High-strength steel formwork stress distribution real-time monitoring system and method

Abstract

The invention relates to the technical field of stress monitoring, and discloses a high-strength steel formwork stress distribution real-time monitoring system and method, and the method comprises the steps: synchronously collecting the stress value of each position of a high-strength steel formwork through a sensor array, and constructing a stress distribution matrix of the high-strength steel formwork; based on the stress distribution matrix, identifying a stress transmission area of a stress wave; based on the stress transfer area, reconstructing a propagation path of stress waves; based on the propagation path, calculating the phase distortion degree when the stress wave passes through the splicing seam of the high-strength steel template; and on the basis of the phase distortion degree, early warning is conducted on the splicing seam stripping risk of the high-strength steel formwork. According to the method, the accuracy of real-time monitoring of stress distribution of the high-strength steel formwork is improved, and the stripping risk of the splicing seam of the high-strength steel formwork can be effectively pre-warned.

Description

Technical Field

[0001] The present invention relates to the technical field of stress monitoring, and particularly to a real-time monitoring system and method for stress distribution of high-strength steel formwork. Background Art

[0002] As the core support system for large cast-in-place concrete structures, high-strength steel formwork is widely used in projects such as bridges and high-rise buildings. It has been facing the following core challenges for a long time: there are stress mutations in the joint areas formed by splicing multiple steel plates, which are prone to cause local cracking and even structural failure. Currently, there are various means for stress monitoring of high-strength steel formwork. Some projects adopt the traditional strain gauge monitoring method, by pasting strain gauges at key parts of the formwork and converting stress changes into electrical signals for collection and analysis. Others use fiber Bragg grating sensors to sense stress conditions through changes in optical signals. These technologies can achieve stress monitoring to a certain extent, but in the actual application process, deficiencies are still exposed.

[0003] Regarding key issues such as the reconstruction of the propagation path of stress waves in high-strength steel formwork and the calculation of phase distortion at the splicing joint, the existing technologies lack effective solutions. In actual engineering, accurately grasping the stress wave propagation path is crucial for deeply understanding the structural stress state and evaluating structural integrity. However, the current monitoring systems are difficult to accurately record the stress wave propagation path. Similarly, at the splicing joint, due to the complexity of the splicing process of high-strength steel formwork and the influence of external environmental factors, the stress state at the splicing joint is complex. The existing technologies are difficult to accurately and timely detect the possible peeling risks at the splicing joint.

[0004] For example, Chinese patent application with publication number CN117129129A discloses an on-line dynamic monitoring device and on-line monitoring method for residual stress. Among them, the on-line monitoring device includes a conveying roller table, a monitoring frame erected above the conveying roller table, and a stress monitoring device installed on the monitoring frame for monitoring the residual stress of the steel plate to be measured; the stress monitoring device includes a moving component, a monitoring probe, and a laser irradiation head installed on the monitoring frame; the distance between the monitoring probe and the steel plate to be measured is 10 - 100 mm; the laser irradiation head is inclined and arranged on the side wall of the monitoring probe, the inclination direction of the laser irradiation head is the side where the monitoring probe and the laser irradiation head approach each other, and the inclination angle of the laser irradiation head is the included angle with the vertical direction of 0° - 75°. The on-line monitoring device of this invention has a simple structure, high monitoring efficiency and high precision, can monitor the residual stress of the overall steel plate, ensure accurate stress monitoring, and improve monitoring efficiency.

[0005] The Chinese patent application with the publication number CN118032184A discloses a method for monitoring the stress of formwork during on-site concrete pouring. The invention is realized through four steps: real-time monitoring of formwork stress, data acquisition, alarm and early warning, and concrete pouring. By setting stress sensors on the formwork, the invention can monitor the stress change of the formwork in real time, providing timely and accurate data support for on-site construction. When the formwork stress exceeds the preset safety threshold, the data processing center will immediately send out a warning signal to notify the on-site construction personnel to take corresponding measures, effectively preventing the occurrence of dangerous situations. Multiple types of sensors such as resistance strain sensors, displacement sensors, manganese copper piezoresistive sensors or formwork stress sensors are used to adapt to the needs of different scenarios and improve the applicability of the monitoring method.

[0006] All of the above prior arts have the problems raised in this background art: it is difficult to accurately and timely detect the possible peeling risk.

[0007] The information disclosed in this background art section is only intended to increase the understanding of the overall background of the present invention, and should not be regarded as an admission or any form of implication that this information constitutes the prior art known to those of ordinary skill in the art. Summary of the Invention

[0008] The technical problem to be solved by the present invention is to overcome the defects of the prior art, provide a real-time monitoring system and method for the stress distribution of high-strength steel formwork, improve the accuracy of real-time monitoring of the stress distribution of high-strength steel formwork, and effectively warn of the peeling risk of the joints of high-strength steel formwork.

[0009] To solve the above technical problems, the present invention provides the following technical solutions:

[0010] On the one hand, the present invention provides a method for real-time monitoring of the stress distribution of high-strength steel formwork, including the following steps:

[0011] Synchronously collect the stress values at each position of the high-strength steel formwork through a sensor array, and construct a stress distribution matrix of the high-strength steel formwork;

[0012] Based on the stress distribution matrix, identify the stress transmission region of the stress wave;

[0013] Based on the stress transmission region, reconstruct the propagation path of the stress wave;

[0014] Based on the propagation path, calculate the phase distortion degree when the stress wave passes through the joint of the high-strength steel formwork;

[0015] Based on the phase distortion degree, give an early warning of the peeling risk of the joint of the high-strength steel formwork.

[0016] As a preferred embodiment of the real-time monitoring method for stress distribution of the high-strength steel formwork according to the present invention, it includes: based on the stress distribution matrix, identifying the stress transmission region of the stress wave, specifically including:

[0017] S100: Calculate the conjugate transpose matrix of the stress distribution matrix;

[0018] S200: Calculate the covariance matrix of the stress distribution matrix and its conjugate transpose matrix;

[0019] S300: Perform eigenvalue decomposition on the covariance matrix to obtain the eigenvalues and eigenvectors of the covariance matrix;

[0020] S400: Based on the eigenvalues and eigenvectors of the covariance matrix, use the multiple signal classification algorithm to calculate the spatial spectrum of the stress wave;

[0021] S500: Perform peak detection on the spatial spectrum of the stress wave to obtain the stress transmission region.

[0022] As a preferred embodiment of the real-time monitoring method for stress distribution of the high-strength steel formwork according to the present invention, it includes: the stress distribution matrix is a matrix with N rows and T columns; N is the number of sensors in the sensor array, and T is the number of sampling points of any sensor; any row of the stress distribution matrix corresponds to the stress values collected by the same sensor at each moment, and any column corresponds to the stress values collected by each sensor at the same moment;

[0023] The covariance matrix is a matrix with N rows and N columns, which is used to describe the correlation between the signals collected by different sensors in the sensor array;

[0024] The spatial spectrum of the stress wave is used to describe the energy intensity of the stress wave in each direction of the high-strength steel formwork and is used to locate the propagation direction of the stress wave; in the spatial spectrum, the energy intensity of the stress wave in the direction corresponding to the angle is denoted as ; any angle is used to describe the direction of the stress wave relative to the sensor array.

[0025] As a preferred embodiment of the real-time monitoring method for stress distribution of the high-strength steel formwork according to the present invention, it includes: performing peak detection on the spatial spectrum of the stress wave to obtain the stress transmission region; specifically including:

[0026] Set the energy intensity threshold; read the energy intensity in the direction corresponding to each angle in the spatial spectrum of the stress wave;

[0027] Mark all directions with energy intensity greater than the energy intensity threshold as stress transmission directions;

[0028] Determine the stress transfer region based on the stress transfer direction; the stress transfer region is the region composed of sensors included in all stress transfer directions.

[0029] As a preferred embodiment of the real-time monitoring method for stress distribution of the high-strength steel formwork of the present invention, wherein: based on the stress transfer region, reconstruct the propagation path of stress waves, specifically including:

[0030] Record adjacent sensor pairs composed of any two adjacent sensors in the stress transfer region;

[0031] Read the sensing signals of the sensors included in each adjacent sensor pair based on the stress distribution matrix;

[0032] Calculate the stress wave time difference of each adjacent sensor pair; the stress wave time difference is the time difference between the stress wave propagating to the two sensors included in the adjacent sensor pair;

[0033] Calculate the stress wave path difference of each adjacent sensor pair based on the stress wave time difference of each adjacent sensor pair; the stress wave path difference is the distance that the stress wave propagates between the two sensors;

[0034] Establish a coordinate system and record the coordinates of each sensor in the sensor array in the coordinate system;

[0035] Based on the stress wave path difference of each adjacent sensor pair in the stress transfer region and the coordinates of the sensors in the coordinate system, fit the propagation path equation of the stress wave to obtain the propagation path of the stress wave.

[0036] As a preferred embodiment of the real-time monitoring method for stress distribution of the high-strength steel formwork of the present invention, wherein: the method for calculating the stress wave time difference of each adjacent sensor pair is as follows:

[0037] Calculate the generalized cross-correlation coefficient of the sensing signals of the sensors included in each adjacent sensor pair at different time delays; if the maximum value of the generalized cross-correlation coefficient at different time delays is greater than a preset correlation threshold, the time delay corresponding to the maximum value of the generalized cross-correlation coefficient is the stress wave time difference of the adjacent sensor pair.

[0038] As a preferred embodiment of the real-time monitoring method for stress distribution of the high-strength steel formwork of the present invention, wherein: the phase distortion degree is the phase difference between before and after the stress wave passes through the splicing joint; the calculation of the phase distortion degree when the stress wave passes through the splicing joint of the high-strength steel formwork specifically includes:

[0039] Calculate the trajectory equation of any splicing joint in the coordinate system;

[0040] Based on the trajectory equation of the splicing seam and the propagation path of the stress wave, determine whether the stress wave passes through the splicing seam; if the stress wave passes through any splicing seam, calculate the phase distortion degree when the stress wave passes through the splicing seam.

[0041] As a preferred solution of the real-time monitoring method for the stress distribution of the high-strength steel formwork of the present invention, wherein: calculating the phase distortion degree when the stress wave passes through the splicing seam of the high-strength steel formwork further includes:

[0042] Extract the sensing signals of the two sensors included in the adjacent sensor pair corresponding to when the stress wave passes through the splicing seam, and record them as and ;

[0043] Perform band-pass filtering on and , and decompose and into component signals in m frequency bands;

[0044] Perform Hilbert transform on the component signals in the corresponding frequency bands of and respectively to obtain the phases of the component signals in the corresponding frequency bands;

[0045] Calculate the phase difference between the component signals in the corresponding frequency bands of and to obtain the phase distortion degree in the corresponding frequency band.

[0046] As a preferred solution of the real-time monitoring method for the stress distribution of the high-strength steel formwork of the present invention, wherein: based on the phase distortion degree, give an early warning of the peeling risk of the splicing seam of the high-strength steel formwork, specifically including:

[0047] Conduct a stress wave cross-seam experiment on the high-strength steel formwork; record the phase difference data of the stress wave before and after passing through the splicing seam of the high-strength steel formwork in each frequency band; based on the phase difference data, set the phase difference threshold interval for each frequency band;

[0048] If the phase distortion degree in each frequency band is within the phase difference threshold interval corresponding to the frequency band, there is no peeling risk for the splicing seam of the high-strength steel formwork; otherwise, there is a peeling risk for the splicing seam of the high-strength steel formwork, and send a peeling risk warning message.

[0049] In a second aspect, the present invention provides a real-time monitoring system for the stress distribution of a high-strength steel formwork, including a data acquisition module, a data processing module, a stress analysis module, a path reconstruction module, a phase calculation module, and a risk warning module; wherein:

[0050] The data acquisition module synchronously acquires the stress values at each position of the high-strength steel formwork through a sensor array;

[0051] The data processing module is used to construct a stress distribution matrix of the high-strength steel formwork;

[0052] The stress analysis module identifies the stress transmission region of the stress wave based on the stress distribution matrix;

[0053] The path reconstruction module reconstructs the propagation path of the stress wave based on the sensing signals of the sensors in the stress transmission region;

[0054] The phase calculation module is used to determine whether the stress wave passes through the splicing joint; if it passes through, the sensing signals of the corresponding adjacent sensor pairs are extracted, and the phase distortion degree when the stress wave passes through the splicing joint in different frequency bands is calculated;

[0055] The risk warning module warns of the risk of peeling at the splicing joint of the high-strength steel formwork based on the phase distortion degree of the stress wave in each frequency band.

[0056] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0057] This application can accurately locate the propagation direction of the stress wave, determine the stress transmission region, and accurately reconstruct the propagation path of the stress wave in the high-strength steel formwork, providing strong support for in-depth understanding of the stress distribution of the high-strength steel formwork. Through operations such as band-pass filtering and Hilbert transform, the phase distortion degree of the corresponding frequency band is calculated, and the phase change situation when the stress wave passes through the splicing joint can be accurately obtained.

[0058] This application warns of the risk of peeling at the splicing joint of the high-strength steel formwork according to the comparison result between the phase distortion degree and the threshold interval. Through multi-frequency band analysis, the peeling characteristics at different depths and ranges are comprehensively captured, avoiding the limitations of single-frequency band analysis, improving the accuracy and reliability of the criterion, timely discovering potential safety hazards, and ensuring the safe use of the high-strength steel formwork. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for description in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts. Among them:

[0060] Figure 1 is a flowchart of a method for real-time monitoring of the stress distribution of a high-strength steel formwork provided by the present invention;

[0061] Figure 2 is a structural schematic diagram of a system for real-time monitoring of the stress distribution of a high-strength steel formwork provided by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0062] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations on the technical solution of the present invention. Without conflict, the technical features in the embodiments of the present invention and the embodiments can be combined with each other.

[0063] Embodiment 1:

[0064] This embodiment introduces a method for real-time monitoring of the stress distribution of high-strength steel formwork. Referring to Figure 1 , the method includes the following steps:

[0065] Synchronously collect the stress values at each position of the high-strength steel formwork through a sensor array, and construct a stress distribution matrix of the high-strength steel formwork;

[0066] The stress distribution matrix is a matrix with N rows and T columns; N is the number of sensors in the sensor array, and T is the number of sampling points of any sensor; any row of the stress distribution matrix corresponds to the stress values collected by the same sensor at each moment, and any column corresponds to the stress values collected by each sensor at the same moment.

[0067] Preferably, filter and denoise the stress distribution matrix; for example, independently filter the signals collected by each sensor through a Butterworth band-pass filter to eliminate noise interference.

[0068] Based on the stress distribution matrix, identify the stress transmission region of the stress wave; specifically including:

[0069] S100: Calculate the conjugate transpose matrix of the stress distribution matrix;

[0070] S200: Calculate the covariance matrix of the stress distribution matrix and its conjugate transpose matrix;

[0071] The covariance matrix is a matrix with N rows and N columns, which is used to describe the correlation between the signals (i.e., stress values) collected by different sensors in the sensor array. The diagonal elements in the covariance matrix are the variances of the signals collected by the corresponding sensors, and the non-diagonal elements represent the covariance between the signals collected by the corresponding two sensors. The magnitude of the covariance represents the magnitude of the correlation between the corresponding two signals.

[0072] S300: Perform eigenvalue decomposition on the covariance matrix to obtain the eigenvalues and eigenvectors of the covariance matrix;

[0073] Solve the characteristic equation by numerical calculation tools such as MATLAB, perform eigenvalue decomposition on the covariance matrix to obtain multiple sets of eigenvalues and the corresponding eigenvectors; sort the eigenvalues in descending order; divide the eigenvectors of the covariance matrix into the signal subspace and the noise subspace according to the magnitudes of the corresponding eigenvalues, specifically including: dividing the eigenvectors corresponding to the eigenvalues less than the preset eigenvalue threshold into the noise subspace and constructing the noise subspace matrix.

[0074] S400: Calculate the spatial spectrum of the stress wave by using the multiple signal classification algorithm based on the eigenvalues and eigenvectors of the covariance matrix;

[0075] The spatial spectrum of the stress wave is used to describe the energy intensity of the stress wave in each direction of the high-strength steel formwork and is used to locate the propagation direction of the stress wave; in the spatial spectrum, the energy intensity of the stress wave in the direction corresponding to the angle is denoted as ; any angle is used to describe the direction of the stress wave relative to the sensor array. In this embodiment, preferably, the geometric center of the sensor array is used as the reference, a direction in the plane of the sensor array is selected as the reference direction and marked as 0°, and the angle sizes of any angles are defined clockwise or counterclockwise. For example, for a linearly uniformly distributed sensor array, with the normal direction as the reference direction, 90° represents the right direction of the array, and -90° represents the left direction of the array.

[0076] The spatial spectrum of the stress wave is calculated by using the multiple signal classification algorithm by constructing the array steering vector. represents the array steering vector corresponding to the angle , corresponding to . The multiple signal classification algorithm calculates the spatial spectrum of the stress wave based on the orthogonality relationship between the array steering vector and the noise subspace matrix. The value of is related to the orthogonality between the array steering vector and the noise subspace matrix. If is completely orthogonal to the noise subspace matrix, then the value of is larger, indicating a higher probability of the existence of a stress wave in the direction corresponding to the angle ; conversely, if is not orthogonal to the noise subspace matrix, then the value of is smaller, indicating a lower probability of the existence of a stress wave in the direction corresponding to the angle . In the spatial spectrum of the stress wave, obvious peaks appear in the directions where the stress wave exists.

[0077] S500: Perform peak detection on the spatial spectrum of the stress wave to obtain the stress transmission region; specifically including:

[0078] Set an energy intensity threshold; read the energy intensity in the direction corresponding to each angle in the spatial spectrum of the stress wave;

[0079] Mark all directions with energy intensity greater than the energy intensity threshold as stress transmission directions;

[0080] Based on the stress transmission directions, determine the stress transmission region; the stress transmission region is the region composed of sensors included in all stress transmission directions.

[0081] The fluctuations in the stress values collected by sensors in the direction with energy intensity greater than the energy intensity threshold are caused by the transmission of stress waves, while the fluctuations in the stress values collected by sensors in the direction with energy intensity not greater than the energy intensity threshold are caused by noise. By determining the stress transmission region, only the signals within this angular range are processed in the subsequent propagation path reconstruction, ignoring the sensors irrelevant to the stress wave direction, reducing the computational amount, and at the same time ensuring that the path reconstruction is based on effective signals, thereby improving the path reconstruction accuracy of the stress wave.

[0082] Based on the stress transmission region, reconstruct the propagation path of the stress wave; specifically including:

[0083] Record adjacent sensor pairs composed of any two adjacent sensors in the stress transmission region;

[0084] Based on the stress distribution matrix, read the sensing signals of the sensors included in each group of adjacent sensor pairs; the sensing signal is the time series of the stress values collected by the corresponding sensors, that is, the corresponding row of the corresponding sensors in the stress distribution matrix.

[0085] Calculate the stress wave time difference of each group of adjacent sensor pairs; the stress wave time difference is the time difference between the stress wave propagating to the two sensors included in the adjacent sensor pair; the method for calculating the stress wave time difference of each group of adjacent sensor pairs is as follows:

[0086] Calculate the generalized cross-correlation coefficient of the sensing signals of the sensors included in each group of adjacent sensor pairs at different time delay amounts; if the maximum value of the generalized cross-correlation coefficient at different time delay amounts is greater than a preset correlation threshold, then the time delay amount corresponding to the maximum value of the generalized cross-correlation coefficient is the stress wave time difference of the adjacent sensor pair. The generalized cross-correlation coefficient (GCC-PHAT) is used to measure the correlation between two time signals at different time delay amounts. The maximum value of the generalized cross-correlation coefficient corresponds to the time delay amount when the two time signals are most correlated.

[0087] Based on the time difference of stress waves between each pair of adjacent sensors, calculate the path difference of stress waves for each pair of adjacent sensors; the path difference of stress waves is the distance that stress waves propagate between two sensors; multiply the time difference of stress waves by the pre-calibrated wave speed to obtain the path difference of stress waves; for example, typical wave speeds in high-strength steel include: the wave speed of compression waves is 5900 m / s, and the wave speed of shear waves is 3200 m / s, etc.

[0088] Establish a coordinate system and record the coordinates of each sensor in the sensor array in the coordinate system;

[0089] Based on the path difference of stress waves for each pair of adjacent sensors in the stress transmission area and the coordinates of the sensors in the coordinate system, fit the propagation path equation of stress waves to obtain the propagation path of stress waves.

[0090] This application preferably uses the least squares method for function fitting; mark the coordinates of the sensors included in the pair of adjacent sensors with the maximum value of the generalized cross-correlation coefficient greater than the preset correlation threshold as the known coordinate points on the propagation path of stress waves, and fit the complete propagation path of stress waves in combination with the path difference of stress waves for each pair of adjacent sensors.

[0091] Based on the propagation path, calculate the phase distortion degree when stress waves pass through the splicing seam of the high-strength steel formwork;

[0092] The phase distortion degree is the phase difference between before and after stress waves pass through the splicing seam; calculating the phase distortion degree when stress waves pass through the splicing seam of the high-strength steel formwork specifically includes:

[0093] Calculate the trajectory equation of any splicing seam in the coordinate system; the splicing seam is usually a regular curve or straight line, and its trajectory can be described by an equation in the coordinate system.

[0094] Based on the trajectory equation of the splicing seam and the propagation path of the stress waves, determine whether the stress waves pass through the splicing seam; judge whether the propagation path intersects with the splicing seam through the propagation path equation of the stress waves and the trajectory equation of the splicing seam. If they intersect, the stress waves pass through the splicing seam.

[0095] If the stress waves pass through any splicing seam, calculate the phase distortion degree when the stress waves pass through the splicing seam; specifically including:

[0096] Extract the sensing signals of the two sensors included in the pair of adjacent sensors corresponding to when the stress waves pass through the splicing seam, and record them as and ; the pair of adjacent sensors corresponding to when the stress waves pass through the splicing seam are the two adjacent sensors that the stress waves pass through before and after passing through the splicing seam. For example, calculate the intersection coordinates of the propagation path and the splicing seam; based on the intersection coordinates, find two adjacent sensors on the propagation path that are the closest to the intersection and on both sides of the splicing seam.

[0097] For and perform band - pass filtering to decompose and into component signals in m frequency bands; m is a positive integer;

[0098] Respectively perform Hilbert transform on the component signals in the corresponding frequency bands of and to obtain the phases of the component signals in the corresponding frequency bands;

[0099] Calculate and the difference in the phases of the component signals in the corresponding frequency bands to obtain the phase distortion degree in the corresponding frequency band.

[0100] Based on the phase distortion degree, give an early warning of the risk of the splicing seam peeling of the high - strength steel formwork. Specifically, it includes:

[0101] Conduct a stress - wave cross - seam experiment on the high - strength steel formwork; record the phase - difference data of the stress wave passing through the splicing seam of the high - strength steel formwork before and after passing through the splicing seam for each frequency band; based on the phase - difference data, set the phase - difference threshold interval for each frequency band;

[0102] If the phase distortion degree of each frequency band is within the phase - difference threshold interval of the corresponding frequency band, there is no risk of the splicing seam of the high - strength steel formwork peeling; otherwise, there is a risk of the splicing seam of the high - strength steel formwork peeling, and send a peeling - risk warning message.

[0103] The preferred way to set the phase - difference threshold interval for each frequency band in this embodiment is as follows:

[0104] Conduct multiple experiments on healthy high - strength steel formworks and record the phase - difference data of the stress wave crossing the splicing seam for each frequency band. For example, for the stress wave in the frequency band of 4.5 kHz to 5.5 kHz, the mean value of the phase difference of the stress wave crossing the splicing seam in multiple experiments is denoted as and the variance is denoted as . Then the phase - difference threshold interval for the frequency band of 4.5 kHz to 5.5 kHz is .

[0105] When stress waves propagate in high-strength steel formwork, their phase characteristics change due to variations in the interface contact state. When the splicing joint is in a healthy state, the interface contact is good, and the phase difference of the stress wave after passing through the splicing joint is small and stable. However, when there is delamination in the splicing joint, the interface contact is poor, and the phase difference of the stress wave after passing through the splicing joint increases significantly. This change in the phase difference reflects the interface state of the splicing joint and provides a direct basis for identifying delamination risks. Multi-band analysis can comprehensively capture delamination characteristics at different depths and ranges. Low-frequency waves have strong penetration and are sensitive to deep delamination; high-frequency waves have high resolution and are sensitive to near-surface delamination. By analyzing the phase difference data of multiple bands, the health state of the splicing joint can be more comprehensively evaluated, avoiding the limitations of single-band analysis, thereby improving the accuracy and reliability of the criterion.

[0106] Embodiment 2:

[0107] This embodiment is the second embodiment of the present invention; based on the same inventive concept as Embodiment 1, referring to Figure 2 , this embodiment introduces a real-time monitoring system for stress distribution of high-strength steel formwork, including a data acquisition module, a data processing module, a stress analysis module, a path reconstruction module, a phase calculation module, and a risk warning module; where:

[0108] The data acquisition module synchronously acquires the stress values at each position of the high-strength steel formwork through a sensor array; providing a data basis for subsequent construction of a stress distribution matrix.

[0109] The data processing module is used to construct the stress distribution matrix of the high-strength steel formwork; organizing the acquired stress values into a standard matrix form for subsequent analysis; and at the same time, filtering and denoising the stress distribution matrix, for example, using a Butterworth band-pass filter to independently filter the signals collected by each sensor to remove noise interference and improve data quality.

[0110] The stress analysis module identifies the stress transmission region of the stress wave based on the stress distribution matrix; this module calculates the covariance matrix based on the stress distribution matrix and its conjugate transpose matrix, and performs eigenvalue decomposition on the covariance matrix to obtain eigenvalues and eigenvectors, and constructs a noise subspace; based on the above results, the multiple signal classification algorithm is used to calculate the spatial spectrum of the stress wave, describing the energy intensity of the stress wave in each direction of the high-strength steel formwork; performing peak detection on the spatial spectrum of the stress wave to determine the stress transmission region, clarifying the effective signal range for subsequent processing, reducing the calculation amount and improving the accuracy.

[0111] The path reconstruction module reconstructs the propagation path of the stress wave based on the sensing signals of the sensors in the stress transmission region; this module calculates the time difference and path difference of the stress wave between each pair of adjacent sensors, and based on the path difference of the stress wave and the sensor coordinates, uses the least squares method to fit the propagation path of the stress wave.

[0112] The phase calculation module is used to determine whether the stress wave passes through the splicing joint; if it passes through, the sensing signals of the corresponding adjacent sensor pairs are extracted, and the phase distortion degree of the stress wave passing through the splicing joint in different frequency bands is calculated.

[0113] The risk warning module warns of the risk of peeling of the splicing joint of the high-strength steel formwork based on the phase distortion degree of the stress wave in each frequency band. This module is configured with a phase difference threshold interval for the stress wave in each frequency band; according to the comparison result of the phase distortion degree calculated in real time in each frequency band with the corresponding phase difference threshold interval, the risk of peeling of the splicing joint of the high-strength steel formwork is warned, and if the phase distortion degree exceeds the threshold interval, a peeling risk warning message is sent.

[0114] The specific function implementation of each of the above modules refers to the relevant content in a method for real-time monitoring of the stress distribution of high-strength steel formwork in Embodiment 1, and will not be elaborated here.

[0115] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0116] The embodiments of the present invention have been described above in conjunction with the accompanying drawings. However, the present invention is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of the present invention, those of ordinary skill in the art can also make many forms without departing from the spirit and scope of the present invention, and these all fall within the protection scope of the present invention.

Claims

1. A real-time monitoring method for the stress distribution of high-strength steel formwork, characterized in that: It includes the following steps: Synchronously collect the stress values at each position of the high-strength steel formwork through a sensor array, and construct a stress distribution matrix of the high-strength steel formwork; Based on the stress distribution matrix, identify the stress transmission region of the stress wave; Calculate the stress wave path difference in different sensors; based on the stress wave path difference, reconstruct the propagation path of the stress wave in the stress transmission region; Based on the propagation path, calculate the phase distortion degree when the stress wave passes through the splicing seam of the high-strength steel formwork; Based on the phase distortion degree, give an early warning of the peeling risk of the splicing seam of the high-strength steel formwork.

2. The real-time monitoring method for stress distribution of high-strength steel formwork according to claim 1, characterized in that: Based on the stress distribution matrix, identifying the stress transmission region of the stress wave specifically includes: S100: Calculate the conjugate transpose matrix of the stress distribution matrix; S200: Calculate the covariance matrix of the stress distribution matrix and its conjugate transpose matrix; S300: Perform eigenvalue decomposition on the covariance matrix to obtain the eigenvalues and eigenvectors of the covariance matrix; S400: Based on the eigenvalues and eigenvectors of the covariance matrix, use the multiple signal classification algorithm to calculate the spatial spectrum of the stress wave; S500: Perform peak detection on the spatial spectrum of the stress wave to obtain the stress transmission region.

3. The real-time monitoring method for stress distribution of high-strength steel formwork according to claim 2, characterized in that: The stress distribution matrix is a matrix with N rows and T columns; N is the number of sensors in the sensor array, and T is the number of sampling points of any sensor; Any row of the stress distribution matrix corresponds to the stress values collected by the same sensor at each moment, and any column corresponds to the stress values collected by each sensor at the same moment; The covariance matrix is a matrix with N rows and N columns, which is used to describe the correlation between the signals collected by different sensors in the sensor array; The spatial spectrum of the stress wave is used to describe the energy intensity of the stress wave in each direction of the high-strength steel formwork and to locate the propagation direction of the stress wave; in the spatial spectrum, the energy intensity of the stress wave in the direction corresponding to the angle is denoted as ; any angle is used to describe the direction of the stress wave relative to the sensor array.

4. The real-time monitoring method for the stress distribution of the high-strength steel formwork according to claim 3, characterized in that: Performing peak detection on the spatial spectrum of the stress wave to obtain the stress transmission region; specifically includes: Set the energy intensity threshold; read the energy intensity in the direction corresponding to each angle in the spatial spectrum of the stress wave; Mark all directions with energy intensity greater than the energy intensity threshold as stress transmission directions; Based on the stress transmission directions, determine the stress transmission region; the stress transmission region is the region composed of the sensors included in all stress transmission directions.

5. The real-time monitoring method for stress distribution of high-strength steel formwork according to claim 4, characterized in that: The reconstruction of the propagation path of the stress wave specifically includes: Record the adjacent sensor pairs composed of any two adjacent sensors in the stress transmission region; Based on the stress distribution matrix, read the sensing signals of the sensors included in each group of adjacent sensor pairs; Calculate the stress wave time difference of each group of adjacent sensor pairs; the stress wave time difference is the time difference when the stress wave propagates to the two sensors included in the adjacent sensor pair; Based on the stress wave time difference of each group of adjacent sensor pairs, calculate the stress wave path difference of each group of adjacent sensor pairs; the stress wave path difference is the distance that the stress wave propagates between the two sensors; Establish a coordinate system and record the coordinates of each sensor in the sensor array in the coordinate system; Based on the stress wave path difference of each group of adjacent sensor pairs in the stress transmission region and the coordinates of the sensors in the coordinate system, fit the propagation path equation of the stress wave to obtain the propagation path of the stress wave.

6. The real-time monitoring method for stress distribution of high-strength steel formwork according to claim 5, characterized in that: The method for calculating the stress wave time difference of each group of adjacent sensor pairs is as follows: Calculate the generalized cross-correlation coefficients of the sensing signals of the sensors included in each group of adjacent sensor pairs at different time delay amounts; if the maximum value of the generalized cross-correlation coefficients at the different time delay amounts is greater than a preset correlation threshold, the time delay amount corresponding to the maximum value of the generalized cross-correlation coefficients is the stress wave time difference of the adjacent sensor pair.

7. The real-time monitoring method for stress distribution of high-strength steel formwork according to claim 6, characterized in that: The phase distortion degree is the phase difference before and after the stress wave passes through the splicing joint; Calculating the phase distortion degree when the stress wave passes through the splicing joint of the high-strength steel formwork specifically includes: Calculate the trajectory equation of any splicing joint in the coordinate system; Based on the trajectory equation of the splicing joint and the propagation path of the stress wave, determine whether the stress wave passes through the splicing joint; if the stress wave passes through any splicing joint, calculate the phase distortion degree when the stress wave passes through the splicing joint.

8. The real-time monitoring method for stress distribution of high-strength steel formwork according to claim 7, characterized in that: Calculating the phase distortion degree when the stress wave passes through the splicing joint of the high-strength steel formwork further includes: Extract the sensing signals of the two sensors included in the adjacent sensor pair corresponding to when the stress wave passes through the splicing joint, and record them as and ; Pair With Perform band-pass filtering to decompose And Into component signals in m frequency bands; Perform Hilbert transforms on the component signals in the corresponding frequency bands of and respectively to obtain the phases of the component signals in the corresponding frequency bands; Calculation and the phase difference of the component signals in the corresponding frequency band to obtain the phase distortion degree of the corresponding frequency band.

9. The real-time monitoring method for stress distribution of high-strength steel formwork according to claim 8, characterized in that: Based on the phase distortion degree, give an early warning of the peeling risk of the splicing joint of the high-strength steel formwork, specifically including: Conduct a stress wave cross-seam experiment on the high-strength steel formwork; record the phase difference data before and after the stress wave of each frequency band passes through the splicing joint of the high-strength steel formwork; based on the phase difference data, set the phase difference threshold interval for each frequency band; If the phase distortion degree of each frequency band is within the phase difference threshold interval corresponding to the frequency band, there is no peeling risk for the splicing joint of the high-strength steel formwork; otherwise, there is a peeling risk for the splicing joint of the high-strength steel formwork, and a peeling risk warning message is sent.

10. A real-time monitoring system for the stress distribution of high-strength steel formwork, which is used to implement the real-time monitoring method for the stress distribution of high-strength steel formwork as described in any one of claims 1-9, characterized in that: It includes a data acquisition module, a data processing module, a stress analysis module, a path reconstruction module, a phase calculation module, and a risk warning module; among them: The data acquisition module synchronously acquires the stress values at each position of the high-strength steel formwork through a sensor array; The data processing module is used to construct the stress distribution matrix of the high-strength steel formwork; The stress analysis module identifies the stress transmission area of the stress wave based on the stress distribution matrix; The path reconstruction module reconstructs the propagation path of the stress wave based on the sensing signals of the sensors in the stress transmission area; The phase calculation module is used to determine whether the stress wave passes through the splicing joint; if it passes through, extract the sensing signals of the corresponding adjacent sensor pairs and calculate the phase distortion degree when the stress wave of different frequency bands passes through the splicing joint; The risk warning module gives an early warning of the peeling risk of the splicing joint of the high-strength steel formwork based on the phase distortion degree of the stress wave of each frequency band.

Images