CN116879403A - Nondestructive testing method for steel bars and defects in concrete - Google Patents
Nondestructive testing method for steel bars and defects in concrete Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 81
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- 238000009659 non-destructive testing Methods 0.000 title claims abstract description 28
- 229910000831 Steel Inorganic materials 0.000 title claims abstract description 25
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- 238000003384 imaging method Methods 0.000 claims abstract description 31
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/04—Analysing solids
- G01N29/06—Visualisation of the interior, e.g. acoustic microscopy
- G01N29/0654—Imaging
- G01N29/069—Defect imaging, localisation and sizing using, e.g. time of flight diffraction [TOFD], synthetic aperture focusing technique [SAFT], Amplituden-Laufzeit-Ortskurven [ALOK] technique
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/44—Processing the detected response signal, e.g. electronic circuits specially adapted therefor
- G01N29/4409—Processing the detected response signal, e.g. electronic circuits specially adapted therefor by comparison
- G01N29/4418—Processing the detected response signal, e.g. electronic circuits specially adapted therefor by comparison with a model, e.g. best-fit, regression analysis
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2291/00—Indexing codes associated with group G01N29/00
- G01N2291/02—Indexing codes associated with the analysed material
- G01N2291/023—Solids
- G01N2291/0232—Glass, ceramics, concrete or stone
Abstract
The invention discloses a nondestructive testing method for reinforcing steel bars and defects in concrete, which comprises three subprograms of ultrasonic data acquisition, ultrasonic data inversion analysis and inversion transverse wave velocity value imaging; the ultrasonic data acquisition procedure comprises two steps of acquisition grid point division, ultrasonic signal transmission and acquisition; the ultrasonic data inversion analysis program comprises six steps of ultrasonic source prediction, initial model selection, forward modeling, objective function selection, optimization algorithm selection and prediction model updating; the inversion transverse wave speed value imaging program comprises three steps of transverse wave speed value three-dimensional imaging, rendering threshold analysis and image rendering. According to the invention, SH ultrasonic signal scanning is carried out on the reinforced concrete structure, the full waveform inversion method is utilized to accurately obtain the whole transverse wave velocity value of the reinforced concrete, the image construction of the internal structure is realized by means of the imaging and rendering method of the transverse wave velocity value, and based on the image construction, the internal steel bars and the defect space information can be intuitively and accurately observed.
Description
Technical Field
The invention relates to a nondestructive testing method, in particular to a nondestructive testing method for reinforcing steel bars and defects in concrete.
Background
In infrastructure construction, reinforced concrete is the largest-used engineering material, and plays an important role in various foundation projects. However, concrete itself is brittle and is susceptible to cracking during service due to environmental influences. The protective capability of the cracked concrete is rapidly reduced, so that the protective layer of the reinforcing steel bar is reduced or the internal reinforcing steel bar is directly exposed, and the corrosion rate of the reinforcing steel bar is greatly increased. Therefore, timely and effective detection of concrete defects and internal steel bar states is a key for ensuring the healthy service of engineering structures.
The development of the nondestructive reinforced concrete material performance detection method can furthest reduce the artificial degree of invasion to the material. The existing detection method of the internal defects of the concrete and the state of the steel bars is mostly focused on the abnormal signal data intensity, so that the degree of the internal defects in the concrete structure is distinguished, visual imaging observation is lacking, the spatial distribution state of the internal structure cannot be visually evaluated, and therefore, the key damage indexes of the internal defects and the accurate evaluation of the deterioration development trend are realized. The defect damage in the reinforced concrete structure has diversity, and the durability and the safety of the structure have larger influence difference. There is a need for a method that can accurately grasp the spatial distribution of defects within a reinforced concrete structure.
The shear wave velocity values of two materials of concrete and steel bar are obviously different, SH ultrasonic waves have higher sensitivity to the shear wave velocity values of a reinforced concrete structure, the inversion of the shear wave velocity values of the reinforced concrete can be realized by means of the SH ultrasonic waves, and the accurate imaging of the internal structure can be realized by establishing the functional relation between key damage indexes (type, size and space position) of the internal defects of the concrete and the shear wave velocity values of the reinforced concrete, so that the reinforcement spreading rule and the damage condition of the concrete can be intuitively evaluated.
Disclosure of Invention
The invention aims to: the invention aims to provide a nondestructive testing method capable of accurately identifying the internal steel bars and defects of the internal structure of a reinforced concrete structure.
The technical scheme is as follows: the invention relates to a nondestructive testing method for reinforcing steel bars and defects in concrete, which comprises the following three subprograms:
subroutine one: the ultrasonic data acquisition comprises two steps of data acquisition grid point division, ultrasonic signal transmission and acquisition;
subroutine II: the ultrasonic data inversion analysis comprises six steps of ultrasonic source signal prediction, inversion initial model selection, forward modeling analysis, objective function selection, optimization algorithm selection and prediction model updating;
and a third sub-program: the transverse wave speed value imaging comprises three steps of transverse wave speed value three-dimensional imaging, transverse wave speed rendering threshold analysis and image rendering.
Further, the data acquisition grid points are divided, the longitudinal spacing is 1-2 cm, the transverse spacing is 5-10 cm, and the higher the inversion accuracy is required, the smaller the grid point dividing spacing is; the ultrasonic waves are SH waves, and the number of ultrasonic probes is not less than 32.
Further, the ultrasonic source signal prediction method comprises green equation calculation and source signal prediction calculation, wherein the green equation calculation method comprises the following steps:
Green(f,x,V s )＝W(f,x,V s )/R(f)
wherein, f-the central frequency of ultrasonic wave is Hz when collecting data; x-calculating the position function of the grid points; v (V) s -a transverse wave velocity value of the calculated lattice point; green (f, x, V) s ) -calculating a wave field green's function; w (f, x, V) s ) -predicting the wave field; r (f) -rake wavelet signals;
the method for predicting and calculating the source signal in the frequency domain comprises the following steps:
Source est (f)＝w(f,x,V s )/Green(f,x,V s )
in the formula, f-is the ultrasonic test frequency when data is acquired, and the unit is Hz; x-calculating the position function of the grid points; v (V) s -a transverse wave velocity value of the calculated lattice point; source (Source) est (f) -calculating a source signal with a centre frequency f; w (f, x, V) s ) -predicting the wave field; green (f, x, V) s ) -calculating a wavelength green function.
Further, in the step of selecting the inversion initial model, the initial value of the transverse wave velocity model adopted in the inversion is determined according to the on-site real-time measurement of the ultrasonic probe.
Further, in the forward modeling analysis step, a time domain two-dimensional SH elastic wave equation is adopted to model the forward propagation process of SH waves in concrete:
wherein, the coordinates of the grid points in the x-forward model in the transverse direction, the coordinates of the grid points in the z-forward model in the longitudinal direction and the y-direction perpendicular to the xy plane; rho-density value of the lattice point in forward model, μ -shear modulus value of the lattice point in forward model; v y -velocity of shear transverse wave particles in y-direction, f y -source stress in a direction perpendicular to the xz plane;derivative of the shear stress in the xy plane over time, < >>Derivative of the shear stress in the yz plane over time,/->-derivative of shear transverse wave particle velocity in the y-direction over time; sigma (sigma) yx,x Derivative of the shear stress in the xy-plane in the transverse coordinate x, sigma yz,z Derivative of shear stress in the yz plane in the longitudinal coordinate z, v y,x Derivative of shear transverse wave particle velocity in the y-direction in transverse coordinate x, v y,z -derivative of shear transverse wave particle velocity in the y-direction on the longitudinal coordinate z;
the forward model adopts a mirror stress method on the boundary of the simulated concrete structure surface to simulate strong reflection waves generated by SH elastic waves on the concrete surface; on the remaining boundaries except the concrete structure surface, a perfect matching layer (Perfect Match Layers, PML) is used to absorb the boundary reflection waves.
Further, in the step of selecting the objective function, a least square method is selected as a model inversion objective function, and the calculation process is divided into wave field residual calculation and least square method calculation;
the wave field residual error calculation method comprises the following steps:
Δd s,r ＝D s,r (V s )-d s,r
in the formula, s is an ultrasonic source sensor serial number; r-signal receiving sensor number; v (V) s -medium shear wave velocity values; Δd s,r -wavefield residuals caused by differences in transverse wave velocity values; d (D) s,r (V s ) -predicting wave field data; d, d s,r -actual wave field data;
the least square method comprises the following steps:
wherein V is s -medium shear wave velocity values; e (V) s ) -a least squares value caused by the difference in transverse wave velocity values; Δd s,r -wavefield residuals caused by differences in transverse wave velocity values, T-matrix transpose calculation.
Further, in the optimization algorithm selection step, a gaussian-newton method is adopted to calculate the gradient direction (jacobian matrix) of the transverse wave velocity model, and the calculation method comprises the following steps:
in the method, in the process of the invention,from transverse wave velocity values V at source s and receiver sensor r s A calculated jacobian matrix; />From transverse wave velocity values V in a positive transmission field s A virtual source in the x-direction calculated; />From transverse wave velocity values V in a positive transmission field s Calculated wave field signal data in the x-direction; />From transverse wave velocity values V in a positive transmission field s A virtual source in the calculated z-direction; />From transverse wave velocity values V in a positive transmission field s Calculated wave field signal data in the z-direction.
Further, in the step of updating the prediction model, a shear wave velocity value model is updated by adopting a steepest gradient method, and the calculation method comprises the following steps:
in the formula, n-nth iterative inversion and n+1-n+1th iterative inversion are carried out; v (V) s -medium shear wave velocity values; v (V) s n+1 Transverse wave velocity value, V, of medium at n+1 iterative inversion s n -transverse wave velocity values of the medium at n iterative inversions; alpha n -updating the step size;updating gradient direction, P-Laplace matrix, I-unit matrix and t-matrix transposition calculation by using the transverse wave velocity value model; lambda (lambda) 1 -constant = 0.1, λ 2 -constant = 0.05; Δd s,r -wavefield residuals caused by differences in transverse wave velocity values.
Further, in the transverse wave speed value two-dimensional imaging step, a program is written by MATLAB software based on the transverse wave speed value obtained by inversion, so that numerical matrix imaging is realized.
Further, in the image rendering step, rendering processing is carried out on the image obtained in the step based on the inversion transverse wave speed numerical range, the concrete body is processed in a transparentizing mode, and the internal structure of the concrete is emphasized;
concrete transparent rendering transverse wave speed valueThe range selection method comprises the following steps:
in the method, in the process of the invention,-initial value of transverse wave velocity model, m/s; />Transparent rendering density value range in kg/m 3 ；
Rendering values of defects such as cracksThe range is not higher than 500m/s;
reinforcing steel bar reinforced rendering numerical valueThe range is not less than 3000m/s.
The beneficial effects are that: compared with the prior art, the invention has the following remarkable advantages: (1) The nondestructive testing method for the steel bars and the defects in the concrete is provided, and the problem that the internal transverse wave velocity value distribution cannot be provided in the current nondestructive testing field of the concrete is solved; (2) Based on the Gaussian-Newton optimization algorithm, compared with a conventional full waveform inversion method, the transverse wave velocity value distribution with higher accuracy can be provided, and further higher imaging accuracy is achieved; (3) The imaging method based on the transverse wave velocity value can accurately identify the internal structure of the concrete; (4) The reinforcement spreading rule in the concrete can be judged through the analysis of the matrix value of the inversion transverse wave velocity value; (5) The key damage parameters of the internal defects of the concrete, such as the geometrical characteristic parameters (width, length, shape and space position) of the internal cracks, can be displayed by rendering the image area with low inversion transverse wave velocity value; (6) The method has the advantages that the defect problem inside the concrete can be intuitively and clearly identified by staff in the non-professional technical field through accurate and intuitive rendering imaging effect; (7) The method has stable and clear inversion analysis steps based on the algorithm analysis of physical properties, is suitable for nondestructive testing and identification of the interior of various concrete structures, and has higher stability and applicability.
Drawings
FIG. 1 is a flow chart of a method for non-destructive inspection of steel bars and defects within concrete;
FIG. 2 is a schematic diagram of a two-dimensional cross-section of a horizontal crack detection within a concrete structure;
FIG. 3 is a graph of a density profile of horizontal cracks within a concrete imaged based on inverted shear wave velocity values;
fig. 4 is a schematic view of a two-dimensional cross section of a steel bar inspection in a concrete structure;
FIG. 5 is a graph of density distribution of concrete internal rebar imaged based on inverted shear wave velocity values;
FIG. 6 is a schematic diagram of a two-dimensional cross-section of a circular void detection within a concrete structure;
FIG. 7 is a graph of the density distribution of circular holes in the interior of concrete imaged based on inverted shear wave velocity values.
Detailed Description
The technical scheme of the invention is further described below with reference to the accompanying drawings.
As shown in fig. 1, the nondestructive testing method for the steel bars and defects in the concrete according to the present invention comprises three sub-procedures: subroutine one: ultrasonic data acquisition 1; subroutine II: inverting and analyzing the ultrasonic data 2; and a third sub-program: inversion transverse wave velocity value imaging 3.
The ultrasonic data acquisition program 1 comprises data acquisition grid point division 1-01 and signal transmission and acquisition 1-02. The data acquisition grid point division 1-01 is used for determining the data acquisition position so as to determine a single scanning inversion point, and an ultrasonic instrument is needed for signal emission and acquisition 1-02. The ultrasonic data inversion analysis program 2 comprises 2-01 of ultrasonic source signal prediction, 2-02 of inversion initial model selection, 2-03 of forward modeling analysis, 2-04 of objective function selection, 2-05 of optimization algorithm selection and 2-06 of prediction model update. The ultrasonic source signal prediction 2-01 is used for simulating a quasi-source signal adopted during inversion analysis, an inversion initial model is used for selecting an initial value which is required during inversion and is close to a detected concrete structure density value, forward modeling analysis 2-03 is used for generating predicted wave field data to be compared with actual wavelength data, an objective function is calculated, an optimization algorithm selects 2-05 to perform optimal calculation on the objective function by adopting a Gaussian-Newton optimization method, a gradient updating direction of a transverse wave velocity value model is obtained, and accordingly a model updating direction is provided for transverse wave velocity value model updating, and the transverse wave velocity value model updating is performed by combining calculated updating step length. The inversion transverse wave velocity value imaging program 3 comprises a transverse wave velocity value imaging method 3-01, a transverse wave velocity rendering threshold analysis 3-02 and a transverse wave velocity value distribution image rendering 3-03, wherein the transverse wave velocity value imaging method 3-01 uses MATLAB programming program to image a transverse wave velocity value matrix obtained by inversion, analyzes the transverse wave velocity value matrix according to physical value characteristics of internal structures of the concrete to obtain a transverse wave velocity rendering threshold, and performs rendering analysis on the transverse wave velocity value image, so that the structural distribution situation of the internal structures of the concrete, particularly key damage parameters (size, shape and spatial position) of defects, are identified.
The analysis steps of the full waveform inversion imaging method by utilizing the reinforced concrete internal structure are as follows:
(1) Analyzing the detected concrete structure, and determining division of data acquisition grid points;
(2) Based on the divided data acquisition grid points, utilizing an ultrasonic array instrument to acquire data;
(3) When data inversion analysis starts, predicting an ultrasonic source signal;
(4) Determining an inversion initial transverse wave velocity value model;
(5) Starting from an inversion initial transverse wave velocity value model, forward modeling analysis is carried out;
(6) Comparing the predicted wavelength data generated by the forward model with the actual wavelength data, and selecting an objective function equation;
(7) Selecting a Gaussian-Newton optimization algorithm, reducing an objective function equation, and calculating a model update gradient direction;
(8) Updating the transverse wave speed value model by using a steepest descent method;
(9) Imaging the inversion transverse wave velocity value through MATLAB programming;
(10) Determining a transverse wave velocity value rendering threshold according to analysis of the inverted transverse wave velocity value;
(11) Rendering and imaging the inversion imaging result, and analyzing the key index parameters (size, shape and space position) of the structure and the defect in the concrete structure;
the data acquisition grid point division is determined based on inversion imaging precision, the transverse interval of the acquisition points is 5-10 cm, and the longitudinal interval is 1-2 cm. The ultrasonic wave is SH wave. The number of ultrasonic probes is not less than 32.
The seismic source prediction method comprises green equation calculation and seismic source signal prediction calculation. The calculation method of the green equation comprises the following steps:
Green(f,x,V s )＝W(f,x,V s )/R(f)
wherein, f is the center frequency of ultrasonic wave, hz when collecting data; x-calculating the position function of the grid points; v (V) s -a transverse wave velocity value of the calculated lattice point; green (f, x, V) s ) -calculating a wave field green's function; w (f, x, V) s ) -predicting the wave field; r (f) -Rake wavelet signal.
By the method for calculating the source signal in the frequency domain:
Source est (f)＝w(f,x,V s )/Green(f,x,V s )
wherein, f-when collecting data, the ultrasonic test frequency, hz; x-calculating the position function of the grid points; v (V) s -a transverse wave velocity value of the calculated lattice point; source (Source) est (f) -centreCalculating a source signal with a frequency f; w (f, x, V) s ) -predicting the wave field; green (f, x, V) s ) -calculating a wavelength green function.
Initial value of transverse wave velocity model adopted by inversionAnd the ultrasonic probe is determined according to the on-site real-time measurement of the ultrasonic probe.
The forward modeling analysis adopts a two-dimensional SH elastic wave equation of a time domain to model the forward propagation process of SH waves in a concrete medium:
wherein, the coordinates of the grid points in the x-forward model in the transverse direction, the coordinates of the grid points in the z-forward model in the longitudinal direction and the y-direction perpendicular to the xy plane; rho-density value of the lattice point in forward model, μ -shear modulus value of the lattice point in forward model; v y -velocity of shear transverse wave particles in y-direction, f y -source stress in a direction perpendicular to the xz plane;derivative of the shear stress in the xy plane over time, < >>Derivative of the shear stress in the yz plane over time,/->Shear transverse wave particles in the y-directionDerivative of sub-speed over time; sigma (sigma) yx,x Derivative of the shear stress in the xy-plane in the transverse coordinate x, sigma yz,z Derivative of shear stress in the yz plane in the longitudinal coordinate z, v y,x Derivative of shear transverse wave particle velocity in the y-direction in transverse coordinate x, v y,z -derivative of shear transverse wave particle velocity in the y-direction in the longitudinal coordinate z.
The forward model adopts a mirror stress method on the boundary of the simulated concrete structure surface to simulate strong reflection waves generated by SH elastic waves on the concrete surface; on the remaining boundaries except the concrete structure surface, a perfect matching layer (Perfect Match Layers, PML) is used to absorb the boundary reflection waves.
The method is characterized in that the least square method is used as an objective function of model inversion, and the calculation process of the objective function is divided into wave field residual calculation and least square method calculation.
The wave field residual error calculation method comprises the following steps:
Δd s,r ＝D s,r (V s )-d s,r
in the formula, s is an ultrasonic source sensor serial number; r-signal receiving sensor number; v (V) s -medium shear wave velocity values; Δd s,r -wavefield residuals caused by differences in transverse wave velocity values; d (D) s,r (V s ) -predicting wave field data; d, d s,r -actual wave field data.
The least square method comprises the following steps:
wherein V is s -medium shear wave velocity values; e (V) s ) -a least squares value caused by the difference in transverse wave velocity values; Δd s,r -wavefield residuals caused by differences in transverse wave velocity values, T-matrix transpose calculation.
Further, the optimization algorithm calculates the gradient direction (jacobian matrix) of the transverse wave velocity model by adopting a Gaussian-Newton method, and the calculation method comprises the following steps:
in the method, in the process of the invention,from transverse wave velocity values V at source s and receiver sensor r s A calculated jacobian matrix; />From transverse wave velocity values V in a positive transmission field s A virtual source in the x-direction calculated; />From transverse wave velocity values V in a positive transmission field s Calculated wave field signal data in the x-direction; />From transverse wave velocity values V in a positive transmission field s A virtual source in the calculated z-direction; />From transverse wave velocity values V in a positive transmission field s Calculated wave field signal data in the z-direction;
the prediction model is updated by adopting a fastest gradient method to update a transverse wave velocity model, and the calculation method comprises the following steps:
in the formula, n-nth iterative inversion and n+1-n+1th iterative inversion are carried out; v (V) s -medium shear wave velocity values; v (V) s n+1 Transverse wave velocity value, V, of medium at n+1 iterative inversion s n -transverse wave velocity values of the medium at n iterative inversions; alpha n -updating the step size;updating gradient direction, P-Laplace matrix, I-unit matrix and t-matrix transposition calculation by using the transverse wave velocity value model; lambda (lambda) 1 -constant = 0.1, λ 2 -constant = 0.05; Δd s,r -wavefield residuals caused by differences in transverse wave velocity values.
In the formula, n-nth iterative inversion is carried out; n+1-n+1th iterative inversion; ρ -a medium density value; ρ n+1 -density values of the medium at n+1 iterative inversions; ρ n -density values of the medium at n iterative inversions; beta n -updating the step size;-updating the gradient direction by the density value model;
the transverse wave speed value two-dimensional imaging is performed, MATLAB software is utilized to write an image based on the inversion transverse wave speed value, and therefore physical value distribution conditions in the concrete structure are identified;
the image rendering is carried out on the image obtained in the steps based on the numerical range of the inversion transverse wave speed value, and comprises a transparent processing concrete body, so that the crack defect in the protruding concrete structure is emphasized, and the reinforcing steel bar structure in the protruding concrete is emphasized. Concrete transparent rendering transverse wave speed valueThe range selection method comprises the following steps:
in the method, in the process of the invention,-initial value of transverse wave velocity model, m/s; />Transparent rendering density value range, kg/m 3 ；
Rendering values of defects such as cracksThe range is not higher than 500m/s;
reinforcing steel bar reinforced rendering numerical valueThe range is not less than 3000m/s.
Example 1
Inversion imaging of cracks in concrete: reinforced concrete members were fabricated with dimensions of 50 cm. Times.50 cm. Times.19 cm. In casting, the horizontal cracks are simulated by embedding the foam sheet in advance, the transverse wave velocity value of the foam sheet is measured to be about 100m/s, the dimensions are 10cm multiplied by 1cm, and the foam sheet is embedded at the center position 10cm away from the surface of the component.
Dividing the surface of the formed concrete member into acquisition grid points, setting the transverse acquisition interval of the grid points to be 20cm, setting the longitudinal acquisition interval to be 1cm, and adopting an ultrasonic instrument to acquire ultrasonic data according to the points divided by the acquisition grid points. As shown in fig. 2, the ultrasonic instrument is placed right above the horizontal crack, and the area of the broken line in the figure is 20cm x 19cm of the area to be inverted, for testing the side view of the concrete member.
Based on the acquired ultrasonic data, an ultrasonic source signal is predicted first at the beginning of inversion. And secondly, adopting an ultrasonic instrument, randomly selecting 10 point positions on the surface of the formed concrete member to acquire transverse wave speed values, averaging the 10 transverse wave speed values, measuring and calculating to obtain an average transverse wave speed value of about 2500m/s, and using the average value for inverting a required initial model of the transverse wave speed value. .
Based on a transverse wave velocity value initial model and a simulated ultrasonic source, forward modeling analysis is started, so that a predicted wave field signal is obtained, differential calculation is carried out on the predicted wave field signal and an actually collected ultrasonic wave field signal, a least square method calculation is carried out to obtain an objective function, a gradient direction of the objective function is reduced by using Gaussian-Newton optimization algorithm analysis, an update step length is calculated, and the transverse wave velocity value model is updated, so that an inversion transverse wave velocity value matrix is finally obtained.
Numerical imaging is achieved through MATLAB software programming of a density value matrix obtained through inversion, as shown in FIG. 3, the density value matrix is a two-dimensional concrete inversion image based on transverse wave speed values, the right side of the image is the corresponding relation between inverted transverse wave speed values and colors, a dark color area is a transverse wave speed high value area, a bright white color area is a transverse wave speed low value area, a transition area is arranged in the middle of a color column, and different transverse wave speed values are corresponding. As can be seen, there is a low shear velocity line of about 10cm in length and 1mm in width at a depth of about 10cm, and the inversion shear velocity is about 0 to 150m/s. Since the shear wave velocity value of the foam board used for simulating the crack is about 100m/s, it can be inferred that the low shear wave velocity line is a simulated concrete internal crack, and the inversion crack is well matched with the simulated concrete crack in terms of width, length, shear wave velocity value and spatial burial depth. Therefore, the full-wave inversion nondestructive testing method for the transverse wave velocity value of the concrete structure has nondestructive testing capability on the internal structure of the concrete structure, particularly key damage indexes aiming at crack defects, and can provide information such as the width, the length and the space position of the crack through inversion, so that the method is fully proved in the embodiment.
Example 2
Inversion imaging of the steel bars in the concrete: reinforced concrete members were fabricated with dimensions of 50 cm. Times.50 cm. Times.19 cm. And a reinforcing steel bar with the number 18 is embedded in advance during pouring of the test block, the diameter of the reinforcing steel bar is 18mm, and the transverse wave speed value of the reinforcing steel bar is about 3250m/s. The distance between the steel bar and the upper top end is 6cm. The concrete member was cured under standard conditions for 28d.
Dividing the surface of the formed concrete member into acquisition grid points, setting the transverse acquisition interval of the grid points to be 20cm, setting the longitudinal acquisition interval to be 1cm, and adopting an ultrasonic instrument to acquire ultrasonic data according to the points divided by the acquisition grid points. Fig. 4 shows a side view of the ultrasonic instrument and the concrete member during data acquisition, and the ultrasonic instrument is placed right above the steel bar, and the size of the ultrasonic instrument is 20cm multiplied by 19cm in the broken line area in the figure.
Based on the acquired ultrasonic data, an ultrasonic source signal is predicted first at the beginning of inversion. And secondly, adopting an ultrasonic instrument, randomly selecting 10 point positions on the surface of the formed concrete member to acquire transverse wave speed values, averaging the 10 transverse wave speed values, measuring and calculating to obtain an average transverse wave speed value of about 2440m/s, and using the average value for inverting a required initial model of the transverse wave speed value.
Based on a transverse wave velocity value initial model and a simulated ultrasonic source, forward modeling analysis is started, so that a predicted wave field signal is obtained, differential calculation is carried out on the predicted wave field signal and an actually collected ultrasonic wave field signal, a least square method calculation is carried out to obtain an objective function, a gradient direction of the objective function is reduced by using Gaussian-Newton optimization algorithm analysis, an update step length is calculated, and the transverse wave velocity value model is updated, so that an inversion transverse wave velocity value matrix is finally obtained.
Numerical imaging is achieved through MATLAB software programming of a density value matrix obtained through inversion, as shown in FIG. 5, the density value matrix is a two-dimensional concrete structure inversion image based on transverse wave speed values, the right side of the image is the corresponding relation between inverted transverse wave speed values and colors, a dark color area is a transverse wave speed high value area, a bright white color area is a transverse wave speed low value area, a transition area is arranged in the middle of a color column, and different transverse wave speed values are corresponding. As can be seen from the graph, the transverse wave velocity value of the whole concrete is 2440m/s, a high-density value circular area with the diameter of about 18mm exists at the position with the depth range of 6-8 cm, and the inversion transverse wave velocity value is about 3200-3300 m/s. Since the actual shear wave velocity value of the steel bar is about 3250m/s, it can be deduced that the high shear wave velocity circular region is the embedded steel bar in the concrete, and the inverted steel bar is completely matched with the actual embedded steel bar in shape, size and embedded depth. Therefore, the full-wave inversion nondestructive testing method for the transverse wave velocity value of the concrete structure has the nondestructive testing capability on the steel bar structure inside the concrete structure, and the shape, the size, the space position and other information of the steel bar can be provided through inversion, so that the full-wave inversion nondestructive testing method is fully verified in the embodiment.
Example 3
Inversion imaging of the cavity in the concrete: reinforced concrete members were fabricated with dimensions of 50 cm. Times.50 cm. Times.19 cm. The concrete member was cured under standard conditions for 28d. After curing and molding, drilling and molding a circular cavity at the center position with the side depth of 6cm, wherein the radius of the circular cavity is 2cm, the distance from the upper top end of the cavity to the upper surface of the concrete member is 4cm, and the distance from the lower end to the upper surface of the concrete member is 8cm.
Dividing the surface of the formed concrete member into acquisition grid points, setting the transverse acquisition interval of the grid points to be 20cm, setting the longitudinal acquisition interval to be 1cm, and adopting an ultrasonic instrument to acquire ultrasonic data according to the points divided by the acquisition grid points. Fig. 6 shows a side view of the ultrasonic instrument and the concrete member during data acquisition, and it can be seen from the figure that the ultrasonic instrument is placed right above the circular cavity, and the area of the broken line in the figure is an inversion-planned area, and the dimensions are 20cm×19cm.
Based on the acquired ultrasonic data, an ultrasonic source signal is predicted first at the beginning of inversion. And secondly, adopting an ultrasonic instrument, randomly selecting 10 point positions on the surface of the formed concrete member to acquire transverse wave speed values, averaging the 10 transverse wave speed values, measuring and calculating to obtain an average transverse wave speed value of about 2530m/s, and using the average value for inverting a required initial model of the transverse wave speed value.
Based on a transverse wave velocity value initial model and a simulated ultrasonic source, forward modeling analysis is started, so that a predicted wave field signal is obtained, differential calculation is carried out on the predicted wave field signal and an actually collected ultrasonic wave field signal, a least square method calculation is carried out to obtain an objective function, a gradient direction of the objective function is reduced by using Gaussian-Newton optimization algorithm analysis, an update step length is calculated, and the transverse wave velocity value model is updated, so that an inversion transverse wave velocity value matrix is finally obtained.
Numerical imaging is achieved through MATLAB software programming of a transverse wave velocity value matrix obtained through inversion, as shown in FIG. 7, the matrix is a two-dimensional concrete inversion image based on transverse wave velocity values, the right side of the image is the correspondence between inverted density values and colors, a dark color area is a transverse wave velocity high value area, a bright white color area is a transverse wave velocity low value area, a transition area is arranged in the middle of a color column, and different transverse wave velocity values are corresponding. As can be seen, there is a circular region with a diameter of about 4cm and a low shear velocity value, and the inversion shear velocity value is about 0 to 50m/s, at a depth ranging from 4 to 8cm. Because the transverse wave velocity value of the real cavity is 0, the low transverse wave velocity circular area can be deduced to be a circular cavity formed by drilling in concrete, and the inversion cavity is basically consistent with the real cavity of the concrete in shape, size, transverse wave velocity value and space burial depth. Therefore, the full-wave inversion nondestructive testing method for the transverse wave velocity value of the concrete structure has the nondestructive testing capability for the circular cavity structure inside the concrete structure, and information such as the shape, the size and the spatial position of the cavity can be provided through inversion, so that the full-wave inversion nondestructive testing method is fully verified in the embodiment.
Claims (10)
1. A nondestructive testing method for reinforcing steel bars and defects in concrete, which is characterized by comprising the following three subprograms:
subroutine one: the ultrasonic data acquisition comprises two steps of data acquisition grid point division, ultrasonic signal transmission and acquisition;
subroutine II: the ultrasonic data inversion analysis comprises six steps of ultrasonic source signal prediction, inversion initial model selection, forward modeling analysis, objective function selection, optimization algorithm selection and prediction model updating;
and a third sub-program: the transverse wave speed value imaging comprises three steps of transverse wave speed value three-dimensional imaging, transverse wave speed rendering threshold analysis and image rendering.
2. The nondestructive testing method for the internal steel bars and defects of the concrete according to claim 1, wherein the data acquisition grid points are divided, the longitudinal spacing is 1-2 cm, the transverse spacing is 5-10 cm, the ultrasonic waves are SH waves, and the number of ultrasonic probes is not less than 32.
3. The method for the nondestructive testing of steel bars and defects in concrete according to claim 1, wherein the ultrasonic source signal prediction method comprises green's equation calculation and source signal prediction calculation, and the green's equation calculation method is as follows:
Green(f,x,V s )＝W(f,x,V s )/R(f)
wherein, f-the central frequency of ultrasonic wave is Hz when collecting data; x-calculating the position function of the grid points; v (V) s -a transverse wave velocity value of the calculated lattice point; green (f, x, V) s ) -calculating a wave field green's function; w (f, x, V) s ) -predicting the wave field; r (f) -rake wavelet signals;
the method for predicting and calculating the source signal in the frequency domain comprises the following steps:
Source est (f)＝w(f,x,V s )/Green(f,x,V s )
in the formula, f-is the ultrasonic test frequency when data is acquired, and the unit is Hz; x-calculating the position function of the grid points; v (V) s -a transverse wave velocity value of the calculated lattice point; source (Source) est (f) -calculating a source signal with a centre frequency f; w (f, x, V) s ) -predicting the wave field; green (f, x, V) s ) -calculating a wavelength green function.
4. The method for non-destructive testing of steel bars and defects in concrete according to claim 1, wherein in the step of selecting the inversion initial model, the initial value of the transverse wave velocity model used for inversion is determined by measuring in situ and in real time according to an ultrasonic probe.
5. The nondestructive testing method for reinforcing steel bars and defects in concrete according to claim 1, wherein in the forward modeling analysis step, a time domain two-dimensional SH elastic wave equation is adopted to model the forward propagation process of SH waves in the concrete:
wherein, the coordinates of the grid points in the x-forward model in the transverse direction, the coordinates of the grid points in the z-forward model in the longitudinal direction and the y-direction perpendicular to the xy plane; rho-density value of the lattice point in forward model, μ -shear modulus value of the lattice point in forward model; v y -velocity of shear transverse wave particles in y-direction, f y -source stress in a direction perpendicular to the xz plane;derivative of the shear stress in the xy plane over time, < >>Derivative of the shear stress in the yz plane over time,/->-derivative of shear transverse wave particle velocity in the y-direction over time; sigma (sigma) yx,x Derivative of the shear stress in the xy-plane in the transverse coordinate x, sigma yz,z Derivative of shear stress in the yz plane in the longitudinal coordinate z, v y,x Derivative of shear transverse wave particle velocity in the y-direction in transverse coordinate x, v y,z -derivative of shear transverse wave particle velocity in the y-direction on the longitudinal coordinate z;
the forward model adopts a mirror stress method on the boundary of the simulated concrete structure surface to simulate strong reflection waves generated by SH elastic waves on the concrete surface; and absorbing boundary reflection waves by adopting a perfect matching layer on the rest boundaries except the surface of the concrete structure.
6. The nondestructive testing method for reinforcing steel bars and defects in concrete according to claim 1, wherein in the objective function selecting step, a least square method is selected as a model inversion objective function, and the calculation process is divided into wave field residual calculation and least square method calculation;
the wave field residual error calculation method comprises the following steps:
Δd s,r ＝D s,r (V s )-d s,r
in the formula, s is an ultrasonic source sensor serial number; r-signal receiving sensor number; v (V) s -medium shear wave velocity values; Δd s,r -wavefield residuals caused by differences in transverse wave velocity values; d (D) s,r (V s ) -predicting wave field data; d, d s,r -actual wave field data;
the least square method comprises the following steps:
wherein V is s -medium shear wave velocity values; e (V) s ) -a least squares value caused by the difference in transverse wave velocity values; Δd s,r -wavefield residuals caused by differences in transverse wave velocity values, T-matrix transpose calculation.
7. The nondestructive testing method for reinforcing steel bars and defects in concrete according to claim 1, wherein in the optimization algorithm selecting step, a gaussian-newton method is adopted to calculate a gradient direction of a transverse wave velocity model, and the calculation method comprises the following steps:
in the method, in the process of the invention,from transverse wave velocity values V at source s and receiver sensor r s A calculated jacobian matrix; />From transverse wave velocity values V in a positive transmission field s A virtual source in the x-direction calculated; />From transverse wave velocity values V in a positive transmission field s Calculated wave field signal data in the x-direction; />From transverse wave velocity values V in a positive transmission field s A virtual source in the calculated z-direction; />From transverse wave velocity values V in a positive transmission field s Calculated wave field signal data in the z-direction.
8. The nondestructive testing method for reinforcing steel bars and defects in concrete according to claim 1, wherein in the step of updating the prediction model, a shear wave velocity value model is updated by a steepest gradient method, and the calculation method is as follows:
in the formula, n-nth iterative inversion and n+1-n+1th iterative inversion are carried out; v (V) s -medium shear wave velocity values; v (V) s n+1 Transverse wave velocity value, V, of medium at n+1 iterative inversion s n -transverse wave velocity values of the medium at n iterative inversions; alpha n -updating the step size;updating gradient direction, P-Laplace matrix, I-unit matrix and t-matrix transposition calculation by using the transverse wave velocity value model; lambda (lambda) 1 -constant = 0.1, λ 2 -constant = 0.05; Δd s,r -wavefield residuals caused by differences in transverse wave velocity values.
9. The nondestructive testing method for steel bars and defects in concrete according to claim 1, wherein in the step of two-dimensional imaging of transverse wave velocity values, matrix imaging is realized by adopting MATLAB software programming based on transverse wave velocity values obtained by inversion.
10. The nondestructive inspection method of steel bar and defect inside concrete according to claim 9, wherein in the image rendering step, the image obtained in claim 9 is rendered based on the inversion transverse wave velocity numerical range, the concrete body is transparentized, and the internal structure of the concrete is emphasized;
concrete transparent rendering transverse wave speed valueThe range selection method comprises the following steps:
in the method, in the process of the invention,-initial value of transverse wave velocity model, m/s; />Transparent rendering density value range in kg/m 3 ；
Rendering values of defects such as cracksThe range is not higher than 500m/s;
reinforcing steel bar reinforced rendering numerical valueThe range is not less than 3000m/s.
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| CN117538289A (en) * | 2024-01-10 | 2024-02-09 | 中铁十六局集团第一工程有限公司 | Nondestructive testing method for construction quality of steel reinforced concrete structure node |
| CN117570889A (en) * | 2024-01-15 | 2024-02-20 | 湖北神龙工程测试技术有限公司 | Nondestructive testing method for diameter of steel bar in concrete |
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| CN117538289A (en) * | 2024-01-10 | 2024-02-09 | 中铁十六局集团第一工程有限公司 | Nondestructive testing method for construction quality of steel reinforced concrete structure node |
| CN117538289B (en) * | 2024-01-10 | 2024-03-22 | 中铁十六局集团第一工程有限公司 | Nondestructive testing method for construction quality of steel reinforced concrete structure node |
| CN117570889A (en) * | 2024-01-15 | 2024-02-20 | 湖北神龙工程测试技术有限公司 | Nondestructive testing method for diameter of steel bar in concrete |
| CN117570889B (en) * | 2024-01-15 | 2024-03-26 | 湖北神龙工程测试技术有限公司 | Nondestructive testing method for diameter of steel bar in concrete |
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