and perform code prefix matching with the extended spatial location code of the component to determine whether the monitoring point of the collected values ​​is within the spatial coverage of the component, and generate code prefix matching results; For the entries that successfully match in the encoding prefix matching results, the collected values ​​are bound to the extended spatial location code of the component to generate a single binding relationship entry, so that each entry is compliant in both time period and spatial matching; All compliant single binding relationship entries are summarized and arranged in the order of rotation time period and extended spatial position code of the component to generate the preliminary binding relationship entries.

4. The method of claim 3, wherein, For the successfully matched entries in the time period range matching results, the corresponding collected values ​​are extracted and matched with the extended spatial location code of the component to determine whether the monitoring point of the collected value is within the spatial coverage area of ​​the component, and the code prefix matching result is generated, including: Extract the preset geometric boundaries of the corresponding components from the full-element BIM model of the bridge, convert the preset geometric boundaries into quantifiable spatial coordinate ranges, and generate a set of component spatial coordinate ranges; The coordinates of the monitoring points corresponding to the collected values ​​are extracted from the set of deformation data embedded in the time period. The coordinates of the monitoring points are converted into a coordinate format consistent with the set of spatial coordinate ranges of the components to generate a standardized set of monitoring point coordinates. The coordinate positions of the standardized monitoring point coordinate set are compared with the spatial coordinate range set of the components to determine whether the coordinates of each monitoring point fall within the spatial coordinate range of the corresponding component, and a coordinate position comparison result is generated. For entries falling within the range in the coordinate position comparison results, the extended spatial position code prefix of the corresponding component is extracted, and consistency verification is performed with the area code of the monitoring point corresponding to the collected value to generate a code prefix verification result. For entries that pass the encoding prefix verification, they are marked as encoding prefix matching successful; for entries that fail the verification, they are marked as encoding prefix matching failed, and a matching status mark set is generated. The coordinate position comparison results, the encoding prefix verification results, and the matching status marker set are integrated to generate the encoding prefix matching results, so as to determine the matching status and basis of each entry.

5. The method of claim 1, wherein, Based on the component-monitoring data mapping relationship set, the preset geometric boundaries and inherent attribute entries of the corresponding components in the bridge full-element BIM model are extracted. Using the preset geometric boundaries as a reference, abnormal collected values ​​in the structural deformation monitoring data are located and calibrated to obtain a calibrated set of component deformation collected values, including: Based on the component-monitoring data mapping relationship set, the preset geometric boundary and the inherent attribute entries corresponding to each component are extracted from the bridge full-element BIM model. The preset geometric boundary is converted into a quantifiable spatial range description, and a component spatial range-attribute association set is generated. The structural deformation monitoring data of each time period in the component-monitoring data mapping relationship set is compared with the corresponding component spatial range in the component spatial range-attribute association set to determine whether the monitoring point corresponding to the collected value exceeds the spatial range description of the component, and a spatial location comparison result is generated. The spatial position comparison results are used to identify continuous deviations over time periods. Cases in which the collected values ​​of the same component exceed the spatial range description for multiple consecutive rotation periods are marked. The start and end times of the continuous deviations are recorded to determine the continuous characteristics of the deviations. For the continuously deviating marking results, the inherent attribute entries of the corresponding components are extracted, the intrinsic correlation between the inherent attribute entries and the deviation is analyzed, and combined with the changing trend of the collected values ​​over a continuous period, a preliminary judgment result of the cause of the deviation is generated; Based on the preliminary judgment results of the cause of the deviation, the continuously deviating collected values ​​are interpolated and corrected within the time period. With other normal collected values ​​of the same component in the same time period as a reference, the deviating collected values ​​are numerically adjusted to generate corrected deformation collected values. The corrected deformation acquisition values ​​are integrated with the acquisition values ​​not marked as deviations, and arranged according to the rotation time period and the order of components to generate the calibrated component deformation acquisition value set, so that the deformation acquisition value of each component conforms to its spatial range constraints.

6. The method according to claim 5, characterized in that, The process of identifying continuous deviations in the spatial position comparison results involves marking cases where the collected values ​​for multiple consecutive rotation periods of the same component exceed the spatial range description, recording the start and end times of the continuous deviation, and determining the persistence characteristics of the deviation, including: Extract all rotation time period deviation states of each component from the spatial location comparison results, combine them with the inherent attribute entries of the corresponding components in the bridge full-element BIM model, filter out the components whose inherent attributes contain rotation deformation sensitive annotations, and organize all time period deviation states of these components into a component time period deviation initial set. For each component entry in the initial screening set whose time period deviates from the component's time period, the deformation acquisition value of the point in the structural deformation monitoring data of the corresponding time period is matched, and the deviation status of each time period is bound to the acquisition environment label of the corresponding acquisition value to generate a time period acquisition value association set, so that the time period and the acquisition value correspond one-to-one. Traverse the associated set of collected values ​​for the time period, calculate the consistency of the deviation state between adjacent time periods for each component's consecutive time period entries, mark the entries with consecutive deviation states that exceed the spatial range description as suspected consecutive deviation sequences, and generate the time period deviation continuity discrimination result; For the suspected continuous deviation sequence in the time period deviation continuity discrimination result, the coordinates of the monitoring points of the corresponding time period collection values ​​are extracted, and a secondary coordinate comparison is performed with the preset geometric boundary of the corresponding component in the bridge full-element BIM model to verify the accuracy of the deviation state and generate a deviation time period boundary verification set. From the deviation time period boundary verification set, continuous time periods that still exceed the spatial range description after secondary comparison are selected, and the first time period of each continuous sequence is marked as the continuous deviation start time period and the last time period is marked as the continuous deviation end time period, generating continuous deviation time period marking results; For each continuous deviation sequence in the continuous deviation time period marking results, calculate the difference in the number of time periods between the start time period and the end time period, and combine it with the deformation sensitivity attribute annotation of the corresponding component to generate a deviation persistence feature description set containing time period length and deformation sensitivity association description, and determine the persistence feature of the deviation.

7. The method according to claim 6, characterized in that, The process involves traversing the associated set of collected values ​​for each time period, calculating the consistency of deviation states between adjacent time periods for each component's consecutive time period entries, marking entries where consecutive deviation states exceed the spatial range description as suspected consecutive deviation sequences, and generating time period deviation continuity discrimination results, including: The associated set of time period collection values ​​is split by component, and all rotation time period entries of each component are extracted separately and strictly sorted according to the rotation time sequence to generate the component time period sequence split result. For each component time period sequence in the component time period sequence splitting result, the deviation state of adjacent time periods is extracted in pairs. The deviation state of the previous time period and the deviation state of the next time period are combined to form a deviation state pair, generating a set of adjacent time period deviation pairs that covers all consecutive adjacent time periods. For each deviation state pair in the adjacent time period deviation pair set, the consistency degree is judged. If the deviation state of the preceding and following time periods is both described as exceeding the spatial range, it is marked as a consistent pair; otherwise, it is marked as a non-consistent pair. The proportion of consistent pairs in the time period sequence of each component is counted to generate the deviation state consistency degree result. For the continuous time segment in the deviation state consistency result where the proportion of consistent pairs reaches 100%, the complete segment from the start time of the first consistent pair to the end time of the last consistent pair is extracted, and these segments are marked as continuous deviation candidate sequences to generate a continuous deviation candidate sequence set. For each candidate sequence in the continuous deviation candidate sequence set, the inherent attribute entries of the corresponding component in the bridge full-element BIM model are combined to verify the matching of the component's rotation action type with the deviation sequence in the corresponding time period, filter out matching candidate sequences, and generate candidate sequence verification results. For the matching candidate sequences in the candidate sequence verification results, check the number of time periods covered by the sequence, mark the candidate sequences that cover three or more time periods as suspected continuous deviation sequences, organize all marked sequences and corresponding component information, and generate the time period deviation continuity discrimination result.

8. The method according to claim 1, characterized in that, The process of matching the calibrated component deformation acquisition value set to the corresponding component attribute configuration node of the bridge full-element BIM model, and synchronously adjusting the spatial connection relationship between components according to the change amplitude of the calibrated component deformation acquisition values, to obtain the iteratively updated bridge BIM model includes: Extract the deformation acquisition value corresponding to each component from the set of deformation acquisition values ​​of the calibrated components, perform node positioning matching with the attribute configuration node of the corresponding component in the full-element BIM model of the bridge, determine the attribute configuration node path corresponding to the deformation acquisition value of each component, and generate an attribute node-acquisition value correspondence table. Each deformation acquisition value in the calibrated component deformation acquisition value set is written into the attribute configuration node of the corresponding component, overwriting the preset deformation information in the original node, generating an attribute configuration node set with real-time deformation acquisition values, and completing the initial binding of acquisition values ​​with the BIM model. Extract the deformation acquisition value of each component from the attribute configuration node set with real-time deformation acquisition value, analyze the spatial position change of the component corresponding to the deformation acquisition value, generate a component spatial position change description set, and determine the position change of each component. By combining the description set of changes in the spatial position of the components with the spatial connection relationship between the components in the full-element BIM model of the bridge, the degree of influence of each component's position change on the spatial connection of adjacent components is calculated, a description set of the degree of influence of component connection is generated, and the scope of influence is quantified. Based on the description set of the degree of influence of component connection, the spatial position of adjacent components is adjusted synchronously. The adjustment range is proportional to the change of the deformation acquisition value of the corresponding component, so that the spatial connection relationship between components meets the position requirements after deformation. The adjusted spatial positions and spatial connections of the components are synchronized to the full-element BIM model of the bridge, and the spatial coordinates and connection constraint information of the components in the model are updated to generate the iteratively updated bridge BIM model.

9. The method according to claim 8, characterized in that, The method combines the description set of spatial position changes of the components with the spatial connection relationship between components in the full-element BIM model of the bridge to calculate the degree of influence of each component position change on the spatial connection of adjacent components, and generates a description set of the degree of influence of component connection, including: Extract the list of adjacent components for each component from the full-element BIM model of the bridge, determine the direct adjacent components of each component, and generate a list set of component adjacency relationships; Extract the spatial position change of each component from the set of component spatial position change descriptions, convert the spatial position change of each component into a unit format consistent with the spatial coordinates of adjacent components, and generate a standardized set of position change amounts. For each adjacent component of each component, extract the spatial connection constraints between the adjacent component and the component, determine the type of connection constraint and the allowable range of positional variation, and generate a connection constraint description set; The standardized set of position changes is matched with the set of connection constraint descriptions to determine whether the position change of the component exceeds the allowable range of the connection constraint of the adjacent component, and a constraint matching result is generated. For cases where the constraint matching results exceed the allowable range, the magnitude of the component position change exceeding the constraint range is calculated and quantified as an impact value. For cases where the position does not exceed the range, the impact value is marked as zero. The influence values ​​of each component on its adjacent components are organized and arranged in the order of the components and their adjacent components to generate a set of descriptions of the influence of component connections.

10. A computer system, characterized in that, include: A memory, wherein a computer program is stored; A processor is configured to load the computer program to implement the BIM-based bridge rotation visual monitoring method as described in any one of claims 1-9.

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