Rebar detector precision calibration system and method

Abstract

The present application relates to the technical field of data calibration, and discloses a reinforcing bar detector precision calibration system and method, the system comprises: a detection unit, a calculation unit, an analysis unit, an equalization unit and a calibration unit, after the detection unit acquires a double-frequency mixed echo signal, the calculation unit first decomposes the signal mode to obtain a double-main-mode response vector and a secondary-mode coordination value, then calculates a double-frequency distortion factor in combination with interlayer amplitude variation, interlayer rate of coordination and other parameters, and further can quantify the strength of the electromagnetic lens effect, while the mode adaptation critical value obtained by the analysis unit can provide a basis for signal calibration, the signal equalization coefficient of the equalization unit can determine the direction of signal calibration, and finally the calibration unit combines double-frequency layer domain superposition degree, medium adaptation superposition adjustment amount and other parameters to superimpose and calibrate double-frequency signal components based on the signal equalization coefficient, effectively corrects signal distortion, and realizes precision calibration of ancient building wall reinforcing bar detection.

Description

Technical Field

[0001] This invention relates to the field of signal calibration technology, specifically to a precision calibration system and method for rebar detectors. Background Technology

[0002] Currently, rebar detectors are used to assess the safety and durability of buildings by utilizing the property of electromagnetic waves reflecting at the boundaries of different materials. When electromagnetic waves propagate inside concrete and encounter different media such as rebar, they are reflected. By receiving and analyzing the reflected waves, information about the boundary between the concrete and the rebar can be obtained, thereby acquiring relevant information about the building and achieving the purpose of detection.

[0003] However, the above-mentioned detection methods still have the following drawbacks when detecting ancient buildings: After long-term natural aging, the concrete of ancient buildings will form a carbonized layer on the surface, and the internal steel bars are prone to rust due to corrosion. The contact area (interface) between these two different media is also uneven and there are abrupt changes in dielectric parameters, which will form an electromagnetic lens effect, causing unexpected refraction, scattering and phase shift during the propagation of electromagnetic waves, resulting in signal distortion of reflected waves and reducing detection accuracy. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a precise calibration system and method for rebar detectors, solving the aforementioned problems.

[0005] The above-mentioned technical objective of the present invention is achieved through the following technical solution: The rebar detector precision calibration system includes: The detection unit is used to sequentially transmit two electromagnetic waves of different frequencies to the same detection point in the target area based on the rebar detector, and obtain a dual-frequency mixed echo signal. The two electromagnetic waves of different frequencies are low-frequency electromagnetic waves and high-frequency electromagnetic waves, and the target area is the wall of an ancient building. The computing unit is used to perform mode decomposition on the dual-frequency hybrid echo signal to obtain the dual principal mode response vectors and secondary mode co-operation values ​​of the two frequencies. It calculates the dual principal mode response vectors and secondary mode co-operation values ​​to generate a dual-frequency distortion factor representing the intensity of the electromagnetic lensing effect. The analysis unit is used to perform covariance analysis on the dual principal mode response vectors and secondary mode covariance values ​​to obtain the mode fit critical value. The dual-frequency distortion factor is compared with the mode fit critical value to generate factor identifiers. The equalization unit is used to analyze the magnitude and characteristics of the dual-frequency distortion factor based on the factor identifier to obtain the signal equalization coefficient; The calibration unit is used to superimpose the signal components of the two frequencies separated from the dual-frequency mixed echo signal according to the signal equalization coefficient to generate a calibrated signal.

[0006] Furthermore, mode decomposition is performed on the dual-frequency hybrid echo signal to obtain the dual principal mode response vectors and secondary mode co-mode values ​​for the two frequencies, including: Medium interference characteristics are identified in dual-frequency hybrid echo signals to generate modal distortion characteristics. Based on the complementary characteristics of the penetration depth of low-frequency electromagnetic waves and the resolution of high-frequency electromagnetic waves, the differences in the propagation paths of the two frequency signals in a three-layer medium are analyzed, and frequency domain correlation coefficients are generated. Based on the modal distortion characteristics and combined with the frequency domain correlation coefficient, the dual-frequency mixed echo signal is dynamically stripped to separate the first core component dominated by the low-frequency signal and the second core component dominated by the high-frequency signal, thus obtaining the dual principal mode feature vector. The residual wave components not covered by the dual-primary-mode eigenvectors in the dual-frequency hybrid echo signal are extracted. The cooperative wave intensity of the residual components and the two core components is calculated by combining the frequency domain correlation coefficient, and the dual-primary-mode response vector and the secondary-mode cooperative value are generated.

[0007] Furthermore, the dual principal mode response vectors and secondary mode co-operational values ​​are calculated to generate a dual-frequency distortion factor representing the intensity of the electromagnetic lensing effect, including: The signal amplitude variation characteristics of the low-frequency and high-frequency dual principal mode response vectors in the three-layer medium of the target region are extracted respectively to generate interlayer amplitude values; The dynamic variation of submodal cooperative values ​​with the propagation of dual principal modal response vectors in three media layers was analyzed, and the distribution ratio of the abnormal correlation strength between submodal cooperative values ​​and dual principal modal response vectors in different media layers was calculated to generate the cooperative anomaly interlayer rate. Based on the interlayer amplitude value, the medium property is corrected for the cooperative anisotropic interlayer rate, and the medium coupling coefficient is generated. Based on the physical characteristics of low-frequency and high-frequency electromagnetic waves, the response adaptation differences of the two frequency signals in the medium are calculated by combining the interlayer amplitude values, and a dual-frequency domain weighting is generated.

[0008] Furthermore, the dual principal mode response vectors and secondary mode co-operational values ​​are calculated to generate a dual-frequency distortion factor representing the intensity of the electromagnetic lensing effect, which also includes: The dielectric coupling coefficient is dynamically matched with the dual-frequency domain weighting to generate a global reference value; The steady-state characteristics of the submodal cooperative values ​​are extracted to generate cooperative steady-state coefficients; The global reference value is adjusted based on the cooperative steady-state coefficients to generate a dual-frequency distortion factor representing the intensity of the electromagnetic lensing effect.

[0009] Furthermore, covariance analysis was performed on the dual principal modal response vectors and secondary modal covariance values ​​to obtain the modal fit critical values, including: The synchronous variation amplitudes of the dual principal modal response vectors and secondary modal co-variance values ​​of low frequency and high frequency in each medium layer of the target region are calculated respectively. By comparing the co-variance differences of the dual principal modal response vectors and secondary modal co-variance values ​​in the same medium layer, the hierarchical co-variance characteristic values ​​are obtained. Based on the difference in propagation speed between low-frequency and high-frequency electromagnetic waves in different dielectric layers, and combined with the calculation of the propagation time delay between the dual principal mode response vector and the secondary mode cooperative value using the layered covariant eigenvalue, the time delay corrected layered covariant intensity is obtained. By analyzing the non-homogeneity of each layer of medium in the target region, the layered covariance intensity is locally adjusted to obtain the locally adapted covariance intensity. Calculate the characteristic parameters of each medium layer in the target region, and based on the characteristic parameters, analyze the reasonable fluctuation range of the local adaptive covariance intensity when there is no electromagnetic lensing effect, and generate a dynamic reference range. Based on the dynamic baseline range and the intensity of local adaptive covariance, the boundary values ​​that can distinguish between normal covariance and abnormal covariance are calculated, and the modal adaptation critical values ​​are generated.

[0010] Furthermore, the dual-frequency distortion factor is compared with the modal adaptation threshold to generate factor identifiers, including: Calculate the matching degree between the dual-frequency distortion factor and the modal adaptation critical value at low and high frequencies, and generate the dual-frequency domain adaptation index; The transient interference intensity of each layer of medium in the target area to the dual-frequency signal is analyzed, the transient disturbance of the medium is generated, and the dual-frequency domain adaptation index is corrected according to the transient disturbance of the medium to obtain the transient correction adaptation value. The critical response characteristics of the dual-frequency signal in the three-layer medium are calculated to obtain the dual-frequency domain adaptation reference band. The transient correction adaptation value is compared with the dual-frequency domain adaptation reference band to generate factor identifiers.

[0011] Furthermore, based on the factor identifier, the magnitude and characteristics of the dual-frequency distortion factor are analyzed to derive the signal equalization coefficients, including: When the factor is marked as qualified, the degree of coordination between the dual-frequency distortion factor and the modal adaptation critical value in each medium layer is calculated to generate the distortion coordination compliance degree. Based on the characteristic differences between low-frequency electromagnetic waves and high-frequency electromagnetic waves, the deviation of the dual-frequency signals is calculated, and the dual-frequency characteristic adaptation deviation is generated. The influence of the dynamic reference range on the dual-frequency characteristic adaptation deviation is analyzed, and the dynamic perturbation adaptation coefficient of the medium is generated. Based on the dual-frequency distortion factor, the fluctuation amplitude and characteristic consistency are calculated to generate the qualified state distortion stability.

[0012] Furthermore, based on the factor identifier, the magnitude and characteristics of the dual-frequency distortion factor are analyzed to derive the signal equalization coefficient, which also includes: The qualified state distortion stability, distortion coordination compliance and dual-frequency characteristic adaptation deviation are analyzed to determine the equalization adjustment direction. The adjustment direction is dynamically calibrated according to the medium dynamic disturbance adaptation coefficient to generate a two-dimensional equalization reference quantity. Calculate the energy efficiency matching ratio between the first core component and the second core component in the dual-frequency hybrid echo signal; Based on the energy efficiency adaptation ratio, the energy efficiency of the two-dimensional equalization benchmark is optimized and adjusted to generate the signal equalization coefficient.

[0013] Furthermore, based on the signal equalization coefficient, the signal components of the two frequencies separated from the dual-frequency mixed echo signal are superimposed to generate a calibrated signal, including: Based on the signal equalization coefficient, the matching superposition strength of the first core component and the second core component in each medium layer is calculated to generate the dual-frequency layer domain superposition degree. Based on the two-dimensional equalization reference quantity, the superposition degree of the dual-frequency layer domain is corrected to generate the medium-adaptive superposition adjustment quantity. Based on the medium adaptation superposition adjustment amount, and combining the complementary characteristics of low-frequency signal penetration and high-frequency signal resolution, the first core component and the second core component are synergistically fused and superimposed to generate the calibrated signal.

[0014] Furthermore, a method for precise calibration of a rebar detector, applied to the aforementioned precise calibration system for a rebar detector, includes: Step S1 is used to obtain a dual-frequency mixed echo signal by sequentially transmitting two electromagnetic waves of different frequencies to the same detection point in the target area using a rebar detector. The two electromagnetic waves of different frequencies are low-frequency electromagnetic waves and high-frequency electromagnetic waves, and the target area is the wall of an ancient building. Step S2 is used to perform mode decomposition on the dual-frequency hybrid echo signal to obtain the dual principal mode response vectors and secondary mode co-operation values ​​of the two frequencies. The dual principal mode response vectors and secondary mode co-operation values ​​are calculated to generate a dual-frequency distortion factor representing the intensity of the electromagnetic lens effect. Step S3 is used to perform covariance analysis on the dual principal mode response vector and the secondary mode covariance value to obtain the mode fit critical value. The dual frequency distortion factor is compared with the mode fit critical value to generate factor identifiers. Step S4 is used to analyze the magnitude and characteristics of the dual-frequency distortion factor based on the factor identifier, and to obtain the signal equalization coefficient. Step S5 is used to superimpose the signal components of the two frequencies separated from the dual-frequency mixed echo signal according to the signal equalization coefficient to generate a calibrated signal.

[0015] In summary, the present invention has the following main beneficial effects: By identifying the medium interference characteristics of the dual-frequency hybrid echo signal to generate modal distortion features, and then combining the complementary characteristics of low-frequency and high-frequency electromagnetic waves to analyze the propagation path differences and generate frequency domain correlation coefficients, dynamic stripping of the dual-frequency hybrid echo signal is achieved, accurately separating the first core component and the second core component, and thus obtaining the dual principal mode response vector and the secondary mode cooperative value. Subsequently, the interlayer amplitude values ​​of the dual principal mode response vectors are extracted, the cooperative anisotropic interlayer rate of the secondary mode cooperative value is calculated, the cooperative anisotropic interlayer rate is corrected by the medium coupling coefficient, dynamic matching is completed by combining the dual-frequency domain weighting, and the global reference value is adjusted according to the cooperative steady-state coefficient. Finally, a dual-frequency distortion factor that can accurately reflect the intensity of the electromagnetic lensing effect is generated. The dual-frequency distortion factor can provide a basis for judgment for subsequent calibration, and the factor identifier generated by comparing the modal adaptation critical value with the dual-frequency distortion factor can determine the direction of signal calibration and reduce signal distortion caused by the electromagnetic lensing effect.

[0016] By calculating the distortion synergy compliance rate to determine the degree of conformity between the dual-frequency distortion factor and the modal adaptation critical value, and then by using the dual-frequency characteristic adaptation deviation to understand the deviation of the dual-frequency signal, the influence of the dynamic reference range is analyzed in conjunction with the medium dynamic perturbation adaptation coefficient. At the same time, the qualified state distortion stability is calculated to evaluate the fluctuation and consistency of the dual-frequency distortion factor, thereby determining the equalization adjustment direction and calibrating the generation of the dual-dimensional equalization reference quantity. Subsequently, the dual-dimensional equalization reference quantity is optimized and adjusted in conjunction with the energy efficiency adaptation ratio of the first core component and the second core component, and finally the signal equalization coefficient is generated. Then, the dual-frequency layer domain superposition degree is calculated based on the signal equalization coefficient, and the superposition degree is corrected by the medium adaptation superposition adjustment amount. Finally, the two core components are synergistically fused and superimposed in conjunction with the complementary characteristics of low-frequency and high-frequency electromagnetic waves to generate the calibrated signal. Through layer-by-layer calibration, the problems of signal refraction, scattering and phase shift caused by electromagnetic lens effect are corrected to ensure the accuracy of the reflected wave signal and improve the accuracy of the rebar detector in detecting ancient buildings. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the precision calibration system for the rebar detector of the present invention; Figure 2 This is a flowchart of the precise calibration method for the rebar detector of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] refer to Figure 1 and Figure 2 The rebar detector precision calibration system includes: The detection unit is used to sequentially transmit two electromagnetic waves of different frequencies to the same detection point in the target area based on the rebar detector, and obtain a dual-frequency mixed echo signal. The two electromagnetic waves of different frequencies are low-frequency electromagnetic waves and high-frequency electromagnetic waves, and the target area is the wall of an ancient building. Among them, low-frequency electromagnetic waves (5kHz-50kHz) are characterized by stronger penetration ability as the frequency decreases, but have lower resolution and are more sensitive to large steel bars. However, their signals are also more susceptible to electromagnetic lensing effects. High-frequency electromagnetic waves (50kHz-500kHz) are characterized by higher resolution at higher frequencies, making them more sensitive to shallow, dense steel meshes, but they have weak penetration ability and are more easily absorbed and scattered by carbonized surfaces. The computing unit is used to perform mode decomposition on the dual-frequency hybrid echo signal to obtain the dual principal mode response vectors and secondary mode co-operation values ​​of the two frequencies. It calculates the dual principal mode response vectors and secondary mode co-operation values ​​to generate a dual-frequency distortion factor representing the intensity of the electromagnetic lensing effect. The analysis unit is used to perform covariance analysis on the dual principal mode response vectors and secondary mode covariance values ​​to obtain the mode fit critical value. The dual-frequency distortion factor is compared with the mode fit critical value to generate factor identifiers. The equalization unit is used to analyze the magnitude and characteristics of the dual-frequency distortion factor based on the factor identifier to obtain the signal equalization coefficient; The calibration unit is used to superimpose the signal components of the two frequencies separated from the dual-frequency mixed echo signal according to the signal equalization coefficient to generate a calibrated signal.

[0020] The detection unit emits low-frequency waves (5kHz-50kHz) and high-frequency waves (50kHz-500kHz). The low-frequency waves, with their strong penetration, are adapted to deep, large-scale steel reinforcement, while the high-frequency waves, with their high resolution, capture shallow, dense steel meshes, achieving complementary advantages between the two frequencies. The calculation unit generates dual-frequency distortion factors through modal decomposition to quantify the intensity of the electromagnetic lensing effect. The analysis unit, combined with covariance analysis, determines the modal adaptation critical value, providing a basis for distortion judgment. The equalization and calibration units generate signal equalization coefficients based on factor identifiers, dynamically superimposing and calibrating the dual-frequency signal components to correct signal distortion caused by electromagnetic wave refraction, scattering, and phase shift. Finally, a precise calibration signal is output, solving the problem of low detection accuracy under the interference of special aging media in ancient buildings.

[0021] In one embodiment, mode decomposition is performed on the dual-frequency hybrid echo signal to obtain the dual principal mode response vectors and secondary mode co-mode values ​​for the two frequencies, including: The process involves identifying media interference characteristics in a dual-frequency hybrid echo signal and generating modal distortion features. Specifically, this includes: filtering out noise above 500kHz from the dual-frequency hybrid echo signal; dividing the signal into time segments, with each segment lasting 0.1 milliseconds; measuring the signal strength at each frequency point within each time segment at fixed intervals (1kHz), and recording the results in a measurement table; simultaneously emitting electromagnetic waves of the same frequency into the air, dividing the signal into time segments and measuring the intensity at each frequency point in the same manner to create a standard signal table; comparing the intensity at the same time segment and frequency point in the two tables, subtracting the standard intensity from the measured intensity, and then dividing by the standard intensity to obtain the difference ratio; if the absolute value of the difference ratio exceeds 0.3, marking that time-frequency point as an interference point; and summing the signal strengths of all interference points and dividing by the total signal strength to generate the modal distortion features. Based on the complementary characteristics of the penetration depth of low-frequency electromagnetic waves and the resolution of high-frequency electromagnetic waves, this study analyzes the differences in the propagation paths of the two frequency signals in a three-layer medium, generating a frequency domain correlation coefficient. The three layers are a carbonization layer, concrete, and a steel reinforcement layer. Specifically, the process includes: obtaining the propagation times of the low-frequency and high-frequency signals in the three layers and calculating the propagation time difference between them in each layer; for each layer, extracting the low-frequency signal waveform A and the high-frequency signal waveform B, dividing them into equal-length blocks of 50 sampling points each (the last block with fewer than 50 sampling points is discarded); for each block (low-frequency signal block AK and high-frequency signal block BK), dividing the covariance of the two signals by the product of their respective standard deviations and taking the absolute value (range 0-1), using the median of all absolute values ​​as the amplitude correlation value for that layer; setting the weights for the carbonization layer (0.2), concrete layer (0.5), and steel reinforcement layer (0.3); multiplying the propagation time difference of each layer by the amplitude correlation value and then by the corresponding weight, and finally summing the calculation results for the three layers to obtain the frequency domain correlation coefficient. In the target area, the carbonized layer is a weak surface structure. Although it has strong absorption and scattering effects on high-frequency electromagnetic waves, it is only the initial contact layer for signal propagation and not the main propagation space for dual-frequency signals. Therefore, its weight should not be too high or too low. Setting it to 0.2 is just right to balance the situation, preventing the weight from increasing the local influence of the surface layer if it is too high, and ignoring its attenuation effect on high-frequency signals if it is too low. Concrete is the main structure of the ancient building wall and is the main channel for the propagation of dual-frequency electromagnetic waves. Low frequencies need to penetrate concrete to reach the steel reinforcement layer, and high frequencies need to maintain resolution within the concrete to identify shallow steel reinforcement. The dual-frequency signals mainly form differences within the concrete layer, so its weight is relatively high at 0.5. The steel reinforcement layer is the detection target. The dual-frequency signals (low frequencies are sensitive to large steel reinforcements, and high frequencies are sensitive to dense steel reinforcement meshes) ultimately need to be reflected by the steel reinforcement to form an echo. The quality of the reflected signal directly determines the accuracy of the calibration. The steel reinforcement layer is the final reflection source of the signal, so its weight is 0.3. Based on modal distortion characteristics and frequency domain correlation coefficients, the dual-frequency mixed echo signal is dynamically stripped to separate the first core component dominated by the low-frequency signal and the second core component dominated by the high-frequency signal, resulting in dual principal mode feature vectors. Specifically, this involves: considering frequency bands with a frequency domain correlation coefficient < 0.5 as independent dominant segments, dividing the 5-50kHz range into a low-frequency independent segment and the 50-500kHz range into a high-frequency independent segment; subtracting the modal distortion characteristics from 1 to obtain the interference suppression coefficient; and using a 5th-order Chebyshev bandpass filter (low-frequency passband 5-50kHz, high-frequency passband 50-500kHz). z) Separate the original components of the two frequency bands from the mixed signal, and multiply the interference suppression coefficient by the value of each sampling point of the two original components to obtain the processed first core component and second core component; for the processed first and second core components, traverse the intensity value of all sampling points of the component and record the maximum value. The maximum value is the feature value, and thus obtain the first principal mode feature value representing the low frequency and the second principal mode feature value representing the high frequency. Combine the first principal mode feature value and the second principal mode feature value in the order of low frequency to high frequency to obtain the dual principal mode feature vector; The residual fluctuation components not covered by the dual-dominant mode eigenvectors in the dual-frequency hybrid echo signal are extracted. The cooperative fluctuation intensity of the residual components and the two core components is calculated using the frequency domain correlation coefficient, generating the dual-dominant mode response vector and the secondary mode cooperative value. Specifically, for each sampling point, the intensity value of the hybrid signal at that point is subtracted from the intensity value of the first core component, and then the intensity value of the second core component is subtracted to obtain the residual value of each sampling point. The residual values ​​of all points are arranged in chronological order to form the residual fluctuation components. Using 30 sampling points as a window, the cross-correlation coefficients (covariance divided by the product of their respective standard deviations) between the residual fluctuation components and the first core component, and between the residual components and the second core component are processed in each window. The cross-correlation coefficients are then multiplied by the frequency domain correlation coefficient to obtain the results. The average of all window results is calculated to obtain the first and second cooperative fluctuation intensities. The first cooperative fluctuation intensity representing low frequency and the second cooperative fluctuation intensity representing high frequency are combined in low-frequency to high-frequency order to obtain the dual-dominant mode response vector. The first and second cooperative fluctuation intensities are added together and divided by 2 to obtain the secondary mode cooperative value.

[0022] By filtering out noise and comparing with standard signals to identify media interference, modal distortion characteristic quantities are generated. Then, frequency domain correlation coefficients are generated by combining the weights of three layers of media and propagation characteristics to accurately capture the propagation differences of dual-frequency signals. Subsequently, dual-frequency core components are dynamically stripped and residual components are extracted. By calculating the cooperative wave intensity, dual principal mode response vectors and secondary mode cooperative values ​​are generated to achieve refined decomposition and calibration analysis of distorted signals. This ensures that the effects of electromagnetic wave refraction, scattering and phase shift can be specifically corrected, thereby improving the calibration accuracy of steel reinforcement detection in ancient buildings.

[0023] In one embodiment, the dual principal mode response vector and the secondary mode co-operational value are calculated to generate a dual-frequency distortion factor representing the intensity of the electromagnetic lensing effect, including: The signal amplitude variation characteristics of the low-frequency and high-frequency dual principal mode response vectors in the three-layer medium of the target area are extracted to generate interlayer amplitude values. Specifically, the following steps are taken: starting from the moment of electromagnetic wave emission (time 0), the initial signal amplitude is obtained, which is the baseline; when the signal amplitude first shows a sudden increase or decrease compared to the baseline value with a change exceeding 10%, this moment is recorded as t1, which is the interface time for the electromagnetic wave to enter the carbonized layer from the air, so 0-t1 is the time interval of the carbonized layer; after entering the carbonized layer, the signal amplitude maintains a new stable value. When the signal amplitude again shows a sudden increase or decrease compared to this stable value with a change exceeding 10%, this moment is recorded as t2, which is the interface time for the electromagnetic wave to enter the concrete layer from the carbonized layer, so t1-t2 is the time interval of the concrete; after entering the concrete, the signal amplitude stabilizes again. When the amplitude shows a third sudden increase or decrease compared to this stable value with a change exceeding 10%, this moment is recorded as t3, which is the interface time for the electromagnetic wave to enter the steel reinforcement layer from the concrete, so t2-t3 is the time interval of the steel reinforcement layer. For the first core component of the low frequency, the average amplitude of all sampling points in each interval is calculated to obtain the three-layer amplitude of the low frequency. For the second core component of the high frequency, the same calculation method is used to obtain the three-layer amplitude of the high frequency. The absolute difference between the amplitude of the carbonation layer and the concrete layer, and the absolute difference between the amplitude of the concrete layer and the steel layer are calculated separately for the low frequency. The two absolute differences are used as the interlayer amplitude values ​​of the low frequency. The absolute difference between the amplitude of the carbonation layer and the concrete layer, and the absolute difference between the amplitude of the concrete layer and the steel layer are calculated separately for the high frequency. The two absolute differences are used as the interlayer amplitude values ​​of the high frequency. The dynamic variation of submodal co-occurrence values ​​with the propagation of dual principal modal response vectors in three media layers was analyzed. The distribution ratio of the anomalous correlation strength between submodal co-occurrence values ​​and dual principal modal response vectors in different media layers was calculated to generate the co-occurrence anomaly rate. Specifically, according to the time intervals of the carbonized layer, concrete layer, and steel layer, the submodal co-occurrence values ​​and dual principal modal response vectors (first co-occurrence intensity and second co-occurrence intensity) in each layer were divided into several segments with 30 consecutive sampling points. The last segment with less than 30 sampling points was discarded. For each segment, the correlation coefficient between the submodal co-occurrence value of the segment and the low-frequency first co-occurrence intensity of the corresponding segment was calculated (the correlation coefficient is calculated by dividing the covariance of all points in the segment by the product of the standard deviations of the two), and the correlation coefficient between the submodal co-occurrence value of the segment and the high-frequency second co-occurrence intensity of the corresponding segment were calculated. The absolute values ​​of the two correlation coefficients were calculated. If either of the two absolute values ​​of any segment is greater than 0.6, all 30 sampling points in the segment are marked as anomalous correlation points; otherwise, they are not marked. Divide the number of abnormal correlation points in each layer by the total number of sampling points in that layer to obtain the abnormality ratio of each layer; multiply the abnormality ratio of each layer by the weight of its corresponding layer (0.2 for carbonized layer, 0.5 for concrete, and 0.3 for steel reinforcement layer) and sum them to obtain the cooperative anomaly interlayer rate. Based on the interlayer amplitude values, the dielectric properties of the cooperative anisotropic interlayer rate are corrected to generate the dielectric coupling coefficient. Specifically, this includes: calculating the mean of two low-frequency interlayer amplitude values ​​to obtain the low-frequency average amplitude; calculating the mean of two high-frequency interlayer amplitude values ​​to obtain the high-frequency average amplitude; adding the low-frequency average amplitude and the high-frequency average amplitude to obtain the dielectric amplitude reference; calculating the difference between the maximum values ​​of the low-frequency and high-frequency interlayer amplitude values; dividing the dielectric amplitude reference by the difference to obtain the ratio, where if the difference is 0, the ratio is directly 1; subtracting the ratio from 1 and multiplying it by the cooperative anisotropic interlayer rate to obtain the dielectric coupling coefficient. Based on the physical differences between low-frequency and high-frequency electromagnetic waves, and combined with the interlayer amplitude variation values, the response adaptation differences of the two frequency signals in the medium are calculated to generate a dual-frequency domain weighting. Specifically, this involves: adding the two interlayer amplitude variation values ​​of the low-frequency signal to obtain the total low-frequency amplitude; adding the two interlayer amplitude variation values ​​of the high-frequency signal to obtain the total high-frequency amplitude; dividing the total low-frequency amplitude by the sum of the total low-frequency amplitude and the total high-frequency amplitude to obtain the low-frequency domain weighting; dividing the total high-frequency amplitude by the sum of the total low-frequency amplitude and the total high-frequency amplitude to obtain the high-frequency domain weighting; and combining the low-frequency domain weighting and the high-frequency domain weighting in a fixed order of low frequency first and high frequency last to form a dual-frequency domain weighting.

[0024] In one embodiment, the calculation of the dual principal mode response vector and the secondary mode co-operational value to generate a dual-frequency distortion factor representing the intensity of the electromagnetic lensing effect further includes: The dielectric coupling coefficient is dynamically matched with the dual-frequency domain weight to generate a global reference value. Specifically, the low-frequency domain weight and the high-frequency domain weight in the dual-frequency domain weight are multiplied by the dielectric coupling coefficient to obtain the corrected low-frequency domain value and the corrected high-frequency domain value. Then, the corrected low-frequency domain value and the high-frequency domain value are added to obtain the global reference value. The steady-state characteristics of the submodal cooperative values ​​are extracted to generate cooperative steady-state coefficients. Specifically, for each sampling point, the difference between the maximum and minimum values ​​of the submodal cooperative values ​​is calculated to obtain the range; then the mean of the submodal cooperative values ​​of all sampling points is calculated; the range is divided by the mean to obtain the relative volatility; then 1 is subtracted from the relative volatility to obtain the cooperative result; the cooperative result is normalized to the range of 0-1, which is the cooperative steady-state coefficient. The global reference value is adjusted based on the cooperative steady-state coefficients to generate a dual-frequency distortion factor representing the intensity of the electromagnetic lens effect. Specifically, the cooperative steady-state coefficients are multiplied by the global reference value, and the product is normalized to 0-1, which is the dual-frequency distortion factor.

[0025] By dividing the time intervals of the carbonized layer, concrete layer, and steel reinforcement layer, the amplitude of the dual-frequency signal in each layer and the inter-layer amplitude variation can be calculated. This allows for the analysis of the differences in the influence of different media on the signal, thus accurately locating the source of interference. Furthermore, by analyzing the correlation between the secondary mode co-mode value and the dual principal mode response vector through 30 sampling points, and combining the media layer weights to generate the co-mode anomaly inter-layer rate, the degree of abnormal correlation caused by the electromagnetic lensing effect in each layer can be understood. Calibration and adjustment are performed based on the differences in different media layers. Finally, by using the media coupling coefficient and the dual-frequency domain weighting, the interference of media properties can be further eliminated, the dual-frequency characteristics can be adapted, and the calibration direction can be more clearly defined.

[0026] In one embodiment, covariance analysis is performed on the dual principal modal response vectors and secondary modal covariance values ​​to obtain modal adaptation critical values, including: The synchronous variation amplitudes of the low-frequency and high-frequency dual-principal mode response vectors and secondary-mode co-variance values ​​in each medium layer of the target region are calculated separately. By comparing the co-variance differences of the dual-principal mode response vectors and secondary-mode co-variance values ​​within the same medium layer, the hierarchical co-variance characteristic values ​​are obtained. Specifically, for the three-layer time interval, for each layer, the difference between the maximum and minimum values ​​of all first co-variance intensities in the dual-principal mode response vectors within that layer is calculated to obtain the total low-frequency variation; the difference between the maximum and minimum values ​​of the secondary-mode co-variance values ​​within the same layer is also calculated to obtain the total co-variance; the total low-frequency variation is divided by the total co-variance to obtain the low-frequency synchronous variation amplitude; simultaneously, the difference between the maximum and minimum values ​​of all second co-variance intensities in the dual-principal mode response vectors within that layer is calculated to obtain the total high-frequency variation; the total high-frequency variation is divided by the total co-variance within the same layer to obtain the high-frequency synchronous variation amplitude; within the same layer, the high-frequency synchronous variation amplitude is subtracted from the low-frequency synchronous variation amplitude to obtain the hierarchical co-variance characteristic value of that layer. Based on the difference in propagation speed between low-frequency and high-frequency electromagnetic waves in different dielectric layers, and combined with the propagation time delay between the dual principal mode response vector and the secondary mode cooperative value calculated by the layered covariance eigenvalue, the time delay-corrected layered covariance intensity is obtained. Specifically, this includes: obtaining the propagation speed of low-frequency and high-frequency electromagnetic waves in each dielectric layer, multiplying the speed by the duration of the time interval of each dielectric layer to obtain the thickness of each layer; for example, the duration of the carbonized layer is obtained by subtracting 0 from t1; within the same layer, the propagation time of the low-frequency wave is subtracted from the propagation time of the high-frequency wave to obtain the propagation time delay; and then multiplying the layered covariance eigenvalue by (1 minus the propagation time delay and then dividing by the total propagation time of the layer) to obtain the time delay-corrected layered covariance intensity. The non-uniformity of each layer of medium in the target region is analyzed, and the layered covariance intensity is locally adjusted to obtain the locally adapted covariance intensity. Specifically, this includes: for each layer in the three-layer time interval, calculating the standard deviation of the covariance values ​​of all submodal modes in that layer; dividing 1 by (1 + standard deviation) to obtain the non-uniformity correction coefficient; and multiplying the layered covariance intensity by the non-uniformity correction coefficient to obtain the locally adapted covariance intensity. Calculate the characteristic parameters of each dielectric layer in the target region. Based on these parameters, analyze the reasonable fluctuation range of the local adaptive covariance intensity when there is no electromagnetic lensing effect, and generate a dynamic reference range, specifically including: The characteristic parameters of each medium layer are the thickness of the carbonation layer, the density of the concrete layer, and the degree of corrosion of the steel reinforcement layer. The thickness of the carbonation layer is obtained by multiplying the duration of the carbonation layer time interval by the propagation speed of electromagnetic waves in the carbonation layer. The incident intensity and outgoing intensity of the low-frequency signal in the concrete layer are acquired in real time. The attenuation rate of the low-frequency signal in this layer is obtained by subtracting the outgoing intensity from the incident intensity and then dividing by the incident intensity. This attenuation rate is the density of the concrete layer. The reflection intensity of the standard non-corroded steel reinforcement is acquired. The degree of corrosion of the steel reinforcement layer is obtained by dividing the high-frequency reflected signal intensity by the reflection intensity of the standard non-corroded steel reinforcement. Without electromagnetic lensing effect, the local adaptive covariant strength is corrected according to parameters: for every 0.1 mm increase in carbonation layer thickness, the local adaptive covariant strength decreases by 3%, resulting in the first corrected local adaptive covariant strength; for every 5% increase in concrete layer density, the first corrected local adaptive covariant strength also increases by 4%, resulting in the second corrected local adaptive covariant strength; for every 5% increase in the degree of corrosion of the reinforcing steel layer, the second corrected local adaptive covariant strength decreases by 2%, resulting in the final corrected covariant strength; the interval formed by multiplying the corrected covariant strength by 95% and by 105% is the dynamic reference range; Based on the dynamic baseline range and the local adaptive covariance intensity, the boundary value that can distinguish between normal covariance and anomalous covariance is calculated, and the modal adaptation critical value is generated. Specifically, the upper limit of the dynamic baseline range is used as the modal adaptation critical value; when the local adaptive covariance intensity is less than or equal to the modal adaptation critical value, it is determined to be normal covariance; when the local adaptive covariance intensity is greater than the modal adaptation critical value, it is determined to be anomalous covariance. The dynamic reference range is a reasonable fluctuation range of local adaptation covariance intensity when there is no electromagnetic lensing effect. Within this range, the covariance is a reasonable fluctuation caused by the normal characteristics of the medium, without distortion interference. The core of this scheme is to identify abnormal covariance caused by electromagnetic lensing effect. Abnormal covariance will lead to detection deviation, and abnormal covariance will inevitably exceed the reasonable range. Therefore, when the local adaptation covariance intensity exceeds the upper limit of the dynamic reference range, it indicates that the covariance deviates from the normal range without lensing effect. Therefore, the upper limit of the dynamic reference range is directly used as the modal adaptation critical value, which meets the needs of accurate calibration of steel bar detection in ancient buildings.

[0027] By calculating the synchronous change amplitude of the low-frequency and high-frequency dual principal mode response vectors and secondary mode co-variation values ​​within each medium layer, the layered covariance characteristic values ​​are obtained, providing a basis for the preliminary location of covariance anomalies during calibration. Then, by combining the propagation time delay with the difference in propagation speed of dual-frequency electromagnetic waves, the time delay-corrected layered covariance intensity is obtained, eliminating the interference of time delay on calibration judgment. Furthermore, the local adaptation covariance intensity is obtained through medium non-homogeneity adjustment. Based on the dynamic reference range, the modal adaptation critical value is determined. The modal adaptation critical value clarifies the normal covariance boundary without electromagnetic lensing effect, allowing calibration to accurately distinguish between normal medium fluctuations and distortion interference, ensuring more targeted calibration and improving the calibration accuracy of steel reinforcement detection in ancient buildings.

[0028] In one embodiment, the dual-frequency distortion factor is compared with the modal adaptation threshold to generate a factor identifier, including: The matching degree between the dual-frequency distortion factor and the modal adaptation threshold is calculated at low and high frequencies to generate a dual-frequency domain adaptation index. Specifically, for low-frequency signals, 1 is subtracted from (dual-frequency distortion factor divided by modal adaptation threshold) to obtain the low-frequency matching degree; for high-frequency signals, 1 is subtracted from (dual-frequency distortion factor divided by modal adaptation threshold) to obtain the high-frequency matching degree; if the low-frequency matching degree or the high-frequency matching degree is negative, the matching degree is 0; the low-frequency matching degree is multiplied by the low-frequency domain weight, and the high-frequency matching degree is multiplied by the high-frequency domain weight to obtain the dual-frequency domain adaptation index. The transient interference intensity of each layer of medium in the target area to the dual-frequency signal is analyzed to generate the transient disturbance quantity of the medium. The dual-frequency domain adaptation index is then corrected based on the transient disturbance quantity to obtain the transient correction adaptation value. Specifically, for each of the three time intervals, the mean amplitude of all low-frequency sampling points in that layer is subtracted from the mean amplitude of all low-frequency sampling points in that layer to obtain the difference. The mean of the absolute values ​​of all differences is calculated to obtain the mean low-frequency transient interference of that layer. Similarly, the mean amplitude of all high-frequency sampling points in that layer is subtracted from the mean amplitude of all high-frequency sampling points in that layer to obtain the difference. The mean of the absolute values ​​of all differences is calculated to obtain the mean high-frequency transient interference of that layer. For each layer, the mean low-frequency transient interference is added to the mean high-frequency transient interference, divided by 2, and then multiplied by the weight of the corresponding layer. The results of the three layers are then summed to obtain the transient disturbance quantity of the medium. Finally, 1 is subtracted from the transient disturbance quantity of the medium, multiplied by the dual-frequency domain adaptation index, and the result is normalized to between 0 and 1, which is the transient correction adaptation value. The critical response characteristics of the dual-frequency signal in a three-layer medium are calculated to obtain a dual-frequency domain adaptation reference band. The transient correction adaptation value is compared with the dual-frequency domain adaptation reference band to generate a factor identifier. Specifically, for each medium layer, the modal adaptation critical value is multiplied by the weight of the corresponding layer to obtain the critical response value of each of the three layers; the sum of the critical response values ​​of the three layers is multiplied by 0.9 to obtain the lower limit of the reference band; the sum of the critical response values ​​of the three layers is multiplied by 1.1 to obtain the upper limit of the reference band; if the transient correction adaptation value is between the upper and lower limits of the reference band, a factor identifier representing qualification is generated, and the factor identifier is 1; if the transient correction adaptation value is not between the upper and lower limits of the reference band, a factor identifier representing non-qualification is generated, and the factor identifier is 0; when the factor identifier is 0, the detection unit, calculation unit and analysis unit are triggered to recalculate until a qualification identifier is generated. The maximum number of triggers is 3. If more than 3 times are triggered, an alarm is issued and manual intervention is required.

[0029] By calculating the low-frequency matching degree and high-frequency matching degree and combining the low-frequency domain weighting and high-frequency domain weighting, a dual-frequency domain adaptation index is generated. This quantifies the calibration adaptation degree between the dual-frequency distortion factor and the modal adaptation critical value. Then, the transient disturbance of each medium layer is analyzed to generate the transient disturbance of the medium. The dual-frequency domain adaptation index is corrected to obtain the transient correction adaptation value, eliminating the influence of transient interference on the calibration judgment. Based on the factor identifier, a recalculation mechanism is triggered when the factor identifier is unqualified, ensuring that the factor identifier can accurately reflect the calibration adaptation status.

[0030] In one embodiment, based on the factor identifier, the magnitude and characteristics of the dual-frequency distortion factor are analyzed to obtain the signal equalization coefficient, including: When the factor is marked as qualified, the degree of coordination between the dual-frequency distortion factor and the modal adaptation critical value in each medium layer is calculated to generate the distortion coordination compliance degree. Specifically, for each medium layer, 1 is subtracted from (dual-frequency distortion factor ÷ modal adaptation critical value) to obtain the intra-layer compliance degree of that layer. If the intra-layer compliance degree is negative, the intra-layer compliance degree is 0. The intra-layer compliance degree of each layer is multiplied by the weight of the corresponding layer, and the product results of the three layers are added together to obtain the distortion coordination compliance degree. Based on the characteristic differences between low-frequency and high-frequency electromagnetic waves, the deviation of the dual-frequency signals is calculated to generate the dual-frequency characteristic adaptation deviation. Specifically, this includes: multiplying the dual-frequency distortion factor by the low-frequency domain weight and the high-frequency domain weight respectively to obtain the equivalent low-frequency component and the equivalent high-frequency component of the dual-frequency distortion factor; dividing the equivalent low-frequency component and the equivalent high-frequency component of the dual-frequency distortion factor by the modal adaptation critical value respectively to obtain the low-frequency characteristic deviation ratio and the high-frequency characteristic deviation ratio; multiplying the low-frequency characteristic deviation ratio by 0.6 and the high-frequency characteristic deviation ratio by 0.4 to obtain the dual-frequency characteristic adaptation deviation. Among these, since the low-frequency signal needs to resist the electromagnetic lens effect, which is the focus of this scheme, the weight of the low-frequency characteristic deviation ratio is higher by 0.6; while the high-frequency signal needs to resist medium absorption, and its influence is weaker than that of the low-frequency signal, so the weight of the high-frequency characteristic deviation ratio is lower by 0.4. The influence of the dynamic reference range on the adaptation deviation of dual-frequency characteristics is analyzed, and the dynamic perturbation adaptation coefficient of the medium is generated. Specifically, the difference between the upper limit and the lower limit of the dynamic reference range is calculated, and the difference is divided by the corrected covariance intensity to obtain the width ratio, which is used to reflect the dynamic perturbation amplitude. The width ratio is subtracted from 1, and the calculation result is normalized to between 0 and 1, which is the dynamic perturbation adaptation coefficient of the medium. Based on the dual-frequency distortion factor, its fluctuation amplitude and characteristic consistency are calculated to generate the qualified state distortion stability. Specifically, this includes: calculating the difference between the maximum and minimum values ​​of the dual-frequency distortion factor at the current and the two previous qualified times, dividing the difference by the mean of the three dual-frequency distortion factors to obtain the relative fluctuation amplitude; dividing the current dual-frequency distortion factor by the low-frequency domain weight to obtain the first ratio, dividing the current dual-frequency distortion factor by the high-frequency domain weight to obtain the second ratio; dividing the first ratio by the second ratio to obtain the third ratio; calculating the absolute value of the difference between the third ratio and 1, and then subtracting the absolute value from 1 to obtain the characteristic consistency; and normalizing the sum of the relative fluctuation amplitude × 0.4 and the characteristic consistency × 0.6 to 0-1, which is the qualified state distortion stability. Among them, characteristic consistency is a key factor in measuring whether the low-frequency and high-frequency characteristics of the current dual-frequency signal are balanced. Since the detection of steel bars in ancient buildings requires dual-frequency complementarity, this is one of the key judgment criteria for calibration, so the weight is too high at 0.6; while relative fluctuation amplitude only measures the numerical fluctuation of the dual-frequency distortion factor when it is currently qualified and the previous two times, so the weight is too low at 0.4.

[0031] In one embodiment, the analysis of the magnitude and characteristics of the dual-frequency distortion factor based on the factor identifier to obtain the signal equalization coefficient further includes: Analyzing the qualified-state distortion stability, distortion coordination compliance, and dual-frequency characteristic adaptation deviation, the adjustment direction for balancing is determined. The adjustment direction is dynamically calibrated based on the medium's dynamic perturbation adaptation coefficient, generating a two-dimensional balancing reference quantity. Specifically, this includes: calculating the average of the three most recent qualified-state distortion stability values; if the current qualified-state distortion stability is less than this average value, adjustment needs to be made in the direction of improving stability; multiplying the distortion coordination compliance by 0.5 to obtain a correction value; if the current distortion coordination compliance is less than this correction value, adjustment needs to be made in the direction of improving compliance; and calculating the average of the three most recent dual-frequency characteristic adaptation deviations; if the current dual-frequency characteristic adaptation deviation is greater than this average value, adjustment needs to be made in the direction of balancing dual frequencies. The stability adjustment requirement is obtained by subtracting the current qualified-state distortion stability from the average of the three most recent qualified-state distortion stability values. If the stability adjustment requirement is negative, the stability adjustment requirement is 0; otherwise, the original value is maintained. The compliance adjustment requirement is obtained by subtracting the current distortion coordination compliance from the correction value. If the compliance adjustment requirement is negative, the compliance adjustment requirement is 0; otherwise, the original value is maintained. The equalization adjustment requirement is obtained by subtracting the average of the three most recent dual-frequency characteristic adaptation deviations from the current dual-frequency characteristic adaptation deviation. If the equalization adjustment requirement is negative, the equalization adjustment requirement is 0; otherwise, the original value is maintained. Set the weight of the stable adjustment demand value to 0.3, the weight of the standard adjustment demand value to 0.4, and the weight of the equilibrium adjustment demand value to 0.3; multiply the stable adjustment demand value, the standard adjustment demand value, and the equilibrium adjustment demand value by the medium dynamic disturbance adaptation coefficient, then multiply them by their respective weights and add them together. Normalize the sum to 0-1, which is the two-dimensional equilibrium benchmark quantity. In the calibration of steel bar detectors for ancient buildings, the stability adjustment requirement corresponds to the adjustment requirement of the qualified distortion stability. It only ensures the consistency of values ​​in multiple calibrations and must be based on the existing standard. It is only an auxiliary guarantee, so its weight is set to 0.3. The standard compliance adjustment requirement corresponds to the adjustment requirement of the distortion coordination compliance. The compliance is the degree of conformity between the dual-frequency distortion factor and the modal adaptation critical value (the modal adaptation critical value is used to identify the core boundary of the electromagnetic lens effect) in each medium layer. It is the bottom line for qualified calibration and has the most critical impact, so its weight is set to 0.4. The balance adjustment requirement corresponds to the adjustment requirement of the dual-frequency characteristic adaptation deviation. It only ensures the balance of the dual-frequency characteristics and must also be based on the standard. Therefore, it also plays an auxiliary role, so its weight is set to 0.3. The energy efficiency matching ratio of the first core component and the second core component in the dual-frequency hybrid echo signal is calculated, specifically including: for each layer of medium, the low-frequency average amplitude of the layer is divided by the duration of the time interval of the layer to obtain the low-frequency energy efficiency of the layer; the high-frequency average amplitude of the layer is divided by the duration of the time interval of the layer to obtain the high-frequency energy efficiency of the layer; for the first core component, the low-frequency energy efficiency of the carbonation layer × 0.2 + the low-frequency energy efficiency of the concrete layer × 0.5 + the low-frequency energy efficiency of the steel reinforcement layer × 0.3 is used to obtain the total energy efficiency of the first core component; For the second core component, the total energy efficiency of the second core component is obtained by multiplying the high-frequency energy efficiency of the carbonation layer by 0.2, the high-frequency energy efficiency of the concrete layer by 0.5, and the high-frequency energy efficiency of the steel reinforcement layer by 0.3. Divide the total energy efficiency of the first core component by the total energy efficiency of the second core component to obtain the energy efficiency ratio. Based on the energy efficiency adaptation ratio, the energy efficiency of the two-dimensional equalization benchmark is optimized and adjusted to generate the signal equalization coefficient. Specifically, the process includes: calculating the absolute value of the difference between the energy efficiency adaptation ratio and 1 to obtain the energy efficiency deviation; subtracting the energy efficiency deviation from 1 to obtain the energy efficiency correction coefficient; multiplying the two-dimensional equalization benchmark by the energy efficiency correction coefficient, and normalizing the product to 0-1, which is the signal equalization coefficient.

[0032] By calculating the calibration compliance of the dual-frequency distortion factor and the modal adaptation critical value, the dual-frequency characteristic adaptation deviation is generated to clarify the degree of deviation of the dual-frequency signal from the calibration benchmark. The dynamic perturbation adaptation coefficient of the medium is obtained by combining the dynamic benchmark range. Then, the qualified state distortion stability is generated by the relative fluctuation amplitude and characteristic consistency to ensure calibration stability. Further analysis is used to determine the calibration adjustment direction. Finally, the signal equalization coefficient is generated so that the signal equalization coefficient fully matches the calibration standard and dual-frequency characteristics, thereby improving the accuracy of ancient building steel reinforcement detection calibration.

[0033] In one embodiment, the signal components of the two frequencies separated from the dual-frequency mixed echo signal are superimposed according to the signal equalization coefficient to generate a calibrated signal, including: Based on the signal equalization coefficient, the adaptive superposition strength of the first core component and the second core component in each medium layer is calculated to generate the dual-frequency layer domain superposition degree. Specifically, for each medium layer, the adaptive superposition strength of each layer is obtained by multiplying the signal equalization coefficient by the low-frequency average amplitude of the layer and the signal equalization coefficient by the high-frequency average amplitude of the layer. The adaptive superposition strength of each layer is multiplied by the corresponding layer weight, and the results of the three layers are added together and normalized to 0-1, which is the dual-frequency layer domain superposition degree. Based on the two-dimensional equalization reference quantity, the superposition degree of the two-frequency layer domain is corrected to generate the medium adaptation superposition adjustment quantity. Specifically, the following steps are taken: subtract the two-dimensional equalization reference quantity from 1 to obtain the reference deviation; multiply the superposition degree of the two-frequency layer domain by the reference deviation to obtain the superposition correction quantity; add the superposition degree of the two-frequency layer domain to the superposition correction quantity, and then normalize the result to the range of 0-1, which is the medium adaptation superposition adjustment quantity. Based on the dielectric adaptation superposition adjustment amount, and combining the complementary characteristics of low-frequency signal penetration and high-frequency signal resolution, the first core component and the second core component are synergistically fused and superimposed to generate the calibrated signal. Specifically, this includes: multiplying the first core component by the product of the dielectric adaptation superposition adjustment amount and the low-frequency domain weight to obtain the low-frequency calibrated component; multiplying the second core component by the product of the dielectric adaptation superposition adjustment amount and the high-frequency domain weight to obtain the high-frequency calibrated component; adding the low-frequency calibrated component and the high-frequency calibrated component point by point, and normalizing the result to the 0-1 range, which is the calibrated signal.

[0034] The adaptive superposition strength of each medium layer is calculated by signal equalization coefficient. The superposition degree of the dual-frequency layer domain is generated by combining the medium layer weight. Then, the superposition degree of the dual-frequency layer domain is corrected by the dual-dimensional equalization reference quantity to obtain the medium adaptation superposition adjustment quantity. The medium adaptation of the calibration is optimized. Finally, based on this adjustment quantity, the first core component and the second core component are adjusted by combining the low-frequency domain weight and the high-frequency domain weight respectively. The calibrated signal is generated by fusing and superimposing the samples one by one. The complementary characteristics of the dual-frequency signals are fully utilized to accurately correct the signal errors caused by refraction, scattering and phase shift, and improve the signal accuracy of the ancient building steel reinforcement detection calibration.

[0035] In one embodiment, a method for precise calibration of a rebar detector, using the aforementioned precise calibration system for a rebar detector, includes: Step S1 is used to obtain a dual-frequency mixed echo signal by sequentially transmitting two electromagnetic waves of different frequencies to the same detection point in the target area using a rebar detector. The two electromagnetic waves of different frequencies are low-frequency electromagnetic waves and high-frequency electromagnetic waves, and the target area is the wall of an ancient building. Step S2 is used to perform mode decomposition on the dual-frequency hybrid echo signal to obtain the dual principal mode response vectors and secondary mode co-operation values ​​of the two frequencies. The dual principal mode response vectors and secondary mode co-operation values ​​are calculated to generate a dual-frequency distortion factor representing the intensity of the electromagnetic lens effect. Step S3 is used to perform covariance analysis on the dual principal mode response vector and the secondary mode covariance value to obtain the mode fit critical value. The dual frequency distortion factor is compared with the mode fit critical value to generate factor identifiers. Step S4 is used to analyze the magnitude and characteristics of the dual-frequency distortion factor based on the factor identifier, and to obtain the signal equalization coefficient. Step S5 is used to superimpose the signal components of the two frequencies separated from the dual-frequency mixed echo signal according to the signal equalization coefficient to generate a calibrated signal.

[0036] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A precision calibration system for rebar detectors, characterized in that, include: The detection unit is used to sequentially transmit two electromagnetic waves of different frequencies to the same detection point in the target area based on the rebar detector, and obtain a dual-frequency mixed echo signal. The two electromagnetic waves of different frequencies are low-frequency electromagnetic waves and high-frequency electromagnetic waves, and the target area is the wall of an ancient building. The computing unit is used to perform mode decomposition on the dual-frequency hybrid echo signal to obtain the dual principal mode response vectors and secondary mode co-operation values ​​of the two frequencies, including: identifying the medium interference characteristics of the dual-frequency hybrid echo signal and generating mode distortion characteristic quantities; Based on the complementary characteristics of the penetration depth of low-frequency electromagnetic waves and the resolution of high-frequency electromagnetic waves, the differences in the propagation paths of the two frequency signals in a three-layer medium are analyzed, and frequency domain correlation coefficients are generated. Based on the modal distortion characteristics and combined with the frequency domain correlation coefficient, the dual-frequency mixed echo signal is dynamically stripped to separate the first core component dominated by the low-frequency signal and the second core component dominated by the high-frequency signal, thus obtaining the dual principal mode feature vector. Extract the residual wave components in the dual-frequency hybrid echo signal that are not covered by the dual principal mode eigenvectors, and calculate the cooperative wave intensity of the residual components and the two core components by combining the frequency domain correlation coefficient, thereby generating the dual principal mode response vector and the secondary mode cooperative value; The dual principal mode response vector and the secondary mode co-occurrence value are calculated to generate a dual-frequency distortion factor representing the intensity of the electromagnetic lensing effect; The analysis unit is used to perform covariance analysis on the dual principal modal response vectors and secondary modal covariance values, obtain the modal adaptation critical value with a clear normal covariance boundary without electromagnetic lensing effect, compare the dual-frequency distortion factor with the modal adaptation critical value, and generate factor identifiers, including: calculating the matching degree between the dual-frequency distortion factor and the modal adaptation critical value at low and high frequencies, and generating the dual-frequency domain adaptation index; The transient interference intensity of each layer of medium in the target area to the dual-frequency signal is analyzed, the transient disturbance of the medium is generated, and the dual-frequency domain adaptation index is corrected according to the transient disturbance of the medium to obtain the transient correction adaptation value. The critical response characteristics of the dual-frequency signal in the three-layer medium are calculated to obtain the dual-frequency domain adaptation reference band. The transient correction adaptation value is compared with the dual-frequency domain adaptation reference band to generate a factor identifier. If the transient correction adaptation value is between the upper and lower limits of the reference band, a factor identifier representing qualification is generated. If the transient correction adaptation value is not between the upper and lower limits of the reference band, a factor identifier representing non-qualification is generated. The equalization unit is used to analyze the magnitude and characteristics of the dual-frequency distortion factor based on the factor identifier to obtain the signal equalization coefficient. The aforementioned characteristics include the characteristics of low-frequency electromagnetic waves and high-frequency electromagnetic waves. The calibration unit is used to superimpose the signal components of the two frequencies separated from the dual-frequency mixed echo signal according to the signal equalization coefficient to generate a calibrated signal.

2. The precision calibration system for the rebar detector according to claim 1, characterized in that, The dual-primary-mode response vectors and secondary-mode co-occurrence values ​​are calculated to generate a dual-frequency distortion factor representing the intensity of the electromagnetic lensing effect, including: The signal amplitude variation characteristics of the low-frequency and high-frequency dual principal mode response vectors in the three-layer medium of the target region are extracted respectively to generate interlayer amplitude values; The dynamic variation of submodal cooperative values ​​with the propagation of dual principal modal response vectors in three media layers was analyzed, and the distribution ratio of the abnormal correlation strength between submodal cooperative values ​​and dual principal modal response vectors in different media layers was calculated to generate the cooperative anomaly interlayer rate. Based on the interlayer amplitude value, the medium property is corrected for the cooperative anisotropic interlayer rate, and the medium coupling coefficient is generated. Based on the physical characteristics of low-frequency and high-frequency electromagnetic waves, the response adaptation differences of the two frequency signals in the medium are calculated by combining the interlayer amplitude values, and a dual-frequency domain weighting is generated.

3. The precision calibration system for the rebar detector according to claim 2, characterized in that, The calculation of the dual principal mode response vectors and secondary mode co-operational values ​​generates a dual-frequency distortion factor representing the intensity of the electromagnetic lensing effect, and also includes: The dielectric coupling coefficient is dynamically matched with the dual-frequency domain weighting to generate a global reference value; The steady-state characteristics of the submodal cooperative values ​​are extracted to generate cooperative steady-state coefficients; The global reference value is adjusted based on the cooperative steady-state coefficients to generate a dual-frequency distortion factor representing the intensity of the electromagnetic lensing effect.

4. The precision calibration system for the rebar detector according to claim 1, characterized in that, Covariance analysis was performed on the covariance values ​​of the two principal modal response vectors and the secondary modal covariance values ​​to obtain the modal fit critical values, including: The synchronous variation amplitudes of the dual principal modal response vectors and secondary modal co-variance values ​​of low frequency and high frequency in each medium layer of the target region are calculated respectively. By comparing the co-variance differences of the dual principal modal response vectors and secondary modal co-variance values ​​in the same medium layer, the hierarchical co-variance characteristic values ​​are obtained. Based on the difference in propagation speed between low-frequency and high-frequency electromagnetic waves in different dielectric layers, and combined with the calculation of the propagation time delay between the dual principal mode response vector and the secondary mode cooperative value using the layered covariant eigenvalue, the time delay corrected layered covariant intensity is obtained. By analyzing the non-homogeneity of each layer of medium in the target region, the layered covariance intensity is locally adjusted to obtain the locally adapted covariance intensity. Calculate the characteristic parameters of each medium layer in the target region, and based on the characteristic parameters, analyze the reasonable fluctuation range of the local adaptive covariance intensity when there is no electromagnetic lensing effect, and generate a dynamic reference range. Based on the dynamic baseline range and the intensity of local adaptive covariance, the boundary values ​​that can distinguish between normal covariance and abnormal covariance are calculated, and the modal adaptation critical values ​​are generated.

5. The precision calibration system for the rebar detector according to claim 3, characterized in that, Based on the factor identifier, the magnitude and characteristics of the dual-frequency distortion factor are analyzed to obtain the signal equalization coefficient, including: When the factor is marked as qualified, the degree of coordination between the dual-frequency distortion factor and the modal adaptation critical value in each medium layer is calculated to generate the distortion coordination compliance degree. Based on the characteristic differences between low-frequency electromagnetic waves and high-frequency electromagnetic waves, the deviation of the dual-frequency signals is calculated, and the dual-frequency characteristic adaptation deviation is generated. The influence of the dynamic reference range on the dual-frequency characteristic adaptation deviation is analyzed, and the dynamic perturbation adaptation coefficient of the medium is generated. Based on the dual-frequency distortion factor, the fluctuation amplitude and characteristic consistency are calculated to generate the qualified state distortion stability.

6. The precision calibration system for the rebar detector according to claim 5, characterized in that, Based on the factor identifier, the magnitude and characteristics of the dual-frequency distortion factor are analyzed to derive the signal equalization coefficient, which also includes: The qualified state distortion stability, distortion coordination compliance and dual-frequency characteristic adaptation deviation are analyzed to determine the equalization adjustment direction. The adjustment direction is dynamically calibrated according to the medium dynamic disturbance adaptation coefficient to generate a two-dimensional equalization reference quantity. Calculate the energy efficiency matching ratio between the first core component and the second core component in the dual-frequency hybrid echo signal; Based on the energy efficiency adaptation ratio, the energy efficiency of the two-dimensional equalization benchmark is optimized and adjusted to generate the signal equalization coefficient.

7. The precision calibration system for a rebar detector according to claim 6, characterized in that, Based on the signal equalization coefficient, the signal components of the two frequencies separated from the dual-frequency mixed echo signal are superimposed to generate a calibrated signal, including: Based on the signal equalization coefficient, the matching superposition strength of the first core component and the second core component in each medium layer is calculated to generate the dual-frequency layer domain superposition degree. Based on the two-dimensional equalization reference quantity, the superposition degree of the dual-frequency layer domain is corrected to generate the medium-adaptive superposition adjustment quantity. Based on the medium adaptation superposition adjustment amount, and combining the complementary characteristics of low-frequency signal penetration and high-frequency signal resolution, the first core component and the second core component are synergistically fused and superimposed to generate the calibrated signal.

8. A method for precise calibration of a rebar detector, applied to the precise calibration system for a rebar detector as described in any one of claims 1-7, characterized in that, include: Step S1 is used to obtain a dual-frequency mixed echo signal by sequentially transmitting two electromagnetic waves of different frequencies to the same detection point in the target area using a rebar detector. The two electromagnetic waves of different frequencies are low-frequency electromagnetic waves and high-frequency electromagnetic waves, and the target area is the wall of an ancient building. Step S2 is used to perform mode decomposition on the dual-frequency hybrid echo signal to obtain the dual principal mode response vectors and secondary mode co-operation values ​​of the two frequencies. The dual principal mode response vectors and secondary mode co-operation values ​​are calculated to generate a dual-frequency distortion factor representing the intensity of the electromagnetic lens effect. Step S3 is used to perform covariance analysis on the dual principal mode response vector and the secondary mode covariance value to obtain the mode fit critical value. The dual frequency distortion factor is compared with the mode fit critical value to generate factor identifiers. Step S4 is used to analyze the magnitude and characteristics of the dual-frequency distortion factor based on the factor identifier, and to obtain the signal equalization coefficient. Step S5 is used to superimpose the signal components of the two frequencies separated from the dual-frequency mixed echo signal according to the signal equalization coefficient to generate a calibrated signal.

Images