An intelligent monitoring and management system for the hoisting construction of box girders of super-high piers

Abstract

The present invention relates to the technical field of box girder construction, and specifically to an intelligent monitoring and management system for the hoisting construction of box girders on ultra-high piers, including: a construction acquisition module for collecting construction monitoring data during box girder construction; a structural simulation module for extracting the support connection points during box girder construction from the construction monitoring data, obtaining the stress change values at the support connection points, converting the stress change values into stress change curves, and setting stress gain vectors according to the stress change curves of the support connection points; a settlement identification module for extracting the settlement amounts of the support connection points from the construction monitoring data, and combining the settlement amounts with the stress change values according to the direction and value of the settlement amount distribution to obtain a settlement distribution map during box girder construction; a structural matching module for analyzing the relationships between the support connection points in the settlement distribution map and sequentially determining the matching degrees of the support connection points in the settlement distribution map; improving the construction efficiency and safety.

Description

Technical Field

[0001] The present invention relates to the technical field of box girder construction, and specifically to an intelligent monitoring and management system for the hoisting construction of box girders on super-high piers. Background Art

[0002] In the field of hoisting construction of box girders on super-high piers, traditional monitoring and management methods mainly rely on manual inspections and experience judgments. There are many deficiencies in this method, such as inaccurate data collection, untimely analysis, and incomplete risk identification. With the rapid development of information technology, intelligent monitoring and management systems have gradually become an important means to solve these problems. However, most of the existing intelligent systems are targeted at specific construction links or problems and lack comprehensive and systematic solutions.

[0003] For example, Chinese Patent Publication No. CN117933689A discloses a method for risk management in the decision-making stage of bridge construction technology based on ontology. By introducing various technical knowledge sources of the knowledge base of bridge construction technology risks, a bridge construction technology ontology knowledge base is constructed, and the entity classes and relationships between classes of the bridge construction technology ontology knowledge base are defined. Based on the bridge construction technology ontology knowledge base, a bridge construction technology risk chain is obtained; and based on the bridge construction technology risk chain, a semantic web rule for bridge construction technology risks is constructed; the semantic web rule for bridge construction technology risks is subjected to ontology consistency verification, and based on the semantic web rule for bridge construction technology risks after consistency verification, a decision is made on the bridge construction technology risk solution.

[0004] For example, Chinese Patent Publication No. CN118798830A discloses a method and system for the construction progress management of cast-in-place box girders based on BIM, which is used to improve the accuracy of the construction progress management of cast-in-place box girders based on BIM. The method includes: performing correlation processing on structural data and construction progress data to obtain progress correlation data, and performing simulation analysis on the progress correlation data to obtain construction plan improvement data; collecting strain, temperature, and vibration data in real time to obtain original spectral data, processing and classifying the original spectral data to obtain structured construction data; performing progress analysis on the structured construction data to obtain actual progress data, comparing the actual progress data with the construction progress data to obtain progress deviation data; performing intelligent analysis on the progress deviation data to obtain warning data and cause diagnosis data, and performing decision analysis and processing on the warning data and cause diagnosis data to obtain suggestion data.

[0005] The prior art shows that bridge construction will be set according to risk weights and semantics. However, when it comes to box girder construction, it is necessary to determine the common characteristics of stress changes and settlement changes to accurately find out what problems are likely to occur in the current bridge during construction under various factors such as stress and settlement changes, and perform intelligent processing on these problems to improve construction efficiency and safety. Summary of the Invention

[0006] To solve the above technical problems, the technical solution adopted by the present invention is as follows: An intelligent monitoring and management system for hoisting construction of super-high pier box girders, comprising: a construction data acquisition module for acquiring construction monitoring data during the box girder construction.

[0007] A structure simulation module for extracting the support connection points during the box girder construction from the construction monitoring data, obtaining the stress change values at the support connection points, converting the stress change values into stress change curves, and setting stress gain vectors according to the stress change curves of the support connection points.

[0008] A settlement identification module for extracting the settlement amounts of the support connection points from the construction monitoring data, combining the settlement amounts with the stress change values according to the directions and values of the settlement amount distributions to obtain a settlement distribution map during the box girder construction.

[0009] A structure matching module for analyzing the relationships between the support connection points in the settlement distribution map, sequentially determining the matching degrees of the support connection points in the settlement distribution map, and adjusting the stress gain vectors according to the matching degrees of the support connection points in the settlement distribution map.

[0010] A risk assessment module for determining the risk influence range during the box girder construction according to the adjusted stress gain vectors, and adjusting the box girder construction plan according to the risk influence range.

[0011] The beneficial effects of the present invention are as follows: First, the structure simulation module of the present invention can extract the stress change values of the support connection points, identify the obtained stress change values according to the support connection points at adjacent positions to obtain possible stress mutations in different regions, convert these prone parts into movement trends, and then convert them into stress change curves. Finally, stress gain vectors corresponding to the stress change curves are set. This helps to accurately evaluate the stability and safety of the box girder structure, focuses more on the stress mutation situation, is easy to identify stress changes under unconventional conditions, and improves the overall stress identification efficiency.

[0012] Second, the settlement identification module of the present invention can extract the settlement amounts of the support connection points, identify the settlement amounts and settlement directions, obtain the settlement paths according to the different stresses existing in the settlement amounts, and then verify the positions where the current settlement and load exist to obtain the load paths under the current settlement amounts. Finally, the load paths and settlement paths are combined to generate a settlement distribution map. This helps to intuitively display the settlement situation during the box girder construction process, and is more helpful for evaluating the stability of the upper structure of the bridge, providing an important basis for subsequent risk assessment.

[0013] III. The structure matching module of the present invention can analyze the relationships of the support connection points in the settlement distribution map, adjust the stress gain vector according to the matching degree, verify the uniformity of the corresponding distribution of the current settlement amount by the matching degree of the settlement amount at each position relative to the maximum settlement amount, and then combine the matching degree with the stress gain vector, so that after considering different settlement amounts and the positions of the support connection points, the relevant data when the current settlement amount occurs, which helps to optimize the design and construction plan of the box girder structure and improve the stability and safety of the structure.

[0014] IV. The risk assessment module of the present invention can determine the risk influence range according to the adjusted stress gain vector, adjust the box girder construction plan, take the adjusted stress gain vector as the main body for identification, set multiple risk area identifiers, and then obtain multiple groups of data according to the difference in marking time, quantify the differences in the corresponding characteristics on the risk areas, and finally divide the ranges of these risk areas, which helps to timely discover and respond to potential risks during the construction process and ensure the safety and smooth progress of the construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The present invention will be further described below in conjunction with the drawings and embodiments.

[0016] Figure 1 It is a system framework diagram of an intelligent monitoring and management system for the hoisting construction of a super high pier box girder.

[0017] Figure 2 It is a flow schematic diagram of the structure simulation module of an intelligent monitoring and management system for the hoisting construction of a super high pier box girder.

[0018] Figure 3 It is a flow schematic diagram of the settlement identification module of an intelligent monitoring and management system for the hoisting construction of a super high pier box girder.

[0019] Figure 4 It is a flow schematic diagram of the structure matching module of an intelligent monitoring and management system for the hoisting construction of a super high pier box girder.

[0020] Figure 5 It is a flow schematic diagram of the risk assessment module of an intelligent monitoring and management system for the hoisting construction of a super high pier box girder. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0021] The embodiments of the present invention will be described in detail below. The following described embodiments are exemplary and are only used to explain the present invention and should not be construed as a limitation to the present invention. For those not specified in the embodiments regarding specific technologies or conditions, they shall be carried out according to the technologies or conditions described in the literature in this field or according to the product specifications.

[0022] Refer to Figure 1, a smart monitoring and management system for hoisting construction of super-high pier box girders, comprising: a construction data collection module, a structure simulation module, a settlement identification module, a structure matching module and a risk assessment module; the output end of the construction data collection module is connected to the structure simulation module, the output end of the structure simulation module is connected to the settlement identification module, the output end of the settlement identification module is connected to the structure matching module, and the output end of the structure matching module is connected to the risk assessment module.

[0023] The construction data collection module is used to collect construction monitoring data during the box girder construction.

[0024] The structure simulation module is used to extract the support connection points during the box girder construction from the construction monitoring data, obtain the stress change values at the support connection points, convert the stress change values into stress change curves, and set stress gain vectors according to the stress change curves of the support connection points.

[0025] The settlement identification module is used to extract the settlement amounts of the support connection points from the construction monitoring data, and combine the settlement amounts with the stress change values according to the direction and value of the settlement amount distribution to obtain a settlement distribution map during the box girder construction.

[0026] The structure matching module is used to analyze the relationships between the support connection points in the settlement distribution map, determine the matching degrees of the support connection points in the settlement distribution map in sequence, and adjust the stress gain vectors according to the matching degrees of the support connection points in the settlement distribution map.

[0027] The risk assessment module is used to determine the risk influence range during the box girder construction according to the adjusted stress gain vectors, and adjust the box girder construction plan according to the risk influence range.

[0028] In an embodiment of the present invention, the construction monitoring data is mainly divided into two parts: structure and stress data. The stress part is the stress change of the box girder and the support structure during installation; the structure part is the displacement, offset and settlement amount of the support structure, as well as the connection point position and accuracy of the support structure during the box girder construction. At this time, the construction monitoring data will be simply divided. The stress aspect mainly indicates whether there will be problems during the current box girder construction, and whether there will be relevant settlement and offset when problems occur, and locate the problem points according to this part of the offset and settlement, find out whether there will be uneven settlement problems during the box girder construction, and finally reduce the risks of the box girder construction after locating the relevant problem points.

[0029] In an embodiment of the present invention, the structure simulation module is mainly used to extract the support connection points during the box girder construction from the construction monitoring data, and judge the stress that appears during the construction according to these connection points, and find out whether there will be unstable problems in the structures and positions represented by these stresses.

[0030] The support connection points will represent the connection points that need to be observed on the main support structure of the box girder during the construction of the box girder. At the same time, these connection points will also represent the points used for connecting multiple box girders on the box girder. These connection points can indicate whether the current installation of the box girder is normal. At this time, stress sensors and displacement sensors are set at the positions of these points to detect whether there is overloading or underloading at these points.

[0031] The stress change curve is mainly used to simulate the stress changes at each support connection point used for installing the box girder during the box girder installation construction, to prevent situations such as longitudinal bending, rigid torsion, distortion, and lateral bending during installation. These situations will cause the installation of the box girder to be unstable and result in installation defects in the installed vector, causing corresponding losses. The stress gain amount represents the difference in these stress changes, and according to the stress changes in the transverse and longitudinal directions, it is used to identify whether risks will occur. Then, a stress gain vector is set to complete the overall processing and identification. This vector will represent the positions where there may be risks at the support connection points on the support structure, and convert these positions into vector form for facilitating the monitoring of the settlement amount during the construction of the box girder.

[0032] As Figure 2 shown, the implementation method of the structural simulation module includes: converting the stress change values at the support connection points into a stress change sequence according to the positions of the support connection points; at this time, the converted stress change sequence is set according to the time when data is collected at the support connection points to obtain a corresponding time sequence.

[0033] For the stress change values of the same support connection point at different time points, calculate the stress mean absolute difference of each support connection point; the stress mean absolute difference at this time is to first calculate the average value of the stress change values at all support connection points, and then for each support connection point, calculate the absolute difference relative to the average value of the stress change values at all support connection points, and then average this absolute difference according to the total amount of data collected at each support connection point to obtain the stress mean absolute difference of each support connection point. This stress mean absolute difference is used to reflect the degree of dispersion of the stress change at the support connection point relative to the overall situation to measure the stress change situation.

[0034] Compare the stress mean absolute differences of adjacent support connection points and analyze the stress movement situation of the stress mean absolute differences of adjacent support connection points relative to the positions of the support connection points to obtain the stress movement trend corresponding to the support connection points. This stress movement trend will represent the distribution of the support connection points during construction, and in these distribution situations, when stress changes occur, what movement trend the stress presents at the corresponding positions of these connection points.

[0035] When analyzing the stress movement, analyze the corresponding extreme changes in these support connection points, and connect the corresponding points to find the stress movement trend to be identified. For example, the implementation method of the stress movement trend corresponding to the support connection points includes: dividing the adjacent support connection points into intervals according to the value of the mean absolute difference of stress for the support connection points, obtaining multiple stress division intervals corresponding to the support connection points. This stress division interval represents an interval set for the relative change of the stress value. This interval is mainly divided according to the position where the support connection point is located, and according to the situation and value of these data, determine the interval that different support connection points need to fall into.

[0036] For each stress division interval, calculate the probability of the boundary value occurrence of each support connection point within the stress division interval. The probability of the boundary value occurrence represents the probability that the value of the mean absolute difference of stress on a single support connection point is exactly equal to the upper limit value and the lower limit value of the stress division interval. This probability will represent the extreme situation of the stress occurrence of the support connection points within this interval.

[0037] Connect the support connection points corresponding to the maximum probability of the boundary value occurrence in each stress division interval, and regard the connected support connection points as the stress movement trend corresponding to the support connection points. This stress movement trend will make it more convenient to manage different support connection points during construction, and at the same time can help engineering personnel quickly identify the existing patterns and anomalies during the current construction.

[0038] After completing the setting of the movement trend, it is necessary to convert the values on the movement trend into a stress change curve. At this time, the conversion method will calculate the relative data change rate of the support connection points existing on the movement trend, that is, the ratio value of the stress change value of the support connection points existing on the movement trend to the moving average value of the stress change value, and represent the specific stress change value and the ratio value together in the change curve to show how the stress changes on the corresponding support connection points during the current construction.

[0039] Based on the obtained stress movement trend, identify the support connection points existing on the stress movement trend, calculate the relative data change rate of the corresponding support connection points, and obtain the stress change curve according to the relative data change rate and the stress change value of the support connection points existing on the stress movement trend.

[0040] Meanwhile, according to the display of the stress change curve, a stress gain vector will be set for the current stress change curve. Generally, the stress gain vector is obtained by converting the data in the current stress change curve into a vector to get an input vector. Then, using the data in the current stress change curve, an inverse covariance matrix is established, and the transpose matrix of the input vector is generated. Finally, the product of the inverse covariance matrix and the input vector, the product of the transpose matrix of the input vector, the inverse covariance matrix, and the input vector, plus a regularization parameter, are divided to obtain a stress gain vector. The regularization parameter used at this time is generally a number set to prevent the denominator from being zero.

[0041] At this time, the peaks in the stress change curve will be identified, and these peaks and the data adjacent to the peaks will be used as the data for setting the stress gain vector at this time to obtain a stress gain vector that is prominent in the current stress change. Setting this stress gain vector at this time is mainly to distinguish and find out the characteristic data that may have significant changes or are likely to cause instability in some areas from the stress change curve, to emphasize the local mutation points and abnormal points during the construction process, and to use this vector in combination with subsequent data to complete the monitoring of the entire construction process.

[0042] In an embodiment of the present invention, the settlement identification module is mainly used to identify the settlement amount of the support connection points. At the same time, the direction and value of the settlement amount need to be marked to obtain a settlement distribution map. At this time, it mainly identifies whether there are different settlement amounts at different support connection points during the box girder construction. The settlement amount is described by the displacement of each support connection point, and after verifying the direction and corresponding value of the displacement, it is identified whether there is uneven settlement to determine the stability of the construction. At the same time, it will also determine the possible load conditions on each support connection point when the settlement amount appears to adjust the settlement amount in time so that each support connection point can achieve uniform settlement.

[0043] As Figure 3 shown, the implementation method of the settlement identification module includes: obtaining the displacement of the support connection point in the horizontal direction and the vertical direction, and sequentially setting the settlement amount and settlement angle of the support connection point.

[0044] At this time, the displacement of the support connection point in the horizontal direction and the vertical direction is obtained. According to the displacement in the horizontal direction and the vertical direction, the angle at which the current support connection point generates displacement can be known. This angle is considered the settlement angle of the settlement amount. The settlement amount is expressed as the displacement of the support connection point in the vertical direction. Then, it is necessary to compare the actual settlement amount in the case of the current displacement and the settlement direction under the combination of multiple points to determine whether the surrounding points can achieve uniform settlement.

[0045] Vectorially synthesize the settlement angles of adjacent support connection points, and set the direction after synthesis as the settlement direction; at this time, add the displacements of adjacent support connection points in the horizontal and vertical directions respectively, and use the arctangent function to calculate the added angle, which is the settlement direction at this time; generally, this settlement direction will be the same as the settlement angles of multiple support connection points during calculation. If there are differences, it means that there is uneven settlement in this part. At the same time, compare the displacements in the horizontal and vertical directions to determine the settlement path generated by the settlement amount at this time, and then judge whether the overall settlement is normal according to the settlement path, and finally obtain a settlement distribution map.

[0046] Based on the settlement amount and settlement direction of the support connection points, invert the load distribution of the support connection points; the way to invert the load distribution is to use the current settlement amount and settlement direction as inputs, and calculate using the gradient descent method, genetic algorithm, and particle swarm optimization methods. Select the load amounts with the highest similarity to the current settlement amount and settlement direction in the historical data, and represent these load amounts in the form of numerical values and distributions. Among them, the gradient descent method is to minimize the difference between the angle values of the current settlement amount and settlement direction and the historical data. When the difference in the angle values of the settlement amount and settlement direction at all support connection points is minimized, select the load amounts existing at the corresponding positions; the genetic algorithm is to describe the fitness of the current settlement amount and settlement direction input values using the mean square error, and then perform crossover and replacement until the iteration is completed, and output the load amounts corresponding to the support connection points after iteration; the particle swarm optimization is to find the positions of the settlement amount and settlement direction values of each support connection point in the particle swarm, and then update the velocity and position of the particle swarm to complete the distribution of the support connection points, and then obtain a load amount; the purpose of using these three algorithms is to invert the load existing at the current support connection points to judge whether the settlement of the current support connection points is normal and to explain whether these contents can finally achieve complete processing.

[0047] Obtain the actual load diagram of the support connection points, superimpose the actual load diagram of the support connection points with the load distribution, and set the load path according to the superimposed load value and the stress change value of the support connection points; at this time, the actual load diagram represents the actual load value of the support connection points, and then superimpose the load value of the inverted load distribution with the actual load value to obtain a load path; the superposition is to calculate the average value of the load value and the actual load amount in the load distribution, and then find the load concentration area and the magnitude of the stress change value in this area. Find a path corresponding to the maximum stress direction in the load concentration area as the path identified at this time, which can facilitate the evaluation of the strength and stability of different structures during the construction of the box girder when settlement occurs.

[0048] The way to set the load path is as follows: calculate the load proportion value of the superimposed load value of a single support connection point in all superimposed load values, and when the load proportion value is greater than the first proportion threshold, mark the corresponding support connection point. Taking the center point of the marked support connection points as the center and the maximum distance between the marked support connection points as the diameter, divide the load concentration area. The first proportion threshold is the value set for the proportion of each point load value in the total in historical data, that is, the current support connection point sets the first proportion threshold used at this time according to the average value of the load proportion values in historical data. In different situations, the first proportion threshold can be values such as 60%, 80%, and 120% of the average value of the load proportion values in historical data to select the positions with larger current load values. These positions are generally key points during the construction of the box girder, and these points can better represent the strength and stability of the overall construction. Taking the center point of the marked support connection points as the center is to select the point located in the center among these marked points, and then use this point as the center. After that, set the diameter according to the maximum distance between the marked points, which can enclose these load concentration points as much as possible, making the stress changes identified in this area more prominent.

[0049] Connect the support connection points within the load concentration area in the direction of the maximum stress to obtain the load path. The maximum stress direction of the support connection point is, in three dimensions, to decompose the stress change value generated by the support connection point into components on three coordinate systems. Based on the component with the maximum stress value among the components on the three coordinate systems, then starting from this component, connect the support connection points existing at the corresponding direction angle of this component, and then keep connecting until a path can be obtained within the current load concentration area. This path is the load path. The implementation method of obtaining the load path also includes: if there is no point in the direction of the maximum stress of the support connection point, then fit the maximum stress direction to the settlement direction. Fitting means finding the average value of the angles of the components of the two angles in the same coordinate system to obtain an angle value in the coordinate system corresponding to the maximum stress direction, and connect the support connection point closest to the ray extending from this angle value. Connect the support connection point closest to the fitted maximum stress direction to obtain the load path, thus completing the connection of the support connection points within the load area. The load identified in this way will be concentrated and displayed according to the stress changes, preventing the corresponding stress received by the corresponding structure from being ignored when identifying the corresponding load for the settlement amount.

[0050] After that, generate the settlement path according to the settlement amount and settlement direction of the support connection points, and combine the settlement path with the load path and output it as a settlement distribution map. The settlement path is to multiply the generated settlement amount by the angle corresponding to the settlement direction to generate an area related to the settlement amount. This area will present a polygonal pattern to represent the specific settlement volume of the settlement amount in the corresponding direction. After that, output the settlement path and the load path according to the specific values.

[0051] When dealing with a series of problems such as uneven foundation settlement, unreasonable load distribution, and construction quality control, the output of the combined settlement path and load path as a settlement distribution map also includes: verifying whether the load path and the settlement path intersect. When they intersect, the intersection point is output; when they do not intersect, the load path and the settlement path are output to obtain the settlement distribution map. At this time, if the load path and the settlement path do not intersect, this is usually a positive signal, indicating that when the structure is under load, its foundation or support structure has not undergone adverse settlement. In this case, the original construction plan can be continued, but settlement monitoring still needs to be maintained to ensure the safety of the structure during the entire construction and use process. If the load path and the settlement path intersect, immediate action needs to be taken to evaluate and address potential safety issues. First, a detailed geological survey and structural analysis should be carried out on the intersection area to determine the cause and extent of the settlement. According to the survey and analysis results, measures such as foundation reinforcement, support structure adjustment, or load redistribution may be required to reduce the impact of settlement on the structure. In some cases, temporary or permanent strengthening treatments may also be needed for the structure to ensure its safety and stability.

[0052] What is output in the settlement distribution map in this case indicates whether there is a relationship between the load path and the settlement path, and the part without a relationship is output to remind external engineering personnel how to carry out the current box girder construction.

[0053] In an embodiment of the present invention, the structure matching module is mainly used to analyze the relationship between the support connection points in the settlement distribution map, analyze the remaining support connection points after the settlement distribution map is identified and processed for settlement, load, and stress distribution, calculate the relationship between these points and the settlement amount, and set a matching degree. Then, this matching degree is used as a calculated value for comprehensive calculation with the stress gain vector. In this way, it is determined whether the normal deformation is exceeded under the corresponding settlement condition, and whether the value of the stress gain vector at this time can correspond to the settlement amount, and the stress gain vector is adjusted accordingly to determine whether the current construction is in a normal situation.

[0054] Such as Figure 4As shown in the figure, the structural matching module is implemented as follows: According to the distribution of each support connection point in the settlement distribution map, the Pearson correlation coefficients between each support connection point and its adjacent support connection points are calculated in sequence. The Pearson correlation coefficients between each support connection point and its adjacent support connection points are calculated by using the settlement amounts existing at these points and historical data to obtain the calculated Pearson correlation coefficients. That is, the settlement amounts of the current support connection point and the adjacent support connection point are calculated with the average value of the settlement amounts at this position in the historical data, and all support connection points in the settlement distribution map are traversed. The value of the calculated Pearson correlation coefficient is used as the analysis result of the relationship between each support connection point in the settlement distribution map at this time. This Pearson correlation coefficient will represent the settlement pattern existing between the corresponding support connection points in the currently set settlement distribution map.

[0055] Based on the settlement amounts of each support connection point in the settlement distribution map, the matching degrees corresponding to each support connection point in the settlement distribution map are set. For the matching degrees set here, the difference between the settlement amounts of the current support connection point and the adjacent support connection point is divided by the maximum settlement amount in the settlement distribution map, and the absolute value of the divided value is set as the matching degree at this time. This matching degree is used to quantify the coordination degree between each support connection point.

[0056] Based on the Pearson correlation coefficients between each support connection point and its adjacent support connection points in the settlement distribution map and the matching degrees corresponding to each support connection point, the stress gain vector is adjusted. At this time, the obtained Pearson correlation coefficient is used. First, a gain adjustment amplitude corresponding to this Pearson correlation coefficient is selected from the database. This value represents the adjustment ratio value. Then, this amplitude is multiplied by the average value of the matching degrees and added to the initial stress gain vector to complete the adjustment of the stress gain vector on the corresponding support connection point. The stress gain vector adjusted at this time refers to the part corresponding to the support connection points existing in the settlement distribution map. Through the Pearson correlation coefficient analysis of these points, the linear relationship between each support connection point and its adjacent points can be quantified, so as to more accurately identify the key areas and change trends in the settlement distribution map; combined with the matching degree information, it can further ensure that the adjustment of the stress gain vector is more in line with the actual situation and improve the accuracy of the analysis; according to the differences in the correlation coefficients and matching degrees, different adjustment strategies can be adopted for different support connection points, making the adjustment of the stress gain vector more targeted; this helps to optimize the stability and safety of the overall structure, especially in areas with more serious settlement problems.

[0057] In an embodiment of the present invention, the risk assessment module is mainly used to determine, according to the adjusted stress gain vector, which positions among the support connection points may have risks in the scenario of the adjusted stress gain vector, explain these risky places, and adjust the construction plan of the box girder. During risk assessment, it mainly identifies places where stress changes may be prominent through the stress gain vector. Normally, when the stress at multiple support connection points reaches 90% of the design value multiple times and then meets the design requirements, the construction of the box girder can be completed. However, if there are still problems after marking the stress at single or multiple points using the vector and analyzing and processing it multiple times according to the settlement amount, it is necessary to identify the possible risk ranges for these situations, output these ranges and reasons, and adjust the construction plan during construction to ultimately ensure the normal construction of the box girder.

[0058] As Figure 5 shown, the implementation method of the risk assessment module is as follows: According to the adjusted stress gain vector, it determines whether there are risks in the support connection points corresponding to the stress gain vector and sets multiple risk area identifiers. This is identified based on the adjusted stress gain vector. At this time, the identification method is to identify whether the vector value of the stress gain vector can reach 90% of the design value multiple times within consecutive time points, and the subsequent vector values will show stable values to meet the design requirements. If not, the corresponding support connection points will be marked to obtain multiple risk area identifiers.

[0059] Obtain the marking time of the risk area identifier. If the time difference between the marking times of two risk area identifiers is less than the marking time threshold, the two risk area identifiers are regarded as a group of risk area identifiers, and the risk area identifiers within each group are compared to capture risk difference characteristics; the selection of the marking time threshold depends to a large extent on the specific engineering background, construction progress arrangement, and characteristics of the monitoring data; the main purpose of setting this threshold is to identify those risk areas that may be related to each other due to construction activities or external condition changes within a similar time period.

[0060] For example, in a certain construction stage such as concrete pouring with a relatively short duration, within a few hours to one day in total, the marking time threshold should be set relatively small, such as choosing 1, 3, or 6 hours, in order to capture the risks directly related to this activity.

[0061] For a construction process with a longer duration, lasting for several weeks to several months, the marking time threshold can be set slightly longer, such as 1 day, 3 days, or 7 days in length, to cover the possible changes during the entire activity period. Ensure that under the construction period, the current construction content can be properly classified to identify possible risk problems.

[0062] The risk difference characteristics will indicate the different locations where risks occur within each group at this time, so as to identify what forms of risks have emerged during this similar time period, facilitating the overall construction plan control. The risk difference characteristics at this time will include differences in aspects such as spatio-temporal correlation, mechanical properties, construction activity correlation, and environmental factors.

[0063] Suppose the two risk area identifiers being compared at this time are Area A and Area B. Then, the time difference between Area A and Area B is calculated to be 2 hours, indicating that the problems in these two areas occurred almost simultaneously. After analyzing the spatial positions of Area A and Area B, it is found that they are on the same side and are approximately 10 meters apart, suggesting that they may be caused by the same construction activity. This illustrates the difference in spatio-temporal correlation.

[0064] It can also be explained from the aspect of mechanical properties. Suppose the maximum principal stress value in Area A is 250 MPa, and the direction is northeast; the maximum principal stress value in Area B is 260 MPa, and the direction is also northeast, indicating that they have a similar stress concentration pattern. After that, it is found that the settlement in Area A is 10 mm, while the settlement in Area B is 12 mm, and both show a gradually increasing trend, but the growth rate in Area B is slightly faster. Finally, it is identified that the maximum strain in Area A is 0.002, and the maximum strain in Area B is 0.0025, indicating that the deformation in Area B is more significant. Specific problems at these positions can be identified from the aspect of mechanical properties at this time.

[0065] At the same time, these identified risk difference characteristics are also related to the correlation of construction activities. For example, by consulting the construction log, it is found that the concrete pouring operations near Area A and Area B were completed at the 20th hour, and it is speculated that the problem may be caused by uneven local loads during the pouring process. Further analyzing the load application situation, it is confirmed that Area A and Area B did indeed bear relatively high local loads. At this time, there is a problem of excessive construction time, and abnormal problems existing during construction can also be discovered.

[0066] Finally, in terms of the environment, the weather conditions are compared to find out whether the abnormal settlement during construction is affected by the environment.

[0067] According to the occurrence probability of the risk difference characteristics within the risk area identifier, set the risk impact range corresponding to the risk area identifier. At this time, the risk impact range represents the impact degree of the corresponding part in the risk difference characteristics. The occurrence probabilities of the risk difference characteristics are weighted and summed, and the obtained value after summation is regarded as the value of the corresponding risk impact range. According to different values of the risk impact range, multiple risk impact ranges of different sizes are obtained. At this time, the range set according to the value of the risk impact range will be divided using the average value of the risk impact range value, and the forms of 30%, 60%, 90% of the average value and greater than the average value are selected in turn to divide the risk impact range.

[0068] Finally, according to the risk impact range, the way to adjust the box girder construction plan is to output the currently obtained risk impact range to the external control terminal. Engineering personnel find the corresponding construction plan from the database according to the actual distribution and value of the risk impact range to complete the adjustment of the current construction plan, so as to realize the intelligent monitoring of box girder construction. That is, obtain the construction process of the risk impact range, associate the risk impact range with the database for calculation, calculate the cosine similarity between the risk impact range and the box girder construction plan in the database under each construction process, and use the box girder construction plan with the maximum cosine similarity value to adjust the current box girder construction plan. At this time, when calculating the data in the risk impact range and the database, the risk difference features existing in the risk impact range and the weighted sum calculated according to the occurrence probability of the risk difference features are used to calculate the cosine similarity with the box girder construction plan in the database. The box girder construction plan will design corresponding simulated design values in advance to judge how to adjust the construction plan when risks occur during construction. Then, adjust the current construction according to the box girder construction plan with the maximum cosine similarity value under each construction process to complete the timely monitoring and processing of the on-site construction situation.

[0069] Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention, and still be covered by the protection scope of the present invention.

Claims

1. An intelligent monitoring and management system for the hoisting construction of super-high pier box beams, characterized in that: include: Construction collection module, used to collect construction monitoring data during box girder construction; The structural simulation module is used to extract the support connection points during the box girder construction from the construction monitoring data, obtain the stress change values ​​on the support connection points, convert the stress change values ​​into stress change curves, and set the stress gain vector according to the stress change curves of the support connection points; The settlement identification module is used to extract the settlement of the support connection point from the construction monitoring data, and combine the settlement with the stress change value according to the direction and value of the settlement distribution to obtain the settlement distribution diagram during the box girder construction; A structural matching module is used to analyze the relationship between each support connection point in the settlement distribution diagram, determine the matching degree of each support connection point in the settlement distribution diagram in turn, and adjust the stress gain vector according to the matching degree of each support connection point in the settlement distribution diagram; The risk assessment module is used to determine the risk impact range during box girder construction based on the adjusted stress gain vector, and adjust the box girder construction plan according to the risk impact range; The implementation methods of the settlement identification module include: Obtain the horizontal displacement and vertical displacement of the support connection point, and set the settlement amount and settlement angle of the support connection point in turn; Perform vector synthesis of the settlement angles of adjacent support connection points, and set the synthesized direction as the settlement direction; Based on the settlement amount and settlement direction of the support connection point, the load distribution of the support connection point is inverted; Obtain the actual load diagram of the support connection point, superimpose the actual load diagram of the support connection point with the load distribution, and set the load path according to the superimposed load value and the stress change value of the support connection point; Generate a settlement path according to the settlement amount and settlement direction of the support connection point, and check whether the load path and the settlement path intersect. If they do, output the intersection point; if they do not intersect, output the load path and the settlement path to obtain a settlement distribution diagram; The load path is set as follows: Calculate the load ratio of the superimposed load value of a single support connection point to all superimposed load values, and when the load ratio value is greater than a first ratio threshold, mark the corresponding support connection point, and divide the load concentration area with the center point of the marked support connection point as the center of the circle and the maximum distance between the marked support connection points as the diameter; The support connection points in the load concentration area are connected according to the direction of maximum stress to obtain the load path.

2. According to claim 1, the intelligent monitoring and management system for super-high pier box girder hoisting construction is characterized in that: The implementation methods of the structural simulation module include: According to the position of the support connection point, the stress change value at the support connection point is converted into a stress change sequence; For the stress change values ​​of the same support connection point at different time points, calculate the average absolute difference of stress at each support connection point; Compare the average absolute difference of stresses at adjacent support connection points, and analyze the stress movement of the average absolute difference of stresses at adjacent support connection points relative to the position of the support connection points to obtain the stress movement trend corresponding to the support connection points; Based on the acquired stress movement trend, the support connection points existing on the stress movement trend are identified, and the relative data change rate of the corresponding support connection points is calculated. According to the relative data change rate and stress change value of the support connection points existing on the stress movement trend, the stress change curve is obtained.

3. According to claim 2, the intelligent monitoring and management system for super-high pier box girder hoisting construction is characterized in that: The implementation methods of stress movement trend corresponding to support connection points include: The adjacent support connection points are divided into intervals according to the value of the mean absolute difference of stress, so as to obtain stress division intervals corresponding to the multiple support connection points; For each stress division interval, the probability of occurrence of the boundary value of each support connection point in the stress division interval is calculated; The support connection points corresponding to the maximum probability of occurrence of the boundary value in each stress division interval are connected, and the connected support connection points are regarded as the stress movement trend corresponding to the support connection points.

4. According to claim 3, the intelligent monitoring and management system for super-high pier box girder hoisting construction is characterized in that: The implementation method of obtaining the load path also includes: If there is no point in the maximum stress direction of the support connection point, the maximum stress direction is fitted to the settlement direction, and the support connection points closest to the fitted maximum stress direction are connected to obtain the load path.

5. According to claim 1, the intelligent monitoring and management system for super-high pier box girder hoisting construction is characterized in that: The implementation of the structure matching module is as follows: According to the distribution of each support connection point in the settlement distribution diagram, the Pearson correlation coefficient between each support connection point and the adjacent support connection point is calculated in turn; Based on the settlement amount of each support connection point in the settlement distribution map, the matching degree corresponding to each support connection point in the settlement distribution map is set; The stress gain vector is adjusted based on the Pearson correlation coefficient between each support connection point and the adjacent support connection points in the settlement distribution diagram and the matching degree corresponding to each support connection point.

6. The intelligent monitoring and management system for super-high pier box girder hoisting construction according to claim 1 is characterized in that: The implementation of the risk assessment module is as follows: According to the adjusted stress gain vector, determine whether the support connection point corresponding to the stress gain vector has risks, and set multiple risk area identifiers; Obtain the marking time of the risk area identification. If the difference between the marking times of two risk area identifications is less than the marking time threshold, the two risk area identifications are regarded as a group of risk area identifications, and the risk area identifications in each group are compared to capture the risk difference characteristics. According to the probability of occurrence of risk difference characteristics within the risk area identification, set the risk impact range corresponding to the risk area identification.

7. The intelligent monitoring and management system for super-high pier box girder hoisting construction according to claim 6 is characterized in that: According to the scope of risk impact, the box girder construction plan is adjusted as follows: Obtain the construction process within the risk impact range, associate the risk impact range with the database, calculate the cosine similarity between the risk impact range and the box girder construction plan in the database under each construction process, and adjust the current box girder construction plan based on the box girder construction plan with the largest cosine similarity value.

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