Concrete crack detection method based on coupling of infrared thermal field and Rayleigh wave field

Abstract

The present invention discloses a concrete crack detection method based on the coupling of infrared thermal field and Rayleigh wave field, comprising the following steps: using infrared thermal imaging to comprehensively scan the concrete in the target area and identify the location of concrete cracks; calculating the depth of shallow cracks, deep cracks and cracks in the boundary area; extracting the Rayleigh wave amplitude attenuation characteristics to calculate the crack width, and inverting the crack inclination based on the time difference of the first wave arrival of the time domain waveform; superimposing the infrared thermal imaging detection results with the Rayleigh wave detection results, and using a linear interpolation algorithm to construct a three-dimensional visual crack model; inputting the crack location, crack depth, crack width and crack inclination and the three-dimensional visual crack model to generate a large-volume concrete crack detection report. The present invention achieves seamless connection between shallow cracks and deep cracks through coupled detection of infrared thermal field and Rayleigh wave field, and constructs a three-dimensional visual crack model, solving the problems of low efficiency, poor accuracy and incomplete coverage of traditional methods.

Description

Technical Field

[0001] The present invention relates to the technical field of nondestructive testing of concrete structures, and in particular to a concrete crack detection method based on coupling of infrared thermal field and Rayleigh wave field. Background Art

[0002] As one of the most widely used materials in modern construction, concrete's structural safety directly determines its lifespan and functionality. Cracks, the most common form of concrete damage, are not only pathways for moisture and corrosive media to enter, but also a contributing factor to a decrease in structural bearing capacity.

[0003] Accurate detection and quantitative assessment of cracks have become a core issue in the field of engineering safety. Current mainstream detection technologies all have significant limitations, as follows: Infrared thermal imaging, limited by concrete's low thermal diffusivity, can only detect shallow cracks (<5 cm) and is easily affected by ambient temperature and wind speed. The Rayleigh wave method is sensitive to deep cracks, but suffers from near-field interference, resulting in low shallow resolution. The impact echo method requires a densely arranged grid to ensure coverage, resulting in low efficiency and making it difficult to meet the comprehensive inspection needs of large volumes of concrete. The ultrasonic method has stringent requirements for surface flatness, resulting in severe signal attenuation on rough or wet surfaces. The penetration depth of geological radar electromagnetic waves in concrete is limited by the shielding effect of steel mesh.

[0004] In summary, existing technologies struggle to achieve full-depth, high-precision, non-destructive detection of concrete cracks. This invention, by coupling infrared thermal fields with Rayleigh wave fields and combining them with three-dimensional modeling technology, aims to overcome the limitations of a single method and provide a next-generation solution for engineering health diagnostics. Summary of the Invention

[0005] To address the challenges of accurate detection and quantitative assessment of concrete cracks, the present invention provides a concrete crack detection method based on the coupling of infrared thermal fields and Rayleigh wave fields. Through coupled detection of infrared thermal fields and Rayleigh wave fields, a seamless connection between shallow and deep cracks is achieved, and a three-dimensional visual crack model is constructed, addressing the low efficiency, poor accuracy, and incomplete coverage of traditional methods. The present invention is suitable for the rapid positioning, sizing, and three-dimensional visualization of shallow cracks (<5 cm) and deep cracks (≥5 cm).

[0006] To achieve the above objectives, the present invention provides the following technical solution: a concrete crack detection method based on the coupling of infrared thermal field and Rayleigh wave field, comprising the following steps:

[0007] Step S1: Use infrared thermal imaging to fully scan the concrete in the target area, continuously record the temperature field changes on the concrete surface, and identify the location of concrete cracks through temperature gradient mutations; concrete cracks are divided into superficial cracks, deep cracks, and cracks in the junction area;

[0008] Step S2: For shallow cracks, the depth of the shallow cracks is calculated based on a simplified model of the one-dimensional heat conduction equation;

[0009] Step S3: For deep cracks, multi-channel sensors are arranged perpendicular to the direction of the deep cracks to stimulate Rayleigh waves and record the time domain waveform. The cutoff frequency is determined by the mutation point of the spectrum ratio curve to calculate the depth of the deep cracks.

[0010] Step S4: For cracks in the boundary area, infrared thermal imaging and Rayleigh wave methods are used to detect the depth of the cracks in the boundary area. If the depth error is less than 10%, the average of the infrared thermal imaging and Rayleigh wave methods is taken; otherwise, the parameters are optimized and retested;

[0011] Step S5: For shallow cracks, deep cracks, and cracks in the boundary area, extract the amplitude attenuation characteristics of the Rayleigh wave and calculate the crack width; invert the crack dip based on the time difference of the first wave arrival in the time domain waveform;

[0012] Step S6: superimposing the infrared thermal imaging detection results and the Rayleigh wave detection results, and constructing a three-dimensional visual crack model using a linear interpolation algorithm;

[0013] Step S7: Input the crack position in step S1, the crack depth in steps S2 to S4, the crack width and crack inclination in step S5, and the three-dimensional visual crack model in step S6 to generate a mass concrete crack detection report.

[0014] Furthermore, in step S1, infrared thermal imaging is used to comprehensively scan the concrete in the target area, continuously record the temperature field changes on the concrete surface, and identify the location of concrete cracks through the sudden change of temperature gradient. The specific process is as follows:

[0015] Step S11, using an infrared thermal imager pulse heat source to instantaneously heat the concrete surface of the target area, immediately starting the infrared thermal imager after heating, and continuously recording the temperature field changes on the concrete surface;

[0016] Step S12: extract the temperature field change data of the concrete surface after heating, and calculate the temperature gradient of each pixel point by formula (1), which is expressed as:

[0017] (1);

[0018] Where, Indicates any concrete surface in the target area Temperature difference of the point; express Point temperature: maximum temperature; for Point minimum temperature;

[0019] Step S13, set the threshold to =3σ T, if it exceeds the set threshold, it is determined to be a crack area, where σ T is the standard deviation of the ambient temperature.

[0020] Furthermore, in step S2, the depth of the shallow crack is calculated based on the simplified model of the one-dimensional heat conduction equation, specifically:

[0021] (2);

[0022] Where, is the depth of the superficial crack; is the thermal diffusivity of concrete; is the initial temperature difference, i.e. the temperature difference between the concrete surface and the environment at the end of heating; is the residual temperature difference in the shallow crack area at time t, and t is the time after thermal excitation.

[0023] Furthermore, in step S3, multi-channel sensors are arranged perpendicular to the direction of the deep cracks to excite Rayleigh waves and record the time domain waveform. The cutoff frequency is determined by the mutation point of the spectrum ratio curve to calculate the depth of the deep cracks. The specific process is as follows:

[0024] Step S31: Arrange multi-channel sensors perpendicular to the deep fracture, with a channel spacing of 40-60 cm, and a number of ≥4 sensors, symmetrically distributed on both sides of the deep fracture; use an impact hammer or piezoelectric transducer to excite Rayleigh waves, and synchronously collect multi-channel Rayleigh wave time domain waveform data using a data acquisition instrument;

[0025] In step S32, the spectrum of the signals at all sensor test points is obtained by Fourier transform and the amplitude spectrum is obtained. The spectrum ratio mean of the signals at all sensor test points is calculated according to formula (3), which is expressed as:

[0026] (3);

[0027] Where i is the sensor number, ; n is the total number of deployed sensors, n ≥ 4 and is an even number; For the The spectrum ratio of the sensor of channel i to channel i; For the The signal frequency domain amplitude of the channel sensor, is the signal frequency domain amplitude of the i-th sensor; is the mean value of the spectrum ratio;

[0028] Step S33, defining the spectrum ratio mean =0.5 corresponds to the cutoff frequency f c , cutoff frequency f c The depth of the deep crack is one third of the wavelength of the Rayleigh wave, which is calculated as follows:

[0029] (4);

[0030] Where, is the depth of deep cracks; f c is the cutoff frequency; is the Rayleigh wave speed;

[0031] Rayleigh wave speed in formula (4) The results of wave velocity calibration test on concrete in the complete target area show that:

[0032] (5);

[0033] Where L is the known sensor spacing, and Δt is the arrival time difference of the first wave of the Rayleigh wave.

[0034] Furthermore, in step S4, the depth of the cracks in the boundary area is detected by using both infrared thermal imaging and Rayleigh wave methods. If the depth error is less than 10%, the average of the infrared thermal imaging and Rayleigh wave detection values is taken; otherwise, the parameters are optimized and re-detected. The specific process is as follows:

[0035] Cross-validation and error correction of cracks in the interface area: Infrared thermal imaging and Rayleigh wave methods are used for detection respectively. If the depth error of cracks in the interface area detected by infrared thermal imaging and Rayleigh wave methods is less than 10%, the average of the detection results by infrared thermal imaging and Rayleigh wave methods is taken as the final result. If the depth error of cracks in the interface area detected by infrared thermal imaging and Rayleigh wave methods is greater than 10%, the working parameters are adjusted and re-tested, and the impact echo method or ultrasonic method is introduced as a third-party verification. The specific adjustment of the working parameters includes optimizing the infrared pulse frequency, correcting the thermal diffusion coefficient of concrete, using a higher frequency Rayleigh wave source, and correcting the Rayleigh wave velocity.

[0036] Furthermore, in step S5, the Rayleigh wave amplitude attenuation characteristics are extracted for shallow cracks, deep cracks, and cracks in the boundary area to calculate the crack width; the crack dip is inverted based on the time difference of the first wave arrival in the time domain waveform. The specific process is as follows:

[0037] Step S51, the crack inclination is calculated by calculating the arrival time difference of the first wave signals of adjacent sensors on both sides of the deep crack, which is expressed as:

[0038] (6);

[0039] Where, is the crack inclination angle, is the arrival time difference of the first wave signals of adjacent sensors on both sides of the deep crack; is the distance between adjacent sensors on both sides of a deep crack;

[0040] In step S52, the deep crack width is calculated based on the correlation between amplitude attenuation and crack width. The amplitude attenuation index is calculated using formula (7):

[0041] (7);

[0042] Where AI is the amplitude attenuation index; is the sensor amplitude at the rear side of the deep crack; is the sensor amplitude at the front side of the deep crack;

[0043] The relationship between the amplitude attenuation index and the width of deep cracks was calibrated experimentally and expressed using a linear model:

[0044] (8);

[0045] Where w is the width of deep cracks; k and b are linear model fitting parameters, k is the slope, and b is the intercept.

[0046] Furthermore, in step S6, the infrared thermal imaging detection results and the Rayleigh wave detection results are superimposed, and a linear interpolation algorithm is used to construct a three-dimensional visual crack model; the specific process is:

[0047] Based on the infrared thermal imaging detection data and the Rayleigh wave detection data from steps S1 to S5, the infrared thermal imaging detection data and the Rayleigh wave detection data are unified into the same coordinate system: with the lower left corner of the detection area as the origin, the X axis along the crack direction, the Y axis perpendicular to the crack direction, and the Z axis as the depth direction, a linear interpolation algorithm is used to construct a three-dimensional visual crack model, which is represented as follows:

[0048] (9);

[0049] Where, The final detection results of crack location and depth in concrete of the target area; 、 are the crack position and depth detection results of infrared thermal imaging and Rayleigh wave method respectively; λ is the weight coefficient.

[0050] Furthermore, in step S7, the crack position in step S1, the crack depth in steps S2 to S4, the crack width and crack inclination in step S5, and the three-dimensional visual crack model in step S6 are input to generate a mass concrete crack detection report; the specific process is as follows:

[0051] Step S71: Integrate the input data and input the final target area concrete crack position and depth detection results , deep crack inclination angle θ, amplitude attenuation index AI and deep crack width w; use programming software Python or typesetting system LaTeX template to automatically generate inspection reports;

[0052] Step S72: The inspection report includes the inspection time, target area, total number of cracks, and size information, as well as an infrared temperature gradient thermogram with crack outlines, a Rayleigh wave spectrum ratio curve with cutoff frequency, and a three-dimensional visualization crack model diagram showing the spatial distribution of cracks from multiple perspectives.

[0053] Step S73: Based on steps S71 and S72, the obtained inspection report is used as a basis for engineering decision-making.

[0054] Compared with existing technologies, the advantages of this invention are summarized as follows: Full-depth coverage: This method proposes a full-depth crack detection solution that integrates shallow cracks (infrared thermal field) with deep cracks (Rayleigh wave field), enabling accurate assessment of crack depth, inclination, and width. Non-destructive: No drilling is required, preserving structural integrity. High accuracy: The average error of the fused data is less than 5%, supporting 3D visualization and risk quantification. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 It is a schematic diagram of the workflow of the present invention;

[0056] Figure 2 It is a schematic diagram of the on-site detection work arrangement of the present invention;

[0057] In the figure, 1. Concrete in the target area; 2. Deep cracks; 3. Infrared thermal imager; 4. Multi-channel sensor; 5. Impact hammer; 6. Data acquisition instrument. DETAILED DESCRIPTION

[0058] like Figure 1 As shown, the present invention provides a technical solution: a concrete crack detection method based on the coupling of infrared thermal field and Rayleigh wave field, comprising the following steps:

[0059] Step S1: Use infrared thermal imaging to fully scan the concrete in the target area, continuously record the temperature field changes on the concrete surface, and identify the location of concrete cracks through temperature gradient mutations; concrete cracks are divided into superficial cracks, deep cracks, and cracks in the junction area;

[0060] Step S2: For shallow cracks, the depth of the shallow cracks is calculated based on a simplified model of the one-dimensional heat conduction equation;

[0061] Step S3: For deep cracks, multi-channel sensors are arranged perpendicular to the direction of the deep cracks to stimulate Rayleigh waves and record the time domain waveform. The cutoff frequency is determined by the mutation point of the spectrum ratio curve to calculate the depth of the deep cracks.

[0062] Step S4: For cracks in the boundary area, infrared thermal imaging and Rayleigh wave methods are used to detect the depth of the cracks in the boundary area. If the depth error is less than 10%, the average of the infrared thermal imaging and Rayleigh wave methods is taken; otherwise, the parameters are optimized and retested;

[0063] Step S5: For shallow cracks, deep cracks, and cracks in the boundary area, extract the amplitude attenuation characteristics of the Rayleigh wave and calculate the crack width; invert the crack dip based on the time difference of the first wave arrival in the time domain waveform;

[0064] Step S6: superimposing the infrared thermal imaging detection results and the Rayleigh wave detection results, and constructing a three-dimensional visual crack model using a linear interpolation algorithm;

[0065] Step S7: Input the crack position in step S1, the crack depth in steps S2 to S4, the crack width and crack inclination in step S5, and the three-dimensional visual crack model in step S6 to generate a mass concrete crack detection report.

[0066] Furthermore, in step S1, infrared thermal imaging is used to comprehensively scan the concrete in the target area, continuously record the temperature field changes on the concrete surface, and identify the location of concrete cracks through the sudden change of temperature gradient. The specific process is as follows:

[0067] Step S11, as Figure 2 As shown, the surface of the target area concrete 1 is instantaneously heated using an infrared thermal imager pulse heat source (pulse width 1-2s, heat flux density controlled at 1-2kW / m²). Immediately after heating, the infrared thermal imager 3 is activated to continuously record the temperature field changes on the concrete surface (sampling frequency ≥ 10 Hz, lasting 30-60 seconds).

[0068] Step S12: extract the concrete surface temperature field change data within 0–60 seconds after heating, and calculate the temperature gradient of each pixel point using formula (1), which is expressed as:

[0069] (1);

[0070] Where, Indicates any concrete surface in the target area Temperature difference of the point; express Point temperature: maximum temperature; for Point minimum temperature;

[0071] Step S13, set the threshold to =3σ T , if it exceeds the set threshold, it is determined to be a crack area, where σ T is the standard deviation of the ambient temperature.

[0072] Furthermore, in step S2, the depth of the shallow crack is calculated based on the simplified model of the one-dimensional heat conduction equation, specifically:

[0073] (2);

[0074] Where, is the depth of the superficial crack; is the thermal diffusion coefficient of concrete ( ); is the initial temperature difference, i.e. the temperature difference between the concrete surface and the environment at the end of heating; is the residual temperature difference in the shallow crack area at time t, and t is the time after thermal excitation (60s in this example).

[0075] Furthermore, in step S3, multi-channel sensors are arranged perpendicular to the direction of the deep cracks to excite Rayleigh waves and record the time domain waveform. The cutoff frequency is determined by the mutation point of the spectrum ratio curve to calculate the depth of the deep cracks. The specific process is as follows:

[0076] Step S31, as Figure 2 As shown, multi-channel sensors 4 are arranged perpendicular to the deep crack direction, with a channel spacing of 40-60 cm, and the number of sensors is ≥4, symmetrically distributed on both sides of the deep crack 2; an impact hammer 5 or a piezoelectric transducer is used to excite Rayleigh waves, and a data acquisition device 6 is used to synchronously collect multi-channel Rayleigh wave time domain waveform data;

[0077] In step S32, the spectrum of the signals at all sensor test points is obtained by Fourier transform and the amplitude spectrum is obtained. The spectrum ratio mean of the signals at all sensor test points is calculated according to formula (3), which is expressed as:

[0078] (3);

[0079] Where i is the sensor number, ; n is the total number of deployed sensors, n ≥ 4 and is an even number; For the The spectrum ratio of the sensor of channel i to channel i; For the The signal frequency domain amplitude of the channel sensor, is the signal frequency domain amplitude of the i-th sensor; is the mean value of the spectrum ratio;

[0080] Step S33, defining the spectrum ratio mean =0.5 corresponds to the cutoff frequency f c , cutoff frequency f c The depth of the deep crack is one third of the wavelength of the Rayleigh wave, which is calculated as follows:

[0081] (4);

[0082] Where, is the depth of deep cracks; f c is the cutoff frequency; is the Rayleigh wave speed;

[0083] Rayleigh wave speed in formula (4) The results of wave velocity calibration test on concrete in the complete target area show that:

[0084] (5);

[0085] Where L is the known sensor spacing, and Δt is the arrival time difference of the first wave of the Rayleigh wave.

[0086] Furthermore, in step S4, the depth of the cracks in the boundary area is detected by using both infrared thermal imaging and Rayleigh wave methods. If the depth error is less than 10%, the average of the infrared thermal imaging and Rayleigh wave detection values is taken; otherwise, the parameters are optimized and re-detected. The specific process is as follows:

[0087] Cross-validation and error correction of cracks in the interface area: Infrared thermal imaging and Rayleigh wave methods are used for detection respectively. If the depth error of cracks in the interface area detected by infrared thermal imaging and Rayleigh wave methods is less than 10%, the average of the detection results by infrared thermal imaging and Rayleigh wave methods is taken as the final result. If the depth error of cracks in the interface area detected by infrared thermal imaging and Rayleigh wave methods is greater than 10%, the working parameters are adjusted and re-tested, and the impact echo method or ultrasonic method is introduced as a third-party verification. The specific adjustment of the working parameters includes optimizing the infrared pulse frequency, correcting the thermal diffusion coefficient of concrete, using a higher frequency Rayleigh wave source, and correcting the Rayleigh wave velocity.

[0088] Furthermore, in step S5, the amplitude attenuation characteristics of the Rayleigh wave are extracted for the shallow cracks, deep cracks, and cracks in the boundary area to calculate the crack width; the crack dip is inverted based on the first wave arrival time difference; the specific process is as follows:

[0089] Step S51, the crack inclination is calculated by calculating the arrival time difference of the first wave signals of adjacent sensors on both sides of the deep crack, which is expressed as:

[0090] (6);

[0091] Where, is the crack inclination angle, is the arrival time difference of the first wave signals of adjacent sensors on both sides of the deep crack; is the distance between adjacent sensors on both sides of a deep crack;

[0092] In step S52, the deep crack width is calculated based on the correlation between amplitude attenuation and crack width. The amplitude attenuation index is calculated using formula (7):

[0093] (7);

[0094] Where AI is the amplitude attenuation index; is the sensor amplitude at the rear side of the deep crack; is the sensor amplitude at the front side of the deep crack;

[0095] The relationship between the amplitude attenuation index and the width of deep cracks was calibrated experimentally and expressed using a linear model:

[0096] (8);

[0097] Where w is the width of deep cracks; k and b are linear model fitting parameters, k is the slope, and b is the intercept.

[0098] Furthermore, in step S6, the infrared thermal imaging detection results and the Rayleigh wave detection results are superimposed, and a linear interpolation algorithm is used to construct a three-dimensional visual crack model; the specific process is:

[0099] Based on the infrared thermal imaging detection data from steps S1 and S2 and the Rayleigh wave detection data from steps S3 and S5, the infrared thermal imaging detection data and the Rayleigh wave detection data are unified into the same coordinate system: with the lower left corner of the detection area as the origin, the X axis along the crack direction, the Y axis perpendicular to the crack direction, and the Z axis as the depth direction, a linear interpolation algorithm is used to construct a three-dimensional visual crack model, which is represented as follows:

[0100] (9);

[0101] Where, The final detection results of crack location and depth in concrete of the target area; 、 are the crack position and depth detection results of infrared thermal imaging and Rayleigh wave detection, respectively; λ is the weight coefficient (in this example, λ can be set to 0.8 for shallow cracks and 0.3 for deep cracks).

[0102] Furthermore, in step S7, the crack position in step S1, the crack depth in steps S2 to S4, the crack width and crack inclination in step S5, and the three-dimensional visual crack model in step S6 are input to generate a mass concrete crack detection report; the specific process is as follows:

[0103] Step S71: Integrate the input data and input the final target area concrete crack position and depth detection results , deep crack inclination angle θ, amplitude attenuation index AI and deep crack width w; use programming software Python or typesetting system LaTeX template to automatically generate inspection reports;

[0104] Step S72: The inspection report includes the inspection time, target area, total number of cracks, and size information, as well as an infrared temperature gradient thermogram with crack outlines, a Rayleigh wave spectrum ratio curve with cutoff frequency, and a three-dimensional visualization crack model diagram showing the spatial distribution of cracks from multiple perspectives.

[0105] Step S73: Based on steps S71 and S72, the obtained inspection report is used as a basis for engineering decision-making.

[0106] The above description is a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications that do not depart from the disclosure of the present invention should be included in the scope of protection of the present invention.

Claims

1. A concrete crack detection method based on the coupling of infrared thermal field and Rayleigh wave field, characterized by: The following steps are involved: Step S1: Use infrared thermal imaging to fully scan the concrete in the target area, continuously record the temperature field changes on the concrete surface, and identify the location of concrete cracks through temperature gradient mutations; concrete cracks are divided into superficial cracks, deep cracks, and cracks in the junction area; Step S2: For shallow cracks, the depth of the shallow cracks is calculated based on a simplified model of the one-dimensional heat conduction equation; Step S3: For deep cracks, multi-channel sensors are arranged perpendicular to the direction of the deep cracks to stimulate Rayleigh waves and record the time domain waveform. The cutoff frequency is determined by the mutation point of the spectrum ratio curve to calculate the depth of the deep cracks. Step S4: For cracks in the boundary area, infrared thermal imaging and Rayleigh wave methods are used to detect the depth of the cracks in the boundary area. If the depth error is less than 10%, the average of the infrared thermal imaging and Rayleigh wave methods is taken; otherwise, the parameters are optimized and retested; Step S5: For shallow cracks, deep cracks and cracks in the boundary area, extract the Rayleigh wave amplitude attenuation characteristics and calculate the crack width; Invert the crack dip based on the first wave arrival time difference of the time domain waveform; Step S6: superimposing the infrared thermal imaging detection results and the Rayleigh wave detection results, and constructing a three-dimensional visual crack model using a linear interpolation algorithm; Step S7: Input the crack position in step S1, the crack depth in steps S2 to S4, the crack width and crack inclination in step S5, and the three-dimensional visual crack model in step S6 to generate a mass concrete crack detection report; In step S1, infrared thermal imaging is used to fully scan the concrete in the target area, continuously record the temperature field changes on the concrete surface, and identify the location of concrete cracks through sudden changes in temperature gradients. The specific process is as follows: Step S11, using an infrared thermal imager pulse heat source to instantaneously heat the concrete surface of the target area, immediately starting the infrared thermal imager after heating, and continuously recording the temperature field changes on the concrete surface; Step S12: extract the temperature field change data of the concrete surface after heating, and calculate the temperature gradient of each pixel point by formula (1), which is expressed as: （1）； Where, Indicates any concrete surface in the target area Temperature difference of the point; express Point temperature: maximum temperature; for Point minimum temperature; Step S13, set the threshold to =3σ T , if it exceeds the set threshold, it is determined to be a crack area, where σ T is the standard deviation of ambient temperature; In step S2, the depth of the shallow crack is calculated based on the simplified model of the one-dimensional heat conduction equation, specifically: （2）； Where, is the depth of the superficial crack; is the thermal diffusivity of concrete; is the initial temperature difference, i.e. the temperature difference between the concrete surface and the environment at the end of heating; is the residual temperature difference in the shallow crack area at time t, where t is the time after thermal excitation; In step S6, the infrared thermal imaging detection results are superimposed with the Rayleigh wave detection results, and a three-dimensional visual crack model is constructed using a linear interpolation algorithm. The specific process is as follows: Based on the infrared thermal imaging detection data and the Rayleigh wave detection data from steps S1 to S5, the infrared thermal imaging detection data and the Rayleigh wave detection data are unified into the same coordinate system: with the lower left corner of the detection area as the origin, the X axis along the crack direction, the Y axis perpendicular to the crack direction, and the Z axis as the depth direction, a linear interpolation algorithm is used to construct a three-dimensional visual crack model, which is represented as follows: ； Where, The final detection results of crack location and depth in concrete of the target area; 、 are the crack position and depth detection results of infrared thermal imaging and Rayleigh wave method respectively; λ is the weight coefficient.

2. The concrete crack detection method based on infrared thermal field and Rayleigh wave field coupling according to claim 1 is characterized in that: In step S3, a multi-channel sensor is arranged perpendicular to the direction of the deep crack to excite Rayleigh waves and record the time domain waveform. The cutoff frequency is determined by the mutation point of the spectrum ratio curve to calculate the depth of the deep crack. The specific process is as follows: Step S31: Arrange multi-channel sensors perpendicular to the deep fracture, with a channel spacing of 40-60 cm, and a number of ≥4 sensors, symmetrically distributed on both sides of the deep fracture; use an impact hammer or piezoelectric transducer to excite Rayleigh waves, and synchronously collect multi-channel Rayleigh wave time domain waveform data using a data acquisition instrument; In step S32, the spectrum of the signals at all sensor test points is obtained by Fourier transform and the amplitude spectrum is obtained. The spectrum ratio mean of the signals at all sensor test points is calculated according to formula (3), which is expressed as: （3）； Where i is the sensor number, ; n is the total number of deployed sensors, n ≥ 4 and is an even number; For the The spectrum ratio of the sensor of channel i to channel i; For the The signal frequency domain amplitude of the channel sensor, is the signal frequency domain amplitude of the i-th sensor; is the mean value of the spectrum ratio; Step S33, defining the spectrum ratio mean =0.5 corresponds to the cutoff frequency f c , cutoff frequency f c The depth of the deep crack is one third of the wavelength of the Rayleigh wave, which is calculated as follows: （4）； Where, is the depth of deep cracks; f c is the cutoff frequency; is the Rayleigh wave speed; Rayleigh wave speed in formula (4) The results of wave velocity calibration test on concrete in the complete target area show that: （5）； Where L is the known sensor spacing, and Δt is the arrival time difference of the first wave of the Rayleigh wave.

3. The concrete crack detection method based on infrared thermal field and Rayleigh wave field coupling according to claim 2 is characterized in that: In step S4, the depth of the cracks in the boundary area is detected by using both infrared thermal imaging and Rayleigh wave methods. If the depth error is less than 10%, the average of the infrared thermal imaging and Rayleigh wave detection values is taken; otherwise, the parameters are optimized and re-detected. The specific process is as follows: Cross-validation and error correction of cracks in the interface area: Infrared thermal imaging and Rayleigh wave methods are used for detection respectively. If the depth error of cracks in the interface area detected by infrared thermal imaging and Rayleigh wave methods is less than 10%, the average of the detection results by infrared thermal imaging and Rayleigh wave methods is taken as the final result. If the depth error of cracks in the interface area detected by infrared thermal imaging and Rayleigh wave methods is greater than 10%, the working parameters are adjusted and re-tested, and the impact echo method or ultrasonic method is introduced as a third-party verification. The specific adjustment of the working parameters includes optimizing the infrared pulse frequency, correcting the thermal diffusion coefficient of concrete, using a higher frequency Rayleigh wave source, or correcting the Rayleigh wave velocity.

4. The method for detecting concrete cracks based on coupling of infrared thermal field and Rayleigh wave field according to claim 3 is characterized in that: In step S5, for shallow cracks, deep cracks, and cracks in the boundary area, the Rayleigh wave amplitude attenuation characteristics are extracted to calculate the crack width; based on the time difference of the first wave arrival in the time domain waveform, the crack dip is inverted. The specific process is as follows: Step S51, the crack inclination is calculated by calculating the arrival time difference of the first wave signals of adjacent sensors on both sides of the deep crack, which is expressed as: （6）； Where, is the crack inclination angle, is the arrival time difference of the first wave signals of adjacent sensors on both sides of the deep crack; is the distance between adjacent sensors on both sides of a deep crack; In step S52, the deep crack width is calculated based on the correlation between amplitude attenuation and crack width. The amplitude attenuation index is calculated using formula (7): （7）； Where AI is the amplitude attenuation index; is the sensor amplitude at the rear side of the deep crack; is the sensor amplitude at the front side of the deep crack; The relationship between the amplitude attenuation index and the width of deep cracks was calibrated experimentally and expressed using a linear model: （8）； Where w is the width of deep cracks; k and b are linear model fitting parameters, k is the slope, and b is the intercept.

5. The concrete crack detection method based on infrared thermal field and Rayleigh wave field coupling according to claim 4 is characterized in that: In step S7, the crack position in step S1, the crack depth in steps S2 to S4, the crack width and crack inclination in step S5, and the three-dimensional visual crack model in step S6 are input to generate a mass concrete crack detection report; the specific process is as follows: Step S71: Integrate the input data and input the final target area concrete crack position and depth detection results , deep fracture inclination angle θ, amplitude attenuation index AI and deep fracture width w; Automatically generate test reports using programming software Python or typesetting system LaTeX templates; Step S72: The inspection report includes the inspection time, target area, total number of cracks, and size information, as well as an infrared temperature gradient thermogram with crack outlines, a Rayleigh wave spectrum ratio curve with cutoff frequency, and a three-dimensional visualization crack model diagram showing the spatial distribution of cracks from multiple perspectives. Step S73: Based on steps S71 and S72, the obtained inspection report is used as a basis for engineering decision-making.

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