A method for realizing rust thickness calculation and imaging characterization based on terahertz technology

Abstract

The application discloses a method for realizing rust thickness calculation and imaging characterization based on terahertz technology, and the method comprises the following steps: obtaining a reflection spectrum data set of a rusted steel plate with a covering layer, and obtaining a phase difference parameter and a time of flight parameter through the reflection spectrum data set; wherein, after scanning and processing the rusted steel plate with the covering layer through a terahertz reflection spectrum technology, a reflection spectrum data set with scanning point information is obtained; based on the phase difference parameter and the time of flight parameter, the covering layer thickness and the rust layer thickness are calculated through a thickness layer calculation formula; and the rust imaging characterization is completed through the reflection spectrum data set, the covering layer thickness and the rust layer thickness, and then the rust imaging characterization is output. Through the method for realizing rust thickness calculation and imaging characterization based on the terahertz technology, the direct calculation of the covering layer thickness and the rust layer thickness of the rusted steel plate is realized, and the accurate quantitative characterization of the rust is also realized.

Description

Technical Field

[0001] This invention relates to the field of nondestructive testing technology for corrosion, and in particular to a method for calculating and imaging corrosion thickness based on terahertz technology. Background Technology

[0002] Steel, with its abundant reserves, low price, and excellent mechanical properties, is widely used in civil engineering for structural construction such as high-rise buildings, long-span steel structures, and steel bridges. Its properties are affected by external environmental factors such as temperature, humidity, and Cl-. - Corrosion and other factors can cause steel surfaces to rust. This corrosion process typically occurs beneath covering materials such as concrete, paint, rubber, and epoxy resin, and is highly concealed in its early stages. By the time corrosion can be effectively detected, the load-bearing capacity and durability of the steel structure may have already been significantly reduced. Therefore, the effective determination and characterization of the location, area, and thickness of corrosion is of paramount importance.

[0003] Common non-destructive testing (NDT) methods include ultrasonic testing, X-ray testing, eddy current testing, penetrant testing, and magnetic particle testing. Terahertz technology, which refers to electromagnetic waves with frequencies between 100 GHz and 10 THz, can penetrate non-polar materials, be reflected at the surface of metallic polar materials, and undergo both reflection and transmission at the interface of different dielectric materials. This characteristic meets the technical requirements for NDT of steel structure corrosion. However, current research on terahertz reflection spectroscopy for corrosion detection focuses primarily on qualitative characterization of corrosion, i.e., determining whether the steel substrate has rusted, rather than accurate quantitative characterization of corrosion, including the rust area, shape, and thickness. Calculating corrosion thickness using terahertz reflection spectroscopy in existing technologies requires complex conditions, demands high operator skill, and is inherently complex.

[0004] Therefore, the existing terahertz technology for non-destructive testing of corrosion still needs improvement and development. Summary of the Invention

[0005] The technical problem this application aims to solve is to provide a method for calculating and imaging corrosion thickness based on terahertz technology, addressing the shortcomings of existing technologies. This invention enables the calculation and imaging of corrosion thickness using terahertz technology, thereby achieving accurate quantitative characterization of corrosion.

[0006] To address the shortcomings of the existing technology, the first aspect of this application provides a method for calculating and imaging characterizing corrosion thickness based on terahertz technology, the method comprising:

[0007] A reflection spectrum dataset of a rusted steel plate with a coating was obtained, and the phase difference parameter and time-of-flight parameter were obtained from the reflection spectrum dataset. Specifically, after scanning the rusted steel plate with the coating using terahertz reflection spectroscopy, a reflection spectrum dataset with scan point information was obtained.

[0008] Based on the phase difference parameter and flight time parameter, the thickness of the covering layer and the thickness of the corrosion layer are calculated using the thickness layer calculation formula.

[0009] The corrosion imaging characterization was completed and output using the reflectance spectrum dataset, the thickness of the overburden layer, and the thickness of the corrosion layer.

[0010] The process of obtaining the reflection spectrum dataset of the corroded steel plate with the coating layer, and obtaining the phase difference parameter and time-of-flight parameter from the reflection spectrum dataset, specifically includes:

[0011] A measurement area is pre-defined on the corroded steel plate, and the scanning point is set on the measurement area;

[0012] The terahertz reflection spectroscopy technique is used to perform terahertz reflection spectroscopy scanning on the scanning points within the measurement area to obtain a reflection spectrum dataset.

[0013] The process of obtaining the phase difference parameter and time-of-flight parameter from the reflection spectrum dataset specifically includes:

[0014] After obtaining the reflection spectrum dataset, feature recognition binary classification is performed on the reflection spectrum dataset to obtain binary representations of corrosion and non-corrosion at each location of the scan point.

[0015] The process of obtaining the phase difference parameter and time-of-flight parameter from the reflection spectrum dataset specifically includes:

[0016] Based on the binary classification of rust and non-rust at the scanning point location, the phase difference parameters of the steel plate signal and the corresponding reference signal at each scanning point location are obtained;

[0017] Based on the binary classification of corrosion and non-corrosion at the scanning point location and the reflection spectrum dataset, the terahertz reflection spectrum signal amplitude and its corresponding time parameter of all scanning points in the scanning area are extracted to obtain the time-of-flight parameter.

[0018] The calculation of the overburden thickness and corrosion layer thickness based on the phase difference parameter and flight time parameter using the thickness layer calculation formula specifically includes:

[0019] When scanning the corroded steel plate using terahertz reflection spectroscopy, the received terahertz reflection spectroscopy signal is simultaneously processed as a terahertz transmission signal.

[0020] Based on the phase difference parameter and time of flight parameter, the optical parameters at the scanning point and the thickness layer calculation formula are obtained by combining the transmission optical parameter calculation formula and the reflection spectrum thickness calculation formula.

[0021] The thickness of the coating layer and the thickness of the corrosion layer are obtained by using the optical parameters at the scanning point and the formula for calculating the thickness layer.

[0022] The calculation of the overburden thickness and corrosion layer thickness based on the phase difference parameter and flight time parameter using the thickness layer calculation formula specifically includes:

[0023] When the terahertz reflection spectroscopy technique is used to scan the corroded steel plate, the signal angle of the terahertz incident signal is 0 degrees.

[0024] The process of characterizing and outputting corrosion imaging data using reflectance spectrum datasets, overburden thickness, and corrosion layer thickness specifically includes:

[0025] The corrosion imaging characterization includes visualization of the shape and area of ​​the corrosion, as well as quantitative characterization of the overburden and corrosion layers.

[0026] A second aspect of this application provides a device for calculating and imaging corrosion thickness based on terahertz technology, the device comprising:

[0027] The information parameter acquisition module acquires the reflection spectrum dataset of the corroded steel plate with the coating layer, and obtains the phase difference parameter and time-of-flight parameter from the reflection spectrum dataset; in particular, after scanning the corroded steel plate with the coating layer using terahertz reflection spectroscopy technology, a reflection spectrum dataset with scanning point information is obtained.

[0028] The thickness calculation module calculates the thickness of the covering layer and the thickness of the corrosion layer based on the phase difference parameter and the time of flight parameter using the thickness layer calculation formula.

[0029] The imaging characterization module completes and outputs the corrosion imaging characterization using the reflectance spectrum dataset, the thickness of the overburden layer, and the thickness of the corrosion layer.

[0030] A third aspect of this application provides a computer-readable storage medium, characterized in that the computer-readable storage medium stores one or more programs, which can be executed by one or more processors to implement the steps in the terahertz-based corrosion thickness calculation and imaging characterization method described above.

[0031] A fourth aspect of this application provides a terminal device, characterized in that it includes: a processor, a memory, and a communication bus; the memory stores a computer-readable program that can be executed by the processor;

[0032] The communication bus enables communication between the processor and the memory;

[0033] When the processor executes the computer-readable program, it implements the steps in the above-described method for calculating and imaging characterizing corrosion thickness based on terahertz technology.

[0034] Beneficial Effects: Compared with existing technologies, this application provides a method for calculating and imaging characterizing corrosion thickness based on terahertz technology. The method includes acquiring a reflection spectrum dataset of a corroded steel plate with a coating layer, and obtaining phase difference parameters and time-of-flight parameters from the reflection spectrum dataset. Specifically, after scanning the corroded steel plate with the coating layer using terahertz reflection spectroscopy, a reflection spectrum dataset with scanning point information is obtained. Based on the phase difference parameters and time-of-flight parameters, the coating layer thickness and corrosion layer thickness are calculated using a thickness calculation formula. The corrosion imaging characterization is completed and output using the reflection spectrum dataset, coating layer thickness, and corrosion layer thickness. Through this method, the present invention can perform feature recognition binary classification using the acquired reflection spectrum dataset to obtain corroded and non-corroded areas; then, by obtaining the phase difference parameters and time-of-flight parameters from the reflection spectrum dataset, the coating layer thickness and corrosion layer thickness at each location can be directly obtained from the terahertz reflection signal; based on the obtained corroded areas and corresponding thickness information, accurate quantitative characterization of corrosion can be achieved. In summary, this application proposes a method for calculating and imaging the corrosion thickness based on terahertz technology. This method can determine whether the steel substrate material under the coating is corroded, thereby achieving accurate characterization of corrosion, including the visualization and quantitative characterization of corrosion shape, region, and corrosion thickness. Attached Figure Description

[0035] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0036] Figure 1 A flowchart of a method for calculating and imaging characterizing corrosion thickness based on terahertz technology provided by the present invention;

[0037] Figure 2 The terahertz spectrometer and its schematic diagram provided for embodiments of the present invention;

[0038] Figure 3 A schematic diagram illustrating the principle of single-point thickness measurement using terahertz reflection spectroscopy technology provided in this embodiment of the invention.

[0039] Figure 4This is a schematic diagram of a corrosion imaging method provided in an embodiment of the present invention;

[0040] Figure 5 This is a terahertz scanning point matrix diagram provided in an embodiment of the present invention;

[0041] Figure 6 This is a schematic diagram illustrating the extraction of thresholds and time parameters from different types of terahertz reflection signal spectra provided in embodiments of the present invention.

[0042] Figure 7 This is a schematic diagram of the terahertz reflectance spectral scanning measurement of a rust-prone steel plate sample provided in an embodiment of the present invention;

[0043] Figure 8 A schematic diagram showing the results of rust identification and rust thickness calculation of a spot rust paint coating sample provided in an embodiment of the present invention;

[0044] Figure 9 A schematic diagram illustrating the visualization of a rust-spotted steel plate sample within a scanning area, provided in an embodiment of the present invention.

[0045] Figure 10 This is a schematic diagram of the terahertz reflectance spectral scanning measurement of a fully corroded steel plate sample provided in an embodiment of the present invention;

[0046] Figure 11 A schematic diagram showing the results of rust identification and rust thickness calculation of a fully rusted paint coating sample provided in an embodiment of the present invention;

[0047] Figure 12 A schematic diagram of the visualization characterization of a fully rusted steel plate sample within the scanning area provided in an embodiment of the present invention;

[0048] Figure 13 This is a schematic diagram of the device for calculating and imaging corrosion thickness based on terahertz technology, provided in an embodiment of the present invention. Detailed Implementation

[0049] This application provides a method for calculating and imaging characterizing corrosion thickness based on terahertz technology. To make the objectives, technical solutions, and effects of this application clearer and more explicit, the following detailed description is provided with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only for explaining this application and are not intended to limit this application.

[0050] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this application means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when we say an element is “connected” or “coupled” to another element, it can be directly connected or coupled to the other element, or there may be intermediate elements. Furthermore, “connected” or “coupled” as used herein can include wireless connections or wireless coupling. The term “and / or” as used herein includes all or any units and all combinations of one or more associated listed items.

[0051] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the same meaning as in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined as herein.

[0052] Furthermore, if the embodiments of this invention involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by this invention.

[0053] Steel, with its abundant reserves, low price, and excellent mechanical properties, is widely used in civil engineering for structures such as high-rise buildings, long-span steel structures, and steel bridges. However, steel surfaces are susceptible to corrosion due to external environmental factors such as temperature, humidity, and chloride ion (Cl-) corrosion. This corrosion process typically occurs beneath covering materials such as concrete, paint, rubber, and epoxy resin, and is highly concealed in its early stages. By the time corrosion can be effectively detected, the load-bearing capacity and durability of the steel structure may have already been significantly reduced. Therefore, the effective determination and characterization of the location, area, and thickness of corrosion is of paramount importance.

[0054] Common non-destructive testing (NDT) methods include ultrasonic testing, radiographic testing, eddy current testing, penetrant testing, and magnetic particle testing. However, these techniques all have insurmountable limitations when used for corrosion detection. Current NDT techniques for steel structure corrosion suffer from problems such as complex equipment, cumbersome operation, limited ability to roughly identify corroded areas, and significant dependence on the coating material, steel structure size, and shape; furthermore, they cannot accurately measure the thickness of the corrosion layer. Terahertz technology refers to electromagnetic waves with frequencies between 100 GHz and 10 THz. These waves can penetrate non-polar materials, reflect off the surface of metallic polar materials, and simultaneously reflect and transmit at the interface of different media materials. This characteristic meets the technical requirements for non-destructive testing of the corrosion state of steel structures using terahertz wave technology. However, existing research on terahertz reflection spectroscopy for corrosion detection focuses more on the qualitative characterization of corrosion, i.e., determining whether the steel substrate has rusted, rather than achieving accurate quantitative characterization of corrosion, including the corrosion area, shape, and thickness. Furthermore, the calculation of corrosion thickness using terahertz reflection spectroscopy in existing technologies requires complex conditions, high operator skill, and is difficult.

[0055] In the terahertz technology-based method for calculating and imaging characterizing rust thickness provided by this invention, the reflection spectrum dataset of the rusted steel plate is obtained by terahertz reflection spectroscopy, thereby obtaining the thickness of the rusted steel plate coating and the thickness of the rust layer, and realizing rust imaging characterization.

[0056] Instance methods

[0057] like Figure 1 The diagram shows a flowchart of a method for calculating and imaging corrosion thickness based on terahertz technology, provided by an embodiment of the present invention. This method can be applied to terminal devices. In this embodiment of the invention, combined with... Figure 1 The method is described, and the method includes the following steps:

[0058] Step S10: Obtain the reflection spectrum dataset of the corroded steel plate with the coating layer, and obtain the phase difference parameter and time of flight parameter through the reflection spectrum dataset; wherein, after scanning the corroded steel plate with the coating layer by terahertz reflection spectroscopy, a reflection spectrum dataset with scanning point information is obtained.

[0059] Specifically, a reflection spectrum dataset with scanning point information is obtained by scanning a rusted steel plate with a coating layer using terahertz reflection spectroscopy. The reflection spectrum dataset contains scanning points arranged according to certain rules. The phase difference parameter and time-of-flight parameter are obtained from the reflection spectrum dataset with scanning point information.

[0060] Furthermore, the step of obtaining the reflection spectrum dataset of the corroded steel plate with the coating layer, and obtaining the phase difference parameter and time-of-flight parameter from the reflection spectrum dataset, specifically includes:

[0061] A measurement area is pre-defined on the corroded steel plate, and the scanning point is set on the measurement area;

[0062] The terahertz reflection spectroscopy technique is used to perform terahertz reflection spectroscopy scanning on the scanning points within the measurement area to obtain a reflection spectrum dataset.

[0063] Specifically, before implementing the method described in this invention, a rusted steel plate is pre-acquired, and a measurement area is delineated on the rusted steel plate. Scanning points are set according to a predetermined point spacing. The measurement area can be any region on the rusted steel plate, selected based on actual conditions. The scanning points are set on the measurement area, with scanning points (x, y) set according to the point spacing. In one embodiment, the optional point spacing Δx = Δy = 0.2 mm is used to set the scanning points, ensuring that the scanning points cover the entire measurement area, and that each scanning point is 0.2 mm away from other scanning points in both the horizontal and vertical directions. Terahertz reflection spectroscopy is used to perform terahertz reflection spectroscopy scanning on the scanning points within the measurement area, resulting in a 0-40 ps time-domain spectrum. The terahertz reflection spectroscopy technique can be used in various applications such as... Figure 2 The terahertz spectrometer shown is implemented.

[0064] like Figure 3 As shown, this is a terahertz scanning point matrix diagram provided in an embodiment of the present invention. After the corroded steel plate is scanned using terahertz reflection spectroscopy technology, a reflection spectrum dataset is obtained. The scanning point information in the reflection spectrum dataset is as follows: Figure 3 As shown, each position (x, y) contains a terahertz reflection time-domain spectrum signal of 0-40 ps, ​​and the point spacing in each scanning point is the same. Optionally, the point spacing can be 0.2 mm.

[0065] Furthermore, obtaining the phase difference parameter and time-of-flight parameter from the reflection spectrum dataset specifically includes:

[0066] After obtaining the reflection spectrum dataset, feature recognition binary classification is performed on the reflection spectrum dataset to obtain binary representations of corrosion and non-corrosion at each location of the scan point.

[0067] Specifically, after obtaining the reflection spectrum dataset, which includes the location information (x, y) of all scanning points within the measurement area and the corresponding time-domain reflection spectrum signals of the scanning points, an algorithm is used to perform feature recognition binary classification on the data of each scanning point to obtain a binary representation of corrosion and non-corrosion at the scanning point location. In one embodiment, the reflection spectrum dataset can be subjected to feature recognition binary classification using a Python algorithm.

[0068] Furthermore, the binary classification characterization includes two categories: rusted steel plates with a coating and uncorroded steel plates with a coating. At the rusted location of the coated steel plate, the terahertz reflection spectrum mainly shows three signal amplitudes, and the magnitudes of the three reflected signal amplitudes are not significantly different. At the uncorroded location of the coated steel plate, the terahertz reflection spectrum mainly shows two signal amplitudes, and the intensity of the second signal amplitude is significantly higher than that of the first signal amplitude. Specifically, as shown... Figure 6 As shown, these are the characteristic signals of the uncorroded area and the corroded area, respectively. The terahertz reflection spectrum at the uncorroded location of the covered steel plate mainly has two signal amplitudes, while at the corroded location of the covered steel plate, the terahertz reflection spectrum mainly has three signal amplitudes.

[0069] Furthermore, obtaining the phase difference parameter and time-of-flight parameter from the reflection spectrum dataset specifically includes:

[0070] Based on the binary classification of rust and non-rust at the scanning point location, the phase difference parameters of the steel plate signal and the corresponding reference signal at each scanning point location are obtained;

[0071] Based on the binary classification of corrosion and non-corrosion at the scanning point location and the reflection spectrum dataset, the terahertz reflection spectrum signal amplitude and its corresponding time parameter of all scanning points in the scanning area are extracted to obtain the time-of-flight parameter.

[0072] Specifically, the phase difference parameter refers to the phase difference between the sample signal and the corresponding reference signal at the scanning point, based on the determination of whether there is corrosion at the scanning point location. In this invention, the sample signal at the scanning point is the terahertz reflection signal at that scanning point in the terahertz reflection spectrum, and the reference signal is related to whether the measurement point is corroded. When the scanning point is corroded, the reference signal is defined as the terahertz reflection signal at the first uncorroded position in the terahertz scanning area, i.e., the measurement area; when the measurement point is uncorroded, the reference signal is defined as the terahertz reflection signal of the uncoated steel material. The terahertz reflection signal of the uncoated steel material can be directly measured from the steel material itself. Based on whether each point is corroded, this operation can further obtain the phase difference information between the signal and the reference signal at each scanning point.

[0073] The extraction of time-of-flight (TOF) parameters refers to the following: based on the determination of corrosion status and phase difference parameters of each scanning point through feature recognition and binary classification, an algorithm is used to define a variable threshold N to extract the amplitude of the terahertz reflection spectrum signal and its corresponding time parameters for all scanning points within the measurement area. Specifically, for non-corroded areas, two amplitude and time parameters are extracted, corresponding to the thickness of the overburden layer; for corroded areas, three amplitude and time parameters are extracted, corresponding to the thickness of the overburden layer and the thickness of the corrosion layer. In one implementation, a Python algorithm is used to define a half-threshold N. Specifically, as shown... Figure 6 As shown, by defining a half-value threshold N, the amplitude and corresponding time parameters are extracted in the non-corroded area. The two amplitudes extracted in the non-corroded area correspond to the thickness of the overburden layer; the three amplitudes extracted in the corroded area correspond to the thickness of the corroded layer and the overburden layer; and the corresponding time parameters are extracted again.

[0074] Step S20: Based on the phase difference parameter and flight time parameter, calculate the thickness of the covering layer and the thickness of the corrosion layer using the thickness layer calculation formula;

[0075] Specifically, in this invention, the thickness of the overburden layer and the thickness of the rust layer are calculated by obtaining the phase parameters and time-of-flight parameters, thereby enabling quantitative characterization of the thickness when performing rust imaging characterization.

[0076] Furthermore, the calculation of the overburden thickness and corrosion layer thickness based on the phase difference parameter and time-of-flight parameter using the thickness layer calculation formula specifically includes:

[0077] When scanning the corroded steel plate using terahertz reflection spectroscopy, the received terahertz reflection spectroscopy signal is simultaneously processed as a terahertz transmission signal.

[0078] Based on the phase difference parameter and time of flight parameter, the optical parameters at the scanning point and the thickness layer calculation formula are obtained by combining the transmission optical parameter calculation formula and the reflection spectrum thickness calculation formula.

[0079] The thickness of the coating layer and the thickness of the corrosion layer are obtained by using the optical parameters at the scanning point and the formula for calculating the thickness layer.

[0080] Specifically, such as Figure 3 As shown, the terahertz pulse waves emitted by the terahertz spectrometer can penetrate common coating materials and corrosion layers, generating terahertz reflection signals at the interfaces of air-coating, coating-corrosion, and steel substrate materials, namely reflection signals 1, 2, and 3. These reflection signals are received by the detector in the terahertz spectrometer, forming a complete time-domain spectral signal, which is reflected in the reflection spectrum dataset. The time-of-flight difference between the amplitudes in the time-domain spectral signal is related to the thickness of the coating and corrosion layers. Both satisfy formula (1):

[0081]

[0082] Where D is the layer thickness, c is the speed of light, ΔT is the time-of-flight difference corresponding to the amplitude in the terahertz reflection time-domain spectrum, and n is the scalar value of the refractive index of each layer of material. In the prior art, the determination of the refractive index value in formula (1) requires the use of terahertz transmission spectroscopy. By measuring the reference signal and the sample signal, Fourier transform is performed to obtain the amplitude and phase of the signal. The optical parameters are then calculated according to the existing classical data processing model based on the Fresnel formula, as expressed in formulas (2) and (3):

[0083]

[0084]

[0085] Where n(w) is the refractive index, denoted as α(w), where w is the frequency, d is the sample thickness in the terahertz transmission spectrum experiment, α(w) is the absorption coefficient, and A(w) is the amplitude ratio of the sample to the reference signal. The sample thickness parameter in the terahertz transmission spectrum is obtained directly by precision measuring instruments.

[0086] In the above calculation process, it is necessary to measure the refractive index values ​​of the coating material and the corrosion layer material using terahertz transmission spectroscopy. During this measurement process, it is necessary to take separate samples of the coating material or the corrosion layer material, and it is also necessary to strictly control the size, thickness, and surface flatness of the samples. That is, in the original process of measuring the thickness of the corrosion layer using terahertz reflection spectroscopy, additional terahertz transmission spectroscopy is required, which greatly increases the complexity of the experiment and places higher demands on the operators.

[0087] In this invention, the received terahertz reflection spectrum signal is simultaneously processed as a terahertz transmission signal. By combining the calculation formulas for transmission spectrum optical parameters and reflection spectrum thickness, the optical parameters and corrosion layer thickness at the measurement location can be directly determined.

[0088] Furthermore, the calculation of the overburden thickness and corrosion layer thickness based on the phase difference parameter and time-of-flight parameter specifically includes:

[0089] When the terahertz reflection spectroscopy technique is used to scan the corroded steel plate, the signal angle of the terahertz incident signal is 0 degrees.

[0090] During transmission and reflection, the attenuation of terahertz signals depends only on their scattering within the transmitted sample, such as... Figure 3As shown, the received terahertz reflection amplitude signal 2 penetrates the coating material twice, and the amplitude signal 3 penetrates the coating and rust layer thicknesses twice. Therefore, the terahertz reflection signal at the rusted part of the coating steel takes the reflection signal at the uncorroded part as the reference signal. At the same time, the terahertz reflection signal at the uncorroded part of the coating steel takes the reflection signal at the uncoated steel as the reference signal. The relationship between thickness D and d in formulas (1), (2), and (3) is d = 2D. The refractive index value n in formula (1) is a scalar of the refractive index values ​​in formulas (2) and (3).

[0091] During terahertz reflection spectroscopy measurements, the incident angle of the terahertz signal is ensured to be 0 degrees, perpendicular to the plane of the corroded steel plate being measured, thus satisfying the approximate conditions of the terahertz transmission spectroscopy calculation formula. The terahertz reflection spectral signal is reflected at the surface of the metal substrate, and the reflection attenuation of the terahertz signal can be neglected. Therefore, by simultaneously solving the formulas relating thickness D and d (D = 2d) and formulas 1 and 2, the refractive index value n(w) based on terahertz reflection spectroscopy can be obtained. R The calculation formula (4), that is, the formula for calculating the optical parameters at the scanning point:

[0092]

[0093] in, The phase difference between the sample and the reference signal is the phase difference parameter obtained in this invention.

[0094] Furthermore, substituting formula (4) into formula 1, we can obtain the layer thickness D based on terahertz reflection spectroscopy. R The calculation formula, i.e., the formula for calculating the thickness layer:

[0095]

[0096] The above method yields a formula for calculating layer thickness based on terahertz reflection spectroscopy. Formula (5) illustrates that by measuring the signals of the reference and sample using terahertz reflection spectroscopy, and then performing a Fourier transform, information such as the phase and amplitude of the sample and reference signals can be obtained. Furthermore, by extracting the time-of-flight difference in the terahertz reflection spectral signal, the refractive index value and layer thickness value of the corresponding layer material at the measurement location can be calculated. This invention, through the above calculation method, eliminates the need to measure the refractive index values ​​of the coating and corrosion layers required in conventional thickness measurement methods; it enables thickness measurement at the scanning point location using only terahertz reflection spectroscopy.

[0097] Step S30: Complete and output the corrosion imaging characterization using the reflectance spectrum dataset, overburden thickness, and corrosion layer thickness;

[0098] Specifically, this invention achieves visual characterization of the shape, area, and thickness of rust through rust imaging. At the same time, this method can extract information such as the maximum, minimum, and average values ​​of the rust layer thickness, as well as the proportion of rusted and unrusted areas.

[0099] Furthermore, the step of characterizing and outputting corrosion imaging data using reflectance spectrum datasets, overburden thickness, and corrosion layer thickness specifically includes:

[0100] The corrosion imaging characterization includes visualization of the shape and area of ​​the corrosion, as well as quantitative characterization of the overburden and corrosion layers.

[0101] Specifically, based on the above operations, corrosion assessment and corresponding layer thickness calculation were implemented at each scanning point location. The location information (x, y) of each scanning point, along with the corrosion layer thickness and overburden thickness values ​​at each point, were obtained from the reflectance spectrum dataset. A two-layer location matrix map could be directly generated using a Python algorithm, where the two layers refer to the overburden and corrosion layers; the color settings in the map are related to the corresponding thickness values. Specifically for the corrosion layer, two-dimensional and three-dimensional visualization results of the corrosion could be further extracted. Simultaneously, based on the obtained corrosion layer thickness data at each point, feature values ​​of the corrosion layer thickness could be further extracted, such as the maximum, minimum, and average corrosion thickness, as well as the corrosion area percentage. This operation, combining corrosion assessment at each scanning point location, overburden and corrosion layer thickness calculation, and a location matrix imaging algorithm, achieves corrosion imaging characterization, including visualization of corrosion shape and area, and quantitative characterization of corrosion layer thickness values.

[0102] Furthermore, the present invention through Figure 4 The implementation process of the present invention will be further explained in detail below:

[0103] Step S41: Obtain a sample of the corroded steel plate;

[0104] Step S42: Obtain the reflectance spectrum dataset using terahertz reflectance spectroscopy.

[0105] Step S42.1: Based on the obtained reflectance spectrum dataset, obtain the position information (x, y) of each scanning point;

[0106] Step S42.2: Based on the obtained reflection spectrum dataset, obtain the terahertz reflection spectrum time-domain signal;

[0107] Step S43: Identify and classify the core features of the terahertz reflection spectrum time domain signal; obtain a two-class classification of corrosion through feature identification, which includes two categories: corrosion and non-corrosion;

[0108] Step S44.1: Calculate phase parameters based on the binary classification of corrosion;

[0109] Step S44.2: Extract flight time difference parameters based on the binary classification of corrosion;

[0110] Step S45: Calculate the layer thickness based on the phase parameter and time-of-flight difference parameter;

[0111] Step S46: Based on the obtained location information of each scanning point and the thickness calculation results, perform corrosion imaging characterization.

[0112] Furthermore, in another embodiment, for early accelerated point corrosion caused by a 5 wt% NaCl solution, a layer of red paint is applied, and then the corroded steel plate is cured under natural conditions for two months.

[0113] The reflection spectrum dataset with scan point information obtained after scanning and processing using terahertz reflection spectroscopy technology is as follows: Figure 7 As shown, the measurement area is the central area of ​​the steel plate, with a measurement area size of 25.8mm × 25.8mm, 130 points in the x and y directions, and a point spacing of 0.2mm.

[0114] After scanning and measurement using terahertz reflectance spectroscopy, the terahertz reflectance spectral signals within the measurement area include two types: signals from the uncorroded areas of the steel plate and signals from the corroded areas, such as... Figure 8 As shown in a) and b) of the diagram. From the terahertz reflection signal data along the midline of the measurement area, two types of terahertz reflection signals can be clearly identified, representing the corroded area and the uncorroded area, respectively. Figure 8 As shown in c) . Therefore, a Python algorithm was used to perform binary classification of all points within the scanned area into corroded and uncorroded locations, and then signal processing was performed to obtain the phase difference parameter information for each point. Furthermore, as... Figure 5 As shown, the time-of-flight difference parameter and layer thickness were extracted from the scanned data by using different threshold values ​​N. The calculated thicknesses of the rust and overburden layers at the midline position are shown below. Figure 8 As shown in d).

[0115] Based on the assessment of corrosion at various points within the scanning area, and the calculation of phase difference parameters and layer thickness, the corrosion can be visualized using the coordinates of the scanning points and the thickness values. Figure 9 As shown. Figure 9 Image a) shows the imaging characterization of the rust layer and overburden layer within the scanned area. The method of this invention can also achieve two-dimensional and three-dimensional visualization of the rust region and shape beneath the overburden layer, such as... Figure 9 As shown in b) and c) of the diagram. Within the measurement area of ​​the corroded steel plate in this example, the quantity distribution of rust layer thickness values ​​within different ranges can be obtained, as shown in... Figure 9As shown in d), the maximum value of the rust layer thickness is 303.2 μm, the minimum value is 40.7 μm, the average thickness is 121.9 μm, and the rust area accounts for 19.3% of the scanned area. This embodiment demonstrates that the method of the present invention can directly achieve the visual characterization of the shape, area, and thickness of the rust area under the covering layer through terahertz reflection spectroscopy.

[0116] In another embodiment, measurements were taken on a steel plate whose surface was completely rusted using a NaCl solution, covered with a layer of red paint, and then cured under natural conditions for two months.

[0117] The reflection spectrum dataset with scan point information obtained after scanning and processing using terahertz reflection spectroscopy technology is as follows: Figure 10 As shown, the measured area is 16.4mm × 16.4mm, with 83 points in the x and y directions and a point spacing of 0.2mm.

[0118] The steel plate substrate beneath the paint coating was completely corroded. Figure 11 Figure a) illustrates the main types of reflection signals measured by terahertz reflection spectroscopy. As can be seen from the figure, there are three signal amplitudes in the terahertz reflection signal, and the optical time difference corresponding to each amplitude is related to the thickness of the paint coating and the corrosion layer. Taking the terahertz reflection signal data of the center line of the scanning area as an example, the optical time corresponding to the signal amplitude and the thickness values ​​of each layer were extracted using the method described in this invention. Figure 11 In section b), three signal amplitudes can be distinguished, and then the thickness can be calculated, resulting in the following: Figure 11 As shown in c).

[0119] Based on the thickness calculation at each scanned location, the corrosion can be visualized using matrix position coordinates and thickness values, such as... Figure 12 As shown. Figure 12 Image a) shows the imaging characterization of the rust layer and overburden layer within the measurement area. The results indicate that a rust layer exists beneath the overburden material within the scanned area, and its thickness distribution is relatively uniform. Meanwhile, Figure 12 Figures b) and c) illustrate two-dimensional and three-dimensional visualizations of the area of ​​the rusted region under the overburden layer using the method of the present invention. Figure 12 Figure d) shows the quantitative variation of the rust layer thickness within different thickness ranges. Furthermore, the method described in this invention can extract features of the rust layer thickness beneath the overburden layer. The maximum rust layer thickness value is 323.9 μm, the minimum is 72.5 μm, and the average thickness is 187.0 μm. Most importantly, the rusted area occupies 100% of the scanned area.

[0120] like Figure 13As shown, a second aspect of the present invention provides a device for calculating and imaging corrosion thickness based on terahertz technology, the device comprising:

[0121] The information parameter acquisition module S131 acquires the reflection spectrum dataset of the corroded steel plate with the coating layer, and obtains the phase difference parameter and time of flight parameter through the reflection spectrum dataset; wherein, after scanning the corroded steel plate with the coating layer by terahertz reflection spectroscopy technology, a reflection spectrum dataset with scanning point information is obtained.

[0122] The thickness calculation module S132 calculates the thickness of the covering layer and the thickness of the corrosion layer based on the phase difference parameter and the flight time parameter using the thickness layer calculation formula.

[0123] The imaging characterization module S133 completes and outputs the corrosion imaging characterization using the reflectance spectrum dataset, the thickness of the overburden layer, and the thickness of the corrosion layer.

[0124] A third aspect of this application provides a computer-readable storage medium, characterized in that the computer-readable storage medium stores one or more programs, which can be executed by one or more processors to implement the steps in the terahertz-based corrosion thickness calculation and imaging characterization method described above.

[0125] A fourth aspect of this application provides a terminal device, characterized in that it includes: a processor, a memory, and a communication bus; the memory stores a computer-readable program that can be executed by the processor;

[0126] The communication bus enables communication between the processor and the memory;

[0127] When the processor executes the computer-readable program, it implements the steps in the above-described method for calculating and imaging characterizing corrosion thickness based on terahertz technology.

[0128] In summary, this invention provides a method for calculating and imaging characterizing corrosion thickness based on terahertz technology. The method includes acquiring a reflection spectrum dataset of a corroded steel plate with a coating layer, and obtaining phase difference and time-of-flight parameters from the reflection spectrum dataset. Specifically, after scanning the corroded steel plate with the coating layer using terahertz reflection spectroscopy, a reflection spectrum dataset with scan point information is obtained. Based on the phase difference and time-of-flight parameters, the coating layer thickness and corrosion layer thickness are calculated using a thickness calculation formula. The corrosion imaging characterization is then completed and output using the reflection spectrum dataset, coating layer thickness, and corrosion layer thickness. Through this method, this invention can perform feature recognition and binary classification using the acquired reflection spectrum dataset to identify corroded and non-corroded areas. Then, by obtaining the phase difference and time-of-flight parameters from the reflection spectrum dataset, the corresponding coating layer thickness and corrosion layer thickness can be directly derived from the terahertz reflection signal. Based on the obtained corroded areas and their corresponding thicknesses, accurate quantitative characterization of corrosion can be achieved.

[0129] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0130] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and direct memory bus dynamic RAM (RDRAM).

[0131] It should be understood that the application of the present invention is not limited to the examples above. Those skilled in the art can make improvements or modifications based on the above description, and all such improvements and modifications fall within the protection scope of the appended claims.

Claims

1. A method for calculating and imaging characterizing corrosion thickness based on terahertz technology, characterized in that, include: A reflection spectrum dataset of a corroded steel plate with a coating was obtained, and the phase difference and time-of-flight parameters were derived from the dataset. Specifically, after scanning the corroded steel plate with the coating using terahertz reflection spectroscopy, a reflection spectrum dataset with scan point information was obtained, including: A measurement area is pre-defined on the corroded steel plate, and the scanning point is set on the measurement area; The terahertz reflectance spectroscopy technique is used to perform terahertz reflectance spectroscopy scanning and measurement on the scanning points within the measurement area to obtain a reflectance spectroscopy dataset. After obtaining the reflection spectrum dataset, feature recognition binary classification is performed on the reflection spectrum dataset to obtain binary representations of corrosion and non-corrosion at each location of the scan point; Based on the binary classification of rust and non-rust at the scanning point location, the phase difference parameters of the steel plate signal and the corresponding reference signal at each scanning point location are obtained; Based on the binary classification of corrosion and non-corrosion at the scanning point location and the reflection spectrum dataset, the terahertz reflection spectrum signal amplitude and its corresponding time parameter of all scanning points in the scanning area are extracted to obtain the time-of-flight parameter. Based on the phase difference parameter and flight time parameter, the thickness of the covering layer and the thickness of the corrosion layer are calculated using the thickness layer calculation formula. The calculation of the overburden thickness and corrosion layer thickness based on the phase difference parameter and flight time parameter using the thickness layer calculation formula specifically includes: When scanning the corroded steel plate using terahertz reflection spectroscopy, the received terahertz reflection spectroscopy signal is simultaneously processed as a terahertz transmission signal. Based on the phase difference parameter and time of flight parameter, the optical parameters at the scanning point and the thickness layer calculation formula are obtained by combining the transmission optical parameter calculation formula and the reflection spectrum thickness calculation formula. The thickness of the coating layer and the thickness of the corrosion layer are obtained by using the optical parameters at the scanning point and the thickness calculation formula. The corrosion imaging characterization is completed and output using the reflectance spectrum dataset, the thickness of the overburden layer, and the thickness of the rust layer. The visualization characterization of the corrosion is achieved through matrix position coordinates and thickness values.

2. The method for calculating and imaging characterizing corrosion thickness based on terahertz technology according to claim 1, characterized in that, The calculation of the overburden thickness and corrosion layer thickness based on the phase difference parameter and flight time parameter using the thickness layer calculation formula specifically includes: When the terahertz reflection spectroscopy technique is used to scan the corroded steel plate, the signal angle of the terahertz incident signal is 0 degrees.

3. The method for calculating and imaging characterizing corrosion thickness based on terahertz technology according to claim 1, characterized in that, The process of characterizing and outputting corrosion imaging data using reflectance spectrum datasets, overburden thickness, and corrosion layer thickness specifically includes: The corrosion imaging characterization includes visualization of the shape and area of ​​the corrosion, as well as quantitative characterization of the overburden and corrosion layers.

4. A device for calculating and imaging characterizing corrosion thickness based on terahertz technology, wherein the device is used to implement the method for calculating and imaging characterizing corrosion thickness based on terahertz technology as described in any one of claims 1-3, characterized in that, The device includes: The information parameter acquisition module acquires the reflection spectrum dataset of the corroded steel plate with the coating layer, and obtains the phase difference parameter and time-of-flight parameter from the reflection spectrum dataset; in particular, after scanning the corroded steel plate with the coating layer using terahertz reflection spectroscopy technology, a reflection spectrum dataset with scanning point information is obtained. The thickness calculation module calculates the thickness of the covering layer and the thickness of the corrosion layer based on the phase difference parameter and the time of flight parameter using the thickness layer calculation formula. The imaging characterization module completes and outputs the corrosion imaging characterization using the reflectance spectrum dataset, the thickness of the overburden layer, and the thickness of the corrosion layer.

5. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores one or more programs, which can be executed by one or more processors to implement the steps in the terahertz-based method for calculating and imaging characterizing corrosion thickness as described in any one of claims 1-3.

6. A terminal device, characterized in that, include: Processor, memory, and communication bus; the memory stores a computer-readable program that can be executed by the processor; The communication bus enables communication between the processor and the memory; When the processor executes the computer-readable program, it implements the steps in the method for calculating and imaging characterizing corrosion thickness based on terahertz technology as described in any one of claims 1-3.

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