A road and bridge construction monitoring method and system based on deep learning and BIM

Abstract

The invention discloses a road and bridge construction monitoring method and system based on deep learning and BIM, and relates to the technical field of road and bridge construction monitoring. The three-dimensional model and deep learning algorithm of the road and bridge engineering established by BIM technology, as well as a data acquisition module, are used to obtain the initial position and current position of the monitoring point of the current road and bridge structure. The data monitoring and processing module is used to calculate the output displacement change KW, the stress value YL at the monitoring point, and the health index JK in sequence. Based on the health index JK and the warning conditions set by the warning module, the current road and bridge structure is monitored in real time. According to the warning result, the monitoring and adjustment are performed by using the system configuration and optimization module. The invention effectively solves the problems and shortcomings of the prior art by introducing advanced monitoring technology and intelligent analysis means, improves the monitoring accuracy and efficiency, realizes real-time warning and decision support, and provides a strong guarantee for the safety and durability of the road and bridge engineering.

Description

Technical Field

[0001] The present invention relates to the technical field of road and bridge construction monitoring, and in particular to a road and bridge construction monitoring method and system based on deep learning and BIM. Background Art

[0002] Road and bridge construction monitoring is an important part of ensuring project quality and traffic safety. With the rapid development of urbanization and the increase in transportation demand, the safety and reliability of roads and bridges have become the key to protecting people’s lives and property. Therefore, it is necessary to adopt advanced monitoring methods and systems to understand the construction status of roads and bridges in real time, and to discover and deal with problems in a timely manner.

[0003] However, some existing monitoring methods still rely on manual inspections and simple sensor monitoring, which are easily affected by human and environmental factors, resulting in inaccurate monitoring data. Due to the inaccuracy of monitoring data and the lack of real-time analysis capabilities, existing methods are often unable to detect potential safety hazards in a timely manner, resulting in untimely warnings, and are accompanied by low monitoring efficiency, which cannot meet the monitoring needs of large-scale road and bridge projects. In addition, existing methods lack intelligent data analysis methods, lack in-depth mining and analysis of monitoring data, and cannot provide comprehensive structural health status assessments and timely early warning measures. In order to overcome these shortcomings, road and bridge construction monitoring methods and systems based on deep learning and BIM came into being. Summary of the invention

[0004] The purpose of the present invention is to provide a road and bridge construction monitoring method based on deep learning and BIM, which solves the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides a road and bridge construction monitoring method based on deep learning and BIM, and the specific implementation steps are as follows:

[0006] Step 1: Use the three-dimensional model of the road and bridge project established by BIM technology, the deep learning algorithm, and the data acquisition module to obtain the initial position and current position of the current road and bridge structure monitoring point;

[0007] Step 2: Using the data monitoring and processing module, calculate the output displacement change KW, the stress value YL at the monitoring point, and the health index JK in sequence;

[0008] Step 3: Based on the health index JK and the warning conditions set by the warning module, real-time warning monitoring is performed on the current road and bridge structure;

[0009] Step 4: Based on the warning results, use the system configuration and optimization module to perform monitoring and adjustment;

[0010] The data monitoring and processing module includes a unit for directly reflecting the change of the spatial position of the road and bridge structure, a unit for determining the stress condition of the road and bridge structure, and a unit for comprehensively evaluating the health status of the road and bridge structure.

[0011] Optionally, the equipment used by the data acquisition module includes a sensor, a data acquisition card, and a data recorder;

[0012] The equipment used by the data monitoring and processing module includes computers and servers;

[0013] The equipment used by the early warning module includes early warning equipment;

[0014] The equipment used in the system configuration and optimization module includes BIM software and tools.

[0015] Optionally, the calculation formula for the unit that directly reflects the change in the spatial position of the road bridge structure is as follows:

[0016] KW=SQRT[(X2-X1) 2 +(Y2-Y1) 2 +(Z2-Z1) 2 ];

[0017] in:

[0018] KW is the displacement change;

[0019] X2 is the current horizontal coordinate;

[0020] X1 is the initial horizontal coordinate;

[0021] Y2 is the current vertical coordinate;

[0022] Y1 is the initial vertical coordinate;

[0023] Z2 is the current vertical coordinate;

[0024] Z1 is the initial vertical coordinate;

[0025] (X1, Y1, Z1) reflects the initial position of the current road and bridge structure monitoring point;

[0026] (X2, Y2, Z2) reflects the current position of the current road and bridge structure monitoring point.

[0027] Optionally, the calculation formula for determining the stress condition unit of the road and bridge structure is as follows:

[0028] YL=KW×T×J-((X2-X1) / J)×T;

[0029] in:

[0030] YL is the stress value at the monitoring point;

[0031] T is the elastic modulus of the material;

[0032] J is the distance between monitoring points, and J reflects the distance between the position (X1, Y1, Z1) and the position (X2, Y2, Z2).

[0033] Optionally, the calculation formula of the comprehensive evaluation unit of the road and bridge structure health status is as follows:

[0034] JK=(YL max / YL allow )×(1-(KW total / SQRT(M)))-YL avg / YL max ;

[0035] in:

[0036] JK is the health index, and its value range is {0-1};

[0037] YL max is the maximum monitored stress value, YL max Reflects the maximum stress value among all monitoring points on the road and bridge structure;

[0038] YL allow is the maximum stress value, YL allow It reflects the maximum known stress value corresponding to the monitoring point at the beginning of the road and bridge structure design;

[0039] KW total is the total displacement change, KW total It reflects the sum of the displacements of all monitoring points on the road and bridge structure that produce spatial changes;

[0040] M is the road and bridge area;

[0041] YL avg is the average stress value, YL avg Reflects the average degree of stress values ​​of all monitoring points monitored on the road and bridge structure.

[0042] Optionally, the total displacement change KW total The calculation formula is as follows:

[0043] KW total =KW1+KW2+KW3+……+KW;

[0044] KW1 is the displacement change of the first monitoring point, KW2 is the displacement change of the second monitoring point, KW3 is the displacement change of the third monitoring point, and KW is the displacement change of the current monitoring point;

[0045] The stress average value YL avgThe calculation formula is as follows:

[0046] YL avg =(YL1+YL2+YL3+……+YL n ) / n;

[0047] n is the total monitoring point, which reflects the sum of all monitoring points on the road and bridge structure;

[0048] YL1 is the stress value at the first monitoring point, YL2 is the stress value at the second monitoring point, YL3 is the stress value at the third monitoring point, and YL n is the stress value at the nth monitoring point;

[0049] Among them, the stress value YL at the nth monitoring point n That is the stress value YL at the monitoring point.

[0050] Optionally, the monitoring analysis based on the health index JK and its value range of {0-1} is as follows:

[0051] If the health index JK result is between {0.7-1}, it reflects that the current road and bridge structure is relatively stable and safe, and the current monitoring method should be maintained for real-time monitoring;

[0052] If the health index JK result is between {0.6-0}, it reflects that the current road and bridge structure has serious health problems and potential risks. A comprehensive inspection of the road and bridge structure should be carried out and the total number of monitoring points n should be increased.

[0053] The present invention also provides a road and bridge construction monitoring system based on deep learning and BIM, including a data acquisition module, a data monitoring and processing module, an early warning module and a system configuration and optimization module;

[0054] Data acquisition module: responsible for obtaining the current coordinates of the monitoring point from the sensor and the initial coordinates from the data recorder;

[0055] Data monitoring and processing module: responsible for calculating the output displacement change KW, stress value YL at the monitoring point, and health index JK in sequence;

[0056] Early warning module: responsible for setting the early warning conditions of the health index JK, and performing real-time early warning, monitoring, adjustment and display of the early warning conditions of the health index JK;

[0057] System configuration and optimization module: responsible for adjusting the monitoring points and monitoring frequency according to the monitoring adjustment display.

[0058] Optionally, the system configuration and optimization module includes a BIM model interface, monitoring point configuration software and monitoring frequency optimization software.

[0059] Compared with the prior art, the present invention has the following beneficial effects:

[0060] 1. The present invention integrates high-precision sensors and deep learning algorithms, so that the system can obtain monitoring data in real time and accurately, and automatically process and analyze data, thereby improving the accuracy of monitoring data. The deep learning algorithm conducts in-depth mining and analysis of monitoring data, so that the system can discover potential safety hazards and abnormal changes, and thus provide a more comprehensive structural health status assessment. In addition, the system also predicts and evaluates the structural health status based on historical data and real-time monitoring data, providing a scientific basis for future maintenance and management.

[0061] 2. The present invention utilizes the structural health index JK calculated by the comprehensive evaluation unit of the road and bridge structure health status, so that the system can judge the current health status of the road and bridge structure as a whole in real time, and trigger the early warning system when the health index JK is lower than the preset early warning condition. At the same time, the system can also provide decision support according to the value of the health index JK to help formulate a scientific and reasonable maintenance plan.

[0062] 3. The present invention uses automated monitoring and data analysis methods to greatly improve the monitoring efficiency of the system and reduce the workload of manual inspections and manual data recording. At the same time, the system can also automatically adjust the number and location of monitoring points and the monitoring frequency according to the monitoring results, thereby further optimizing the monitoring resource allocation. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 This is a method flow chart of the road and bridge construction monitoring method and system based on deep learning and BIM;

[0064] Figure 2 This is a schematic diagram of the overall modules of the road and bridge construction monitoring method and system based on deep learning and BIM;

[0065] Figure 3 It is a structural diagram of the data monitoring and processing module of the present invention;

[0066] Figure 4 It is a schematic diagram of early warning of the health index JK in the present invention. DETAILED DESCRIPTION

[0067] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0068] This road and bridge construction monitoring method and system based on deep learning and BIM is different from the existing road and bridge construction monitoring methods and systems. The existing road and bridge construction monitoring methods and systems have the problems of low monitoring efficiency, inaccurate data, and untimely early warning. This algorithm unit effectively solves the problems and shortcomings of the existing technology by introducing advanced monitoring technology and intelligent analysis methods, improves monitoring accuracy and efficiency, realizes real-time early warning and decision support, and provides strong guarantees for the safety and durability of road and bridge projects.

[0069] For example, see Figures 1 to 4 ,This implementation provides a road and bridge construction monitoring method based on deep learning and BIM. The specific implementation steps are as follows:

[0070] Step 1: Use the three-dimensional model of the road and bridge project established by BIM technology, the deep learning algorithm, and the data acquisition module to obtain the initial position and current position of the current road and bridge structure monitoring point;

[0071] Step 2: Using the data monitoring and processing module, calculate the output displacement change KW, the stress value YL at the monitoring point, and the health index JK in sequence;

[0072] Step 3: Based on the health index JK and the warning conditions set by the warning module, real-time warning monitoring is performed on the current road and bridge structure;

[0073] Step 4: Based on the warning results, use the system configuration and optimization module to perform monitoring and adjustment;

[0074] The data monitoring and processing module includes a unit that directly reflects the changes in the spatial position of the road and bridge structure, a unit that determines the stress conditions of the road and bridge structure, and a unit that comprehensively evaluates the health status of the road and bridge structure.

[0075] The equipment used in the data acquisition module includes sensors, data acquisition cards, and data recorders;

[0076] The equipment used in the data monitoring and processing module includes computers and servers;

[0077] The equipment used by the early warning module includes early warning equipment;

[0078] The equipment used in the system configuration and optimization module includes BIM software and tools.

[0079] In this embodiment, the system cooperates with each other through three algorithm units and combines the three operation results of KW, YL and JK to form the core algorithm of the road and bridge construction monitoring system based on deep learning and BIM. Specifically, KW is the displacement change, which can monitor the dynamic changes of the road and bridge structure in real time and detect abnormal displacement of the structure in time, so as to prevent accidents. In addition, KW can also be used as the basic data for subsequent stress calculation and structural health assessment, providing accurate spatial position information for road and bridge construction monitoring. YL is the stress value at the monitoring point. By calculating this value, we can deeply understand the stress condition of the road and bridge structure under specific conditions. JK is the health index, which is an indicator that comprehensively reflects the stress condition, stability and durability of the structure. By calculating JK, the overall performance of the road and bridge structure can be quantitatively evaluated. When JK triggers the early warning condition, the early warning system will be triggered, which will prompt the need for further inspection and maintenance of the structure. This early warning mechanism helps to discover potential safety hazards in a timely manner and avoid accidents. The calculation results of JK can also affect the calculation of KW and YL, so that the three algorithms of this system form a mechanism of mutual correlation and influence. This mechanism not only improves the accuracy and efficiency of monitoring, but also provides strong data support for decision-making during the construction process. At the same time, the cyclic influence mechanism of JK on KW and YL further optimizes the configuration of monitoring resources, forms a closed-loop monitoring and evaluation system, and provides more comprehensive and in-depth information support for road and bridge construction monitoring.

[0080] See also Figures 1 to 4 , the calculation formula that directly reflects the change unit of the road bridge structure in spatial position is as follows:

[0081] KW=SQRT[(X2-X1) 2 +(Y2-Y1) 2 +(Z2-Z1) 2 ];

[0082] in:

[0083] KW is the displacement change;

[0084] X2 is the current horizontal coordinate;

[0085] X1 is the initial horizontal coordinate;

[0086] Y2 is the current vertical coordinate;

[0087] Y1 is the initial vertical coordinate;

[0088] Z2 is the current vertical coordinate;

[0089] Z1 is the initial vertical coordinate;

[0090] (X1, Y1, Z1) reflects the initial position of the current road and bridge structure monitoring point;

[0091] (X2, Y2, Z2) reflects the current position of the current road and bridge structure monitoring point.

[0092] In this embodiment: First, in this algorithm unit, "SQRT[(X2-X1) 2 +(Y2-Y1) 2 +(Z2-Z1) 2 ]” The calculation part is used to calculate the three-dimensional space straight-line distance from the initial position (X1, Y1, Z1) to the current position (X2, Y2, Z2) of the monitoring point, that is, the displacement change KW, which is an important indicator for evaluating structural deformation and movement, and the displacement change KW is the core output of the unit that directly reflects the change of the spatial position of the road and bridge structure. It directly reflects the change of the spatial position of the monitoring point. This value will be used in the calculation of the road and bridge structure stress condition unit and the comprehensive evaluation of the road and bridge structure health status unit as the basic data for evaluating the structural stress and health status;

[0093] This algorithm unit can obtain the dynamic change information of the road and bridge structure in real time by monitoring the change of displacement KW in real time, which is of great significance for timely discovering structural abnormalities and preventing accidents. The real-time monitoring data of displacement change KW can be used as an important reference in the construction process, thereby helping to adjust the construction plan in time to ensure construction quality and safety.

[0094] The calculation of displacement change KW relies on accurate coordinate measurement and calculation technology, so it can accurately reflect the displacement of the monitoring point. High-precision displacement monitoring helps to accurately evaluate the stability and safety of the structure and provide a scientific basis for quality control and risk management during the construction process.

[0095] The change in displacement variation KW can reflect the stress condition and stability of the road and bridge structure. Specifically, when the displacement variation KW suddenly increases, it means that the structure is subjected to a large external force and there are potential safety hazards. By analyzing the changing trend and law of the displacement variation KW, the future state of the structure can be predicted, thereby guiding the adjustment and optimization during the construction process.

[0096] See also Figures 1 to 4 , the calculation formula for determining the stress condition unit of the road and bridge structure is as follows:

[0097] YL=KW×T×J-((X2-X1) / J)×T;

[0098] in:

[0099] YL is the stress value at the monitoring point;

[0100] T is the elastic modulus of the material;

[0101] J is the distance between monitoring points, and J reflects the distance between the position (X1, Y1, Z1) and the position (X2, Y2, Z2).

[0102] In this embodiment, first, the "KW×T×J" calculation part is used to calculate a part of the stress value according to the displacement change KW, the material elastic modulus T and the monitoring point spacing J between the monitoring points. It converts the displacement into the stress value based on the principle of elastic mechanics. This part of the calculation is one of the main components of the stress value YL at the monitoring point. It reflects the direct impact of the displacement on the structural stress. By combining with the calculation of the subsequent part, the final stress value YL at the monitoring point can be obtained;

[0103] The calculation part expression of "((X2-X1) / J)×T" is used to calculate the influence of the relative displacement ratio in the displacement direction on the stress value. It takes into account the component of the displacement in a specific direction and adjusts the stress calculation accordingly. This part of the calculation is a correction to the stress value YL at the monitoring point. It takes into account the possible influence of the displacement direction on the structural stress. By combining it with the results of the first part of the calculation, a more accurate stress value YL at the monitoring point can be obtained.

[0104] This algorithm unit can directly reflect the stress state of the road bridge structure under specific conditions through the stress value YL at the monitoring point, and by analyzing the changes in the stress value YL at the monitoring point, it can understand the stress characteristics of the structure under different working conditions, providing a basis for structural design and optimization. When the stress value YL at the monitoring point exceeds the allowable range, it means that there are safety hazards in the structure, and corresponding measures need to be taken to strengthen and repair it;

[0105] Different materials will produce different stress values ​​YL at the monitoring points under the same displacement. By comparing the stress values ​​YL at the monitoring points of different materials, their stress performance and durability can be evaluated, so as to select more suitable materials for road and bridge construction;

[0106] The change of stress value YL at the monitoring point can reflect the stability and safety of the structure. During the construction process, by real-time monitoring of the change of stress value YL at the monitoring point, potential safety hazards can be discovered in time, providing important reference for construction decisions. Specifically, when it is found that the stress value YL at the monitoring point increases abnormally, the construction can be stopped immediately and an inspection can be carried out to avoid accidents.

[0107] See also Figures 1 to 4 , the calculation formula for the comprehensive evaluation unit of road and bridge structure health status is as follows:

[0108] JK=(YL max / YL allow )×(1-(KW total / SQRT(M)))-YL avg / YL max ;

[0109] in:

[0110] JK is the health index, and its value range is {0-1};

[0111] YL max is the maximum monitored stress value, YL max Reflects the maximum stress value among all monitoring points on the road and bridge structure;

[0112] YL allow is the maximum stress value, YL allow It reflects the maximum known stress value corresponding to the monitoring point at the beginning of the road and bridge structure design;

[0113] KW total is the total displacement change, KW total It reflects the sum of the displacements of all monitoring points on the road and bridge structure that produce spatial changes;

[0114] M is the road and bridge area;

[0115] YL avg is the average stress value, YL avg Reflects the average degree of stress values ​​of all monitoring points monitored on the road and bridge structure;

[0116] Total displacement change KW total The calculation formula is as follows:

[0117] KW total =KW1+KW2+KW3+……+KW;

[0118] KW1 is the displacement change of the first monitoring point, KW2 is the displacement change of the second monitoring point, KW3 is the displacement change of the third monitoring point, and KW is the displacement change of the current monitoring point;

[0119] Stress average value YL avg The calculation formula is as follows:

[0120] YL avg =(YL1+YL2+YL3+……+YL n ) / n;

[0121] n is the total monitoring point, which reflects the sum of all monitoring points on the road and bridge structure;

[0122] YL1 is the stress value at the first monitoring point, YL2 is the stress value at the second monitoring point, YL3 is the stress value at the third monitoring point, and YL n is the stress value at the nth monitoring point;

[0123] Among them, the stress value YL at the nth monitoring point n That is the stress value YL at the monitoring point.

[0124] In this embodiment, the algorithm unit firstly calculates the max / YL allow )” calculation part is used to calculate the maximum monitoring stress value YL experienced by the structure during the monitoring period max and the maximum stress value YL allow It reflects the relative relationship between the structural stress state and the safety limit. This part of the calculation is one of the important components of the structural health index JK, which directly affects the value of the health index JK. By comparing the maximum monitoring stress value YL max and the maximum stress value YL allow , can assess whether the stress state of the structure is safe;

[0125] “(1-(KW total / SQRT(M)))” calculation part is used to calculate the total displacement change KW of all monitoring points total The ratio of the total displacement to the square root of the area M of the road and bridge reflects the relative relationship between the overall deformation degree of the structure and its size. This part of the calculation is used to adjust the influence of the total displacement on the structural health index JK. By considering the structural size, the calculation of the health index JK can be made more reasonable and accurate.

[0126] “YL avg / YL max The calculation part is used to calculate the stress average value YL avg The maximum stress value YL experienced during the monitoring period allow The ratio of the current stress state to the maximum stress state reflects the relative relationship between the current stress state and the maximum stress state. This part of the calculation is a further correction of the structural health index JK. It takes into account the influence of the current stress state on the health index JK. By combining it with the calculation in the previous part, the final health index JK value can be obtained. Among them, the stress average value YL avg It can better reflect the overall force distribution and changes of the structure;

[0127] The unit health index JK of this algorithm can comprehensively reflect the health status of the road and bridge structure, including the stress condition, stability and durability of the structure. By calculating the health index JK, the overall performance of the structure can be quantitatively evaluated, providing a scientific basis for structural management and maintenance. When the health index JK is in the early warning condition, it means that there are serious safety hazards in the structure and immediate measures need to be taken to repair and reinforce it. By setting the early warning conditions of the health index JK, real-time monitoring and early warning of the health status of the structure can be achieved. When the health index JK is close to or in the early warning condition, the system will issue an early warning signal to remind timely intervention measures.

[0128] Early warning and prevention mechanisms help to timely detect potential safety hazards, avoid accidents, and ensure the safe operation of road and bridge structures;

[0129] The change of health index JK can reflect the degradation degree and repair needs of the structure. By analyzing the changing trend and law of health index JK, the future state of the structure can be predicted, so as to formulate a scientific and reasonable maintenance and repair plan. Specifically, when the health index JK continues to decline, it means that the structure has serious degradation problems and needs to be repaired and reinforced immediately. Through timely maintenance and repair, the service life of the structure can be extended and its safety and durability can be improved.

[0130] See also Figures 1 to 4 , based on the health index JK, and its value range of {0-1}, the monitoring analysis is as follows:

[0131] If the health index JK result is between {0.7-1}, it reflects that the current road and bridge structure is relatively stable and safe, and the current monitoring method should be maintained for real-time monitoring;

[0132] If the health index JK result is between {0.6-0}, it reflects that the current road and bridge structure has serious health problems and potential risks. A comprehensive inspection of the road and bridge structure should be carried out and the total number of monitoring points n should be increased.

[0133] In this embodiment, when the health index JK result is between {0.6-0}, the early warning system is triggered, prompting the monitoring system to increase the monitoring frequency of a specific area, which means that the number and position of the monitoring points in the unit that directly reflects the change in the spatial position of the road and bridge structure will be adjusted according to the result of the health index JK, thereby improving the sensitivity and accuracy of the monitoring. Through the cyclic influence mechanism, the monitoring system can dynamically adjust the number and position of the monitoring points according to the change in the health index JK, thereby optimizing the configuration of monitoring resources and improving the monitoring efficiency. The cyclic influence of the unit that comprehensively evaluates the health status of the road and bridge structure on the unit that directly reflects the change in the spatial position of the road and bridge structure enables the monitoring system to form a closed-loop monitoring and evaluation system. In this system, monitoring data is continuously collected, analyzed and utilized to achieve continuous monitoring and early warning of the health status of the road and bridge structure, and through continuous monitoring of the health index JK and observation of the change interval, abnormal changes in the health status of the structure can be discovered in time, and the system can automatically issue an early warning, thereby prompting further inspection and evaluation. This ability to discover potential risks in time helps to avoid serious accidents in unknown states.

[0134] The early warning system can ensure that action is taken before the structural health index drops to a dangerous level. By taking a series of countermeasures, potential problems in the structure can be discovered and repaired in time, thereby improving the safety of the structure, which helps to protect the lives and property of people and reduce the losses caused by structural failure;

[0135] Observing the change range of the health index JK result and issuing early warnings can also help optimize the maintenance strategy of the structure. By analyzing historical data, we can understand the performance change law of the structure under different working conditions, so as to formulate a more scientific and reasonable maintenance plan, which can not only improve maintenance efficiency, but also reduce maintenance costs;

[0136] In summary, the unit that directly reflects the change of the road and bridge structure in spatial position, the unit that determines the stress condition of the road and bridge structure, and the unit that comprehensively evaluates the health status of the road and bridge structure each play an important role in the road and bridge construction monitoring method and system based on deep learning and BIM, and a mechanism of mutual correlation and influence is formed between them. This mechanism not only improves the accuracy and efficiency of monitoring, but also provides strong data support for decision-making during the construction process. At the same time, the cyclic influence mechanism of the unit for comprehensively evaluating the health status of the road and bridge structure on the unit that directly reflects the change of the road and bridge structure in spatial position further optimizes the configuration of monitoring resources, forms a closed-loop monitoring and evaluation system, and provides more comprehensive and in-depth information support for road and bridge construction monitoring. Among them, the beneficial effects of observing the change range of the health index JK results and issuing early warnings include timely discovery of potential risks, improving structural safety, and optimizing maintenance strategies. These effects work together in the field of structural management and provide strong guarantees for the safe operation and sustainable development of the structure.

[0137] For example 2, please refer to Figures 1 to 4 ,This implementation provides a road and bridge construction monitoring system based on deep learning and BIM, including a data acquisition module, a data monitoring and processing module, an early warning module, and a system configuration and optimization module;

[0138] Data acquisition module: responsible for obtaining the current coordinates of the monitoring point from the sensor and the initial coordinates from the data recorder;

[0139] Data monitoring and processing module: responsible for calculating the output displacement change KW, stress value YL at the monitoring point, and health index JK in sequence;

[0140] Early warning module: responsible for setting the early warning conditions of the health index JK, and performing real-time early warning, monitoring, adjustment and display of the early warning conditions of the health index JK;

[0141] System configuration and optimization module: responsible for adjusting the monitoring points and monitoring frequency according to the monitoring adjustment display;

[0142] The system configuration and optimization module includes BIM model interface, monitoring point configuration software and monitoring frequency optimization software.

[0143] In this embodiment, first, in the initialization and data preparation stage, a three-dimensional model of the road and bridge project is established using BIM technology. This model contains key data of the structure's geometry, material properties, and construction information. Subsequently, the locations of the monitoring points are determined, and the initial coordinates (X1, Y1, Z1) of these monitoring points are extracted from the BIM model. At the same time, deep learning algorithms and models are prepared to provide technical support for subsequent data analysis and early warning.

[0144] Next, we enter the displacement monitoring and calculation stage. Through the sensors installed on the road and bridge, we obtain the current coordinates (X2, Y2, Z2) of the monitoring point in real time. Using the data monitoring and processing module, we calculate the output displacement change KW, the stress value YL at the monitoring point, and the health index JK in turn.

[0145] Then, the structural health index JK calculation and early warning stage is entered. Based on the health index JK and the early warning module, the early warning conditions of the health index JK are set to carry out early warning and further inspection and maintenance of the structure.

[0146] Finally, the monitoring and evaluation cycle phase begins. Based on the early warning results, the system configuration and optimization module adjusts the number and location of monitoring points and increases the monitoring frequency of specific areas. Then, new monitoring data is obtained and the previous steps are repeated to form a closed-loop monitoring and evaluation system. This process is dynamic and can be flexibly adjusted according to actual conditions to ensure the safety and quality of road and bridge construction.

[0147] Throughout the entire process, the system consists of multiple modules and units, including data acquisition modules, data monitoring and processing modules, early warning modules, and system configuration and optimization modules. These modules and units work together to achieve real-time monitoring and evaluation of road and bridge construction. At the same time, the system also relies on a variety of equipment, including sensors, data acquisition equipment, computers, and BIM software and tools, which provide necessary support for the normal operation of the system.

[0148] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations can be made to the embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A road and bridge construction monitoring method based on deep learning and BIM, characterized in that: The specific implementation steps are as follows: Step 1: Use the three-dimensional model of the road and bridge project established by BIM technology, the deep learning algorithm, and the data acquisition module to obtain the initial position and current position of the current road and bridge structure monitoring point; Step 2: Using the data monitoring and processing module, calculate the output displacement change KW, the stress value YL at the monitoring point, and the health index JK in sequence; Step 3: Based on the health index JK and the warning conditions set by the warning module, real-time warning monitoring is performed on the current road and bridge structure; Step 4: Based on the warning results, use the system configuration and optimization module to perform monitoring and adjustment; The data monitoring and processing module includes a unit for directly reflecting the change of the spatial position of the road and bridge structure, a unit for determining the stress condition of the road and bridge structure, and a unit for comprehensively evaluating the health status of the road and bridge structure; The equipment used in the data acquisition module includes sensors, data acquisition cards, and data recorders; The equipment used by the data monitoring and processing module includes computers and servers; The equipment used by the early warning module includes early warning equipment; The equipment used in the system configuration and optimization module includes BIM software and tools; The calculation formula that directly reflects the change unit of the road bridge structure in spatial position is as follows: <h2 style=";text-align:left;direction:ltr">KW=SQRT[(X2-X1)<h2 style=";text-align:left;direction:ltr"> 2 <h2 style=";text-align:left;direction:ltr"> +(Y2-Y1)<h2 style=";text-align:left;direction:ltr"> 2 <h2 style=";text-align:left;direction:ltr"> +(Z2-Z1)<h2 style=";text-align:left;direction:ltr"> 2 <h2 style=";text-align:left;direction:ltr"> ]; in: KW is the displacement change; X2 is the current horizontal coordinate; X1 is the initial horizontal coordinate; Y2 is the current vertical coordinate; Y1 is the initial vertical coordinate; Z2 is the current vertical coordinate; Z1 is the initial vertical coordinate; (X1, Y1, Z1) reflects the initial position of the current road and bridge structure monitoring point; (X2, Y2, Z2) reflects the current position of the current road and bridge structure monitoring point; The calculation formula for determining the stress condition unit of the road and bridge structure is as follows: YL=KW×T×J-((X2-X1) / J)×T; in: YL is the stress value at the monitoring point; T is the elastic modulus of the material; J is the distance between monitoring points, and J reflects the distance between the position (X1, Y1, Z1) and the position (X2, Y2, Z2).

2. A road and bridge construction monitoring method based on deep learning and BIM according to claim 1, characterized in that: The calculation formula for the comprehensive evaluation unit of road and bridge structure health status is as follows: JK=(YL max / YL allow )×(1-(KW total / SQRT(M)))-YL avg / YL max ; in: JK is the health index, and its value range is {0-1}; YL max is the maximum monitored stress value, YL max Reflects the maximum stress value among all monitoring points on the road and bridge structure; YL allow is the maximum stress value, YL allow It reflects the maximum known stress value corresponding to the monitoring point at the beginning of the road and bridge structure design; KW total is the total displacement change, KW total It reflects the sum of the displacements of all monitoring points on the road and bridge structure that produce spatial changes; M is the road and bridge area; YL avg is the average stress value, YL avg Reflects the average degree of stress values ​​of all monitoring points monitored on the road and bridge structure.

3. A road and bridge construction monitoring method based on deep learning and BIM according to claim 2, characterized in that: The total displacement change KW total The calculation formula is as follows: KW total =KW1+KW2+KW3+……+KW; KW1 is the displacement change of the first monitoring point, KW2 is the displacement change of the second monitoring point, KW3 is the displacement change of the third monitoring point, and KW is the displacement change of the current monitoring point; The stress average value YL avg The calculation formula is as follows: YL avg =(YL1+YL2+YL3+……+YL n ) / n; n is the total monitoring point, which reflects the sum of all monitoring points on the road and bridge structure; YL1 is the stress value at the first monitoring point, YL2 is the stress value at the second monitoring point, YL3 is the stress value at the third monitoring point, and YL n is the stress value at the nth monitoring point; Among them, the stress value YL at the nth monitoring point n That is the stress value YL at the monitoring point.

4. The road and bridge construction monitoring method based on deep learning and BIM according to claim 3 is characterized in that: The monitoring analysis based on the health index JK and its value range of {0-1} is as follows: If the health index JK result is between {0.7-1}, it reflects that the current road and bridge structure is stable and safe, and the current monitoring method should be maintained for real-time monitoring; If the health index JK result is between {0.6-0}, it reflects that the current road and bridge structure has serious health problems and potential risks. A comprehensive inspection of the road and bridge structure should be carried out and the total number of monitoring points n should be increased.

5. The monitoring system used in the road and bridge construction monitoring method based on deep learning and BIM according to claim 1 is characterized in that: Including data acquisition module, data monitoring and processing module, early warning module and system configuration and optimization module; Data acquisition module: responsible for obtaining the current coordinates of the monitoring point from the sensor and the initial coordinates from the data recorder; Data monitoring and processing module: responsible for calculating the output displacement change KW, stress value YL at the monitoring point, and health index JK in sequence; Early warning module: responsible for setting the early warning conditions of the health index JK, and performing real-time early warning, monitoring, adjustment and display of the early warning conditions of the health index JK; System configuration and optimization module: responsible for adjusting the monitoring points and monitoring frequency according to the monitoring adjustment display.

6. The monitoring system used in the road and bridge construction monitoring method based on deep learning and BIM according to claim 5 is characterized in that: The system configuration and optimization module includes a BIM model interface, monitoring point configuration software and monitoring frequency optimization software.

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