Arc beam construction structure stress real-time monitoring method and system

Abstract

The invention relates to the technical field of structural health monitoring, and discloses a real-time monitoring method and system for stress of an arc-shaped beam construction structure. The method comprises the steps of capturing an original stress fluctuation signal from a sensor network, extracting an energy peak value and an accumulated value of each slice after time domain slicing, judging a stress event boundary according to a combination relation, and generating an event record table. Construction stage segments are divided based on the table, event density and time intervals are counted, stress evolution tracks of all stages are described in combination with space coordinates, and an evolution distribution diagram is generated. And analyzing the distribution map, identifying a region where a stress track is converged or diverged, marking the region as a potential conduction hub, and constructing a stress conduction path radiating from the hub to the periphery by tracking the gradient change direction of a stress value to generate a stress conduction path topological structure. According to the invention, the stress event can be identified more accurately, and the conduction path and mechanism of the stress in the arc-shaped beam can be disclosed dynamically.

Description

Technical Field

[0001] This invention relates to the field of structural health monitoring technology, specifically to a method and system for real-time stress monitoring of curved beam construction structures. Background Technology

[0002] In the construction of complex structures such as curved beams, real-time and accurate monitoring of their internal stress state is crucial to ensuring construction safety and structural performance. Existing technologies typically achieve this monitoring by deploying sensor networks on the structure to continuously collect stress or vibration signals. For stress event identification, conventional methods mainly rely on setting fixed amplitude thresholds or performing simple signal filtering; when the signal amplitude exceeds the preset threshold, it is considered an event. This method is prone to misinterpreting transient noise spikes as valid events in environments with high noise levels and variable signal characteristics, or it fails to effectively capture slow stress changes with low amplitude but continuously accumulating energy, resulting in insufficient accuracy and completeness in event identification.

[0003] After obtaining discrete stress event data, existing analytical methods mostly focus on statically displaying the stress values ​​at monitoring points or generating stress cloud maps based on numerical interpolation. These methods can statically reflect the magnitude and spatial distribution of stress at a specific moment, but they cannot depict the continuous evolution trend of stress state over time, let alone reveal the dynamic transmission process of stress within the structural space. For structures like curved beams with nonlinear force flow paths, static distribution maps cannot clearly indicate the evolution source of stress concentration areas, nor can they determine how stress is transmitted from high-stress areas to other parts, resulting in an understanding of the overall mechanical behavior evolution of the structure remaining at a superficial level. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for real-time monitoring of stress in the construction structure of an arc-shaped beam, so as to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides a method for real-time stress monitoring of an arc-shaped beam construction structure, the method comprising: The original stress fluctuation signal is captured by the sensor network set on the arc beam structure. The original stress fluctuation signal is sliced ​​in the time domain. The energy peak value and energy accumulation value of the stress fluctuation in each time slice are extracted. The start and end boundaries of the stress event are determined according to the combination relationship of the energy peak value and energy accumulation value, and a stress occurrence event record table is generated. Based on the stress occurrence event record table, the time axis of the entire construction process is divided into multiple continuous construction stage segments. Within each construction stage segment, the density of stress occurrence events and the time interval between adjacent events are statistically analyzed. Combined with the spatial coordinate information of the curved beam, the evolution trajectory of stress on the structure within the construction stage segment is depicted, and a stress evolution distribution map of the construction stage is generated. The stress evolution distribution map of the construction stage is analyzed to identify spatial regions in the map where the stress evolution trajectory shows convergence or divergence characteristics. These spatial regions are marked as potential stress transmission hubs. By tracking the direction of change of stress value gradient, stress transmission paths radiating from potential stress transmission hubs to surrounding monitoring points are constructed, generating a stress transmission path topology.

[0006] Preferably, the stress event record table includes a unique identifier for the stress event, an event start time stamp, an event end time stamp, peak energy amplitude, and total cumulative energy; the stress evolution distribution map for the construction stage includes the construction stage number, a stress event density cloud map within the stage, the stage time span, and the structural spatial stress trajectory line; and the stress transmission path topology includes the transmission path identifier, the coordinates of the path's starting hub, the path node sequence, and the transmission direction between nodes.

[0007] Preferably, the steps for generating the stress evolution distribution map during the construction stage are as follows: Read the start and end timestamps of all events in the stress occurrence event record table. Based on the natural clustering of events on the time axis, define a continuous time interval with an event interval less than the construction stage division threshold as a construction stage segment, and assign a stage number to each construction stage segment. For each construction stage segment, retrieve all stress occurrence event records contained therein, extract the structural space coordinates corresponding to each event, calculate the number of stress events per unit area or unit length, and generate the stress event density distribution of the construction stage segment on the structure. Based on the stress event density distribution, points with similar densities and spatial continuity are connected to form a closed contour representing the stress activity area. The center position of the closed contour is traced between different construction stage segments to generate a stress evolution distribution map of the construction stage.

[0008] Preferably, the generation step of the stress transmission path topology is as follows: Analyze each closed contour in the stress evolution distribution diagram of the construction stage, calculate the gradient vector of the total cumulative energy of stress events at each point within the contour, identify streamlines in the gradient vector field that point clearly and converge at one or more points, and mark the convergence point of the streamlines as potential stress transmission hubs. Starting from each potential stress transmission hub, trace along the outward diverging gradient vector field streamline, record the location of each monitoring point along the streamline, and arrange these monitoring points in order of streamline direction to form a complete path from hub to end. Each complete path is assigned an independent identifier, the spatial coordinates of all nodes on the path and the directional relationships between nodes are recorded, all path information is summarized, and a stress transmission path topology is generated.

[0009] Preferably, the method further includes the following steps: The stress conduction path topology is matched with the real-time stress event record table to determine which stress conduction path a newly occurring stress event belongs to, and the relative position and energy contribution of the stress event on its respective path are calculated to generate a stress event-conduction path association mapping table. Based on the stress event and conduction path association mapping table, for each stress conduction path, the sum of the peak energy of all stress events flowing through the stress conduction path within the most recent evaluation time window and the frequency of event occurrence are counted to evaluate the current activity level and energy load level of the stress conduction path and generate a real-time status evaluation report of the path.

[0010] Preferably, the steps for generating the real-time status assessment report of the pathway are as follows: A sliding time window is set for each stress conduction path defined in the stress conduction path topology, and all stress occurrence events falling within the sliding time window are recorded in real time. Based on the stress event and conduction path association mapping table, all stress events belonging to the current evaluation conduction path are selected, and the sum of the energy peaks of these events is calculated as the energy load value within the window of the stress conduction path. At the same time, the number of events is counted as the event activity frequency within the window. The energy load value within the window is compared with a preset energy load threshold, and the event activity frequency within the window is compared with a preset activity frequency threshold. Based on the combined results of the two comparisons, it is determined whether the current conduction path is in an idle state, a normal load state, or an overload warning state, and a real-time status assessment report of the path is generated.

[0011] Preferably, the method further includes the following steps: Based on the real-time status assessment report of the transmission path, the transmission paths marked as overload warning status are monitored in a key manner. The historical stress release rate of each node on the transmission path is analyzed, the stress accumulation trend at the end of the path under the current load is predicted, and a stress release and guidance strategy for the transmission path is formed. Based on the stress relief and guidance strategy, the sampling frequency and signal gain of the key nodes in the transmission path of the sensing network are dynamically adjusted, and a series of auxiliary construction suggestion operation sequences for alleviating stress accumulation are generated.

[0012] Preferably, the steps for forming the stress relief and channeling strategy are as follows: For each conduction path marked as overload warning in the real-time status assessment report of the path, historical stress time history data of all nodes on the stress conduction path are extracted, and a curve model of stress value decay over time at each node during the stress release stage is fitted. Based on the curve model of all nodes, the stress wave propagation delay and release rate attenuation coefficient from the starting hub to the end node of the pathway are calculated, and the curve of stress accumulation at the end node over a period of time under the current continuous energy load input is simulated. Based on the stress accumulation curve of the end node obtained from the simulation in the future period, it is determined whether it will exceed the structural safety threshold. If it will exceed the threshold, the sequence or rate of upstream construction loading is planned to be adjusted, and a stress release and diversion strategy containing specific intervention timing and operation parameters is generated.

[0013] Preferably, the method further includes the following steps: The stress relief and channeling strategy is transformed into a specific monitoring task instruction set, which includes target conduction path identification, key node list, enhanced sampling parameters, and expected stress change pattern. The monitoring task instruction set is executed to enhance monitoring of the target conduction path, and the collected enhanced monitoring data is compared with the expected stress change pattern in real time. Based on the comparison results, the operating parameters in the stress release and venting strategy are dynamically fine-tuned to form a closed-loop control.

[0014] Preferably, when the processor executes the computer program, it implements the steps of the real-time stress monitoring method for the construction structure of the arc-shaped beam as described in any of the above-mentioned methods.

[0015] Compared with the prior art, the beneficial effects of the present invention are: By extracting the peak and cumulative energy values ​​of stress fluctuations within each time slice and determining the start and end boundaries of stress events based on their combined relationship, this method integrates information from both instantaneous impact intensity and sustained energy, enabling a more accurate distinction between real structural mechanical events and environmental noise. Compared to a single amplitude threshold criterion, it exhibits higher detection sensitivity and identification accuracy for both slowly accumulating stress changes and sudden load events, thus providing a more reliable and complete event sequence data foundation for subsequent analysis.

[0016] Based on the generated stress evolution distribution map during the construction phase, spatial regions exhibiting convergence or divergence characteristics in the stress evolution trajectory within the map are analyzed and marked as potential stress transmission hubs. By tracing the direction of stress value gradient changes from these hub points to surrounding monitoring points, radial stress transmission paths are actively constructed. Discrete spatial monitoring points are dynamically connected into a directional network topology, intuitively revealing the main transmission channels and key nodes of force flow during construction. This represents a deepening from static stress state description to dynamic transmission process reproduction, helping to identify risk transmission paths in advance and guide construction intervention. Attached Figure Description

[0017] Figure 1 This is a schematic diagram illustrating the working principle of the real-time stress monitoring method for the construction structure of the arc-shaped beam described in this invention. Figure 2 A flowchart for generating a stress evolution distribution diagram during the construction phase; Figure 3 This is a flowchart illustrating the correlation between stress events and conduction pathways, as well as the status assessment. Figure 4 This is a fitting diagram of stress release attenuation at the nodes of an arc-shaped beam. Figure 5 This is a stress timing monitoring diagram during the construction process of the curved beam. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Please see Figure 1This invention provides a method for real-time stress monitoring of an arc-shaped beam construction structure. The method includes: capturing raw stress fluctuation signals from a sensor network installed on the arc-shaped beam structure; performing time-domain slicing on the raw stress fluctuation signals; extracting the peak energy value and cumulative energy value of stress fluctuations within each time slice; determining the start and end boundaries of stress events based on the combination relationship between the peak energy value and the cumulative energy value; and generating a stress occurrence event record table. Based on the stress occurrence event record table, the time axis of the entire construction process is divided into multiple continuous construction stage segments. Within each construction stage segment, the density of stress occurrence events and the time interval between adjacent events are statistically analyzed. Combined with the spatial coordinate information of the arc-shaped beam, the evolution trajectory of stress on the structure within the construction stage segment is depicted, generating a stress evolution distribution map of the construction stage. The stress evolution distribution map of the construction stage is analyzed to identify spatial regions in the map where the stress evolution trajectory exhibits convergence or divergence characteristics. These spatial regions are marked as potential stress transmission hubs. By tracking the direction of change of stress value gradient, a stress transmission path radiating from the potential stress transmission hub to surrounding monitoring points is constructed, generating a stress transmission path topology.

[0020] Example 1: The stress event record table includes a unique identifier for each stress event, an event start time stamp, an event end time stamp, peak energy amplitude, and total cumulative energy. The stress evolution distribution map during the construction phase includes the construction phase number, a stress event density cloud map within the phase, the phase time span, and the structural spatial stress trajectory line. The stress transmission path topology includes the transmission path identifier, coordinates of the path's starting hub, the sequence of path nodes, and the transmission direction between nodes.

[0021] In practical implementation, the stress event record table serves as the foundational data carrier for subsequent analysis. A typical stress event record table includes the following fields: a unique stress event identifier encoded in the format "EVENT_Date_Serial Number," for example, "EVENT_20231027_015" indicates the 15th stress event captured on October 27, 2023; event start and end timestamps accurate to milliseconds, recording the precise moment when stress fluctuation energy exceeds a threshold and falls back below it, such as the start timestamp "2023-10-27 14:25:36.128" and the end timestamp "2023-10-27 14:25:36.452"; peak energy amplitude recording the maximum amplitude of the stress fluctuation signal during the event, in microstrain, for example, "152.7"; and the total cumulative energy calculated by integrating the square of the signal amplitude over the event duration, used to quantify the total energy of the event, for example, "3845.2 με²·s." The stress evolution distribution map during the construction phase is the core result of visualizing the spatiotemporal evolution of stress. Specifically, the stress evolution distribution map during the construction phase includes: construction phase numbers that are sequentially increased in time, such as "Stage_03"; a stress event density cloud map within the phase that uses interpolation algorithms to transform discrete stress event location information into a continuous two-dimensional or three-dimensional density distribution map, with different colors or grayscale values ​​representing the difference in the number of stress events per unit arc length; a phase time span that records the absolute time of the start and end of this construction phase segment; and a structural spatial stress trajectory line that consists of a series of spatial coordinate points connected in chronological order, depicting the movement path of the core area of ​​stress activity within this construction phase. In some embodiments, the stress transmission path topology is abstractly expressed in the form of a network to represent the stress transmission relationship. The stress transmission path topology includes: a transmission path identifier such as "Path_H2_N", where "H2" represents the starting hub number and "N" represents the path sequence number; the coordinates of the starting hub are derived from the spatial location of potential stress transmission hubs identified in the stress evolution distribution map during the construction phase, such as three-dimensional coordinates "(X:12540mm,Y:8670mm,Z:3200mm)"; the path node sequence is a list of monitoring point identifiers arranged according to the stress transmission direction, such as the sequence "S12→S15→S18→S22" indicating that stress is transmitted along this path; the transmission direction between nodes is marked with arrow symbols in the topology diagram to clearly indicate the direction of stress transmission.

[0022] In practical implementation, the generation of the stress evolution distribution map during the construction phase relies on data processing of the stress occurrence event record table. The sequence of event start timestamps in the stress occurrence event record table is the main basis for dividing construction phase segments. It can be understood that by setting a construction phase division threshold, such as an interval of no more than 30 minutes between consecutive events, the system aggregates events on the timeline that meet this condition into a single construction phase segment. For example, if the end timetamp of event A is 10:00:00 and the start timetamp of event B is 10:15:00, the interval of 15 minutes is less than the threshold, then events A and B are classified into the same construction phase segment. If the start timetamp of subsequent event C is 11:00:00, the interval of 45 minutes with event B is greater than the threshold, then event C marks the beginning of a new construction phase segment. In practical implementation, for each divided construction phase segment, it is necessary to extract the sensor unit installation position coordinates corresponding to all stress occurrence event records within the segment and calculate the event density within a specific section of the curved beam. One density calculation formula is expressed as:

[0023] Where: symbol This indicates a sub-section of the curved beam. The linear event density within an arc length, physically, represents the number of stress events occurring per unit arc length; (symbol) Indicates that in this sub-segment The total number of stress events obtained statistically within the arc length range; symbol Indicates sub-segment The arc length. Based on the density values ​​of all sub-segments. Spatial interpolation can generate a stress event density cloud map covering the entire curved beam. In practice, based on the density cloud map, pixel regions with density values ​​exceeding a set threshold and spatially adjacent are extracted and connected to form one or more closed contours. These closed contours represent the main activity areas of stress within that construction stage. By tracing the geometric center points of the closed contours corresponding to different construction stages and connecting these center points in chronological order, a structural spatial stress trajectory line is formed, thus completing the construction of the stress evolution distribution map for each construction stage.

[0024] In practical implementation, the construction of the stress transmission path topology begins with an in-depth analysis of the stress evolution distribution map during the construction phase. Analyzing each closed contour of stress activity in the stress evolution distribution map during the construction phase requires calculating the spatial gradient of the total cumulative energy of stress events at each sampling point within the contour. For example, a series of grid points are selected within the contour, and the rate of change of the total cumulative energy at each grid point along the axial and radial directions of the curved beam is calculated, resulting in a gradient vector field. In some embodiments, this vector field is depicted using streamline visualization methods, revealing obvious convergence or divergence characteristics in the streamlines. Points where streamlines converge are marked as potential stress transmission hubs, corresponding to load input points or geometric abrupt changes on the structure. Optionally, starting from each identified potential stress transmission hub, the streamlines diverging outwards from it are traced. The tracing process records the locations of monitoring points that the streamlines sequentially cross, forming a complete stress transmission path. For example, a streamline starting from hub H1 passes through monitoring points S05, S08, and S11 in sequence, generating a path with the node sequence "H1→S05→S08→S11". In practice, each such complete path is assigned an independent conduction path identifier, such as "Path_H1_A". Simultaneously, the coordinates of the starting hub, the sequence of nodes, and the conduction direction between adjacent nodes in the sequence are recorded in the topology data. Finally, the paths identified from all potential stress conduction hubs are summarized to form a complete stress conduction path topology. This structure is stored in both graph and attribute table formats, clearly displaying the potential stress conduction skeleton network inside the curved beam.

[0025] Example 2: See Figure 2The process involves reading the start and end timestamps of all events from the stress occurrence event record table. Based on the natural clustering of events along the time axis, a continuous time interval with event intervals less than the construction stage division threshold is defined as a construction stage segment, and a stage number is assigned to each segment. For each construction stage segment, all stress occurrence event records are retrieved, the structural spatial coordinates corresponding to each event are extracted, and the number of stress events per unit area or unit length is calculated to generate a stress event density distribution on the structure. Based on the stress event density distribution, points with similar densities and spatial continuity are connected to form closed contours representing stress activity areas. The movement of the center positions of the closed contours between different construction stage segments is tracked to generate a construction stage stress evolution distribution map. Each closed contour in the construction stage stress evolution distribution map is analyzed, and the gradient vector of the cumulative total energy of stress events at each point within the contour is calculated. Streamlines pointing clearly and converging at one or more points in the gradient vector field are identified, and the convergence points of these streamlines are marked as potential stress transmission hubs. Starting from each potential stress transmission hub, the system traces the outward diverging gradient vector field streamlines, recording the locations of each monitoring point along the streamlines. These monitoring points are then arranged in order of streamline direction, forming a complete path from the hub to the end. Each complete path is assigned an independent identifier, and the spatial coordinates of all nodes on the path and the directional relationships between nodes are recorded. All path information is then summarized to generate the stress transmission path topology.

[0026] In practice, generating the stress evolution distribution map for the construction phase begins with reading the stress occurrence event record table. This table contains the start and end timestamps of each event. The system sequentially scans the start and end timestamps of all events and divides the construction phase into segments based on the natural clustering of events along the time axis. For example, if the construction phase segmentation threshold is set to 1800 seconds, events with an interval of less than 1800 seconds between consecutive stress occurrence events are grouped into the same construction phase segment. Assuming the end timetamp of event A is "2023-11-01 09:30:00" and the start timetamp of event B is "2023-11-01 09:45:15", their interval is 915 seconds. If the time interval between events is less than the threshold, then events A and B belong to the same construction stage segment. If the starting timestamp of subsequent event C is "2023-11-01 10:35:00", and the interval between it and event B is 2985 seconds, which is greater than the threshold, then event C marks the beginning of a new construction stage segment. Each construction stage segment is assigned a unique stage number, such as "Construction Stage Segment_005". In specific implementation, for the divided construction stage segments, it is necessary to extract the spatial coordinates of the sensing units corresponding to all stress occurrence event records within the segment. The spatial coordinates of the sensing units are determined in advance through measurement. For example, the coordinates of monitoring point S101 are (X: 10500mm, Y: 5200mm, Z: 2500mm). These coordinates calculate the stress event density of a specific section on the curved beam. One method for calculating linear density is to count the number of events per unit arc length. Spatial interpolation transforms discrete density values ​​into a continuous intra-stage stress event density cloud map. This intra-stage stress event density cloud map is overlaid on the curved beam structure model with colored contour lines, the color transitioning from blue to red indicating increasing density. In practice, based on the intra-stage stress event density cloud map, adjacent pixel regions with density values ​​exceeding a set threshold (e.g., 0.5 events per meter) are identified and connected to form closed contours representing stress activity areas. For example, two closed contours are identified in the cloud map of construction stage segment _005. Contour C1 contains coordinate points... The set {(x1,y1,z1),(x2,y2,z2)...} and the contour C2 contain the coordinate point set {(x3,y3,z3),(x4,y4,z4)...}. The movement of the geometric center points of the corresponding closed contours between different construction stage segments is tracked, and these center points are connected in chronological order to form the structural spatial stress trajectory line. For example, the contour center of construction stage segment _004 is P4, and the contour center of construction stage segment _005 is P5. Then, a line segment from P4 to P5 is drawn in the construction stage stress evolution distribution map. The final generated construction stage stress evolution distribution map integrates the construction stage number, stage time span, stress event density cloud map within the stage, and structural spatial stress trajectory line.

[0027] In some embodiments, the segmentation of construction phases not only relies on a fixed threshold but also considers the clustering of the total cumulative energy of events. Optionally, when scanning the stress occurrence event record table, the system simultaneously calculates the variance of the total cumulative energy within the event cluster. Only when the time interval between consecutive events is less than the threshold and the variance of the total cumulative energy is less than a set range are they classified into the same construction phase segment. It can be understood that this method can distinguish stress event groups caused by different construction activities. In specific implementation, generating the stress transmission path topology first requires parsing the stress evolution distribution map of the construction phase, analyzing each closed contour in the stress evolution distribution map of the construction phase, and calculating the spatial change rate of the total cumulative energy of stress events at each grid point within the closed contour, i.e., the gradient vector. The gradient vector field reveals the spatial transmission trend of stress energy. A formula for calculating the gradient vector is expressed as:

[0028] Where: symbol Indicates the grid position Gradient vector at point; symbol This indicates the value obtained through interpolation at grid points. The total cumulative energy of stress events at the location; These represent the actual arc length spacing between grid points in the axial direction i and the radial direction j of the curved beam, respectively. Gradient vector The magnitude of the energy change represents the intensity of the energy change, and the direction points to the direction of the fastest energy increase. In practice, based on the gradient vector field within the entire closed contour, a streamline generation algorithm is used to depict the direction field of the vector field and identify the points where streamlines converge. For example, if multiple streamlines converge at a coordinate point (X: 11200mm, Y: 6000mm, Z: 2800mm) in a certain region, this point is marked as a potential stress transmission hub. In practice, the streamline generation algorithm operates based on the gradient vector field within the entire closed contour, which is calculated from the spatial gradient of the total cumulative energy of stress events. The algorithm generates streamlines representing the direction of stress energy transmission by depicting the direction field of the vector field. The streamline generation process involves tracing the continuous direction of the gradient vector, thereby forming a path from the high-energy region to the low-energy region. In the streamline network, the algorithm identifies the points where streamlines converge, i.e., the regions where multiple streamlines converge; these points indicate the locations of stress transmission hubs. For example, when multiple streamlines are observed converging at a coordinate point (X: 11200mm, Y: 6000mm, Z: 2800mm) in a certain region, that point is marked as a potential stress conduction hub. In some embodiments, points where streamlines diverge are also identified as potential stress conduction hubs, representing sources of stress energy.

[0029] In practice, starting from each marked potential stress conduction hub, the algorithm tracks the outward diverging gradient vector field streamline. The tracking algorithm determines the next position based on the gradient vector direction of each point on the streamline and records the sequence of monitoring point positions traversed by the streamline. For example, if the streamline starting from potential stress conduction hub H3 passes through monitoring points S32, S35, and S40 in sequence, a complete path with the node sequence "H3→S32→S35→S40" is generated. Each complete path is assigned a conduction path identifier such as "Path_H3_B". The coordinates of the starting hub, the sequence of nodes, and the conduction direction between nodes are recorded in the data table. The conduction direction between nodes is implicitly represented by the sequence order. For example, "H3→S32" means conduction from H3 to S32. Optionally, for bidirectional conduction paths, two path records with opposite directions are generated. Finally, all identified complete path information is summarized to form a stress conduction path topology stored in a graph data structure. The nodes in the stress conduction path topology correspond to physical monitoring points or potential stress conduction hubs, and the edges represent the stress conduction direction.

[0030] Example 3: See Figure 3 The stress conduction path topology is matched with a real-time stress event record table to determine which stress conduction path a newly occurring stress event belongs to. The relative position and energy contribution of the stress event on its respective path are calculated, generating a stress event-conduction path association mapping table. Based on this mapping table, for each stress conduction path, the sum of the peak energy values ​​of all stress events flowing through the path within the most recent evaluation time window is calculated, along with the event frequency. This assesses the current activity level and energy load of the stress conduction path, generating a real-time path status evaluation report. A sliding time window is set for each conduction path defined in the stress conduction path topology, and all stress event records falling within this window are acquired in real-time. Based on the stress event-conduction path association mapping table, all stress events belonging to the currently evaluated conduction path are selected. The sum of the peak energy values ​​of these events is calculated as the energy load value within the window for the stress conduction path, and the number of events is counted as the event activity frequency within the window. The energy load value within the window is compared with the preset energy load threshold, and the event activity frequency within the window is compared with the preset activity frequency threshold. Based on the combined results of the two comparisons, the current conduction path is determined to be in an idle state, a normal load state, or an overload warning state, and a real-time status assessment report of the path is generated.

[0031] In practical implementation, the generation of the stress event-transmission path association mapping table is based on the matching operation between the stress transmission path topology and the real-time acquired stress event record table. The stress transmission path topology defines multiple directed paths radiating from potential stress transmission hubs. Each path contains a sequence of path nodes. For example, the path node sequence for the transmission path identified as "Path_H2_C" is "H2→S08→S12→S16→S21". When a new stress event is recorded, the system extracts the position coordinates of the sensing unit corresponding to the event. For example, the coordinates of event EV_20231105_078 are (X:10150mm, Y:610). (0mm, Z: 2550mm) This coordinate is used to perform spatial proximity calculations with the node coordinates in all stress conduction path topologies. If the coordinates are found to be closest to the coordinates of node S12 on path "Path_H2_C" and within the tolerance range, then event EV_20231105_078 is determined to belong to conduction path "Path_H2_C". In practice, after determining the attribution, the relative position of the stress occurrence event on its respective path needs to be calculated. The relative position is determined based on the projection position of the event coordinate point on the linear reference path. For example, on path "Path_H2_C", the total path length from the starting hub H2 to the ending node S21 is... The distance from the event projection point to H2 is Then the formula for calculating the relative position parameter ρ is:

[0032] Where: symbol Represents the relative ratio of the projected locations of stress occurrence events along their respective conduction paths; symbol Represents the curved distance from the spatial coordinates of the starting pivot of the conduction path to the projection point of the stress occurrence event coordinates onto the geometric path of that path; symbol This represents the total length of the curve representing the complete geometric path of the conduction pathway from the starting hub to the ending node. If the projection point of event EV_20231105_078 is located between nodes S12 and S16, and the calculated ρ=0.42, then the event is recorded as being located at the 42% position on the pathway "Path_H2_C". In practice, the energy contribution is directly taken from the cumulative energy total field in the stress occurrence event record table. For example, the cumulative energy total of event EV_20231105_078 is 2950με²·s. The attribution relationship, relative position ρ value, and energy contribution are recorded together to form an association mapping record, in the format of "Event ID: EV_20231105_078|Path ID: Path_H2_C|Relative Position: 0.42|Energy Contribution: 2950". The set of all such records constitutes the stress event and conduction pathway association mapping table.

[0033] In some embodiments, the generation of the real-time status assessment report of the pathway is based on the statistical analysis of the stress event-conduction pathway association mapping table. A sliding time window is set for each conduction pathway defined in the stress conduction pathway topology, for example, the window length T_window is set to 3600 seconds and the sliding step size is 300 seconds. All stress event records whose timestamps fall within the current sliding time window are acquired in real time. All stress events belonging to the current conduction pathway to be assessed are filtered according to the stress event-conduction pathway association mapping table. For example, for the conduction pathway "Path_H2_C", in the window [10:00:00, 11:00:00, 12 ... Within [0:00], three events are selected: EV_20231105_076, EV_20231105_077, and EV_20231105_078. The sum of the energy peak values ​​of these events is calculated as the energy load value within the window. For example, if the energy peak amplitudes of the three events are 145.3 με, 128.7 με, and 162.4 με respectively, then the energy load value ∑P within the window is 436.4 με. Simultaneously, the number of events is counted as the event activity frequency within the window. In this example, the event activity frequency within the window is 3 times. Optionally, the event activity frequency within the window can also be calculated as the number of events per unit time, i.e., the frequency. In specific implementation, the evaluation process needs to compare the calculated energy load value within the window with a preset energy load threshold. For example, a preset energy load threshold... The value is 500με. The frequency of events occurring within the window is compared to a preset activity frequency threshold, such as the preset activity frequency threshold. The frequency is 5 times per hour. The state of the conduction pathway is determined by combining the results of two comparisons. The determination logic can be set as follows: if the energy load value ∑P within the window < And the frequency of active events within the window < If ∑P < And the frequency of active events within the window is ≥ , or ∑P≥ And the frequency of active events within the window < Then the conduction path is under normal load; if ∑P≥ And the frequency of active events within the window is ≥ If the conduction path is in an overload warning state, then according to this logic, the ∑P of conduction path "Path_H2_C" is 436.4με < 500με, and the event activity frequency within the window is 3 times < 5 times / hour, so it is determined to be in an idle state. The system generates a real-time status assessment report record for the path, in the format of "Path Identifier: Path_H2_C | Assessment Time Window: 10:00:00-11:00:00 | Energy Load: 436.4με | Event Frequency: 3 | Status: Idle".

[0034] In some embodiments, the threshold comparison can employ a weighted scoring or fuzzy logic method. Optionally, the energy load value and the frequency of active events within the window can be normalized before being compared with the composite threshold. The above evaluation process is periodically executed for each conduction path in the stress conduction path topology to generate a real-time status evaluation report containing all path status entries.

[0035] Example 4: Based on the real-time status assessment report of the transmission path, key monitoring is conducted on the transmission paths marked as overload warning states. The historical stress release rate of each node on the transmission path is analyzed, and the stress accumulation trend at the end of the path under the current load is predicted, forming a stress release and mitigation strategy for the transmission path. According to the stress release and mitigation strategy, the sampling frequency and signal gain of the key nodes on the corresponding transmission path in the sensor network are dynamically adjusted, and a series of auxiliary construction suggestion operation sequences for mitigating stress accumulation are generated. For each transmission path marked as overload warning state in the real-time status assessment report, the historical stress time history data of all nodes on the stress transmission path are extracted, and a curve model of the stress value decaying over time at each node during the stress release stage is fitted. Based on the curve model of all nodes, the stress wave transmission delay and release rate attenuation coefficient from the starting hub to the end node of the path are calculated, simulating the curve of the stress accumulation at the end node changing over time in the future under the current continuous energy load input. Based on the stress accumulation curve of the end node obtained from the simulation in the future, it is determined whether it will exceed the structural safety threshold. If it will exceed the threshold, the sequence or rate of upstream construction loading is planned to be adjusted, and a stress release and diversion strategy containing specific intervention timing and operation parameters is generated.

[0036] In practical implementation, based on the real-time status assessment report of the transmission path, key monitoring is implemented for transmission paths marked with overload warning status. The real-time status assessment report records the identifier of the transmission path with overload warning status, such as "Path_H5_E". Historical stress time history data of all nodes on the transmission path "Path_H5_E" are extracted. The historical stress time history data is the time series of stress values ​​recorded at each monitoring point over a period of time. Curve fitting is performed on the stress value decay process of each node during the stress release phase. The fitting process adopts an exponential decay model, and the formula is:

[0037] Where: symbol Indicates the time after the start of the stress relief phase. Stress value at time; symbol Indicates the start time of the stress relief phase The initial stress value; symbol This represents the stress release rate attenuation coefficient of the node; symbol These are natural constants. The parameters are obtained by fitting historical data from node N21. , The goodness-of-fit coefficient of determination R² is 0.94, indicating that the model can reflect the stress release law of the node.

[0038] Based on the curve model of all nodes, the stress wave propagation delay and release rate attenuation coefficient from the starting hub to the ending node of the pathway are calculated. The stress wave propagation delay is estimated by comparing the time difference of the stress peak occurrence at different nodes for the same stress event, for example, the average time difference of stress wave propagation from node N18 to node N21. The simulation lasts for 8.5 seconds. It simulates the stress accumulation at the end nodes over a future period under the current continuous energy load input. The simulation uses the currently monitored energy load input as the boundary condition, and iteratively calculates the stress accumulation over time by combining the release rate attenuation coefficient λ and the propagation delay of each node to predict the future stress. Stress accumulation at end nodes after time The simulated stress accumulation curve at the end nodes over a future period will be compared with a preset structural safety threshold, which is set according to design specifications, for example, 8500. If the simulation curve shows a future point in time... The accumulated stress will exceed 8500 If the system determines that a risk exists, it will plan to adjust the sequence or rate of upstream construction loading, generating a stress release and mitigation strategy. This strategy includes specific intervention timing and operational parameters, such as "at time..." The concrete pouring rate for Zone_7 was reduced from 15 cubic meters per hour to 8 cubic meters per hour for 120 minutes (see Table 1).

[0039] Table 1: Historical Stress Release Parameters of Each Node in the Conduction Path_H5_E

[0040] In some embodiments, the formation of the stress relief and channeling strategy needs to consider the coupling effect of multi-node attenuation. Optionally, the simulation calculation adopts the transfer matrix method, integrating the attenuation model of each node and the transmission delay between nodes into a system model. It can be understood that this method can more accurately simulate the propagation and dissipation process of stress waves in the path network. In specific implementation, the sampling frequency and signal gain of key nodes on the corresponding conduction path in the sensor network are dynamically adjusted according to the stress relief and channeling strategy. For example, the sampling frequency of key nodes N18, N21, and N25 mentioned in the strategy is increased from the conventional 1Hz to 10Hz, and the signal gain is increased by 6dB to obtain more refined stress change data. In specific implementation, the system generates a series of auxiliary construction suggestion operation sequences for alleviating stress accumulation. The auxiliary construction suggestion operation sequences are a list of specific and executable step instructions converted from the intervention logic in the stress relief and channeling strategy. For example, the operation sequence includes: "Step 1: At time..." Instruct the pouring team F07 to reduce the pumping rate; Step 2: In Minutes, check the stress change rate at node N21; Step 3: If the check passes, maintain a low pouring rate for 120 minutes; Step 4: In "Evaluate the N30 stress value at the end node every minute to determine whether to restore the original rate."

[0041] See Figure 4 This is a stress release attenuation fitting graph for a curved beam node, corresponding to the "Stress Release Law Analysis Stage." Its core purpose is to demonstrate the stress attenuation characteristics of node N21 and the model fitting effect. The stress value decreases exponentially over time, consistent with the typical physical law of stress release in curved beam nodes; the fitting curve almost completely overlaps with historical data. This demonstrates that the exponential decay model can accurately characterize the stress release characteristics of this node; the fitted model can be used to predict future stress changes at this node, providing a quantitative basis for subsequent "stress transmission path analysis" and "stress relief strategy generation". These types of charts are core tools for stress release law analysis: by quantifying the stress decay characteristics of a node, its stress release rate can be clearly defined, assisting in assessing the stress transmission risk of the curved beam structure and supporting the dynamic adjustment of subsequent construction strategies.

[0042] Example 5: The stress relief strategy is transformed into a specific monitoring task instruction set. This set includes target conduction path identifiers, a list of key nodes, enhanced sampling parameters, and expected stress change patterns. The monitoring task instruction set is executed to enhance monitoring of the target conduction path. The collected enhanced monitoring data is compared in real time with the expected stress change patterns. Based on the comparison results, the operating parameters in the stress relief strategy are dynamically fine-tuned to form a closed-loop control.

[0043] In practical implementation, the stress release and channeling strategy will be transformed into a specific monitoring task instruction set. This monitoring task instruction set is a structured data list containing executable instruction parameters. For example, for a stress release and channeling strategy with the conduction path identified as "Path_H5_E", the following monitoring task instruction set is generated: The target conduction path is identified as "Path_H5_E", the key node list includes nodes "H5", "N18", "N21", "N25", and "N30" on this path, and the enhanced sampling parameters include increasing the data sampling frequency of the nodes in the list from the usual 1 Hz to 20 Hz, increasing the signal gain by 10 dB, and the expected stress change pattern is described as "within 1800 seconds after the intervention operation, the stress value of node N30 should increase from the current value..." =8200 microstrains, decaying in an approximately exponential manner, with the goal of reducing the stress value to a threshold value after 1800 seconds. "Below 7500 microstrains", the expected stress variation pattern can be specifically described as a time function. Executing the monitoring task instruction set means that the control center sends configuration commands to the corresponding data acquisition units in the sensor network, dynamically adjusting the sensor sampling parameters in the key node list to the enhanced sampling parameters defined by the instruction set, implementing enhanced monitoring of the target transmission path, and marking the data streams collected during the enhanced monitoring process as enhanced monitoring data.

[0044] In practice, the real-time comparison process compares the collected enhanced monitoring data with the expected stress change pattern, for example, at a time point after the intervention operation begins. =600 seconds, read the real-time stress value of node N30 =7980 microstrain, while from the expected stress change mode function Obtain the expected value at that point in time. =7850 microstrain, calculate the deviation between the two. = - ,get Micro-strain. Based on the deviation sequence obtained from real-time comparison, the operational parameters in the stress release and easing strategy are dynamically fine-tuned. For example, if the initial stress release and easing strategy suggests intervention by "reducing the pre-jacking force of the formwork support in area A7 by 15%", after monitoring that the deviation Δ is continuously positive and greater than the set threshold of 50 micro-strain for more than 300 seconds, a fine-tuning instruction is generated to "adjust the reduction of the pre-jacking force of the formwork support in area A7 from 15% to 18%", and this updated operational parameter is fed back to the construction control system to form a closed-loop control.

[0045] In some embodiments, the expected stress change pattern includes not only the target curve of the terminal node, but also the expected change path of key nodes in the middle of the path. Optionally, the expected stress change pattern can be a matrix of stress value vectors of multiple nodes changing over time. Real-time comparison of the enhanced monitoring data with this matrix is ​​performed, and the Euclidean distance is calculated as a comprehensive deviation index. In a specific implementation, the strategy for dynamically fine-tuning the operating parameters is based on a feedback control law, and one formula for calculating the fine-tuning amount is:

[0046] Where: symbol Indicates time The recommended adjustment amount for a continuously adjustable operating parameter in the stress relief strategy is required; symbol This represents the proportional adjustment coefficient, whose dimensions depend on the units of the operating parameters and the deviation Δ; symbol Indicates time The deviation between the measured value and the expected value calculated in real time; symbol Indicates the integral adjustment coefficient; symbol Indicates the time from the start of the intervention up to the current moment Historical integral of deviation, The radius of curvature of the curved beam; This represents the propagation velocity of stress waves in concrete. For example, the operating parameter is the concrete pouring rate V, measured in cubic meters per hour, and the deviation Δ is measured in microstrain, with coefficients obtained through calibration using historical data. -0.05 (m³ / h) / , -0.0001(m³ / h) / ( If the current deviation The historical deviation integral is 45000. Then the amount of this fine-tuning is calculated. Based on the cubic meters per hour, the system generates a recommendation to further reduce the pouring rate by 11 cubic meters per hour. In some embodiments, the fine-tuning operation is subject to safety boundary constraints, such as the adjusted pouring rate not being lower than the minimum rate allowed by the equipment. The closed-loop control logic checks whether the fine-tuning amount exceeds the preset upper and lower limits of the operating parameters after calculating the fine-tuning amount.

[0047] See Figure 5This is a stress time-series monitoring chart of the construction process of an arc beam, corresponding to the "stress event identification stage." Its core purpose is to demonstrate the correlation between stress fluctuations and key construction stages. Stress remains stable (close to 0) during non-construction stages (no red area), but a significant peak occurs during the key construction stages (red area). After June 9th, the stress peak sharply climbed to over 550 microstrains, far exceeding previous peaks, indicating an abnormal stress surge. The stress peak is strongly correlated with key construction operations, and the subsequent abnormal surge may indicate a risk of structural stress accumulation. This type of chart is a core tool for real-time stress monitoring during construction: by correlating stress fluctuations with construction stages, it can quickly pinpoint the triggering points of stress anomalies, providing direct evidence for identifying "stress event boundaries" and "assessing the structural safety status," and assisting in timely adjustments to construction strategies to avoid stress overload risks.

[0048] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0049] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for real-time stress monitoring of an arc-shaped beam construction structure, characterized in that, Includes the following steps: The original stress fluctuation signal is captured by the sensor network set on the arc beam structure. The original stress fluctuation signal is sliced ​​in the time domain. The energy peak value and energy accumulation value of the stress fluctuation in each time slice are extracted. The start and end boundaries of the stress event are determined according to the combination relationship of the energy peak value and energy accumulation value, and a stress occurrence event record table is generated. Based on the stress occurrence event record table, the time axis of the entire construction process is divided into multiple continuous construction stage segments. Within each construction stage segment, the density of stress occurrence events and the time interval between adjacent events are statistically analyzed. Combined with the spatial coordinate information of the curved beam, the evolution trajectory of stress on the structure within the construction stage segment is depicted, and a stress evolution distribution map of the construction stage is generated. The stress evolution distribution map of the construction stage is analyzed to identify spatial regions in the map where the stress evolution trajectory shows convergence or divergence characteristics. These spatial regions are marked as potential stress transmission hubs. By tracking the direction of change of stress value gradient, stress transmission paths radiating from potential stress transmission hubs to surrounding monitoring points are constructed, generating a stress transmission path topology.

2. The method for real-time stress monitoring of arc-shaped beam construction structures according to claim 1, characterized in that, The stress event record table includes a unique identifier for the stress event, an event start time stamp, an event end time stamp, peak energy amplitude, and total cumulative energy. The stress evolution distribution map for the construction stage includes the construction stage number, a stress event density cloud map within the stage, the stage time span, and the structural spatial stress trajectory line. The stress transmission path topology includes the transmission path identifier, the coordinates of the path's starting hub, the sequence of path nodes, and the transmission direction between nodes.

3. The method for real-time stress monitoring of curved beam construction structures according to claim 1, characterized in that, The specific steps for generating the stress evolution distribution map during the construction phase are as follows: Read the start and end timestamps of all events in the stress occurrence event record table. Based on the natural clustering of events on the time axis, define a continuous time interval with an event interval less than the construction stage division threshold as a construction stage segment, and assign a stage number to each construction stage segment. For each construction stage segment, retrieve all stress occurrence event records contained therein, extract the structural space coordinates corresponding to each event, calculate the number of stress events per unit area or unit length, and generate the stress event density distribution of the construction stage segment on the structure. Based on the stress event density distribution, points with similar densities and spatial continuity are connected to form a closed contour representing the stress activity area. The center position of the closed contour is traced between different construction stage segments to generate a stress evolution distribution map of the construction stage.

4. The method for real-time stress monitoring of curved beam construction structures according to claim 3, characterized in that, The specific steps for generating the stress conduction path topology are as follows: Analyze each closed contour in the stress evolution distribution diagram of the construction stage, calculate the gradient vector of the total cumulative energy of stress events at each point within the contour, identify streamlines in the gradient vector field that point clearly and converge at one or more points, and mark the convergence point of the streamlines as potential stress transmission hubs. Starting from each potential stress transmission hub, trace along the outward diverging gradient vector field streamline, record the location of each monitoring point along the streamline, and arrange these monitoring points in order of streamline direction to form a complete path from hub to end. Each complete path is assigned an independent identifier, the spatial coordinates of all nodes on the path and the directional relationships between nodes are recorded, all path information is summarized, and a stress transmission path topology is generated.

5. The method for real-time stress monitoring of arc-shaped beam construction structures according to claim 4, characterized in that, The method further includes the following steps: The stress conduction path topology is matched with the real-time stress event record table to determine which stress conduction path a newly occurring stress event belongs to, and the relative position and energy contribution of the stress event on its respective path are calculated to generate a stress event-conduction path association mapping table. Based on the stress event and conduction path association mapping table, for each stress conduction path, the sum of the peak energy of all stress events flowing through the stress conduction path within the most recent evaluation time window and the frequency of event occurrence are counted to evaluate the current activity level and energy load level of the stress conduction path and generate a real-time status evaluation report of the path.

6. The method for real-time stress monitoring of an arc-shaped beam construction structure according to claim 5, characterized in that, The specific steps for generating the real-time status assessment report of the pathway are as follows: A sliding time window is set for each stress conduction path defined in the stress conduction path topology, and all stress occurrence events falling within the sliding time window are recorded in real time. Based on the stress event and conduction path association mapping table, all stress events belonging to the current evaluation conduction path are selected, and the sum of the energy peaks of these events is calculated as the energy load value within the window of the stress conduction path. At the same time, the number of events is counted as the event activity frequency within the window. The energy load value within the window is compared with a preset energy load threshold, and the event activity frequency within the window is compared with a preset activity frequency threshold. Based on the combined results of the two comparisons, it is determined whether the current conduction path is in an idle state, a normal load state, or an overload warning state, and a real-time status assessment report of the path is generated.

7. The method for real-time stress monitoring of an arc-shaped beam construction structure according to claim 6, characterized in that, The method further includes the following steps: Based on the real-time status assessment report of the transmission path, the transmission paths marked as overload warning status are monitored in a key manner. The historical stress release rate of each node on the transmission path is analyzed, the stress accumulation trend at the end of the path under the current load is predicted, and a stress release and guidance strategy for the transmission path is formed. Based on the stress relief and guidance strategy, the sampling frequency and signal gain of the key nodes in the transmission path of the sensing network are dynamically adjusted, and a series of auxiliary construction suggestion operation sequences for alleviating stress accumulation are generated.

8. The method for real-time stress monitoring of an arc-shaped beam construction structure according to claim 7, characterized in that, The specific steps for forming the stress relief and channeling strategy are as follows: For each conduction path marked as overload warning in the real-time status assessment report of the path, historical stress time history data of all nodes on the stress conduction path are extracted, and a curve model of stress value decay over time at each node during the stress release stage is fitted. Based on the curve model of all nodes, the stress wave propagation delay and release rate attenuation coefficient from the starting hub to the end node of the pathway are calculated, and the curve of stress accumulation at the end node over time is simulated under the current continuous energy load input. Based on the stress accumulation curve of the end node obtained from the simulation in the future period, it is determined whether it will exceed the structural safety threshold. If it will exceed the threshold, the sequence or rate of upstream construction loading is planned to be adjusted, and a stress release and diversion strategy containing specific intervention timing and operation parameters is generated.

9. The method for real-time stress monitoring of an arc-shaped beam construction structure according to claim 8, characterized in that, The method further includes the following steps: The stress relief and channeling strategy is transformed into a specific monitoring task instruction set, which includes target conduction path identifiers, a list of key nodes, enhanced sampling parameters, and expected stress change patterns. The monitoring task instruction set is executed to enhance monitoring of the target conduction path, and the collected enhanced monitoring data is compared with the expected stress change pattern in real time. Based on the comparison results, the operating parameters in the stress release and venting strategy are dynamically fine-tuned to form a closed-loop control.

10. A real-time stress monitoring system for an arc-shaped beam construction structure, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method for real-time monitoring of stress in the construction structure of an arc-shaped beam as described in any one of claims 1 to 9.

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