Concrete formwork stress monitoring method and system based on intelligent sensor

Abstract

The invention relates to the technical field of online monitoring, in particular to a concrete formwork stress monitoring method and system based on an intelligent sensor, and the method specifically comprises the steps: collecting environment data of a concrete pouring site, building a concrete environment coupling dynamic model, and outputting a formwork side pressure correction value; collecting working condition data of the template, and importing the working condition data of the template into the random vibration response coupling model to generate a space-time stress threat cloud picture borne by the template in real time; a hydration heat temperature field in the concrete pouring process is monitored in real time, and chemical shrinkage strain generated in the concrete pouring process is obtained; and obtaining a template comprehensive failure index according to the stress threat and the chemical shrinkage strain in the space-time stress threat cloud picture, calculating a time-varying failure probability, and triggering graded early warning through the template comprehensive failure index and the time-varying failure probability. According to the invention, the problem of lagging or misjudgment of failure early warning of the template in the prior art is solved.

Description

TECHNICAL FIELD

[0001] The application relates to the online monitoring technical field and is a concrete formwork stress monitoring method and system based on an intelligent sensor. BACKGROUND

[0002] In concrete site pouring construction, formwork stress monitoring is a key link for ensuring structure safety and construction quality, and existing technologies are mostly based on static mechanics models or single dynamic load analysis, and have the following limitations: first, environmental factors (such as ultraviolet radiation, wind speed and temperature gradient) have a dynamic influence on concrete rheological properties and formwork side pressure, and the dynamic influence is often simply processed, so that the side pressure prediction value is greatly deviated from the actual working condition, especially under complex construction environment, and the error is significant due to different weather conditions; second, dynamic load analysis mostly focuses on a single excitation source, lacks modeling of frequency domain superposition effects of multi-source coupled dynamic loads, and thus the spatial resolution of risk stress cloud maps is insufficient, and it is difficult to accurately locate high stress areas; and third, a static threshold criterion is generally used in the failure prediction model, especially without introducing a time-varying failure probability to quantify cumulative damage risk, and the multiphase coupling effect of chemical shrinkage strain and formwork bearing stress is ignored, so that the formwork failure early warning is lagged or misjudged. SUMMARY

[0003] The application solves the problem of formwork failure early warning lag or misjudgment in the prior art, and provides a concrete formwork stress monitoring method and system based on an intelligent sensor.

[0004] In order to achieve the above purpose, the technical scheme of the concrete formwork stress monitoring method based on the intelligent sensor comprises the following steps: environmental data of a concrete pouring site are collected, a concrete environment coupled dynamics model is established, and a formwork side pressure correction value is output; working condition data of the formwork are collected, and the working condition data of the formwork are imported into a random vibration response coupled model to generate a time-space stress threat cloud map of the formwork in real time; a hydration heat temperature field in a concrete pouring process is monitored in real time, and chemical shrinkage strain in the concrete pouring process is obtained; a formwork comprehensive failure index is obtained according to stress threat in the time-space stress threat cloud map and the chemical shrinkage strain, a time-varying failure probability is calculated, and a graded early warning is triggered through the formwork comprehensive failure index and the time-varying failure probability.

[0005] Specifically, the environmental data of the concrete pouring site are collected, the concrete environment coupled dynamics model is established, and a formwork side pressure function is output, including: S11: Collect the original environmental data of the concrete pouring site, and perform denoising and normalization processing on the original environmental data, the environmental data of the concrete pouring site including: template resonance frequency , air convection coefficient , ultraviolet intensity value UV and concrete bleeding data; S12: Establish a concrete environment coupling dynamics model, and preliminarily output the base side pressure through the concrete environment coupling dynamics model, the concrete environment coupling dynamics model being specifically: ; is the concrete density; is the concrete pouring speed vector; t is time; is the concrete viscosity, reflecting the non-Newtonian property of the concrete; g is the acceleration of gravity, affecting the static pressure distribution of the concrete; is the base side pressure; z is the spatial coordinate along the pouring direction; Specifically, the environmental data of the concrete pouring site is collected, a concrete environment coupling dynamics model is established, and a template side pressure function is output, further comprising: S13: Correct the base side pressure preliminarily output by the concrete environment coupling dynamics model through the denoised and normalized environmental data of the concrete pouring site, output the template side pressure correction value, specifically comprising: ; wherein, is the template side pressure correction value, is the environmental correction factor; T is the vertical temperature; UV is the ultraviolet radiation intensity; is the environmental wind speed of the concrete pouring site; Specifically, the working condition data of the template is collected, and the working condition data of the template is imported into the random vibration response model to generate a stress threat cloud map of the template in real time, comprising: S21: Based on the template geometric parameters of the template and the concrete density, calculate the static stress generated by the template self weight and the concrete static pressure on the template ; ; wherein, respectively, are the gravity stress of the template material itself; is the ratio of the actual contact area of the concrete and the template to the total area of the template; S22: Obtain the working condition data of the template, including: gust load, pump pipe pulse pressure and worker trampling position. Perform frequency domain analysis on the working condition data of the template, extract the stress components of each working condition dynamic source, and quantify the contribution of each working condition dynamic source through power spectral density (i.e. PSD) to obtain the dynamic stress at different frequencies. Preferably, the quantification of the contribution of each dynamic source under various operating conditions using power spectral density (PSD) specifically involves: ; When e=1, the dynamic source of the working condition is the gust load; when e=2, the dynamic source of the working condition is the pump pipe pulse pressure; when e=3, the dynamic source of the working condition is the worker's footing position. This represents the dynamic stress amplitude within the e-th frequency band, and indicates the magnitude of the vibration stress borne by the template at that frequency. The power spectral density (PSD) function at frequency The value at (unit: Pa² / Hz) describes the load energy distribution density of the dynamic source under the e-th operating condition in the frequency domain; The load of the dynamic source under the e-th working condition; Let be the power spectral density function, which is the frequency domain energy distribution of the time-history signal of the dynamic source load under the e-th working condition after Fourier transform. The amplification factor represents the frequency of the template. The dynamic amplification capability of the load; The frequency bandwidth represents the frequency range considered in the analysis. Specifically, the process includes collecting working condition data of the template and importing this data into a random vibration response model to generate a stress threat cloud map of the template in real time. It also includes: S23: Based on S21 and S22, the static stress and dynamic stress of each frequency band are imported into the stochastic vibration response coupling model to generate a spatiotemporal stress threat cloud map of the template in real time, specifically: ; in, The stress threat to the template; is the proportional weight of the dynamic source for the e-th working condition; i is the frequency segment, and I is the total number of frequency segments analyzed. Specifically, the hydration heat temperature field during concrete pouring is monitored in real time to obtain the chemical shrinkage strain during formwork pouring. The calculation of the chemical shrinkage strain is as follows: ; in: For chemical shrinkage strain, The chemical shrinkage coefficient of concrete changes dynamically with the hydration process of concrete. The rate of temperature change in the hydration heat temperature field reflects the intensity of the hydration reaction; Specifically, the comprehensive failure index The specific calculation strategy is as follows: ; in, This is the maximum stress that the template can withstand. The ultimate shrinkage strain of concrete. It should be noted that 0.5 is the shrinkage term coefficient, which reflects the low weight of shrinkage strain on overall failure and needs to be combined with the stress term of the template for comprehensive judgment.

[0006] Specifically, the time-varying failure probability The calculation strategy is as follows: ; This represents the stress threat borne by the template at time t. This indicates the cumulative damage to the formwork during the on-site pouring process; m is the Weibull shape parameter, reflecting the rate of material damage accumulation; Specifically, a tiered early warning system is triggered by the template-based comprehensive failure index and time-varying failure probability, including: when If the value is less than 1, no risk warning will be triggered, and concrete pouring will continue. when When the value is ≥1, an orange risk warning is triggered, the concrete pouring speed is reduced, the load is reduced, and reinforcement is carried out. Time-varying failure probability When the value is greater than 0.95, a red risk warning is triggered, work is forced to stop, and the template is replaced.

[0007] In addition, the concrete formwork stress monitoring system based on intelligent sensors of the present invention includes the following modules: Lateral pressure fitting module, spatiotemporal stress quantification module, contraction strain quantification module, and template failure detection module; The side pressure fitting module is used to collect environmental data at the concrete pouring site, establish a coupled dynamic model of the concrete environment, and output the template side pressure correction value. The spatiotemporal stress quantification module is used to collect the working condition data of the template and import the working condition data of the template into the random vibration response coupling model to generate a spatiotemporal stress threat cloud map of the template in real time. The shrinkage strain quantification module is used to monitor the hydration heat temperature field in real time during the concrete pouring process and obtain the chemical shrinkage strain generated during the concrete pouring process. The template failure detection module obtains the template comprehensive failure index based on the stress threat and chemical shrinkage strain in the spatiotemporal stress threat cloud map, and calculates the time-varying failure probability. It then triggers a graded early warning based on the template comprehensive failure index and the time-varying failure probability.

[0008] Compared with the prior art, the technical effects of the present invention are as follows: 1. This invention, through a coupled dynamic model of the concrete environment, for the first time deeply couples environmental parameters such as ultraviolet radiation, wind speed, and temperature gradient with the non-Newtonian fluid characteristics of concrete, dynamically corrects the lateral pressure of the formwork, and solves the defects of traditional static formulas that ignore shear thinning and bleeding effects. 2. In response to the problems of single dynamic load analysis and insufficient spatial resolution, the present invention proposes a random vibration response coupling model to realize frequency domain energy quantification and risk cloud map generation of multi-source loads, and accurately locate high stress risk areas.

[0009] 3. In view of the problems of static failure prediction and neglect of cumulative damage, this invention constructs a multi-parameter fusion failure assessment system, and solves the problem of lag misjudgment by coupling time-varying failure probability with multi-phase early warning. Attached Figure Description

[0010] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein: Figure 1 This is a schematic flowchart of a concrete formwork stress monitoring method based on intelligent sensors according to the present invention. Figure 2 This is a logical diagram illustrating a method for monitoring concrete formwork stress based on intelligent sensors according to the present invention. Figure 3 This is a schematic diagram of the structure of a concrete formwork stress monitoring system based on intelligent sensors according to the present invention. Detailed Implementation

[0011] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0012] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0013] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0014] Example 1. (As shown in the original text) Figure 1 As shown in the figure, an embodiment of the present invention provides a method for monitoring the stress of concrete formwork based on intelligent sensors, such as... Figure 1 As shown, the specific steps include the following: like Figure 2 As shown in the section on the side pressure of the formwork, environmental data of the concrete pouring site are collected, a coupled dynamic model of the concrete environment is established, and the correction value of the side pressure of the formwork is output. include: S11: Collect raw environmental data from the concrete pouring site and perform noise reduction and normalization processing on the raw environmental data. The environmental data from the concrete pouring site includes: formwork resonance frequency. Air convection coefficient UV intensity values ​​and concrete bleeding data; For example, this embodiment provides a normalization processing strategy for raw environmental data, specifically: ,in, is the normalized environmental data; k is the original environmental data before normalization. Minimum and maximum environmental data collected from different data collection points; S12: Establish a coupled dynamic model of the concrete environment, and output the foundation lateral pressure using the coupled dynamic model of the concrete environment. The concrete environment coupled dynamics model is specifically as follows: ; ρ is the density of concrete, used to characterize the mass distribution of concrete; t is the concrete pouring velocity vector, used to describe the concrete flow velocity; t is time. The shear rate-dependent viscosity of concrete reflects its non-Newtonian properties. g is the acceleration due to gravity, which affects the static pressure distribution of concrete. The foundation lateral pressure is represented by z, which is the spatial coordinate along the pouring direction. It should be noted that the concrete environment coupled dynamics model is set based on the non-Newtonian fluid characteristics of concrete and is used to simulate the velocity field and stress distribution during the concrete pouring process to the formwork flow process, providing an analytical premise for the stress analysis of the formwork. For example, in this embodiment, it should be noted that for the coupled dynamics model of the concrete environment, Used to characterize the acceleration force in the concrete pouring site, that is, the inertial force generated by the acceleration of the concrete fluid; For example, in this embodiment, it should be noted that, For concrete viscosity, it should be noted that the viscosity of non-Newtonian fluids varies with shear rate. For example, in this embodiment, it should be noted that, The gravity generated by the self-weight of concrete is mainly in the vertical direction during the on-site pouring of concrete, and the gravity generated by the self-weight of concrete increases with the increase of the pouring height. For example, in this embodiment, it should be noted that, This is the pressure gradient force, which reflects the reaction force of the formwork on the fluid. It should also be noted that the direction of the pressure gradient is the direction in which the pressure increases the fastest, while the pressure on the concrete fluid is in the opposite direction to the pressure gradient (i.e., from the high-pressure area to the low-pressure area). Therefore, this item is represented by a negative sign. For example, in this embodiment, a shear rate-dependent concrete viscosity is also provided. The calculation strategy is as follows: ; in, This represents the initial viscosity of the concrete, i.e., the viscosity when the shear rate γ approaches 0. γ is the ultimate viscosity of concrete, the viscosity at which the shear rate γ approaches infinity. Relaxation time (unit: s), characterizing the viscoelastic response rate; The shear rate is calculated from the concrete pouring speed gradient. ); n is the power law exponent, used to control the steepness of the shear thinning behavior; It should be noted that the aforementioned coupled dynamics model of the concrete environment is specifically designed for the shear thinning behavior of concrete. As the shear rate increases, the concrete viscosity will decrease from... Gradually decrease to ; It should be noted that the shear rate depends on the concrete viscosity. The calculation strategy is based on the Carreau-Yasuda model, which is used to describe the viscosity changes of shear-thinning fluids. It can dynamically correct the viscosity of concrete and accurately simulate non-Newtonian flow behavior. It should be noted that in actual concrete pouring sites, under high shear rates (such as during pumping), the viscosity of concrete decreases and its fluidity increases.

[0015] S13: Correct the foundation lateral pressure output from the initial coupled dynamics model of the concrete environment using environmental data from the concrete pouring site that has undergone noise reduction and normalization. The corrected formwork lateral pressure value is then output, specifically including: ; in, This is the correction value for the template side pressure. Environmental correction factor; T represents vertical temperature; UV represents ultraviolet radiation intensity. The ambient wind speed at the concrete pouring site; For example, in this embodiment, a calculation strategy for the environmental correction factor is provided, specifically as follows: ; in, The ultraviolet radiation influence coefficient (unit: m² / W) converts ultraviolet radiation intensity into a stress correction factor. UV refers to the intensity of ultraviolet radiation, which reflects the promoting effect of light on surface hardening, thereby affecting lateral pressure. For example, in this embodiment, it should be noted that ultraviolet (UV) light promotes concrete hydration, increases surface hardness, reduces bleeding, and thus reduces lateral pressure. Therefore, it is used... The contribution of quantitative light intensity to surface hardening, It was calibrated through experiments; it should also be noted that... A negative number is used to characterize the inhibitory effect of ultraviolet radiation on lateral pressure. The ambient wind speed at the concrete pouring site should be noted. It should be noted that the ambient wind speed at the concrete pouring site will accelerate the evaporation of moisture from the concrete surface, thereby affecting the lateral pressure. k is the air convection coefficient (unit: m / s), which characterizes the resistance of airflow to evaporation; It should be noted that increased wind speed at the concrete pouring site leads to a faster evaporation rate, resulting in reduced surface bleeding, increased concrete density, and higher lateral pressure. The term uses a logarithmic function to prevent the correction factor from diverging when the wind speed is too high; The bleeding rate-temperature gradient coupling coefficient (unit: m² / K²) correlates the temperature gradient with the bleeding rate. The vertical temperature gradient (unit: K / m) is caused by heat of hydration and ambient temperature difference. For example, in this embodiment, it should be noted that the vertical temperature gradient This can cause uneven shrinkage of concrete during on-site pouring, generating additional stress and increasing lateral pressure. In this context, the nonlinear relationship between shrinkage stress and gradient magnitude is represented by the squared term.

[0016] like Figure 2 As shown in the section on stress threat, the working condition data of the template is collected and imported into the random vibration response coupling model to generate a spatiotemporal stress threat cloud map of the template in real time. S21: Based on the formwork's geometric parameters (dimensions, thickness) and concrete density, calculate the static stress on the formwork caused by its own weight and the static pressure of the concrete. ; ; in, These are the gravitational stresses of the template material itself. It should be noted that steel templates have a high density and therefore higher self-weight stresses. This is the ratio of the actual contact area between the concrete and the formwork to the total area of ​​the formwork. For example, in this embodiment, it should be noted that if there are ribs supporting the back of the template, the actual stress-bearing area of ​​the template is less than the total area of ​​the template, and the stress will be concentrated. S22: Obtain the working condition data of the template, including: gust load, pump pipe pulse pressure and worker trampling position. Perform frequency domain analysis on the working condition data of the template, extract the stress components of each working condition dynamic source, and quantify the contribution of each working condition dynamic source through power spectral density (i.e. PSD) to obtain the dynamic stress at different frequencies. In another specific embodiment, the quantification of the contribution of each operating condition dynamic source by power spectral density (PSD) specifically involves: ; When e=1, the dynamic source of the working condition is the gust load; when e=2, the dynamic source of the working condition is the pump pipe pulse pressure; when e=3, the dynamic source of the working condition is the worker's footing position. This represents the dynamic stress amplitude within the e-th frequency band, and indicates the magnitude of the vibration stress borne by the template at that frequency. The power spectral density (PSD) function at frequency The value at (unit: Pa² / Hz) describes the load energy distribution density of the dynamic source under the e-th operating condition in the frequency domain; The load of the dynamic source under the e-th working condition; Let be the power spectral density function, which is the frequency domain energy distribution of the time-history signal of the dynamic source load under the e-th working condition after Fourier transform. The amplification factor represents the frequency of the template. The dynamic amplification capability of the load; The frequency bandwidth represents the frequency range considered in the analysis. It should be noted that the calculation formula for quantifying the contribution of dynamic sources under various operating conditions through power spectral density (PSD) is essentially the conservation of energy in the frequency domain. The left side is the energy (power) of dynamic stress, and the right side is the accumulation of load energy after amplification by the template. Among them, power spectral density describes the energy distribution of the load in the frequency domain, while the amplification factor H describes the system's ability to amplify energy into stress. For example, in this embodiment, the value of H ranges from 1.5 to 2.8, comprehensively reflecting the average dynamic response effect, and is determined through experiments and simulations; By quantifying the contribution of dynamic sources under various working conditions using power spectral density, complex dynamic loads (such as random gusts and periodic pump pipe pulses) can be converted into stress amplitudes in various frequency bands of the template, providing a quantitative basis for subsequent risk assessment. For example, in this embodiment, the gust load power spectral density is described based on the von Karman spectrum. Specifically: ; in, The ambient wind speed at the concrete pouring site; L is the turbulence integral scale (m), which characterizes the characteristic length scale of energy contained in turbulence; K is the KAMAN constant, with a value of 0.0015; f is the vibration frequency of the gust load; It should be noted that the von Karman spectrum is derived from theoretical analysis of atmospheric turbulence and fitting of a large amount of measured data, and is suitable for describing the energy distribution of wind loads at different heights and roughnesses.

[0017] For example, in this embodiment, it should be noted that the pump tube pulse is a periodic pressure change, which can be regarded as a series of equally spaced impulse functions. Therefore, the pump tube pulse load power spectral density It can be: ; in, The period (s) of the pump tube pulse, i.e., the time interval between two adjacent pulses, is related to the pumping frequency. They are reciprocals of each other; The pumping frequency is determined by the flow rate of the pumping equipment and the pump pipe volume, and is the ratio of real-time flow rate to pump pipe volume. The Dirac delta function is the frequency... The value is infinity at some points and zero elsewhere, indicating that energy exists at these discrete frequencies.

[0018] For example, in this embodiment, it should be noted that the worker's trampling can be approximated as a brief impact process, with its load decaying exponentially over time. By performing a Fourier transform on the exponential decay function, its energy distribution in the frequency domain can be obtained. Therefore, the power spectral density of the worker's trampling load can be: ; in, The initial force (N) of the stomp impact represents the maximum force applied at the moment of stomp. The time constant (s) reflects the decay rate of the impact load and is set to 0.2s. f is the frequency (Hz), representing the vibration frequency of the impact load; S23: Based on S21 and S22, the static stress and dynamic stress of each frequency band are imported into the stochastic vibration response coupling model to generate a spatiotemporal stress threat cloud map of the template in real time, specifically: ; in, The stress threat to the template; is the proportional weight of the dynamic source for the e-th working condition; i is the frequency segment, and I is the total number of frequency segments analyzed. Exemplarily, in this embodiment, ; like Figure 2 As shown in the shrinkage strain section, the hydration heat temperature field during concrete pouring is monitored in real time to obtain the chemical shrinkage strain generated during concrete pouring. The calculation of the chemical shrinkage strain is as follows: ; in: For chemical shrinkage strain, The chemical shrinkage coefficient of concrete changes dynamically with the hydration process of concrete. The rate of temperature change in the hydration heat temperature field reflects the intensity of the hydration reaction; like Figure 2 As shown in the failure detection section, the template comprehensive failure index is obtained based on the stress threat and chemical shrinkage strain in the spatiotemporal stress threat cloud map. At the same time, the time-varying failure probability is calculated, and a graded early warning is triggered by the template comprehensive failure index and the time-varying failure probability.

[0019] The comprehensive failure index The specific calculation strategy is as follows: ; in, This is the maximum stress that the template can withstand. The ultimate shrinkage strain of concrete. It should be noted that 0.5 is the shrinkage term coefficient, which reflects the low weight of shrinkage strain on overall failure and needs to be combined with the stress term of the template for comprehensive judgment.

[0020] The time-varying failure probability The calculation strategy is as follows: ; This represents the stress threat borne by the template at time t. This indicates the cumulative damage to the formwork during the on-site pouring process; m is the Weibull shape parameter, reflecting the rate of material damage accumulation; It should be noted, for example, in this embodiment, when m>1, it indicates that the damage accumulates rapidly, that is, the damage grows faster and faster over time; when m=1, the damage accumulation rate is constant; when m<1, the damage accumulation rate gradually slows down. It should be noted that under cyclic pouring or long-term stress, the formwork material will gradually accumulate damage. When the accumulated damage reaches a certain level, the formwork material will fail. For example, in this embodiment, it should be noted that the Weibull distribution is commonly used to describe the failure probability of materials. Its shape parameter m reflects the rate of damage accumulation and the characteristics of the failure mode. The shape parameter m can be adjusted according to the material properties and actual conditions to more accurately describe the failure behavior of the material. For example, for brittle materials, the value of m is usually large, indicating that damage accumulates rapidly and the failure probability increases rapidly over time; while for ductile materials, the value of m may be small, indicating that damage accumulation is relatively slow and the increase in failure probability is relatively gradual.

[0021] It should also be noted that, for damage to the formwork during the concrete pouring process, for example, in this embodiment, it is assumed that the formwork damage event follows a Poisson process, which is a commonly used stochastic process model used to describe the number of times a random event occurs within a certain time period. like Figure 2 As shown in the section on tiered early warning, tiered early warnings are triggered by the template-based comprehensive failure index and time-varying failure probability, specifically including: when If the value is less than 1, no risk warning will be triggered, and concrete pouring will continue. when When the value is ≥1, an orange risk warning is triggered, the concrete pouring speed is reduced, the load is reduced, and reinforcement is carried out. For example, in this embodiment, the reduction in the single concrete pouring speed is 5% of the current concrete pouring speed; Time-varying failure probability When the value is greater than 0.95, a red risk warning is triggered, work is forced to stop, and the template is replaced.

[0022] Example 2. (As shown) Figure 3 As shown in the figure, an embodiment of the present invention provides a concrete formwork stress monitoring system based on intelligent sensors, such as... Figure 3 As shown, it includes the following modules: Lateral pressure fitting module, spatiotemporal stress quantification module, contraction strain quantification module, and template failure detection module; The side pressure fitting module is used to collect environmental data at the concrete pouring site, establish a coupled dynamic model of the concrete environment, and output the template side pressure correction value. The spatiotemporal stress quantification module is used to collect the working condition data of the template and import the working condition data of the template into the random vibration response coupling model to generate a spatiotemporal stress threat cloud map of the template in real time. The shrinkage strain quantification module is used to monitor the hydration heat temperature field in real time during the concrete pouring process and obtain the chemical shrinkage strain generated during the concrete pouring process. The template failure detection module obtains the template comprehensive failure index based on the stress threat and chemical shrinkage strain in the spatiotemporal stress threat cloud map, and calculates the time-varying failure probability. It then triggers a graded early warning based on the template comprehensive failure index and the time-varying failure probability.

[0023] Example 3. This example provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor; The processor executes the aforementioned method for monitoring concrete formwork stress based on smart sensors by calling computer programs stored in memory.

[0024] The electronic device can vary considerably depending on its configuration and performance. It may include one or more Central Processing Units (CPUs) and one or more memories, wherein the memory stores at least one computer program, which is loaded and executed by the processor to implement the concrete formwork stress monitoring method based on intelligent sensors provided in the above-described embodiment. The electronic device may also include other components for implementing its functions; for example, it may have wired or wireless network interfaces and input / output interfaces for data input and output. Further details are omitted here.

[0025] Example 4. This example proposes a computer-readable storage medium on which an erasable and rewritable computer program is stored; When the computer program runs on the computer device, it causes the computer device to perform the aforementioned method for monitoring the stress of concrete formwork based on intelligent sensors.

[0026] For example, computer-readable storage media can be read-only memory (ROM), random access memory (RAM), compact disc read-only memory (CD-ROM), magnetic tape, floppy disk, and optical data storage devices.

[0027] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0028] It should be understood that determining B based on A does not mean determining B solely based on A; it also means determining B based on A and / or other information.

[0029] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the flow or function according to the embodiments of the present invention is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired network and / or wireless network. A computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. Available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. Semiconductor media can be solid-state drives (SSDs).

[0030] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0031] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0032] In the several embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only one method, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0033] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0034] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0035] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0036] The foregoing has shown and described 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 to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A method for monitoring stress in concrete formwork based on intelligent sensors, characterized in that, The method includes: Collect environmental data from the concrete pouring site, establish a coupled dynamics model of the concrete environment, and output the correction value of the formwork side pressure. Collect the working condition data of the template and import the working condition data of the template into the random vibration response coupling model to generate a spatiotemporal stress threat cloud map of the template in real time; Real-time monitoring of the hydration heat temperature field during concrete pouring process to obtain the chemical shrinkage strain generated during concrete pouring. The template comprehensive failure index is obtained based on the stress threat and chemical shrinkage strain in the spatiotemporal stress threat cloud map. At the same time, the time-varying failure probability is calculated, and a graded early warning is triggered by the template comprehensive failure index and the time-varying failure probability.

2. The method for monitoring concrete formwork stress based on intelligent sensors according to claim 1, characterized in that, Collect environmental data from the concrete pouring site, establish a coupled dynamic model of the concrete environment, and output the formwork lateral pressure function, including: S11: Collect raw environmental data from the concrete pouring site and perform noise reduction and normalization processing on the raw environmental data. The environmental data from the concrete pouring site includes: formwork resonance frequency. Air convection coefficient UV intensity values ​​and concrete bleeding data; S12: Establish a coupled dynamic model of the concrete environment, and output the foundation lateral pressure using the coupled dynamic model of the concrete environment. The concrete environment coupled dynamics model is specifically as follows: ； The density of concrete; The vector represents the concrete pouring speed; t represents time. The viscosity of concrete reflects its non-Newtonian properties. g is the acceleration due to gravity, which affects the static pressure distribution of concrete. The base is the lateral pressure; z is the spatial coordinate along the pouring direction.

3. The method for monitoring concrete formwork stress based on intelligent sensors according to claim 2, characterized in that, The process includes collecting environmental data from the concrete pouring site, establishing a coupled dynamics model of the concrete environment, outputting the formwork lateral pressure function, and also includes: S13: Correct the foundation lateral pressure output from the initial coupled dynamics model of the concrete environment using environmental data from the concrete pouring site that has undergone noise reduction and normalization. The corrected formwork lateral pressure value is then output, specifically including: ； in, This is the correction value for the template side pressure. The base lateral pressure varies over time; Environmental correction factor; T is vertical temperature; UV is ultraviolet radiation intensity; The ambient wind speed at the concrete pouring site.

4. The method for monitoring concrete formwork stress based on intelligent sensors according to claim 3, characterized in that, Data on the working conditions of the template is collected and imported into a stochastic vibration response model to generate a stress threat cloud map of the template in real time, including: S21: Based on the formwork geometry parameters and concrete density, calculate the static stress on the formwork caused by its own weight and the static pressure of the concrete. ; ； in, These are the gravitational stresses of the template material itself; This is the ratio of the actual contact area between the concrete and the formwork to the total area of ​​the formwork. S22: Obtain the working condition data of the template, including: gust load, pump pipe pulse pressure and worker trampling position. Perform frequency domain analysis on the working condition data of the template, extract the stress components of each working condition dynamic source, and quantify the contribution of each working condition dynamic source through power spectral density to obtain the dynamic stress at different frequencies.

5. The method for monitoring concrete formwork stress based on intelligent sensors according to claim 4, characterized in that, The system collects working condition data of the template and imports this data into a random vibration response model to generate a stress threat cloud map of the template in real time. It also includes: S23: Based on S21 and S22, the static stress and dynamic stress of each frequency band are imported into the stochastic vibration response coupling model to generate a spatiotemporal stress threat cloud map of the template in real time, specifically: ； in, The stress threat to the template; is the proportional weight of the dynamic source for the e-th operating condition; i is the frequency segment, and I is the total number of frequency segments analyzed.

6. The method for monitoring concrete formwork stress based on intelligent sensors according to claim 5, characterized in that, Real-time monitoring of the hydration heat temperature field during concrete pouring to obtain the chemical shrinkage strain during formwork pouring. The calculation of the chemical shrinkage strain is as follows: ； in: For chemical contraction strain, The chemical shrinkage coefficient of concrete; The rate of temperature change in the hydration heat temperature field.

7. The method for monitoring concrete formwork stress based on intelligent sensors according to claim 6, characterized in that, The comprehensive failure index The specific calculation strategy is as follows: ； in, This represents the maximum stress that the template can withstand. This represents the ultimate shrinkage strain of the concrete.

8. The method for monitoring concrete formwork stress based on intelligent sensors according to claim 7, characterized in that, The time-varying failure probability The calculation strategy is as follows: ； The stress threat borne by the template at time t; This indicates the cumulative damage to the formwork during the on-site pouring process; m is the Weibull shape parameter, reflecting the rate of material damage accumulation.

9. A method for monitoring concrete formwork stress based on intelligent sensors according to claim 8, characterized in that, A tiered early warning system is triggered based on the template-based comprehensive failure index and time-varying failure probability, specifically including: when If the value is less than 1, no risk warning will be triggered, and concrete pouring will continue. when When the value is ≥1, an orange risk warning is triggered, the concrete pouring speed is reduced, the load is reduced, and reinforcement is carried out. Time-varying failure probability When the value is greater than 0.95, a red risk warning is triggered, work is forced to stop, and the template is replaced.

10. A concrete formwork stress monitoring system based on intelligent sensors, used to implement the concrete formwork stress monitoring method based on intelligent sensors as described in any one of claims 1-9, characterized in that, The system includes: Lateral pressure fitting module, spatiotemporal stress quantification module, contraction strain quantification module, and template failure detection module; The side pressure fitting module is used to collect environmental data at the concrete pouring site, establish a coupled dynamic model of the concrete environment, and output the template side pressure correction value. The spatiotemporal stress quantification module is used to collect the working condition data of the template and import the working condition data of the template into the random vibration response coupling model to generate a spatiotemporal stress threat cloud map of the template in real time. The shrinkage strain quantification module is used to monitor the hydration heat temperature field in real time during the concrete pouring process and obtain the chemical shrinkage strain generated during the concrete pouring process. The template failure detection module obtains the template comprehensive failure index based on the stress threat and chemical shrinkage strain in the spatiotemporal stress threat cloud map, and calculates the time-varying failure probability. It then triggers a graded early warning based on the template comprehensive failure index and the time-varying failure probability.

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