Oxide skin detection method and device, electronic equipment and storage medium

Abstract

The invention discloses an oxide skin detection method and device, electronic equipment and a storage medium, and relates to the technical field of nondestructive detection.The oxide skin detection method comprises the steps that oxide skin phase composition information of all sampling points on the surface of hot-rolled strip steel is obtained, and the oxide skin phase composition information comprises oxide skin components and component mass proportions; and for each sampling point, calculating optical parameters according to the oxide skin phase composition information of the sampling point, and calculating the oxide skin thickness of the sampling point according to the terahertz echo signal of the oxide skin on the surface of the hot-rolled strip steel and the optical parameters. The method can guarantee the nondestructive high-precision measurement of the surface oxide skin of the hot-rolled strip steel.

Description

Technical Field

[0001] The present application relates to the field of nondestructive testing technology, and in particular to oxide scale detection methods, devices, electronic equipment and storage media. Background Art

[0002] As a common metal material, hot-rolled strip is widely used in construction, automobile manufacturing, chemical industry and other fields due to its advantages such as low price, strong corrosion resistance, excellent mechanical and processing properties. However, during the hot rolling process, micron-level oxide scale will inevitably form on the surface of the steel. If the oxide scale is damaged, it will seriously affect the service life and performance stability of the hot-rolled strip.

[0003] However, existing oxide scale detection technologies such as optical microscope detection, ultrasonic detection, infrared detection, eddy current detection, etc., have shortcomings such as contact detection, destructive detection, and poor spatial resolution. They cannot be fully applied to the industrial production environment of hot-rolled strip, and it is difficult to ensure non-destructive and high-precision measurement of the oxide scale on the surface of hot-rolled strip. Summary of the invention

[0004] The main purpose of this application is to provide an oxide scale detection method, device, electronic equipment and storage medium, aiming to ensure non-destructive and high-precision measurement of oxide scale on the surface of hot-rolled strip.

[0005] To achieve the above purpose, the present application proposes an oxide scale detection method, which comprises: Obtaining oxide scale phase composition information at each sampling point on the surface of the hot-rolled steel strip, wherein the oxide scale phase composition information includes oxide scale components and component mass ratios; For each of the sampling points, optical parameters are calculated according to the oxide scale phase composition information of the sampling point, and the oxide scale thickness of the sampling point is calculated according to the terahertz echo signal of the oxide scale on the surface of the hot-rolled strip and the optical parameters.

[0006] In one embodiment, the step of obtaining the oxide scale phase composition information at each sampling point on the surface of the hot-rolled steel strip comprises: For each sampling point on the surface of the hot-rolled steel strip, the sampling point is scanned by a preset X-ray diffractometer to obtain a scanning result, wherein the scanning result includes the oxide scale composition of the sampling point; The scanning result is fitted with a full diffraction spectrum by a preset structure refinement algorithm to obtain the component mass ratio of the sampling point.

[0007] In one embodiment, the optical parameter includes a refractive index of an oxide scale, and the step of calculating the optical parameter for each sampling point according to the oxide scale phase composition information of the sampling point includes: For each of the sampling points, obtaining the refractive index of the oxide scale component; The refractive index of the oxide scale at the sampling point is calculated according to the refractive index and the mass ratio of the components.

[0008] In one embodiment, before the step of calculating the oxide scale thickness of the sampling point according to the terahertz echo signal of the oxide scale on the surface of the hot-rolled steel strip and the optical parameters, the step further includes: Construct a sparse decomposition model of terahertz echo signal for the oxide scale on the surface of hot-rolled strip; Solving the optimal solution of the pulse response sequence for the oxide scale on the surface of the hot-rolled strip based on the sparse decomposition model of the terahertz echo signal, and obtaining a sparsely reconstructed pulse response function; The step of calculating the oxide scale thickness at the sampling point according to the terahertz echo signal of the oxide scale on the surface of the hot-rolled strip and the optical parameters comprises: The oxide scale thickness at the sampling point is calculated according to the pulse response function and the optical parameters.

[0009] In one embodiment, the optical parameter includes an oxide skin refractive index, and the step of calculating the oxide skin thickness of the sampling point according to the pulse response function and the optical parameter includes: Determine time delay data according to the impulse response function, wherein the time delay data is the time delay between two adjacent reflections from the sampling point; The oxide scale thickness at the sampling point is calculated according to the time delay data and the oxide scale refractive index.

[0010] In one embodiment, before the step of constructing a sparse decomposition model of a terahertz echo signal for oxide scale on the surface of a hot-rolled steel strip, the step further includes: A time-slice dispersion model for the oxide scale on the surface of hot-rolled steel strip is constructed. The time-slice dispersion model is used to characterize the spatiotemporal morphological evolution characteristics of the pulse waveform of the terahertz time-domain reflection signal of the oxide scale on the surface of the hot-rolled steel strip. The kernel function of the time-slice dispersion model is: , in, represents the kernel function, It represents the dispersion degree of the terahertz echo signal of the oxide scale on the surface of the hot-rolled strip, and n represents the sampling point.

[0011] In one embodiment, the step of constructing a sparse decomposition model of a terahertz echo signal for oxide scale on the surface of a hot-rolled steel strip comprises: A terahertz echo signal sparse decomposition model for the oxide scale on the surface of hot-rolled strip is constructed. The terahertz echo signal sparse decomposition model is expressed as: , Where Y represents the sparse decomposition model of terahertz echo signal, The matrix representing the spread of the terahertz pulse over the entire propagation distance, , The column vector is composed of the time delay sequence of the terahertz reference signal, represents the column vector consisting of impulse response functions, represents Gaussian white noise.

[0012] In addition, to achieve the above purpose, the present application also proposes an oxide scale detection device, which includes: A phase composition information acquisition module is used to acquire the phase composition information of the oxide scale at each sampling point on the surface of the hot-rolled strip, wherein the phase composition information of the oxide scale includes the oxide scale composition and the mass ratio of the composition; The thickness calculation module is used to calculate the optical parameters of each sampling point according to the oxide scale phase composition information of the sampling point, and calculate the oxide scale thickness of the sampling point according to the terahertz echo signal of the oxide scale on the surface of the hot-rolled strip and the optical parameters.

[0013] In addition, to achieve the above objectives, the present application also proposes an electronic device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the oxide scale detection method as described above.

[0014] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the oxide scale detection method as described above are implemented.

[0015] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the oxide scale detection method described above are implemented.

[0016] The present application proposes a scale detection method, which obtains scale phase composition information at each sampling point from the surface of a hot-rolled steel strip, wherein the scale phase composition information includes specific scale components and their component mass ratios; then, the optical parameters of the scale at the corresponding sampling point, such as the refractive index, are calculated based on the scale phase composition information, and at the same time, a terahertz time-domain spectroscopy system is used to perform non-contact scanning on the surface of the hot-rolled steel strip to obtain a terahertz echo signal; finally, the scale thickness at each sampling point is calculated by combining the terahertz echo signal and the optical parameters of the scale at each sampling point.

[0017] In summary, compared with traditional detection methods, the present application can accurately obtain the phase composition information of the oxide scale by combining phase analysis technology with terahertz spectroscopy technology, and calculate accurate optical parameters based on this, thereby achieving high-precision measurement of the oxide scale thickness. At the same time, it can realize non-destructive detection of the oxide scale thickness on the surface of the hot-rolled strip without damaging the surface of the hot-rolled strip. It is suitable for the industrial production environment of hot-rolled strip and ensures non-destructive and high-precision measurement of the oxide scale on the surface of the hot-rolled strip. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0019] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0020] Figure 1 A schematic diagram of a process flow provided for Example 1 of the oxide scale detection method of the present application; Figure 2 A schematic diagram of the phase composition information of oxide scale provided in Example 1 of the oxide scale detection method of the present application; Figure 3 A schematic diagram of the propagation path provided for Example 2 of the oxide scale detection method of the present application; Figure 4 A schematic diagram of the time domain spectrum of the terahertz reflection signal provided in Example 2 of the oxide scale detection method of the present application; Figure 5 A schematic diagram of an impulse response function provided for Example 2 of the oxide scale detection method of the present application; Figure 6 This is a schematic diagram of the module structure of the oxide scale detection device according to an embodiment of the present application; Figure 7 Schematic diagram of the equipment structure of the hardware operating environment involved in the oxide scale detection method in the embodiment of the present application.

[0021] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0022] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0023] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0024] Existing oxide scale detection technologies such as optical microscope detection, ultrasonic detection, infrared detection, eddy current detection, etc., have shortcomings such as contact detection, destructive detection, and poor spatial resolution. They cannot be fully applied to the industrial production environment of hot-rolled strip, and it is difficult to ensure non-destructive and high-precision measurement of the oxide scale on the surface of hot-rolled strip.

[0025] An embodiment of the present application provides a solution, which obtains oxide scale phase composition information at each sampling point from the surface of a hot-rolled steel strip, wherein the oxide scale phase composition information includes specific oxide scale components and their component mass ratios; then, the optical parameters of the oxide scale at the corresponding sampling point, such as the refractive index, are calculated based on the oxide scale phase composition information, and at the same time, a terahertz time-domain spectroscopy system is used to perform non-contact scanning on the surface of the hot-rolled steel strip to obtain a terahertz echo signal; finally, the oxide scale thickness at each sampling point is calculated by combining the terahertz echo signal and the optical parameters of the oxide scale at each sampling point.

[0026] In summary, compared with traditional detection methods, the present application can accurately obtain the phase composition information of the oxide scale by combining phase analysis technology with terahertz spectroscopy technology, and calculate accurate optical parameters based on this, thereby achieving high-precision measurement of the oxide scale thickness. At the same time, it can realize non-destructive detection of the oxide scale thickness on the surface of the hot-rolled strip without damaging the surface of the hot-rolled strip. It is suitable for the industrial production environment of hot-rolled strip and ensures non-destructive and high-precision measurement of the oxide scale on the surface of the hot-rolled strip.

[0027] It should be noted that the execution subject of this embodiment can be an electronic device with data processing, network communication and program running functions, such as a computer, a server, etc., or an electronic device capable of realizing the above functions, etc. The following takes the oxide skin detection terminal as an example to illustrate this embodiment and the following embodiments.

[0028] Based on this, the present application embodiment provides a method for detecting oxide scale, referring to Figure 1 , Figure 1 This is a schematic flow chart of the first embodiment of the oxide scale detection method of the present application.

[0029] In this embodiment, the oxide scale detection method includes steps S10 to S30: Step S10, obtaining oxide scale phase composition information of each sampling point on the surface of the hot-rolled steel strip, wherein the oxide scale phase composition information includes oxide scale components and component mass ratios; It should be noted that the hot-rolled steel strip in this embodiment may be a hot-rolled steel strip prepared in a production environment with an oxygen content of 20.9% and a water vapor content of 15%. After the hot rolling process is completed, the production steel strip is cooled to a desired temperature by spraying water on both sides of the steel strip, and after reaching the desired temperature, it is naturally cooled to room temperature in the air at a slow speed. The oxide scale is formed on the hot-rolled steel substrate during the entire cooling process, and the optical thickness of the oxide scale is relatively thin, generally below 10 μm.

[0030] Material analysis technology is used to perform fine scanning on multiple preset sampling points on the surface of the hot-rolled strip (the sampling points can cover the entire surface of the hot-rolled strip) to collect the physical composition information of the oxide scale at each sampling point, which includes the oxide scale components (FeO, Fe2O3 and Fe3O4, etc.) and their corresponding component mass ratios.

[0031] In a feasible embodiment, step S10 may include steps S101-S102: Step S101, for each sampling point on the surface of the hot-rolled steel strip, scanning the sampling point by a preset X-ray diffractometer to obtain a scanning result, wherein the scanning result includes the oxide scale composition of the sampling point; Using the preset X-ray diffraction (XRD) scanning tool, each sampling point on the surface of the hot-rolled strip is scanned in turn. XRD technology is based on the interaction principle between X-rays and the internal crystal structure of the material, which can reveal the existence and structural characteristics of different phases (including oxide scale components) in the sample. Through this scanning process, the scanning results containing the oxide scale components of each sampling point are obtained.

[0032] Step S102, performing full diffraction spectrum fitting on the scanning result by using a preset structure refinement algorithm to obtain the component mass ratio of the sampling point.

[0033] The scanning results are fitted with the full diffraction spectrum through the preset structure refinement algorithm to obtain the mass ratio of the components at each sampling point. The structure refinement algorithm used is based on advanced mathematical and physical models and powerful computing power, which can accurately fit the full diffraction spectrum obtained by scanning. By continuously adjusting the content parameters of each phase (i.e., different components in the oxide scale) in the model, the algorithm can find the solution that best matches the experimental data, thereby accurately calculating the mass ratio of various components in the oxide scale at each sampling point.

[0034] It should be noted that since it is difficult to distinguish the Fe phase in the oxide scale from the steel matrix, the Fe phase is not considered when calculating the weight fraction of each phase in the oxide scale.

[0035] For example, in a feasible implementation, the full diffraction spectrum is fitted using Rietveld Refinement (structure refinement algorithm) according to the scanning results, and the mass fraction of each iron oxide phase in the oxide scale is estimated by adjusting the crystallographic parameters. The final oxide scale phase composition information is as follows: Figure 2 As shown in the figure, the chart with "2 (deg)" as the horizontal axis and "Intensity (arb)" as the vertical axis is used to show the results of X-ray diffraction, where the horizontal axis represents the diffraction angle (reflecting the crystal structure information) and the vertical axis represents the intensity of the diffraction peak (reflecting the crystal quality, orientation and other information). According to the figure, it can be intuitively understood that the components of the oxide scale include FeO, Fe2O3, Fe3O4 and Fe, and the mass ratio of Fe is not analyzed. The pie chart in the upper right corner of the figure shows the mass ratio of each component, and the mass ratio of FeO:Fe2O3:Fe3O4 is 44%:14%:42%.

[0036] Step S20, for each of the sampling points, calculating optical parameters according to the oxide scale phase composition information of the sampling point, and calculating the oxide scale thickness of the sampling point according to the terahertz echo signal of the oxide scale on the surface of the hot-rolled strip and the optical parameters.

[0037] After obtaining the phase composition information of the oxide scale at each sampling point on the surface of the hot-rolled strip, the optical parameters of the oxide scale at each sampling point are calculated based on the information. Subsequently, terahertz time-domain spectroscopy (THz-TDS) is used to emit terahertz pulses to the surface of the hot-rolled strip, and terahertz echo signals reflected by the oxide scale on the surface of the hot-rolled strip are received. The thickness of the oxide scale at each sampling point is calculated based on the terahertz echo signals and the optical parameters calculated previously, wherein the acquisition time of the terahertz echo signals is not specifically limited.

[0038] In a feasible embodiment, the step of "for each of the sampling points, calculating the optical parameters according to the oxide scale phase composition information of the sampling point" in step S20 may include steps S201-S202: Step S201, obtaining the refractive index of the oxide scale component for each sampling point; For the oxide scale components of each determined sampling point, the refractive index of each oxide scale component (such as FeO, Fe2O3, Fe3O4, etc.) under specific conditions can be obtained by consulting the relevant physical property database or literature.

[0039] In a feasible way, the refractive index of each oxide scale component can also be calculated through a transmission experiment. Specifically, a terahertz time-domain spectroscopy system is used to conduct a transmission experiment on different iron oxide powders. In order to avoid the influence of water vapor on the experimental results, the terahertz time-domain spectroscopy test experiment is carried out in a dry nitrogen environment. Before each test experiment, the reference signal (that is, the signal collected when the iron oxide tablet to be tested is not placed) is measured first, and then the iron oxide tablet is tested separately. The time domain data is converted into a frequency domain spectrum using a fast Fourier transform. According to the literature, by comparing with the amplitude and phase information of the terahertz time domain reference spectrum in free space, the Fresnel formula is used to extract the refractive index of different iron oxides in the terahertz frequency band to describe the dispersion and absorption characteristics. , the refractive index is calculated as: , in, is the frequency, is the phase difference between the sample and the reference signal, is the speed of light, is the thickness of the sample (i.e., iron oxide pellet).

[0040] Step S202, calculating the refractive index of the oxide scale at the sampling point according to the refractive index and the mass ratio of the components.

[0041] After obtaining the refractive index of each oxide scale component, the overall refractive index of the oxide scale at the sampling point is calculated based on the refractive indices of these components and their mass ratios in the oxide scale at the sampling point, thereby fully considering the contribution of different components in the oxide scale and ensuring that the final refractive index value can accurately reflect the optical properties of the oxide scale at the sampling point.

[0042] Specifically, based on the refractive indices of the different oxide scale components (FeO, Fe2O3, Fe3O4, etc.), the oxide scale refractive index of the mixed-phase oxide scale at the sampling point was calculated using the effective medium theory. The calculation formula for the oxide scale refractive index is: , Among them, n eff represents the refractive index of the oxide skin, and are the refractive indices of different oxide scale components and the corresponding volume filling factors. The volume filling factor can be obtained by dividing the quality factors of the respective oxide scale components obtained by analysis by their respective densities.

[0043] In summary, compared with traditional detection methods, the embodiment of the present application, by combining phase analysis technology with terahertz spectroscopy technology, can accurately obtain the phase composition information of the oxide scale, and calculate accurate optical parameters based on this, thereby achieving high-precision measurement of the oxide scale thickness. At the same time, it can achieve non-destructive detection of the oxide scale thickness on the surface of the hot-rolled strip without damaging the surface of the hot-rolled strip. It is suitable for the industrial production environment of hot-rolled strip and ensures non-destructive and high-precision measurement of the oxide scale on the surface of the hot-rolled strip.

[0044] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the first embodiment can be referred to the above description, and will not be described in detail later. On this basis, before step S20, steps S30 to S40 may also be included: Step S30, constructing a sparse decomposition model of the terahertz echo signal for the oxide scale on the surface of the hot-rolled strip; A terahertz echo signal sparse decomposition model specifically for the detection of oxide scale on the surface of hot-rolled strip is constructed. The model is used to effectively process the complex echo signal generated by the interaction between the terahertz wave and the oxide scale on the surface of the hot-rolled strip by using the sparse decomposition theory, ensuring that the model can accurately capture the characteristic information related to the oxide scale characteristics of the hot-rolled strip in the terahertz echo signal.

[0045] Step S40, solving the optimal solution of the impulse response sequence for the oxide scale on the surface of the hot-rolled steel strip based on the sparse decomposition model of the terahertz echo signal to obtain a sparsely reconstructed impulse response function; Based on the constructed sparse decomposition model of terahertz echo signals, the optimal solution of the pulse response sequence of the oxide scale on the surface of the hot-rolled strip is solved, and the optimal solution of the pulse response sequence that can best describe the response characteristics of the oxide scale to the terahertz wave is obtained. Subsequently, the sparse reconstruction technology is used to generate a sparsely reconstructed pulse response function. This function not only retains the important information in the original terahertz echo signal, but also improves the clarity and accuracy of the signal by removing redundancy and noise, thereby obtaining higher quality characteristic information related to the characteristics of the oxide scale of the hot-rolled strip.

[0046] Based on this, the step of "calculating the oxide scale thickness of the sampling point according to the terahertz echo signal of the oxide scale on the surface of the hot-rolled strip and the optical parameters" in step S20 may include step S203: Step S203: calculating the oxide scale thickness at the sampling point according to the impulse response function and the optical parameters.

[0047] The oxide scale thickness at the sampling point is calculated based on the pulse response function obtained by sparse reconstruction and the calculated optical parameters, wherein the pulse response function intuitively reflects the response of the oxide scale on the surface of the hot-rolled strip to the input pulse signal.

[0048] In a feasible embodiment, the optical parameter includes the refractive index of the oxide skin, and step S203 may include steps S2031-S2032: Step S2031, determining time delay data according to the impulse response function, wherein the time delay data is the time delay between two adjacent reflections from the sampling point; By analyzing the pulse response function, the time delay between two adjacent echoes reflected by the oxide scale on the surface of the hot-rolled strip is identified and recorded. The time delay data is directly related to the physical properties of the oxide scale on the surface of the hot-rolled strip, especially its thickness information.

[0049] Step S2032: Calculate the oxide skin thickness at the sampling point according to the time delay data and the oxide skin refractive index.

[0050] Using the obtained time delay data and the calculated oxide scale refractive index, the specific thickness of the oxide scale is calculated. The thickness calculation formula is: , where c is the speed of light in air, is the time delay between two adjacent reflected echoes from the conformal coating, is the refractive index of the oxide skin, that is, the aforementioned n eff .

[0051] In a feasible embodiment, before step S30, step A10 may be further included: Step A10, constructing a time-slice dispersion model for the oxide scale on the surface of the hot-rolled steel strip, wherein the time-slice dispersion model is used to characterize the spatiotemporal morphological evolution characteristics of the pulse waveform of the terahertz time-domain reflection signal of the oxide scale on the surface of the hot-rolled steel strip, and the kernel function of the time-slice dispersion model is: , in, represents the kernel function, It represents the dispersion degree of the terahertz echo signal of the oxide scale on the surface of the hot-rolled strip, and n represents the sampling point.

[0052] In this embodiment, before formally constructing a sparse decomposition model of the terahertz echo signal for the oxide scale on the surface of the hot-rolled strip, a time slice dispersion model for the oxide scale on the surface of the hot-rolled strip is constructed. The model is used to characterize the spatiotemporal morphological evolution characteristics of the pulse waveform of the oxide scale on the surface of the hot-rolled strip in the terahertz time domain reflection signal.

[0053] The time-slice dispersion model captures the effect of oxide skin on the propagation characteristics of terahertz waves through its kernel function. is defined as a piecewise function, the specific form is: , in, As the output of the kernel function, it is directly related to the dispersion degree at each sampling point n (representing different positions on the surface of the hot-rolled strip), a represents the dispersion degree of the terahertz echo signal for the oxide scale on the surface of the hot-rolled strip, and is used to quantify the influence of the oxide scale on the waveform distortion and energy dispersion during the propagation of the terahertz wave. Specifically, a represents the dispersion degree of the terahertz echo signal, and 0≤a≤0.5. For example, in this embodiment, a=0.03 is taken.

[0054] In a feasible embodiment, step S30 may include step S301: Step S301, constructing a terahertz echo signal sparse decomposition model for the oxide scale on the surface of the hot-rolled strip, wherein the terahertz echo signal sparse decomposition model is expressed as: , Where Y represents the sparse decomposition model of terahertz echo signal, The matrix representing the spread of the terahertz pulse over the entire propagation distance, , The column vector is composed of the time delay sequence of the terahertz reference signal, represents the column vector consisting of impulse response functions, represents Gaussian white noise.

[0055] In this embodiment, the mathematical expression of the sparse decomposition model of the terahertz echo signal for the oxide scale on the surface of the hot-rolled strip is determined as follows: , where Y represents the output of the sparse decomposition model of the terahertz echo signal, which is a signal reconstruction result containing the oxide skin information. is a matrix that represents the expansion of the terahertz pulse over the entire propagation distance, and its column vectors are determined by the time-slice dispersion model (through The pulse spread function is composed of , The column vector of is composed of the time delay sequence of the terahertz echo reference signal, h is a column vector composed of impulse response functions, which directly reflects the response characteristics of the oxide skin to the terahertz wave. e represents Gaussian white noise, which is an inevitable interference factor in actual measurement.

[0056] By constructing a sparse decomposition model of the terahertz echo signal for the oxide scale on the surface of hot-rolled strip, the performance of the oxide scale on the surface of hot-rolled strip in the terahertz echo signal can be analyzed more accurately.

[0057] For example, in one possible implementation, Figure 3Schematic diagram of the propagation path of terahertz pulses emitted to hot-rolled steel strips. The hot-rolled steel strips include a steel substrate and an oxide scale wrapped on the surface of the substrate. The reflective terahertz time-domain spectroscopy system emits terahertz pulses to the complete hot-rolled steel strips and obtains the reflected terahertz pulses from the interface between air and oxide scale. Echo and interface between oxide scale and steel substrate The echo is the terahertz reflection signal, and the time domain spectrum of the terahertz reflection signal is as follows: Figure 4 As shown, the horizontal axis Optical delay (ps) is the optical delay (picoseconds), and the vertical axis Amplitude (au) is the amplitude (arbitrary unit).

[0058] In a feasible embodiment, step S40 may include steps S401-S402: Step S401, simplifying the non-convex optimization problem of the terahertz echo signal sparse decomposition model into a convex optimization problem by solving the l1 norm instead of the l0 norm. The convex optimization problem is expressed as: , in, is a regularization parameter used to balance reconstruction accuracy and sparsity, for The l1 norm of ; Since directly solving the sparse decomposition model of the terahertz echo signal based on the l0 norm (i.e. directly finding the solution with the least non-zero elements) is a non-convex optimization problem, the computational complexity is high and it is easy to fall into the local optimum. Therefore, in this embodiment, the l1 norm (i.e. the sum of the absolute values ​​of each element in the vector) is used to replace the l0 norm to transform the problem into a convex optimization problem. The convex optimization problem has the advantages of global optimal solution and easy solution. The converted convex optimization problem is expressed as: , where λ is the regularization parameter used to find the best balance between reconstruction accuracy (i.e., the accuracy of the signal fit) and sparsity (i.e., the number of non-zero elements in the impulse response function), for The l1 norm of , which is used to promote the sparsity of the solution.

[0059] Step S402, solving the convex optimization problem to obtain a sparsely reconstructed impulse response function.

[0060] In a feasible embodiment, step S402 may include steps S4021-S4022: Step S4021, using a two-step iterative shrinkage threshold algorithm to solve the convex optimization problem, and obtaining h The iteration formula is: , , Among them, h0 is the initial vector, and are two convergence parameters of the two-step iterative shrinkage threshold algorithm. In addition, , in, is about the current vector Soft thresholding or shrinkage operator for each component of ; In this embodiment, in order to solve the convex optimization problem, a two-step iterative shrinkage threshold algorithm (Two-Step Iterative Shrinkage / Thresholding Algorithm, TWIST) can be used. The algorithm iteratively updates the vector h , gradually approaching the optimal solution.

[0061] In the TWIST algorithm, each iteration updates the vector based on the results of the previous two iterations and the current gradient information. h Specifically, the iteration formula is: , , Among them, h0 is the initial vector, and are two convergence parameters of the two-step iterative shrinkage threshold algorithm, which are used to control the convergence speed and stability during the iteration process. In addition, , in, is about the current vector A soft threshold or shrinkage operator is applied to each component of , which is used to set elements smaller than a threshold λ to zero to promote sparsity.

[0062] Step S4022: Calculate the impulse response function of sparse reconstruction according to the iterative formula.

[0063] By repeatedly applying the above iterative formula until the convergence condition is met (such as the number of iterations reaches the preset upper limit or the change in the objective function value is less than the preset threshold), the sparsely reconstructed impulse response function h(t) is finally obtained, which can effectively reflect the characteristics of the oxide scale on the surface of the hot-rolled strip, such as thickness, distribution, etc.

[0064] For example, in a feasible implementation manner, the impulse response function after sparse reconstruction is as follows: Figure 5As shown, the horizontal axis Optical delay (ps) is optical delay (picoseconds), and the vertical axis Amplitude (au) is amplitude (arbitrary unit), which describes the change of the amplitude of the optimized terahertz echo over time in the time domain. By analyzing the amplitude and phase of the pulse response function, the thickness of the oxide scale on the surface of the hot-rolled strip can be determined.

[0065] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the oxide scale detection method of the present application. More simple transformations based on this technical concept are all within the protection scope of the present application.

[0066] The present application also provides an oxide scale detection device, please refer to Figure 6 , the oxide skin detection device includes: The phase composition information acquisition module 10 is used to acquire the phase composition information of the oxide scale at each sampling point on the surface of the hot-rolled steel strip, wherein the phase composition information of the oxide scale includes the oxide scale components and the mass ratio of the components; The thickness calculation module 20 is used to calculate the optical parameters of each sampling point according to the oxide scale phase composition information of the sampling point, and calculate the oxide scale thickness of the sampling point according to the terahertz echo signal of the oxide scale on the surface of the hot-rolled strip and the optical parameters.

[0067] Optionally, the phase composition information acquisition module 10 is further used for: For each sampling point on the surface of the hot-rolled steel strip, the sampling point is scanned by a preset X-ray diffractometer to obtain a scanning result, wherein the scanning result includes the oxide scale composition of the sampling point; The scanning result is fitted with a full diffraction spectrum by a preset structure refinement algorithm to obtain the component mass ratio of the sampling point.

[0068] Optionally, the optical parameters include the refractive index of the oxide skin, and the thickness calculation module 20 is also used for: For each of the sampling points, obtaining the refractive index of the oxide scale component; The refractive index of the oxide scale at the sampling point is calculated according to the refractive index and the mass ratio of the components.

[0069] Optionally, the oxide scale detection device further includes a function reconstruction module (not shown), which is used to: Construct a sparse decomposition model of terahertz echo signal for the oxide scale on the surface of hot-rolled strip; Solving the optimal solution of the pulse response sequence for the oxide scale on the surface of the hot-rolled strip based on the sparse decomposition model of the terahertz echo signal, and obtaining a sparsely reconstructed pulse response function; Optionally, the thickness calculation module 20 is further used for: The oxide scale thickness at the sampling point is calculated according to the pulse response function and the optical parameters.

[0070] Optionally, the optical parameters include the refractive index of the oxide skin, and the thickness calculation module 20 is also used for: Determine time delay data according to the impulse response function, wherein the time delay data is the time delay between two adjacent reflections from the sampling point; The oxide scale thickness at the sampling point is calculated according to the time delay data and the oxide scale refractive index.

[0071] Optionally, the scale detection device further includes a dispersion model building module (not shown), and the dispersion model building module is used to: A time-slice dispersion model for the oxide scale on the surface of hot-rolled steel strip is constructed. The time-slice dispersion model is used to characterize the spatiotemporal morphological evolution characteristics of the pulse waveform of the terahertz time-domain reflection signal of the oxide scale on the surface of the hot-rolled steel strip. The kernel function of the time-slice dispersion model is: , in, represents the kernel function, It represents the dispersion degree of the terahertz echo signal of the oxide scale on the surface of the hot-rolled strip, and n represents the sampling point.

[0072] Optionally, the function reconstruction module is also used to: A terahertz echo signal sparse decomposition model for the oxide scale on the surface of hot-rolled strip is constructed. The terahertz echo signal sparse decomposition model is expressed as: , Where Y represents the sparse decomposition model of terahertz echo signal, The matrix representing the spread of the terahertz pulse over the entire propagation distance, , The column vector is composed of the time delay sequence of the terahertz reference signal, represents the column vector consisting of impulse response functions, represents Gaussian white noise.

[0073] The oxide scale detection device provided in the embodiment of the present application adopts the oxide scale detection method in the above embodiment, which can ensure non-destructive and high-precision measurement of the oxide scale on the surface of the hot-rolled strip. Compared with the prior art, the beneficial effects of the oxide scale detection device provided in the embodiment of the present application are the same as the beneficial effects of the oxide scale detection method provided in the above embodiment, and other technical features in the oxide scale detection device are the same as the features disclosed in the oxide scale detection method in the above embodiment, which will not be repeated here.

[0074] An embodiment of the present application provides an electronic device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the oxide scale detection method in the above-mentioned embodiment 1.

[0075] Reference below Figure 7 , which shows a schematic diagram of the structure of an electronic device suitable for implementing the embodiments of the present application. The electronic devices in the embodiments of the present application may include but are not limited to mobile terminals such as laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 7 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0076] like Figure 7 As shown, the electronic device may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the electronic device are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the electronic device to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows an electronic device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have alternatively.

[0077] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0078] The electronic device provided in the embodiment of the present application adopts the oxide scale detection method in the above embodiment, which can ensure non-destructive and high-precision measurement of the oxide scale on the surface of hot-rolled strip steel. Compared with the prior art, the beneficial effects of the electronic device provided in the embodiment of the present application are the same as the beneficial effects of the oxide scale detection method provided in the above embodiment, and other technical features in the electronic device are the same as the features disclosed in the oxide scale detection method in the previous embodiment, which will not be repeated here.

[0079] It should be understood that the various parts disclosed in the embodiments of the present application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0080] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0081] An embodiment of the present application provides a computer-readable storage medium having computer-readable program instructions (ie, a computer program) stored thereon, wherein the computer-readable program instructions are used to execute the oxide scale detection method in the above-mentioned embodiment.

[0082] The computer-readable storage medium provided in the embodiment of the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM: Random Access Memory), a read-only memory (ROM: Read Only Memory), an erasable programmable read-only memory (EPROM: Erasable Programmable Read Only Memory or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM: CD-Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system or device. The program code contained on the computer-readable storage medium can be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency: Radio Frequency), etc., or any suitable combination of the above.

[0083] The computer-readable storage medium may be included in the electronic device, or may exist independently without being installed in the electronic device.

[0084] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by an electronic device, the electronic device: obtains the oxide scale phase composition information of each sampling point on the surface of the hot-rolled steel strip, wherein the oxide scale phase composition information includes the oxide scale components and the mass ratio of the components; for each of the sampling points, calculates the optical parameters according to the oxide scale phase composition information of the sampling point, and calculates the oxide scale thickness of the sampling point according to the terahertz echo signal of the oxide scale on the surface of the hot-rolled steel strip and the optical parameters.

[0085] The computer program code for performing the operation of the embodiment of the present application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on the remote computer, or completely on the remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0086] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0087] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0088] The readable storage medium provided in the embodiment of the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned oxide scale detection method, and can ensure non-destructive and high-precision measurement of oxide scale on the surface of hot-rolled strip. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in the embodiment of the present application are the same as the beneficial effects of the oxide scale detection method provided in the above-mentioned embodiment, and will not be repeated here.

[0089] The present application also provides a computer program product, including a computer program, which implements the steps of the oxide scale detection method as described above when executed by a processor.

[0090] The computer program product provided in this application can solve the technical problem of oxide scale detection. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as the beneficial effects of the oxide scale detection method provided in the above embodiment, which will not be repeated here.

[0091] The above are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect application in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A method for detecting oxide scale, characterized in that: The method comprises: Obtaining oxide scale phase composition information at each sampling point on the surface of the hot-rolled steel strip, wherein the oxide scale phase composition information includes oxide scale components and component mass ratios; For each of the sampling points, optical parameters are calculated according to the oxide scale phase composition information of the sampling point, and the oxide scale thickness of the sampling point is calculated according to the terahertz echo signal of the oxide scale on the surface of the hot-rolled strip and the optical parameters.

2. The scale detection method according to claim 1, characterized in that: The step of obtaining the oxide scale phase composition information at each sampling point on the surface of the hot-rolled strip comprises: For each sampling point on the surface of the hot-rolled steel strip, the sampling point is scanned by a preset X-ray diffractometer to obtain a scanning result, wherein the scanning result includes the oxide scale composition of the sampling point; The scanning result is fitted with a full diffraction spectrum by a preset structure refinement algorithm to obtain the component mass ratio of the sampling point.

3. The scale detection method according to claim 1, characterized in that: The optical parameter includes the refractive index of the oxide scale. The step of calculating the optical parameter for each sampling point according to the oxide scale phase composition information of the sampling point includes: For each of the sampling points, obtaining the refractive index of the oxide scale component; The refractive index of the oxide scale at the sampling point is calculated according to the refractive index and the mass ratio of the components.

4. The scale detection method according to claim 1, characterized in that: Before the step of calculating the oxide scale thickness of the sampling point according to the terahertz echo signal of the oxide scale on the surface of the hot-rolled strip and the optical parameters, the step further includes: Construct a sparse decomposition model of terahertz echo signal for the oxide scale on the surface of hot-rolled strip; Solving the optimal solution of the pulse response sequence for the oxide scale on the surface of the hot-rolled strip based on the sparse decomposition model of the terahertz echo signal, and obtaining a sparsely reconstructed pulse response function; The step of calculating the oxide scale thickness at the sampling point according to the terahertz echo signal of the oxide scale on the surface of the hot-rolled strip and the optical parameters comprises: The oxide scale thickness at the sampling point is calculated according to the pulse response function and the optical parameters.

5. The scale detection method according to claim 4, characterized in that: The optical parameters include the refractive index of the oxide skin, and the step of calculating the oxide skin thickness of the sampling point according to the pulse response function and the optical parameters includes: Determine time delay data according to the impulse response function, wherein the time delay data is the time delay between two adjacent reflections from the sampling point; The oxide scale thickness at the sampling point is calculated according to the time delay data and the oxide scale refractive index.

6. The scale detection method according to claim 4, characterized in that: Before the step of constructing a sparse decomposition model of the terahertz echo signal for the oxide scale on the surface of the hot-rolled strip, the method further includes: A time-slice dispersion model for the oxide scale on the surface of hot-rolled steel strip is constructed. The time-slice dispersion model is used to characterize the spatiotemporal morphological evolution characteristics of the pulse waveform of the terahertz time-domain reflection signal of the oxide scale on the surface of the hot-rolled steel strip. The kernel function of the time-slice dispersion model is: ， in, represents the kernel function, It represents the dispersion degree of the terahertz echo signal of the oxide scale on the surface of the hot-rolled strip, and n represents the sampling point.

7. The scale detection method according to claim 6, characterized in that: The step of constructing a sparse decomposition model of a terahertz echo signal for oxide scale on the surface of a hot-rolled steel strip comprises: A terahertz echo signal sparse decomposition model for the oxide scale on the surface of hot-rolled strip is constructed. The terahertz echo signal sparse decomposition model is expressed as: ， Where Y represents the sparse decomposition model of terahertz echo signal, The matrix representing the spread of the terahertz pulse over the entire propagation distance, , The column vector is composed of the time delay sequence of the terahertz reference signal, represents the column vector consisting of impulse response functions, represents Gaussian white noise.

8. An oxide scale detection device, characterized in that: The device comprises: A phase composition information acquisition module is used to acquire the phase composition information of the oxide scale at each sampling point on the surface of the hot-rolled strip, wherein the phase composition information of the oxide scale includes the oxide scale composition and the mass ratio of the composition; The thickness calculation module is used to calculate the optical parameters of each sampling point according to the oxide scale phase composition information of the sampling point, and calculate the oxide scale thickness of the sampling point according to the terahertz echo signal of the oxide scale on the surface of the hot-rolled strip and the optical parameters.

9. An electronic device, characterized in that: The electronic device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the oxide scale detection method according to any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the oxide scale detection method according to any one of claims 1 to 7 are implemented.

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