Shear wall structure overall response evaluation method based on coupling beam damper local monitoring

Abstract

The invention discloses a coupling beam damper local monitoring-based shear wall structure overall response evaluation method. The method comprises the steps of constructing a graph neural network model according to shear wall structure information of a target building; calibrating the coupling beam damper, and obtaining a stress state characteristic signal from a health state to a limit state to complete training of the graph neural network model; arranging a piezoelectric transducer and a displacement sensor on a coupling beam damper of the target shear wall structure to obtain a target characteristic signal; inputting the target characteristic signal at the target moment into the graph neural network model to obtain the stress state of the coupling beam damper and the mechanical response of the wall column at the target moment; respectively constructing a finite element model of the coupling beam damper and a building structure model containing a target shear wall structure; and respectively inputting the stress state of the coupling beam damper and the mechanical response of the wall column at the target moment into a finite element model and a building structure model for visual display. According to the method, the overall structure response is evaluated by locally monitoring the damper, so that the complexity of a monitoring system is reduced, and the evaluation accuracy is ensured.

Description

Technical Field

[0001] The present invention relates to the field of structural damage identification and health monitoring, and particularly to a method for evaluating the overall response of a shear wall structure based on local monitoring of coupling beam dampers. Background Art

[0002] With the increasing number of high-rise and super high-rise buildings, reinforced concrete coupled shear wall structures have been widely used due to their advantages such as large lateral stiffness and bearing capacity, multiple seismic defense lines, and flexibility of building functions. The coupling beam is the first line of defense in the seismic design of coupled shear wall structures. Under earthquake action, the coupling beam yields and dissipates a large amount of energy. However, reinforced concrete coupling beams have poor deformation capacity, are prone to damage after yielding, and are difficult to repair, which is not conducive to the post-disaster reconstruction of building structures.

[0003] To solve this problem, replaceable coupling beam dampers have been developed and applied. Compared with ordinary concrete coupling beams, replaceable coupling beam dampers can not only effectively absorb and disperse the energy caused by earthquakes or wind loads, reduce the vibration amplitude of the structure, protect buildings and their internal equipment from damage, but also can be replaced in time after damage, which is conducive to the post-disaster reconstruction of building structures.

[0004] Currently, the following methods are mainly used for the health monitoring of coupled shear wall structures with coupling beam dampers:

[0005] 1. Manual detection method, that is, through professional personnel's regular or irregular visual observation, instrument measurement, test detection, etc. of the building, data such as the deformation, cracks, displacement, stress, etc. of the building are obtained for analysis and judgment. However, this method has low efficiency, high cost, poor accuracy, and is greatly affected by human factors, and it is difficult to achieve full coverage of large-scale, complex or high-rise buildings.

[0006] 2. Intelligent monitoring method, that is, by deploying various sensors and devices, such as fiber Bragg gratings, strain gauges, inclinometers, accelerometers, GPS, etc., the structural response data and environmental data of the building are collected in real time or dynamically, and data processing, analysis and early warning are carried out through a cloud server or a local computer. However, this method also faces problems such as difficult information processing due to the variety of sensor types, and slow data processing speed due to the large building model and data volume, which restricts its commercial application. Summary of the Invention

[0007] In view of this, the present invention proposes a method for evaluating the overall response of a shear wall structure based on local monitoring technology of coupling beam dampers. This method aims at the characteristics of the coupling beam damper as the first line of defense of the coupled shear wall structure, and realizes the evaluation of the overall structural response through local monitoring of the damper, which not only reduces the complexity of the monitoring system, but also ensures the accuracy of the evaluation.

[0008] To achieve the above-mentioned invention object, the technical solution provided by the present invention includes:

[0009] A method for evaluating the overall response of a shear wall structure based on local monitoring of coupling beam dampers, comprising the following steps:

[0010] S1. Construct a graph neural network model according to the shear wall structure information of the target building, and the graph neural network model is used to predict the mechanical response of the wall piers according to the stress state of the coupling beam dampers;

[0011] S2. Calibrate the coupling beam dampers to obtain the stress state characteristic signals from the healthy state to the ultimate state for completing the training of the graph neural network model; the characteristic signals include piezoelectric signals and hysteresis curves of the coupling beam dampers under different damage degrees;

[0012] S3. Set piezoelectric transducers and displacement sensors on the coupling beam dampers of the target shear wall structure to obtain target characteristic signals;

[0013] S4. Input the target characteristic signals at the target time into the graph neural network model to obtain the stress state of the coupling beam dampers and the mechanical response of the wall piers at the target time;

[0014] S5. Respectively construct a finite element model of the coupling beam damper and a building structure model including the target shear wall structure;

[0015] S6. Input the stress state of the coupling beam dampers and the mechanical response of the wall piers at the target time into the finite element model and the building structure model respectively for visual display.

[0016] Preferably, it further includes the step:

[0017] S7. Calculate the overall mechanical response of the shear wall structure according to the mechanical response of the wall piers at the target time, and compare it with the code requirements to judge whether the target building can continue to dissipate energy and reduce vibration after an earthquake.

[0018] Preferably, it further includes the step:

[0019] S7. Calculate the mechanical responses of the wall piers at the initial time and the ultimate state respectively according to step S4, calculate the corresponding overall mechanical response of the shear wall structure, and judge the seismic performance of the target building.

[0020] Preferably, the method for calibrating the coupling beam dampers in step S2 includes:

[0021] S201. Fix the coupling beam damper on the shear frame, polish and paste piezoelectric transducers at predetermined positions, and install displacement sensors;

[0022] S202. Conduct a shear test on the coupling beam damper with displacement loading, and collect piezoelectric signals and hysteresis curves from the healthy state to the ultimate state as characteristic signals under different stress states.

[0023] Preferably, the method of constructing a graph neural network model according to the shear wall structure information of the target building in step S1 includes:

[0024] Convert the shear wall structure information of the target building into graph structure data, and use an undirected graph to describe the structural system as follows:

[0025] G=(V, E, A); where V represents the characteristics of the coupling beam and the coupling beam damper, including flexural stiffness and shear stiffness; E represents the characteristics of the shear wall piers, including the flexural stiffness, shear stiffness, and tensile and compressive strength between the piers of each shear wall layer; A represents the topological relationship of the shear wall piers.

[0026] Preferably, in the graph neural network model, the mechanical response of a single pier is expressed as:

[0027] o v =g(θ v , u v , h v ); where θ v , u v represent the rotation angle and displacement of the current pier; h v is the state of the current pier, determined by the states of the adjacent piers;

[0028] The stress state of a single coupling beam damper is expressed as: V v =l(θ v , u v , o v ).

[0029] Preferably, the method of setting piezoelectric transducers on the coupling beam dampers of the target shear wall structure in step S3 includes:

[0030] Set piezoelectric transducers according to different vulnerable parts of the coupling beam damper:

[0031] Set the first piezoelectric transducer at the end plate and flange to monitor the damage at the weld between the flange and the end plate;

[0032] Set the second piezoelectric transducer at the end plate to monitor the buckling damage of the web and the tearing damage at the connection between the web and the end plate;

[0033] Set the third piezoelectric transducer at the flange to monitor the damage at the connection between the web and the flange.

[0034] Preferably, the method of setting displacement sensors on the coupling beam dampers of the target shear wall structure in step S3 includes:

[0035] Fix the displacement sensor on the wall limb or loading beam connected to one end of the coupling beam damper by a magnetic attraction connection method;

[0036] Set a fixing piece on the wall limb or loading beam connected to the other end of the coupling beam damper, and press the probe of the displacement sensor against the connection between the fixing piece and the wall limb or loading beam.

[0037] Preferably, the method for judging the seismic performance of the target building in step S7 includes:

[0038] Calculate the mechanical responses of the overall shear wall structure at the initial moment and the ultimate state respectively and compare them to obtain the performance degradation in terms of ductility capacity and energy dissipation capacity.

[0039] Beneficial effects

[0040] In view of the characteristics of the coupling beam damper as the first line of defense in the coupled shear wall structure, the present invention only conducts local monitoring on the damper, avoiding the installation of a large number of sensors on the entire building structure, reducing the complexity and cost of the monitoring system, and reducing the workload of data acquisition and processing.

[0041] Calibrate the coupling beam damper by the piezoelectric wave method to establish the correspondence between the damage state and the characteristic signal. At the same time, adopt the graph neural network model to reflect the topological relationship of the building structure, and combine finite element analysis to verify the evaluation results, improving the accuracy and reliability of the structural response prediction.

[0042] Conduct local monitoring by setting piezoelectric transducers and displacement sensors on the coupling beam damper. Based on the acquired monitoring data, use the trained graph neural network model to predict the overall structural response, and through establishing a digital twin model, visually display the structural deformation and damage state, realizing the technical route from local monitoring to overall evaluation.

[0043] Provide two evaluation methods: comparison with specification requirements and comparison of pre-earthquake and post-earthquake states. By calculating the changes in the ductility capacity and energy dissipation capacity of the structure, quantitatively evaluate the seismic performance of the building structure, providing a reliable basis for the maintenance and renewal decision-making of the structure. Description of the drawings

[0044] Figure 1 Schematic diagram of the process of the method for evaluating the overall response of a shear wall structure based on local monitoring of a coupling beam damper provided in a preferred embodiment of the present invention;

[0045] Figure 2 Schematic diagram of converting the shear wall structure information of the target building into graph structure data provided in a preferred embodiment of the present invention;

[0046] Figure 3This is a schematic diagram of the calibration test for the coupling beam damper provided in a preferred embodiment of the present invention. Detailed implementation manners

[0047] In order to make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described below with reference to the accompanying drawings. In the description of the present invention, it should be understood that the orientation or positional relationships indicated by the terms "upper", "lower", "front", "rear", "left", "right", "top", "bottom", "inner", "outer", etc. are based on the orientation or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as a limitation to the present invention.

[0048] As Figure 1 shown, this embodiment provides a method for evaluating the overall response of a shear wall structure based on local monitoring of a coupling beam damper, including the following steps:

[0049] S1. Construct a graph neural network model according to the shear wall structure information of the target building, and the graph neural network model is used to predict the mechanical response of the wall piers according to the force state of the coupling beam damper.

[0050] A graph neural network model is a deep learning model specifically for processing graph-structured data. It can automatically learn and extract the relationship features between nodes in the graph, and complete the prediction task through the transmission and aggregation of information in the graph structure. In the field of building structures, a shear wall structure is composed of multiple wall piers connected by coupling beams, and there is a clear topological relationship between the components. The force state of one component will affect adjacent components, and local damage will also affect the overall structural performance through the connection relationship between the components. This mutual relationship between the components has a natural correspondence with the graph structure.

[0051] The present invention selects to use a graph neural network model mainly based on the following considerations: First, the shear wall structure naturally has the characteristics of a graph. The wall piers can be regarded as nodes in the graph, and the coupling beams can be regarded as edges connecting the nodes. The graph neural network can naturally express this connection relationship between the components; Second, the graph neural network has excellent information transmission ability, and can simulate the transmission process of force and deformation in the structure, so as to achieve the goal of inferring the overall response from local monitoring data; Finally, since the graph neural network considers the mutual influence between the components during modeling, it is more suitable for processing data with spatial relationships than traditional neural networks and can provide more accurate prediction results. In some preferred embodiments, a specific method for constructing a graph neural network model according to the shear wall structure information of the target building is given:

[0052] As Figure 2As shown in the figure, the shear wall structure information of the target building is converted into graph structure data, and an undirected graph is used to describe the structural system as follows:

[0053] G = (V, E, A); where V represents the characteristics of coupling beams and coupling beam dampers; E represents the characteristics of shear wall piers; A represents the topological relationship of shear wall piers. Specifically:

[0054]

[0055] Among them, V J represents the flexural stiffness of the coupling beam and coupling beam damper between piers; V G represents the shear stiffness of the coupling beam and coupling beam damper between two piers. E l represents the elastic modulus of the coupling beam, and E z represents the elastic modulus of the coupling beam damper. G l represents the shear modulus of the coupling beam, and G z represents the shear modulus of the coupling beam damper.

[0056]

[0057] Among them, E J represents the flexural stiffness between the piers of each floor of the shear wall; E G represents the shear stiffness between the piers of each floor of the shear wall; E A represents the tensile and compressive strength of each floor of the pier.

[0058]

[0059] Among them, where A ij = 1 indicates that the two piers are connected by a coupling beam and a coupling beam damper, and A ij = -1 indicates that the two piers are a shear wall, and A ij = 0 indicates that the two piers have no connection relationship.

[0060] The graph neural network model takes the pier as the node of the graph and the coupling beam damper as the edge between the nodes. The node features include the geometric and mechanical properties of the pier, and the edge features include the mechanical properties of the coupling beam damper. The stress state of the coupling beam damper (obtained by sensor monitoring) is used as the input, and the mechanical responses (including deformation and internal force) of the adjacent piers are output. In some preferred embodiments, the graph neural network model includes an information transfer network for calculating the state of the pier and a mechanical response prediction network for predicting the stress.

[0061] In the information transfer network, for each pier of the coupled shear wall structure, its state can be represented by the local transfer function h v = f(·), where h v is determined by the states of the piers adjacent to the pier: where θ v , u v represent the rotation angle and displacement of the wall element of the coupled shear wall, h u-1 represents the state of the wall element adjacent to this wall element, and n represents the number of wall elements adjacent to the wall element being calculated. For the entire structure, its eigenvector can be obtained as: H = F(Φ, U, H); It should be understood that h u-1 is an initial state quantity, a parameter value preset by those skilled in the art according to the actual situation and on-site needs at the beginning of each wall element.

[0062] In the mechanical response prediction network, for each wall element of the coupled shear wall, its mechanical response can be represented by the local output function o v = g(·), where o v is determined by the state of this wall element: o v = g(θ v , u v , h v ); The overall mechanical response is: O = G(Φ, U, H); When its state parameter during iteration is: H t+1 = F(Φ, U, H t+1 ); The force on the coupling beam damper can be obtained according to the force and deformation of the wall element: V v = l(θ v , u v , o v ); The forces on all coupling beam dampers are: V = L(Φ, U, O).

[0063] The loss function of the described graph neural network is determined by the force on the coupling beam damper, where V is the shear force on the coupling beam damper predicted by the graph neural network, is the internal force obtained by detecting the coupling beam damper.

[0064] S2. Calibrate the coupling beam damper to obtain the force state characteristic signals from the healthy state to the limit state for completing the training of the described graph neural network model; The characteristic signals include piezoelectric signals and hysteresis curves of the coupling beam damper under different damage degrees.

[0065] It should be understood that calibrating the coupling beam damper is essentially to establish the correspondence between the damage degree of the coupling beam damper and the monitoring signal through laboratory tests. This correspondence will be used as the reference data for evaluating the damage state of the damper in subsequent actual projects and is also the pre-training data of the graph neural network model.

[0066] Specifically, in the calibration test, such as Figure 3As shown in the figure, the coupling beam damper is first fixed on a special test device (shear frame) and a piezoelectric transducer and a displacement sensor are installed. Then, the damper is repeatedly loaded by displacement loading, so that it gradually develops from an intact state to a damaged state. In this process, the piezoelectric transducer collects piezoelectric signals from key parts of the damper, the displacement sensor records the deformation of the damper, and the hysteresis curve of the damper at different loading levels is recorded. These data together constitute the characteristic signal of the damper at different damage levels.

[0067] In some preferred embodiments, a preferred method for setting a piezoelectric transducer on a coupling beam damper of a target shear wall structure is provided, which specifically includes:

[0068] Piezoelectric transducers are set according to different vulnerable parts of the connecting beam damper:

[0069] A first piezoelectric transducer is arranged at the end plate and the flange to monitor damage at the weld between the flange and the end plate;

[0070] A second piezoelectric transducer is arranged at the end plate to monitor buckling damage of the web and tearing damage at the connection between the web and the end plate;

[0071] A third piezoelectric transducer is arranged at the flange to monitor damage at the connection between the web and the flange.

[0072] In some other preferred embodiments, a preferred method for setting a displacement sensor on a coupling beam damper of a target shear wall structure is also provided, which specifically includes:

[0073] Fixing the displacement sensor on a wall limb or a loading beam connected to one end of the connecting beam damper by means of magnetic connection;

[0074] A fixing piece is arranged on the wall limb or the loading beam connected to the other end of the connecting beam damper, and the probe of the displacement sensor is pressed against the connection between the fixing piece and the wall limb or the loading beam.

[0075] The loading process of the calibration test is progressive: first load to the yield displacement of the damper, then increase step by step according to the integer multiples of the yield displacement, and each loading level is reciprocated for three cycles. The calibration test ends when obvious cracks appear in the damper or the bearing capacity drops to 85% of the peak value. Such a loading system ensures that complete characteristic signal data of the damper from the healthy state to the limit state can be obtained.

[0076] The characteristic signals obtained through the calibration test will be used to train the graph neural network model. This training enables the model to accurately infer the damage state of the damper through the monitoring signals collected in the actual project, and then evaluate the response of the overall structure. Therefore, the calibration test is a key link in achieving the transition from local monitoring to overall evaluation.

[0077] S3. Set piezoelectric transducers and displacement sensors on the coupling beam dampers of the target shear wall structure to obtain target characteristic signals.

[0078] Corresponding to the characteristic signals in the calibration test, the target characteristic signals also include the piezoelectric signals and deformation information of the coupling beam dampers, and these signals reflect the damage state of the dampers during actual use. The installation of piezoelectric transducers requires surface treatment at a predetermined position first. The specific method is to use a white marker or chalk to mark the installation position, and the marked range is the radius of the transducer increased by 10 mm, and then use a grinder to polish the marked area until it is bright and flat to ensure that there is no rust, which can guarantee the transmission quality of piezoelectric signals. According to the different vulnerable parts of the coupling beam dampers, three groups of piezoelectric transducers need to be set: the first group is set at the end plate and flange to monitor weld damage; the second group is set at the end plate to monitor the buckling damage of the web and the tearing damage at the connection between the web and the end plate; the third group is set at the flange to monitor the damage at the connection between the web and the flange. Quick-drying glue is used during installation, and uniform pressure is applied to ensure that the transducer is fully attached to the surface of the damper. The displacement sensor is installed by magnetic attraction connection, and the sensor is fixed on the wall limb or loading beam connected to one end of the coupling beam damper. Fixing parts, usually welded steel pipes, need to be set on the wall limb or loading beam connected to the other end of the damper. The probe of the displacement sensor is pressed against the connection between the fixing part and the wall limb or loading beam, so that the lateral deformation of the damper can be accurately measured. This installation method not only ensures the measurement accuracy but also facilitates later maintenance. After the sensor installation is completed, on-site tests need to be carried out to check the fastening of the bolt connection, confirm that the displacement sensor works normally, and at the same time test the piezoelectric transducer to verify whether the acquisition and transmission of piezoelectric signals are normal to ensure that the entire monitoring system can work stably and reliably. These test data will be used as reference values for subsequent damage monitoring and evaluation.

[0079] S4. Input the target feature signal at the target moment into the graph neural network model to obtain the force state of the coupling beam damper and the mechanical response of the wall piers at the target moment. It should be understood that the target feature signal refers to the state information of the coupling beam damper collected in real time by piezoelectric transducers and displacement sensors, including the piezoelectric signals and lateral deformation amounts of each vulnerable part. These signals reflect the working state of the damper at the target moment (i.e., the time point to be evaluated). Input these feature signals into the graph neural network model established and trained in the early stage to first obtain the force state of the coupling beam damper. The force state here refers to the magnitude of the shear force borne by the damper, which can be calculated by the mechanical response prediction network in the model. After obtaining the force state of the damper, the graph neural network model will further calculate the mechanical response of the wall piers. This process is realized through the information transfer network of the model, which considers the topological relationship between the wall piers and can simulate the transmission process of force and deformation in the structure. For each wall pier, its mechanical response is represented by a local transfer function, and the input of this function includes the state of the wall pier itself and the states of the adjacent wall piers. Through iterative calculation, the complete mechanical response including the wall pier rotation angle, displacement, etc. is finally obtained. This method of deriving the overall structural response from local monitoring data makes full use of the advantage of the graph neural network in processing data with spatial relationships and provides reliable calculation results for subsequent structural performance evaluation.

[0080] S5. Construct a finite element model of the coupling beam damper and a building structure model including the target shear wall structure respectively.

[0081] The finite element model of the coupling beam damper reflects the geometric characteristics and mechanical properties of the damper, including the dimensions and material parameters of components such as end plates, flanges, and webs. During the construction process, special attention is paid to the simulation of vulnerable parts, such as the welded connection between the end plate and the flange, the connection between the web and the end plate, etc. The main purpose of this model is to simulate the mechanical behavior of the damper under different force states, calculate its deformation and stress distribution, and provide a basis for evaluating the damage state of the damper.

[0082] The building structure model of the target shear wall structure is a larger-scale model that includes key structural components of the entire building, such as shear wall piers, coupling beams, floor slabs, etc. In this model, the coupling beam damper can be simulated in a simplified manner, mainly focusing on its influence on the overall structural stiffness and deformation. The core purpose of this model is to show the overall response of the structure, including states such as inter-story displacement and wall pier forces, and to visually present the deformation and damage of the structure under different excitations through AR (augmented reality) technology.

[0083] These two models together constitute a multi-scale analysis platform, which can not only analyze the mechanical properties of local components in detail, but also show the response characteristics of the overall structure. Through this hierarchical simulation method, the working state of the structure can be understood and evaluated more comprehensively.

[0084] S6. Input the force state of the coupling beam damper and the mechanical response of the wall limb at the target moment into the finite element model and the building structure model respectively for visual display.

[0085] Specifically, first input the force state of the coupling beam damper calculated by the graph neural network into its finite element model. In this refined model, the force and deformation of each part of the damper can be intuitively displayed, including the stress distribution at vulnerable parts such as the weld connection between the end plate and the flange, the buckling state of the web, and the connection with the end plate. This visual analysis at the local component level helps to identify the potential damage locations and degrees of the damper.

[0086] At the same time, input the predicted mechanical response of the wall limb into the building structure model. This model can show the working state of the entire shear wall structure, including key indicators such as the deformation, force, and inter-story displacement of each floor wall limb. Through augmented reality (AR) technology, these response data can be superimposed on the actual building in three dimensions to intuitively display the overall deformation and damage state of the structure at the target moment. In addition, this visualization method also facilitates engineers to understand and judge the force characteristics of the structure.

[0087] This two-level visual display method can not only reflect the detailed force information of local key components, but also show the response characteristics of the overall structure, providing an intuitive analysis basis for structural performance evaluation.

[0088] In some preferred embodiments, in order to quantitatively evaluate the overall performance of the building structure after an earthquake, the present invention further includes an evaluation step based on code requirements. Specifically, it includes the steps: S7. Calculate the overall mechanical response of the shear wall structure according to the mechanical response of the wall limb at the target moment, and compare it with the code requirements to judge whether the target building can continue to dissipate energy and reduce vibration after the earthquake. In the actual evaluation process, corresponding evaluation indicators and limits need to be determined according to the different performance level requirements of the building. For buildings with general performance levels, mainly focus on basic mechanical response indicators such as inter-story drift ratio and maximum floor displacement; for buildings with higher performance levels, more stringent control indicators such as floor acceleration and component stress also need to be considered. These code requirements are given in the form of limit value X, which are the basic criteria to ensure the safe use of the building.

[0089] By comparing the relationship between the actually calculated response value x and the specification limit value X, the working state of the building structure can be objectively evaluated. When the calculated value x is less than the limit value X, it indicates that the deformation and stress state of the structure meet the specification requirements, and the building can continue to perform its energy dissipation and seismic reduction function; when the calculated value x is close to or exceeds the limit value X, it indicates that the structure may have suffered significant damage, and necessary maintenance or strengthening measures need to be taken in a timely manner to ensure the use safety of the building. This specification-based evaluation method provides a scientific basis for maintenance decisions in engineering practice.

[0090] In some other preferred embodiments, the present invention also provides a structural performance evaluation method based on pre-earthquake and post-earthquake comparison, which specifically includes: S7. Calculate the mechanical responses of the wall members at the initial moment (pre-earthquake state) and the ultimate state (post-earthquake state) respectively according to step S4, calculate the overall mechanical response of the corresponding shear wall structure, and judge the seismic performance of the target building.

[0091] The evaluation of the above seismic performance is mainly carried out from two key aspects: the ductility capacity and the energy dissipation capacity of the structure. Among them, the ductility capacity reflects the ability of the structure to continue to bear deformation without damage, and can be evaluated by comparing the maximum deformation capacities of the structure in the initial state and the ultimate state; the energy dissipation capacity reflects the ability of the structure to consume the earthquake input energy, and can be quantified by comparing the areas of the hysteresis curves of the structure in the two states. Through the changes of these two indicators, the degree of deterioration of the seismic performance of the structure after the earthquake can be comprehensively reflected.

[0092] This evaluation method based on pre-earthquake and post-earthquake comparison can not only quantitatively describe the degree of degradation of the structural performance, but also provide a targeted basis for the maintenance and strengthening plan of the structure. For example, when it is found that the ductility capacity of the structure has decreased significantly, corresponding component strengthening measures can be taken; when the energy dissipation capacity is significantly reduced, it may be necessary to consider replacing or supplementing the energy dissipation device. This evaluation method complements the specification-based evaluation method and jointly constitutes a complete structural performance evaluation system.

[0093] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments, and what is described in the above embodiments and the specification only illustrates the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of the present invention claimed is defined by the appended claims and their equivalents.

Claims

1. A method for evaluating the overall response of a shear wall structure based on local monitoring of a coupling beam damper, characterized in that: The following steps are involved: S1. constructing a graph neural network model based on the shear wall structure information of the target building, wherein the graph neural network model is used to predict the mechanical response of the wall limb according to the stress state of the coupling beam damper; S2. Calibrate the connecting beam damper to obtain characteristic signals of stress states from a healthy state to a limit state, which are used to complete the training of the graph neural network model; the characteristic signals include piezoelectric signals and hysteresis curves of the connecting beam damper at different damage degrees; S3. Setting a piezoelectric transducer and a displacement sensor on the coupling beam damper of the target shear wall structure to obtain a target characteristic signal; S4. Inputting the target characteristic signal at the target time into the graph neural network model to obtain the stress state of the coupling beam damper and the mechanical response of the wall at the target time; S5. Construct a finite element model of the coupling beam damper and a building structure model including the target shear wall structure respectively; S6. Input the stress state of the coupling beam damper and the mechanical response of the wall member at the target moment into the finite element model and the building structure model respectively for visual display.

2. The method for evaluating the overall response of a shear wall structure based on local monitoring of a coupling beam damper according to claim 1, characterized in that: Also includes the steps: S7. Calculate the overall mechanical response of the shear wall structure based on the mechanical response of the wall members at the target moment, and compare it with the requirements of the specification to determine whether the target building can continue to dissipate energy and reduce shock after the earthquake.

3. The overall response evaluation method of shear wall structure based on local monitoring of coupling beam dampers according to claim 1, characterized in that: Also includes the steps: S7. According to step S4, the mechanical responses of the wall members at the initial moment and the limit state are calculated respectively, the mechanical response of the corresponding shear wall structure as a whole is calculated, and the seismic performance of the target building is determined.

4. The method for evaluating the overall response of a shear wall structure based on local monitoring of a coupling beam damper according to claim 1, characterized in that: The method for calibrating the coupling beam damper in step S2 includes: S201. Fix the connecting beam damper on the shear frame, polish and paste the piezoelectric transducer at the predetermined position, and install the displacement sensor; S202. Perform a shear test of displacement loading on the coupling beam damper, and collect piezoelectric signals and hysteresis curves from the healthy state to the limit state as characteristic signals under different stress states.

5. The method for evaluating the overall response of a shear wall structure based on local monitoring of a coupling beam damper according to claim 1, characterized in that: The method for constructing a graph neural network model according to the shear wall structure information of the target building in step S1 includes: The shear wall structure information of the target building is converted into graph structure data, and the structural system is described using an undirected graph as follows: G=(V,E,A); where V represents the characteristics of the coupling beam and coupling beam damper, including bending stiffness and shear stiffness; E represents the characteristics of the shear wall limbs, including the bending stiffness, shear stiffness and tensile and compressive strength between the limbs of each layer of each shear wall; and A represents the topological relationship of the shear wall limbs.

6. The method for evaluating the overall response of a shear wall structure based on local monitoring of a coupling beam damper according to claim 1, characterized in that: In the graph neural network model, the mechanical response of a single wall limb is expressed as: o v =g(θ v ,u v ,h v ), where θ v ,u v Indicates the rotation angle and displacement of the current wall; h v The state of the current wall limb is determined by the state of the adjacent wall limb; The stress state of a single coupling beam damper is expressed as: V v = l(θ v ,u v ,o v ).

7. The method for evaluating the overall response of a shear wall structure based on local monitoring of a coupling beam damper according to claim 1, characterized in that: The method of setting a piezoelectric transducer on the coupling beam damper of the target shear wall structure in step S3 includes: Piezoelectric transducers are set according to different vulnerable parts of the connecting beam damper: A first piezoelectric transducer is arranged at the end plate and the flange to monitor damage at the weld between the flange and the end plate; A second piezoelectric transducer is arranged at the end plate to monitor buckling damage of the web and tearing damage at the connection between the web and the end plate; A third piezoelectric transducer is arranged at the flange to monitor damage at the connection between the web and the flange.

8. The method for evaluating the overall response of a shear wall structure based on local monitoring of a coupling beam damper according to claim 1, characterized in that: The method of setting a displacement sensor on the coupling beam damper of the target shear wall structure in step S3 includes: Fixing the displacement sensor on a wall limb or a loading beam connected to one end of the connecting beam damper by means of magnetic connection; A fixing piece is arranged on the wall limb or the loading beam connected to the other end of the connecting beam damper, and the probe of the displacement sensor is pressed against the connection between the fixing piece and the wall limb or the loading beam.

9. The method for evaluating the overall response of a shear wall structure based on local monitoring of a coupling beam damper according to claim 3, characterized in that: The method for determining the seismic performance of the target building in step S7 includes: The overall mechanical responses of the shear wall structure at the initial moment and the limit state are calculated and compared, and the performance degradation in terms of ductility and energy dissipation capacity is obtained.

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