Building cross beam main body stress analysis system

Abstract

The invention provides a building cross beam main body stress analysis system which comprises a plurality of vibration sensors which are arranged on the central axis of a supporting cross beam at intervals and used for monitoring stress changes of different positions of the supporting cross beam caused by energy attenuation when vibration waves generated by different seismic sources are transmitted to the different positions of the supporting cross beam, the plurality of displacement sensors are arranged at the joints of the supporting surfaces of the supporting cross beams and are used for acquiring displacement signals of the supporting surfaces of the supporting cross beams according to a set period; the processing device is used for comparing the displacement deviation distance with a set reference parameter so as to obtain the displacement amount of each displacement sensor deviating from the supporting surface of the supporting cross beam along with the vibration change of the supporting cross beam, and judging the main deviation part of the supporting cross beam according to the displacement amount corresponding to each displacement signal; and evaluating the main body stress of the supporting cross beam under the stress analysis model based on the main stress part of the supporting cross beam and the main offset part of the supporting cross beam.

Description

Technical Field

[0001] The invention relates to the technical field of hemodialysis monitoring and control, and in particular to a building crossbeam main body force analysis system. Background Art

[0002] As the main load-bearing structure in traditional buildings, beams have important functions. They bear the load from the superstructure and roof, and ensure the stability and safety of the building by transferring the load to other parts. Beams are usually connected to columns or walls to transfer the load to the foundation, ensuring that the building can withstand external forces.

[0003] Due to the uneven force distribution of the building itself, it is usually necessary to analyze the bearing capacity of the beams before designing and determining the structure. However, most traditional buildings are designed based on artificial experience, thus ignoring the loads of the beams from the upper structure and the roof. This results in uneven force on the designed horizontal dispersed loads, which in turn causes the building to be damaged due to concentrated loads. Summary of the invention

[0004] In view of this, the main purpose of the present invention is to provide a building beam main body force analysis system.

[0005] The technical solution adopted by the present invention is as follows:

[0006] The main force analysis system of building beams includes:

[0007] A plurality of vibration sensors are arranged at intervals on the central axis of the support beam, and are used to monitor the force changes at different positions of the support beam caused by energy attenuation when the vibration waves generated by different seismic sources are transmitted to different positions of the support beam, and the main force-bearing parts of the support beam are determined according to the force changes at different positions of the support beam;

[0008] A plurality of displacement sensors are arranged at the connection between the support beam and the support surface, and are used to obtain the displacement signal of the support beam support surface according to a set period;

[0009] A processing device, for receiving a plurality of the displacement signals and synchronously calibrating a displacement offset distance represented by each displacement signal in the plurality of the displacement signals, comparing the displacement offset distance with a set reference parameter to obtain a displacement amount of each displacement sensor from a supporting surface of the supporting beam as the vibration of the supporting beam changes, and determining a main displacement position of the supporting beam according to the displacement amount corresponding to each displacement signal;

[0010] Based on the main stress-bearing parts and the main offset parts of the supporting beam, the main stress of the supporting beam is evaluated under the stress analysis model.

[0011] Furthermore, a first vibration sensor and a second vibration sensor are respectively arranged at intervals on the upper edge portion and the lower edge portion along the central axis of the supporting crossbeam, and a third vibration sensor is arranged at intervals on the central axis;

[0012] The first vibration sensor is used to obtain an upper vibration sensor signal of an upper edge of the supporting beam caused by energy attenuation at an upper edge of the central axis of the supporting beam;

[0013] The second vibration sensor is used to obtain a lower vibration sensor signal of the lower edge of the supporting beam caused by energy attenuation at the lower edge of the central axis of the supporting beam;

[0014] The third vibration sensor is used to obtain the middle vibration sensing signal of the central axis position of the supporting beam caused by energy attenuation of the central axis.

[0015] Furthermore, the first vibration sensor, the second vibration sensor and the third vibration sensor are arranged on the supporting beam in a corresponding and matching manner.

[0016] Further, the first vibration sensor, the second vibration sensor and the third vibration sensor are respectively connected to the processing device, and a force analysis model is provided in the processing device, and the force analysis model is configured to simulate the first vibration change at different positions of the supporting beam caused by energy attenuation based on iterative training of the upper vibration sensor signal and the lower vibration sensor signal, and obtain a first result of the simulation based on the first vibration change;

[0017] Alternatively, the force analysis model is configured to simulate second vibration changes at different positions of the central axis due to energy attenuation based on iterative training of the vibration sensor signal, and obtain a second simulated result based on the second vibration change.

[0018] Furthermore, the force analysis model is constructed according to the following method:

[0019] Acquire position data of different types of sensors arranged on the supporting beam, acquire vibration data and deviation displacement data of different positions of the supporting beam according to the position data, predict force changes of different positions of the supporting beam using a prediction model according to the vibration data, and obtain prediction results, obtain the displacement of the deviation of the supporting beam according to the prediction results and the deviation displacement data, and reversely annotate the vibration data and deviation displacement data of different positions of the supporting beam according to the prediction results and the corresponding displacement of the deviation of the supporting beam to obtain an annotation result;

[0020] Extracting the annotation features corresponding to the annotation results and obtaining at least one annotation feature set, analyzing and associating the annotation feature mappings in the annotation feature set at specific positions of the supporting beams to obtain a corresponding association set;

[0021] Based on the position data, the vibration data and the deviation displacement data corresponding to the same position are associated in one dimension to form a one-dimensional association chain; all the annotation feature sets under each position data are associated, and a two-dimensional association chain is constructed based on the formed one-dimensional association chain; the same annotation results under each position are associated, and a multi-dimensional association chain is constructed based on the formed two-dimensional association chain, and an analysis unit is formed according to the multi-dimensional association chain;

[0022] The analysis units are arranged in parallel according to the position data, and the execution direction channel of the analysis units is set, and the execution direction channel is corresponded to the sensor under the position data to receive the vibration data or deviation displacement data generated by the sensor, so as to construct a force analysis model of the beam body.

[0023] Furthermore, the prediction model is constructed using the following method:

[0024] Acquire vibration data and deviation displacement data of different positions of the support beam in several monitoring cycles according to the position data of different sensor arrangements;

[0025] Using multiple groups of human experts to manually annotate the force characteristics in the vibration data and the deviation displacement data, obtain several groups of force characteristic annotation results, and store them in corresponding storage units;

[0026] A parallel-triggered comparison matrix and a task scheduler are set, wherein the task scheduler is configured to point to the force feature labeling results in the storage unit through a parallel trigger instruction to compare multiple groups of the force feature labeling results obtained under the same position data, and when at least one of the force feature labeling results is consistent with each other, the force feature labeling result is set as a prediction sample;

[0027] The training samples are input into a training program for training to obtain the prediction model.

[0028] By analyzing the stress of the main body of the beam, the present application can obtain the main stress-bearing part of the beam according to the building structure in the building design, and determine the load of the beam from different directions. Therefore, the load can be dispersed by designing the beam structure so that the force can be evenly distributed to various parts of the building to avoid local overload. This balanced force distribution ensures the stability of the building structure and can effectively prevent the building from being damaged due to concentrated loads.

[0029] As another aspect of the present application, the damage to the main body of the beam caused by uneven concentrated loads in existing buildings can be monitored and analyzed. By setting vibration sensors and displacement sensors at different positions of the beam, the force changes acting on different positions of the beam can be monitored in real time. The force analysis model can be used to evaluate the force on the main body of the beam, and the main force-bearing parts of the beam can be obtained. Then, the corresponding load of the beam can be obtained according to the building structure. The main force loads of the beam in the existing building can be analyzed so as to formulate corresponding repair plans. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The following drawings are only used to illustrate and explain the present invention, and are not used to limit the scope of the present invention, wherein:

[0031] Figure 1 A diagram showing the structure of the system of the present invention;

[0032] Figure 2 The first vibration sensor, the second vibration sensor, and the third vibration sensor in the present invention are not provided;

[0033] Figure 3 Flow chart of the method of the present invention. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical solution, design method and advantages of the present invention clearer, the present invention is further described in detail by specific embodiments in conjunction with the accompanying drawings. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0035] Reference Figure 1 and Figure 3 The present application provides a building beam main body force analysis system, comprising:

[0036] A plurality of vibration sensors are arranged at intervals on the central axis of the support beam, and are used to monitor the force changes at different positions of the support beam caused by energy attenuation when the vibration waves generated by different seismic sources are transmitted to different positions of the support beam, and the main force-bearing parts of the support beam are determined according to the force changes at different positions of the support beam;

[0037] A plurality of displacement sensors are arranged at the connection between the support beam and the support surface, and are used to obtain the displacement signal of the support beam support surface according to a set period;

[0038] A processing device, for receiving a plurality of the displacement signals and synchronously calibrating a displacement offset distance represented by each displacement signal in the plurality of the displacement signals, comparing the displacement offset distance with a set reference parameter to obtain a displacement amount of each displacement sensor from a supporting surface of the supporting beam as the vibration of the supporting beam changes, and determining a main displacement position of the supporting beam according to the displacement amount corresponding to each displacement signal;

[0039] Based on the main stress-bearing parts and the main offset parts of the supporting beam, the main stress of the supporting beam is evaluated under the stress analysis model.

[0040] In the above, the vibration sensor should be set on the central axis of the support beam and arranged at intervals along the axis. This ensures that the sensor can capture the propagation of vibration waves on the beam and reflect the force changes at different positions. The number and spacing of sensors should be determined based on the length of the support beam, the cross-sectional dimensions, and the expected monitoring accuracy. Generally speaking, the more sensors there are, the more accurate the monitoring results are, but it also increases cost and complexity. Therefore, it is necessary to reasonably determine the number and spacing of sensors while meeting the monitoring needs.

[0041] Place various types of sensors, such as vibration sensors and displacement sensors, at different locations on the support beam. Record the placement of each sensor, including its specific location (such as coordinates, distance, etc.) and type on the support beam. Arrange the location data of all sensors into a table or database to facilitate subsequent data processing and query.

[0042] When vibration waves generated by different sources are transmitted to the supporting beam, different degrees of vibration will be generated on the beam. These vibration waves will propagate along the central axis of the beam and energy will decay during the propagation process. Due to the propagation and energy decay of the vibration waves, the force conditions at different positions of the supporting beam will change. These changes can be monitored and recorded by vibration sensors.

[0043] By analyzing the data collected by the vibration sensor, the force changes at different positions of the support beam can be obtained. Furthermore, the main force-bearing parts of the support beam can be determined based on these force changes.

[0044] Methods for determining the main stress-bearing parts include: Peak vibration analysis method: By comparing the vibration peak values ​​of sensors at different positions, the areas with the most intense vibration can be found. These areas are often the main stress-bearing parts of the supporting beam.

[0045] Or judge by vibration spectrum analysis: By analyzing the vibration spectrum, we can understand the propagation characteristics of the vibration wave on the supporting beam, such as frequency distribution, amplitude, etc. This information helps to further judge the location and stress of the main stress-bearing parts.

[0046] By using either of the above two methods, through long-term monitoring of the data from the vibration sensor, the changing trend of the stress condition of the support beam can be observed, and potential structural damage or safety hazards can be discovered in a timely manner. By arranging multiple vibration sensors at intervals on the central axis of the support beam, the stress changes of the vibration waves generated by different sources when transmitted to different positions of the support beam can be effectively monitored, and the main stress-bearing parts of the support beam can be determined based on these data.

[0047] In the above, the displacement sensor should be precisely set at the connection between the support beam and the support surface. These connections are usually the contact points between the beam and the supporting structure (such as columns, walls, etc.), and are the areas where the support beam is subjected to the most concentrated force. The number and distribution of sensors should be determined according to the size and shape of the support beam and the expected monitoring accuracy. The number of sensors should be increased at key connections and parts with greater force to ensure that the displacement of the support beam can be fully and accurately captured. The installation of the displacement sensor should be firm and reliable to avoid affecting the accuracy of the data due to looseness or displacement during the monitoring process. At the same time, the installation position of the sensor should be convenient for data reading and transmission.

[0048] The displacement sensor reflects the deformation of the beam by measuring the displacement of the support surface of the beam in a specific direction. These displacements can be linear, angular, or in other forms. According to the set period (such as every second, every minute, etc.), the displacement sensor will collect the displacement signal of the support surface of the beam. These signals can be digital or analog signals, depending on the type of sensor and the output method.

[0049] The collected displacement signals are preprocessed, including noise removal, filtering, calibration and other steps, to improve the accuracy and reliability of the data. By comparing the displacement data at different time points or different positions, the deformation, deformation rate and deformation trend of the supporting beam can be analyzed.

[0050] In the above, the processing device first receives displacement signals from multiple displacement sensors. These signals reflect the displacement offset of the supporting beam at different positions. In order to ensure the consistency and accuracy of the data, the processing device needs to synchronize and calibrate each displacement signal. This means associating the displacement offset distance represented by each displacement signal with a specific timestamp or sampling period, thereby ensuring that all signals are compared on the same time basis.

[0051] The processing device compares the displacement offset distance of each displacement signal with the set reference parameters. These reference parameters may include the initial position of the support beam in a static state, the expected displacement range, etc. Through the comparison, the processing device can calculate the displacement amount of each displacement sensor from the support surface of the support beam as the vibration of the support beam changes. These displacement amounts reflect the dynamic deformation of the support beam at different positions.

[0052] The processing device analyzes the displacement corresponding to each displacement signal. By comparing the displacement at different positions, the area with a larger displacement on the supporting beam, that is, the main deflection part, can be identified.

[0053] In addition to identifying the main deflection points, the processing unit can also analyze the trend and pattern of the displacement signal. This helps to understand the response characteristics of the supporting beam under different vibration conditions and predict potential deflection risks.

[0054] After determining the main deflection locations of the support beam, the processing device combines this information with the main stress locations of the support beam. This helps to more fully understand the stress conditions of the support beam and evaluate its structural safety. The processing device inputs the stress conditions of the support beam into the stress analysis model. It is used to simulate the stress distribution and deformation of the support beam under different load conditions. Through the stress analysis model, the processing device can evaluate the structural response and performance of the support beam under different stress conditions. This includes evaluating key indicators such as the bearing capacity, stiffness, and stability of the support beam.

[0055] In the above, a first vibration sensor and a second vibration sensor are respectively arranged at intervals on the upper edge portion and the lower edge portion along the central axis of the supporting crossbeam, and a third vibration sensor is arranged at intervals on the central axis;

[0056] The first vibration sensor is used to obtain an upper vibration sensor signal of an upper edge of the supporting beam caused by energy attenuation at an upper edge of the central axis of the supporting beam;

[0057] The second vibration sensor is used to obtain a lower vibration sensor signal of the lower edge of the supporting beam caused by energy attenuation at the lower edge of the central axis of the supporting beam;

[0058] The third vibration sensor is used to obtain the middle vibration sensing signal of the central axis position of the supporting beam caused by energy attenuation of the central axis.

[0059] In the above, the first vibration sensor, the second vibration sensor and the third vibration sensor are arranged on the supporting beam in a corresponding and matching manner.

[0060] In the above, the first vibration sensor, the second vibration sensor and the third vibration sensor are respectively connected to the processing device, and a force analysis model is provided in the processing device, and the force analysis model is configured to simulate the first vibration change of different positions of the supporting beam caused by energy attenuation based on iterative training of the upper vibration sensor signal and the lower vibration sensor signal, and obtain the first simulation result based on the first vibration change;

[0061] Alternatively, the force analysis model is configured to simulate second vibration changes at different positions of the central axis due to energy attenuation based on iterative training of the vibration sensor signal, and obtain a second simulated result based on the second vibration change.

[0062] Furthermore, the force analysis model is constructed according to the following method:

[0063] Acquire position data of different types of sensors arranged on the supporting beam, acquire vibration data and deviation displacement data of different positions of the supporting beam according to the position data, predict force changes of different positions of the supporting beam using a prediction model according to the vibration data, and obtain prediction results, obtain the displacement of the deviation of the supporting beam according to the prediction results and the deviation displacement data, and reversely annotate the vibration data and deviation displacement data of different positions of the supporting beam according to the prediction results and the corresponding displacement of the deviation of the supporting beam to obtain an annotation result;

[0064] Extracting the annotation features corresponding to the annotation results and obtaining at least one annotation feature set, analyzing and associating the annotation feature mappings in the annotation feature set at specific positions of the supporting beams to obtain a corresponding association set;

[0065] Based on the position data, the vibration data and the deviation displacement data corresponding to the same position are associated in one dimension to form a one-dimensional association chain; all the annotation feature sets under each position data are associated, and a two-dimensional association chain is constructed based on the formed one-dimensional association chain; the same annotation results under each position are associated, and a multi-dimensional association chain is constructed based on the formed two-dimensional association chain, and an analysis unit is formed according to the multi-dimensional association chain;

[0066] The analysis units are arranged in parallel according to the position data, and the execution direction channel of the analysis units is set, and the execution direction channel is corresponded to the sensor under the position data to receive the vibration data or deviation displacement data generated by the sensor, so as to construct a force analysis model of the beam body.

[0067] In the above, according to the position data of the sensor arrangement, the vibration data and the deviation displacement data of different positions of the supporting beam are collected from the sensor.

[0068] Vibration data may include acceleration, velocity, displacement, etc. that vary over time.

[0069] The deviation displacement data directly reflects the displacement change of the supporting beam in a specific direction.

[0070] The currently collected vibration data is input into the trained prediction model to obtain the prediction results of the force changes at different positions of the supporting beam.

[0071] The predicted results of force changes are compared with the deviation displacement data at the same moment to analyze the correlation and consistency between the two.

[0072] According to the comparison between the prediction results and the deviation displacement data, the deviation displacement of the supporting beam at different positions is calculated. This can be achieved through statistical methods, regression analysis and other means.

[0073] According to the predicted results of force changes and the corresponding deviation displacement, the original vibration data and deviation displacement data are reversely annotated. The annotation content can include data reliability, abnormal values, trend characteristics, etc. When annotating, specific annotation symbols or codes can be used to represent different annotation contents, and the annotation results can be added to the original data table or a new annotation data table can be generated.

[0074] When collecting and processing data, the synchronization of vibration data and deviation displacement data should be ensured to avoid errors caused by time difference.

[0075] In the above, the position data of the sensors at different positions on the supporting beam are obtained, and the vibration data and the deviation displacement data of the corresponding positions are obtained according to the position data. The vibration data and the deviation displacement data corresponding to the same position are associated to form a one-dimensional association chain. Each node in the one-dimensional association chain represents a position, and the data on the node includes the vibration data and the deviation displacement data of the position.

[0076] All the annotated features under each position data are collected to form an annotated feature set. The annotated features may include data reliability, outliers, trend features, etc. Based on the formed one-dimensional association chain, the annotated feature sets under the same position are associated to construct a two-dimensional association chain. Each node in the two-dimensional association chain contains not only vibration data and deviation displacement data, but also the corresponding annotated feature set. Through the two-dimensional association chain, the similarities and differences of the annotated features between different positions can be analyzed.

[0077] On the basis of the two-dimensional association chain, the same annotation results at each position are associated, and the position data with the same or similar annotation features are further connected to form a more complex association network. Each node in the multi-dimensional association chain may contain information in multiple dimensions, such as position, vibration data, deviation displacement data, annotation features, etc. Through the multi-dimensional association chain, the correlation between different positions of the supporting beam and their impact on the overall structural health can be more comprehensively analyzed.

[0078] Furthermore, the prediction model is constructed using the following method:

[0079] Acquire vibration data and deviation displacement data of different positions of the support beam in several monitoring cycles according to the position data of different sensor arrangements;

[0080] Using multiple groups of human experts to manually annotate the force characteristics in the vibration data and the deviation displacement data, obtain several groups of force characteristic annotation results, and store them in corresponding storage units;

[0081] A parallel-triggered comparison matrix and a task scheduler are set, wherein the task scheduler is configured to point to the force feature labeling results in the storage unit through a parallel trigger instruction to compare multiple groups of the force feature labeling results obtained under the same position data, and when at least one of the force feature labeling results is consistent with each other, the force feature labeling result is set as a prediction sample;

[0082] The training samples are input into a training program for training to obtain the prediction model.

[0083] By analyzing the stress of the main body of the beam, the present application can obtain the main stress-bearing part of the beam according to the building structure in the building design, and determine the load of the beam from different directions. Therefore, the load can be dispersed by designing the beam structure so that the force can be evenly distributed to various parts of the building to avoid local overload. This balanced force distribution ensures the stability of the building structure and can effectively prevent the building from being damaged due to concentrated loads.

[0084] As another aspect of the present application, the damage to the main body of the beam caused by uneven concentrated loads in existing buildings can be monitored and analyzed. By setting vibration sensors and displacement sensors at different positions of the beam, the force changes acting on different positions of the beam can be monitored in real time. The force analysis model can be used to evaluate the force on the main body of the beam, and the main force-bearing parts of the beam can be obtained. Then, the corresponding load of the beam can be obtained according to the building structure. The main force loads of the beam in the existing building can be analyzed so as to formulate corresponding repair plans.

[0085] The embodiments of the present invention have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or technical improvements in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. The main force analysis system of building beams is characterized by: include: A plurality of vibration sensors are arranged at intervals on the central axis of the support beam, and are used to monitor the force changes at different positions of the support beam caused by energy attenuation when the vibration waves generated by different seismic sources are transmitted to different positions of the support beam, and the main force-bearing parts of the support beam are determined according to the force changes at different positions of the support beam; A plurality of displacement sensors are arranged at the connection between the support beam and the support surface, and are used to obtain the displacement signal of the support beam support surface according to a set period; A processing device, for receiving a plurality of the displacement signals and synchronously calibrating a displacement offset distance represented by each displacement signal in the plurality of the displacement signals, comparing the displacement offset distance with a set reference parameter to obtain a displacement amount of each displacement sensor from a supporting surface of the supporting beam as the vibration of the supporting beam changes, and determining a main displacement position of the supporting beam according to the displacement amount corresponding to each displacement signal; Based on the main stress-bearing parts and the main offset parts of the supporting beam, the main stress of the supporting beam is evaluated under the stress analysis model.

2. The building beam main body force analysis system according to claim 1 is characterized in that: A first vibration sensor and a second vibration sensor are respectively arranged at intervals along the upper edge portion and the lower edge portion of the central axis of the supporting crossbeam, and a third vibration sensor is arranged at intervals on the central axis; The first vibration sensor is used to obtain an upper vibration sensor signal of an upper edge of the supporting beam caused by energy attenuation at an upper edge of the central axis of the supporting beam; The second vibration sensor is used to obtain a lower vibration sensor signal of the lower edge of the supporting beam caused by energy attenuation at the lower edge of the central axis of the supporting beam; The third vibration sensor is used to obtain the middle vibration sensing signal of the central axis position of the supporting beam caused by energy attenuation of the central axis.

3. The building beam main body force analysis system according to claim 2 is characterized in that: The first vibration sensor, the second vibration sensor and the third vibration sensor are arranged on the supporting beam in a corresponding and matching manner.

4. The building beam main body force analysis system according to claim 2 is characterized in that: The first vibration sensor, the second vibration sensor, and the third vibration sensor are respectively connected to the processing device, and a force analysis model is provided in the processing device, and the force analysis model is configured to simulate the first vibration changes at different positions of the supporting beam caused by energy attenuation based on iterative training of the upper vibration sensor signal and the lower vibration sensor signal, and obtain a first result of the simulation based on the first vibration change; Alternatively, the force analysis model is configured to simulate second vibration changes at different positions of the central axis due to energy attenuation based on iterative training of the vibration sensor signal, and obtain a second simulated result based on the second vibration change.

5. The building beam main body force analysis system according to claim 1, characterized in that: The stress analysis model is constructed according to the following method: Acquire position data of different types of sensors arranged on the supporting beam, acquire vibration data and deviation displacement data of different positions of the supporting beam according to the position data, predict force changes of different positions of the supporting beam using a prediction model according to the vibration data, and obtain prediction results, obtain the displacement of the deviation of the supporting beam according to the prediction results and the deviation displacement data, and reversely annotate the vibration data and deviation displacement data of different positions of the supporting beam according to the prediction results and the corresponding displacement of the deviation of the supporting beam to obtain an annotation result; Extracting the annotation features corresponding to the annotation results and obtaining at least one annotation feature set, analyzing and associating the annotation feature mappings in the annotation feature set at specific positions of the supporting beams to obtain a corresponding association set; Based on the position data, the vibration data and the deviation displacement data corresponding to the same position are associated in one dimension to form a one-dimensional association chain; all the annotation feature sets under each position data are associated, and a two-dimensional association chain is constructed based on the formed one-dimensional association chain; the same annotation results under each position are associated, and a multi-dimensional association chain is constructed based on the formed two-dimensional association chain, and an analysis unit is formed according to the multi-dimensional association chain; The analysis units are arranged in parallel according to the position data, and the execution direction channel of the analysis units is set, and the execution direction channel is corresponded to the sensor under the position data to receive the vibration data or deviation displacement data generated by the sensor, so as to construct a force analysis model of the beam body.

6. The building beam main body force analysis system according to claim 5, characterized in that: The prediction model is constructed using the following method: Acquire vibration data and deviation displacement data of different positions of the support beam in several monitoring cycles according to the position data of different sensor arrangements; Using multiple groups of human experts to manually annotate the force characteristics in the vibration data and the deviation displacement data, obtain several groups of force characteristic annotation results, and store them in corresponding storage units; A parallel-triggered comparison matrix and a task scheduler are set, wherein the task scheduler is configured to point to the force feature labeling results in the storage unit through a parallel trigger instruction to compare multiple groups of the force feature labeling results obtained under the same position data, and when at least one of the force feature labeling results is consistent with each other, the force feature labeling result is set as a prediction sample; The training samples are input into a training program for training to obtain the prediction model.

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