Fabricated building full-life-cycle structure health monitoring system and method

Abstract

The invention discloses a health monitoring system and method for a whole-life-cycle structure of a fabricated building, and belongs to the technical field of health monitoring of fabricated structures. The system comprises a data acquisition module, a data transmission module, a data processing and analysis module, an early warning module and a data visualization module, and an embedded fiber grating strain sensor is embedded in an assembled component in the prefabricated production process of the assembled component to form a prefabricated intelligent component. The sensing element can be used for monitoring steel reinforcement framework information and the concrete state of the structure, the safety performance of components and the structure can be accurately and effectively mastered, early warning can be achieved when the structure is damaged or damaged or seriously accidents occur, and therefore the safety, applicability, durability and integrity of the assembly type structure are guaranteed; and meanwhile, full-life safety monitoring of the fabricated structure is achieved, the requirement of digital construction is met, the industrial status of an enterprise in the field of fabricated construction can be improved, and the core competitiveness of the enterprise is improved.

Description

Technical Field

[0001] This invention relates to the field of prefabricated structure health monitoring technology, specifically to a prefabricated building full life cycle structural health monitoring system and method. Background Technology

[0002] Prefabricated buildings refer to buildings where a large amount of on-site work in traditional construction methods is transferred to factories. Building components and accessories are processed and manufactured in factories, transported to the construction site, and assembled on-site using reliable connection methods.

[0003] Currently, existing health monitoring systems for prefabricated buildings generally rely on manual collection of building structural parameters. This results in a large workload for data collection, low accuracy of analysis results, and the inability to comprehensively assess the health of the building's surface while failing to know the internal condition. Consequently, a comprehensive evaluation of the building's structural health cannot be achieved. Summary of the Invention

[0004] The purpose of this invention is to provide a prefabricated building full life cycle structural health monitoring system and method. By embedding embedded fiber optic strain sensors into the prefabricated components during the prefabrication process, prefabricated intelligent components are formed. The sensing elements can monitor the steel reinforcement cage information and concrete condition of the structure, accurately and effectively grasp the safety performance of the components and structure, and provide early warning when the structure is damaged, destroyed or seriously injured, thereby ensuring the safety, applicability, durability and integrity of the prefabricated structure itself, and solving the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A prefabricated building full life cycle structural health monitoring system includes a data acquisition module, a data transmission module, a data processing and analysis module, an early warning module, and a data visualization module;

[0007] The data acquisition module acquires the longitudinal strain, transverse strain, shear strain, ambient temperature, internal temperature of concrete, and humidity of the building structure in real time through an embedded fiber optic strain sensor.

[0008] The data transmission module is used to transmit the data acquired by the data acquisition module to the data processing and analysis module via a wireless network;

[0009] The data processing and analysis module removes noise and filters the data sent by the data transmission module, calculates the strain-time curve function, the maximum deformation of the building structure, the displacement of the building structure, and the deviation of the building structure from the design standard, and evaluates the safety of the building structure through a finite element analysis model.

[0010] The early warning module is used to calculate the building structure damage coefficient based on the analysis results of the data processing and analysis module, to determine whether there is damage to the structure, to issue an alarm when damage is found, and to generate a building structure assessment report and send it to the data visualization module.

[0011] The data visualization module is used to visualize the building structure assessment report through the real-time building structure monitoring interface.

[0012] Preferably, the formula for removing noise from the data is as follows:

[0013]

[0014] In the formula, D n (t) represents the denoised data, D(t) represents the original data to be denoised, and α represents the denoising coefficient, which takes a value between 0 and 1. Indicates the noise level of the data.

[0015] Preferably, the formula for the data filtering is as follows:

[0016]

[0017] In the formula, F(t) represents the filtered data, D(ti) represents the value of the original data at the past N time points, and N represents the size of the filtering window used to calculate the average value.

[0018] Preferably, the strain-time curve function is as follows:

[0019]

[0020] In the formula, ε(t) represents the strain of the building structure at time t, L(t) represents the length of the building structure at time t, and L0 represents the unstressed length of the building structure.

[0021] Preferably, the formula for calculating the maximum deformation of the building structure is as follows:

[0022] Δ max =max(|μ(t)|)

[0023] In the formula, Δ max The maximum deformation of the building structure is represented by μ(t), and the displacement of the structure at time t is represented by μ(t).

[0024] Preferably, the formula for calculating the displacement of the building structure is as follows:

[0025]

[0026] In the formula, μ(t) represents the structural displacement at time t, u(0) represents the initial displacement of the structure, Δu(τ) represents the displacement change measured by the sensor at time τ, and t represents time.

[0027] Preferably, the formula for calculating the deviation between the building structure and the design standard is as follows:

[0028] Δ=|D actual -D design |

[0029] In the formula, Δ represents the deviation between the building structure and the design standard, and D... actual D represents the actual measured value of the building structure. design This represents the value specified in the design standard.

[0030] Preferably, the finite element analysis model is as follows:

[0031] K*u=Fc

[0032] In the formula, K represents the stiffness matrix, which describes the stiffness characteristics of the structure; u represents the displacement matrix, which describes the displacement of each structural node; and Fc represents the load matrix, which describes the force acting on the structural structure.

[0033] Preferably, the formula for calculating the building structure damage coefficient is as follows:

[0034]

[0035] In the formula, D represents the damage coefficient of the building structure. i D represents the damage index at the i-th monitoring point. max This represents the maximum possible damage within the monitored area, and 'i' represents the index.

[0036] A method for monitoring the structural health of prefabricated buildings throughout their entire life cycle includes the following steps:

[0037] S1. Embedded fiber optic strain sensors (FBGs) are deployed bidirectionally along the main reinforcing bars of the assembled components, with a density of 3 sensors / m² at nodes, and a concrete cover thickness ≤20mm. Real-time acquisition of longitudinal strain, transverse strain, shear strain, ambient temperature, internal concrete temperature, and humidity of the building structure is achieved.

[0038] S2. Transmit the data obtained in S1 via a wireless network;

[0039] S3. Remove noise and filter the data transmitted in S2, calculate the strain-time curve function, the maximum deformation of the building structure, the displacement of the building structure, and the deviation of the building structure from the design standard, and evaluate the safety of the building structure through the finite element analysis model.

[0040] S4. Based on the analysis results in S3, calculate the building structure damage coefficient to determine whether there is damage to the structure. If damage is found, issue an alarm and generate a building structure assessment report.

[0041] S5. Visualize the building structure assessment report through the building structure real-time monitoring interface.

[0042] Compared with the prior art, the beneficial effects of the present invention are:

[0043] This invention, during the prefabrication of prefabricated components, embeds embedded fiber optic strain sensors (FBGs) into the components to create prefabricated intelligent components. These sensors monitor the steel reinforcement and concrete condition, accurately and effectively assessing the safety performance of the components and structure. Early warnings are provided for damage, failure, or serious accidents, ensuring the safety, applicability, durability, and integrity of the prefabricated structure. Simultaneously, it achieves full-lifecycle safety monitoring of the prefabricated structure, meeting digital construction standards. This is expected to increase the company's market share in the prefabricated construction field by 15% to 20%. Furthermore, with the help of advanced monitoring technology, the company's core competitiveness is expected to increase by 30%, thus gaining a stronger competitive advantage in the industry. Attached Figure Description

[0044] Figure 1 This is a schematic diagram of the system structure of the present invention;

[0045] Figure 2 This is a schematic diagram of the method flow of the present invention;

[0046] Figure 3 This is a diagram of the original signal filtering layered processing framework of the present invention. Detailed Implementation

[0047] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0048] Existing health monitoring systems for prefabricated buildings generally rely on manual collection of structural parameters, which suffers from drawbacks such as large data collection workload, low accuracy of analysis results, and the inability to comprehensively assess the health of the building's surface while failing to reveal the internal condition. Therefore, this invention proposes a prefabricated building life-cycle structural health monitoring system and method. Please refer to [link to relevant documentation]. Figure 1-3 The system includes a data acquisition module, a data transmission module, a data processing and analysis module, an early warning module, and a data visualization module;

[0049] The data acquisition module employs embedded fiber optic grating strain sensors (FBGs) to achieve real-time monitoring of the building structure's health status through fiber optic sensing technology. These sensors feature high sensitivity and wide bandwidth, accurately measuring longitudinal, transverse, and shear strains in the building structure to reflect deformation under different load conditions. Simultaneously, combined with temperature sensors, the module can acquire real-time ambient and internal concrete temperatures to assess the impact of temperature changes on structural performance. Furthermore, the module is equipped with humidity sensors to monitor the ambient humidity around the building structure, thereby comprehensively analyzing the potential impact of humidity on material properties. This data is acquired in real-time using advanced digital monitoring methods, providing accurate data for subsequent processing and analysis, ensuring comprehensive assessment and maintenance management of the building structure's health status.

[0050] The data transmission module is responsible for transmitting various monitoring data acquired by the data acquisition module to the data processing and analysis module quickly and securely via a wireless network. This module uses advanced wireless communication technologies, such as Wi-Fi, Bluetooth, or LTE, to ensure efficient data transmission and real-time performance. During data transmission, data compression and encryption technologies are used to reduce communication latency and improve data transmission security, ensuring that sensitive information is not intercepted or tampered with during transmission.

[0051] Before transmission, the data undergoes preprocessing to make the transmitted data more stable and reliable. The selection of the wireless network is optimized based on the site conditions to maximize the clarity of signal transmission and expand the coverage. This module also has self-detection and fault diagnosis capabilities, monitoring the transmission status of data packets in real time. Once packet loss, transmission delay, or errors are detected, it can issue an alarm in a timely manner and attempt to retransmit. This highly reliable data transmission scheme ensures that the data collected during the monitoring process can be quickly and accurately fed back to the data processing and analysis module, thus providing solid data support and foundation for the real-time monitoring and health assessment of building structures.

[0052] After receiving the data sent by the data transmission module, the data processing and analysis module first performs noise reduction and filtering on the raw data. This process mainly uses digital filtering techniques, including low-pass filters and Kalman filters. Through these techniques, interference noise introduced by sensors or the environment can be effectively removed, improving the accuracy and reliability of the data and laying the foundation for subsequent analysis.

[0053] The formula for removing noise from data is shown below:

[0054]

[0055] In the formula, D n (t) represents the denoised data, D(t) represents the original data to be denoised, and α represents the denoising coefficient, which takes a value between 0 and 1. To indicate the noise level of the data, wavelet thresholding is first used for denoising (suitable for strain abrupt change models, preserving strain jump characteristics and eliminating high-frequency electromagnetic interference), followed by Kalman filtering (suitable for temperature drift compensation, separating temperature effects from true strain in real time, and solving the cross-sensitivity problem of FBG), moving weighted average (low-power real-time filtering on edge computing devices) is used to maintain real-time streaming data processing, and finally frequency domain band-stop filtering is performed.

[0056] Based on the data cleansing, the module further calculates the strain-time curve using the formula:

[0057]

[0058] In this formula, ∈(t) represents the strain at time t, L(t) is the current measured length, and L0 is the initial length. By plotting the strain-time curve, the dynamic behavior of the structure under different working conditions can be intuitively reflected, helping engineers to identify potential safety hazards.

[0059] In addition, the module also calculates the maximum deformation of the building structure using the formula:

[0060] Δ max =max(|μ(t)|)

[0061] Δ in this formula max It refers to the maximum deformation of the structure during the monitoring period, where μ(t) is the displacement at time t. The calculation of the maximum deformation enables engineers to understand the ultimate response of the structure after the load is applied, providing a basis for structural health assessment.

[0062] Simultaneously, the module calculates the displacement of the building structure using the following formula:

[0063]

[0064] Where μ(t) represents the structural displacement at time t, u(0) represents the initial displacement of the structure, Δu(τ) represents the displacement change measured by the sensor at time τ, and t represents time. This calculation helps to evaluate the deformation capacity of the structure under complex loading conditions and ensure that it can remain safe and stable during use.

[0065] Furthermore, the module also analyzes the deviation between the building structure and design standards using the formula:

[0066] Δ=|D actual -Ddesign |

[0067] Wherein, Δ is the deviation between the actual measured value and the design standard, which helps to ensure that the design of the structure complies with relevant specifications and standards, and to promptly identify and correct potential design defects;

[0068] Finally, the safety of the building structure is evaluated using a finite element analysis model, employing the formula:

[0069] K*u=Fc

[0070] In this model, K represents the stiffness matrix, u is the displacement vector of each node, and Fc is the external load applied to the structure. The power of finite element analysis lies in its ability to transform complex structural problems into mathematical models, simulate the behavior of buildings under different conditions, and achieve accurate prediction of structural responses. Through detailed modeling of the interactions between nodes and loading conditions, this model can not only identify potential weaknesses in the structure, but also provide data support and decision-making basis for structural optimization design.

[0071] Based on the above analysis process and technical methods, the data processing and analysis module provides comprehensive protection for the health monitoring of building structures. Through scientific data processing and rigorous analysis methods, it ensures the safety and reliability of buildings and provides a solid basis for decision-making in engineering practice.

[0072] The early warning module plays a crucial role in the entire monitoring system. It is responsible for real-time assessment of the building structure's health status based on the analysis results generated by the data processing and analysis module. This module uses advanced computing technology to determine the damage coefficient of the building structure based on the monitoring data. This coefficient is calculated using the following formula:

[0073]

[0074] In this formula, D represents the structural damage coefficient. i D represents the damage index at the i-th monitoring point. max It represents the maximum possible damage within the entire monitoring area. This indicator can not only quantify the degree of structural damage, but also provide data for subsequent decision-making.

[0075] To effectively assess the degree of damage to a building, this module sets damage criteria: a damage coefficient D < 0.1 for no damage, 0.1 ≤ D < 0.3 for minor damage, 0.3 ≤ D < 0.5 for moderate damage, and D ≥ 0.5 for severe damage. These levels help guide engineers in assessing the actual condition of the structure and taking appropriate measures. Furthermore, the comprehensive assessment must consider the structure's material properties, service life, and environmental factors to ensure timely identification of potential risks under different working conditions. The monitoring system should set baselines and conduct real-time monitoring using historical data. A corresponding alarm mechanism should automatically issue an alarm when the damage coefficient exceeds the threshold and promptly provide status information to relevant personnel. Simultaneously, a regular re-inspection plan should be developed to ensure that even under normal conditions, long-term accumulated minor deformations can prevent serious safety issues. This comprehensive monitoring and assessment scheme not only effectively identifies the building's damage status but also provides a solid basis for subsequent maintenance management and decision-making.

[0076] In addition, the early warning module is responsible for generating detailed building structure assessment reports. These reports integrate monitoring data, damage assessments, and analyses of potential safety hazards. The assessment report includes information such as the structure's current status, historical trends, damage assessment results, and recommended maintenance measures. This report is then sent to the data visualization module for intuitive display and analysis. In the data visualization module, these assessment reports are visualized through a real-time building structure monitoring interface. This interface presents the data analysis results graphically, including dynamic strain diagrams, displacement curves, damage distribution maps, and key information from the assessment report. Using charts and images, users can quickly understand the building's condition and its changes, facilitating rapid decision-making and planning.

[0077] In summary, the early warning module not only provides intelligent means for real-time monitoring of building structures, but also greatly improves building safety through damage coefficient calculation and alarm mechanisms. At the same time, the data visualization module transforms complex assessment results into easily understandable information through an intuitive interface, enabling relevant personnel to make scientific analyses and emergency responses to the building status in the first instance, effectively maintaining the long-term safety and stability of the building.

[0078] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A prefabricated building life-cycle structural health monitoring system, characterized in that: It includes a data acquisition module, a data transmission module, a data processing and analysis module, an early warning module, and a data visualization module; The data acquisition module acquires the longitudinal strain, transverse strain, shear strain, ambient temperature, internal temperature of concrete, and humidity of the building structure in real time through an embedded fiber optic strain sensor. The data transmission module is used to transmit the data acquired by the data acquisition module to the data processing and analysis module via a wireless network; The data processing and analysis module removes noise and filters the data sent by the data transmission module, calculates the strain-time curve function, the maximum deformation of the building structure, the displacement of the building structure, and the deviation of the building structure entity from the design standard, and evaluates the safety of the building structure through a finite element analysis model. The early warning module is used to calculate the building structure damage coefficient based on the analysis results of the data processing and analysis module, to determine whether there is damage to the structure, to issue an alarm when damage is found, and to generate a building structure assessment report and send it to the data visualization module. The data visualization module is used to visualize the building structure assessment report through the real-time building structure monitoring interface.

2. The prefabricated building full life cycle structural health monitoring system according to claim 1, characterized in that: The formula for removing noise from the data is as follows: In the formula, D n (t) represents the denoised data, D(t) represents the original data to be denoised, and α represents the denoising coefficient, which takes a value between 0 and 1. Indicates the noise level of the data.

3. The prefabricated building full life cycle structural health monitoring system according to claim 2, characterized in that: The formula for data filtering is as follows: In the formula, F(t) represents the filtered data, D(ti) represents the value of the original data at the past N time points, and N represents the size of the filtering window used to calculate the average value.

4. The prefabricated building full life cycle structural health monitoring system according to claim 3, characterized in that: The curve function of strain changing with time is shown below: In the formula, ∈(t) represents the strain of the building structure at time t, L(t) represents the length of the building structure at time t, and L0 represents the unstressed length of the building structure.

5. The prefabricated building full life cycle structural health monitoring system according to claim 4, characterized in that: The formula for calculating the maximum deformation of a building structure is as follows: D max =max(|μ(t)|) In the formula, Δ max The maximum deformation of the building structure is represented by μ(t), and the displacement of the structure at time t is represented by μ(t).

6. The prefabricated building full life cycle structural health monitoring system according to claim 5, characterized in that: The formula for calculating the displacement of the building structure is as follows: In the formula, μ(t) represents the structural displacement at time t, u(0) represents the initial displacement of the structure, Δu(τ) represents the displacement change measured by the sensor at time τ, and t represents time.

7. The prefabricated building full life cycle structural health monitoring system according to claim 6, characterized in that: The formula for calculating the deviation between the building structure and the design standard is as follows: Δ=|D actual -D design | In the formula, Δ represents the deviation between the building structure and the design standard, and D... actual D represents the actual measured value of the building structure. design This represents the value specified in the design standard.

8. The prefabricated building full life cycle structural health monitoring system according to claim 7, characterized in that: The finite element analysis model is shown below: K*u=Fc In the formula, K represents the stiffness matrix, which describes the stiffness characteristics of the structure; u represents the displacement matrix, which describes the displacement of each structural node; and Fc represents the load matrix, which describes the force acting on the structural structure.

9. A prefabricated building life-cycle structural health monitoring system according to claim 8, characterized in that: The formula for calculating the damage coefficient of a building structure is as follows: In the formula, D represents the damage coefficient of the building structure. i D represents the damage index at the i-th monitoring point. max This represents the maximum possible damage within the monitored area, and 'i' represents the index.

10. A method for monitoring the structural health of prefabricated buildings throughout their entire life cycle, characterized in that: Includes the following steps: S1. The longitudinal strain, transverse strain, shear strain, ambient temperature, internal temperature of concrete, and humidity of the building structure are acquired in real time using embedded fiber optic strain sensors. S2. Transmit the data obtained in S1 via a wireless network; S3. Remove noise and filter the data transmitted in S2, calculate the strain-time curve function, the maximum deformation of the building structure, the displacement of the building structure, and the deviation of the building structure from the design standard, and evaluate the safety of the building structure through the finite element analysis model. S4. Based on the analysis results in S3, calculate the building structure damage coefficient to determine whether there is damage to the structure. If damage is found, issue an alarm and generate a building structure assessment report. S5. Visualize the building structure assessment report through the building structure real-time monitoring interface.

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