CN118130507B - High-precision quantitative detection method for embedded depth of internal defects of nonmetallic material - Google Patents
High-precision quantitative detection method for embedded depth of internal defects of nonmetallic material Download PDFInfo
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Abstract
The invention relates to a high-precision quantitative detection method for the burial depth of internal defects of a nonmetallic material, which belongs to the field of microwave nondestructive detection and comprises the following steps: forming a sensor by the lens and the rectangular waveguide with the opening, and keeping a constant distance from the surface of the object to be measured; collecting a plurality of S 11 discrete spectrum response points which have the same thickness and the same material as the object to be detected and have no defects through a sensor, and converting the discrete spectrum response points into S 11 time domain signals serving as reference S 11 time domain signals; collecting a plurality of S 11 discrete spectrum response points of a sensor at a certain position of an object to be detected, and converting the discrete spectrum response points into S 11 time domain signals serving as detected S 11 time domain signals; based on a feature extraction algorithm, linear fitting is carried out on feature parameters, and the relation between the feature parameters and the defect burying depth is established, so that quantitative detection is realized. The invention combines the open rectangular waveguide with the lens, so that the sensor has high concentrated electric field distribution, the defect detection effect is improved, and the advantages of time domain signal analysis in longitudinal information acquisition can be effectively utilized.
Description
Technical Field
The invention relates to the field of microwave nondestructive detection, in particular to a high-precision quantitative detection method for the buried depth of internal defects of a nonmetallic material.
Background
Nonmetallic materials are widely used in a variety of industries, however, during the production, processing and application stages of these materials, damage or defects may occur due to the influence of various environmental factors; these problems, which are not detected and repaired in time, not only impair the performance and safety of the material, but may also constitute a significant risk for the overall safety of the relevant engineering structure. Therefore, how to effectively identify these defects is particularly critical. At present, a nondestructive detection technology based on microwaves has remarkable advantages, and the technology penetrates through nonmetallic materials through microwave signals and interacts with internal structures of the nonmetallic materials, so that high efficiency is shown when various nonmetallic materials are detected; the technology does not need to generate ionizing radiation and does not depend on a coupling agent, is a non-invasive detection method, and particularly, the microwave near-field detection technology is widely applied and accepted in the field of nonmetallic material detection with excellent sensitivity and resolution.
In the field of near-field microwave nondestructive detection, the technology based on sensor raster scanning is mainly divided into two main types of resonant sensors and non-resonant sensors according to the structural types of the sensors. Resonance type sensors are known for their ability to detect with high accuracy, however, their ability to penetrate electric fields is weak and are mainly suitable for detecting defects on the surface and subsurface of materials. In contrast, non-resonant sensors have deeper penetration depths, are suitable for detecting internal defects, and are generally in the form of open waveguides, transmission lines, and the like, and particularly open rectangular waveguides are most widely used. However, the electric field concentration of such sensors is relatively poor, resulting in a limit on detection accuracy. On the other hand, the near-field microwave nondestructive testing method based on sensor raster scanning can be divided into a method based on frequency domain response and time domain response according to the analyzed signal domain category. The frequency domain response analysis, typically based on an S-parameter frequency domain signal, is based on the principle that the presence of defects can cause discontinuities in the material properties, thereby causing a change in the S-parameter. The detection of defects is realized by analyzing the amplitude, phase and frequency variation of S parameters at a specific frequency point or a frequency band. In contrast, time domain response analysis detects defects by analyzing reflection peak characteristics, such as time of arrival lamps, in the time domain signal based on the S parameter. The method can reveal the independent contribution of different components to the S parameter when microwaves propagate in the measured object, and is beneficial to the quantification of defect depth information. Since such techniques require wide bandwidth sensor operation, non-resonant sensors, such as open rectangular waveguides, are typically employed. However, the gain of the conventional open rectangular waveguide is limited, resulting in insufficient detection accuracy based on such sensors.
The Chinese patent application with the application number 2022108896483 discloses a method for imaging the internal corrosion state of a reinforced concrete structure based on microwave detection, which comprises the following steps: s1, setting a moving stride D1 and a scanning frequency f1 of a rectangular waveguide along an X axis and a moving stride D2 and a scanning frequency f2 of the rectangular waveguide along a Y axis; s2, scanning by utilizing a rectangular waveguide to obtain a position interval of the reinforced bar in the concrete foundation; s3, scanning the concrete foundation by utilizing a rectangular waveguide to obtain a reference value matrix Γ0 of which the reinforcing steel bars are not corroded; s4, carrying out X-axis parallel scanning on the reinforced concrete foundation by utilizing the rectangular waveguide to obtain a transmission coefficient matrix set Γ for representing the corrosion degree of the reinforced concrete, and marking a subset in the transmission coefficient matrix set Γ according to the corrosion degree; and S5, importing the transmission coefficient matrix set Γ and the position information of the corresponding corrosion steel bar into MATLAB for data imaging processing to obtain a three-dimensional imaging diagram. The scheme is convenient for engineering technicians to intuitively obtain the internal corrosion condition of the reinforced concrete foundation. But it is mainly focused on the detection of objects to be measured of a larger size, such as reinforced concrete structures, using rectangular waveguides. Moreover, this technique has limited detection accuracy due to insufficient beam concentration.
The China patent with the application number 201710655231X discloses a composite insulator defect nondestructive detection system based on the reflection characteristic of a microwave band, which comprises a femtosecond laser source, a wave guide device, an exchange port, a wave recorder and a data analysis module; the femtosecond laser source is used for generating a detection signal; the wave guide device is used for connecting the femtosecond laser source with the exchange port; the switching port comprises a branching mirror surface with bidirectional permeability to microwave band signals and is used for separating incident signals and reflected signals, and the data analysis module performs time domain analysis on the incident signals and the reflected signals to simulate and calculate the basic condition of the composite insulator at a measured point so as to perform defect judgment. The invention adopts a new composite insulator defect detection mode, and can effectively detect the defects inside the composite insulator. But it is based on time domain signal analysis and does not cover detection applications after the waveguide has been combined with a lens, especially when the electromagnetic wave passes through the lens, its phase is modulated, resulting in the traditional defect features in S-parameter time domain signals no longer applicable.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, provides a high-precision quantitative detection method for the embedded depth of the internal defects of a nonmetallic material, and solves the problems existing in the prior art.
The aim of the invention is achieved by the following technical scheme: a high-precision quantitative detection method for the buried depth of a non-metallic material internal defect comprises the following steps:
placing the designed GRIN MS lens on one side of the open rectangular waveguide facing the object to be detected, forming a sensor with the open rectangular waveguide, and keeping a constant distance between the sensor and the surface of the object to be detected;
Collecting a plurality of discrete spectrum response points which have the same thickness and the same material as the object to be measured and have no defects through a sensor, and converting the discrete spectrum response points into S 11 time domain signals which are used as reference S 11 time domain signals for subsequent discrimination;
Collecting a plurality of discrete frequency spectrum response points of a sensor at a certain position of an X-Y plane in the Z direction of an object to be detected, and converting the discrete frequency spectrum response points into S 11 time domain signals serving as acquired detected S 11 time domain signals;
And based on a characteristic extraction algorithm of S 11 time domain signal analysis, the relation between the characteristic parameters and the defect burial depth is established by carrying out linear fitting on the characteristic parameters, so that the quantitative detection of the defect burial depth is realized.
The feature extraction algorithm based on S 11 time domain signal analysis establishes a relation between the feature parameter and the defect burial depth by performing linear fitting on the feature parameter, so as to realize quantitative detection of the defect burial depth, and specifically comprises the following steps:
Converting the S 11 frequency domain signal into an S 11 time domain signal through Fourier inversion to obtain a reference S 11 time domain signal corresponding to the reference S 11 frequency domain signal and a detected S 11 time domain signal;
Based on a time window and by utilizing a normalized correlation quantity, quantifying the similarity between a reference S 11 time domain signal and a detected S 11 time domain signal in a certain time window, and sliding the time window in a set step to obtain a local similarity sequence in the whole time;
the local similarity sequence consists of a plurality of discrete points, and interpolation is carried out among the discrete points by adopting a piecewise three-time Hermite interpolation polynomial method to form a continuous curve;
The horizontal axis N value when the similarity is first reduced to the threshold value M is positioned through the continuous curve and is used as a key characteristic parameter;
And linearly fitting the N values with different defect burial depths h, and establishing a relation between the N values and the h to realize quantitative detection of the defect burial depths.
The GRIN MS lens consists of metamaterial units with different refractive indexes, the refractive indexes of the metamaterial units gradually change along the diameter of the GRIN MS lens, the diameter of the GRIN MS lens is D, the thickness of the GRIN MS lens is T, the focal distance is S, and the requirements are metTo ensure that each optical path of the wave source to the GRIN MS lens surface has an equal phase delay, r represents the radial distance from the lens center to a point, n (r) represents the refractive index function as a function of radial distance r, and n 0 is the maximum refractive index at the lens center.
The GRIN MS lens comprises a core layer and an impedance matching layer, wherein the upper surface and the lower surface of the core layer are respectively provided with an impedance matching layer, the refractive indexes of the core layer, the impedance matching layer and the GRIN MS lens are respectively n CL、nIML and n, the thicknesses of the core layer, the impedance matching layer and the GRIN MS lens are respectively T CL、TIML and T, and the requirements are met。
The core layer is formed by overlapping three core layer units, each core layer unit comprises three dielectric layers, the thicknesses of the upper dielectric layer and the lower dielectric layer are the same and are smaller than those of the middle dielectric layer, rectangular rings and two C-shaped structures are respectively printed on the upper side and the lower side of the middle dielectric layer, and the rectangular rings are printed in the middle of the two C-shaped structures.
The length, width and height dimensions of the core layer unit comprise 4.25mm multiplied by 1.05mm, the thickness of the middle dielectric layer is 0.508mm by adopting Roger 3003 as a substrate material, the thickness of the upper dielectric layer and the lower dielectric layer is 0.254mm by adopting Roger 5880 as a substrate material, and the thicknesses of the rectangular ring and the C-shaped structure are 0.017mm.
The impedance matching layer comprises an impedance matching layer unit, the impedance matching layer unit comprises three dielectric layers, the thicknesses of the upper dielectric layer and the lower dielectric layer are the same and smaller than the thickness of the middle dielectric layer, rectangular rings and two C-shaped structures are respectively printed on the upper side and the lower side of the middle dielectric layer, and the rectangular rings are printed in the middle of the two C-shaped structures.
The length, width and height dimensions of the impedance matching layer unit comprise 4.25mm multiplied by 1.05mm, the middle dielectric layer adopts Roger 5880 as a substrate material, the thickness of the middle dielectric layer is 2.237mm, the upper dielectric layer and the lower dielectric layer adopt Foam materials as substrate materials, the thickness of the upper dielectric layer is 1mm, and the thicknesses of the rectangular ring and the C-shaped structure are 0.0065mm.
The invention has the following advantages: a high-precision quantitative detection method for the buried depth of a non-metallic material internal defect combines an open rectangular waveguide with a GRIN MS lens for signal acquisition, so that the sensor has high-concentration electric field distribution, and the defect detection effect can be remarkably improved; the problem that the traditional defect characteristics of the S11 time domain signal disappear after the lens is loaded on the open rectangular waveguide is solved through a new algorithm based on characteristic parameter extraction, and the advantages of the time domain signal analysis in longitudinal information acquisition can be effectively utilized while the performance of the sensor is improved.
Drawings
FIG. 1 is a schematic diagram of the GRIN MS lens according to the present invention;
FIG. 2 is a schematic diagram of a core layer unit;
FIG. 3 is a schematic diagram of an impedance matching layer unit;
FIG. 4 is a schematic diagram of GRIN MS lens acquisition signals;
fig. 5 is a flow chart of the detection algorithm.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Accordingly, the following detailed description of the embodiments of the application, as presented in conjunction with the accompanying drawings, is not intended to limit the scope of the application as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by a person skilled in the art without making any inventive effort, are intended to be within the scope of the present application. The application is further described below with reference to the accompanying drawings.
The invention relates to a high-precision quantitative detection method for the buried depth of a non-metallic material internal defect based on a GRIN MS lens and a characteristic parameter extraction algorithm, which aims to solve the problem of poor detection precision caused by limited gain of a traditional open rectangular waveguide. The algorithm establishes the relation between the characteristic parameters and the defect burial depth by carrying out linear fitting on the characteristic parameters, so as to realize quantitative detection of the defect burial depth. The method specifically comprises the following steps:
1. GRIN MS lens designs based on sandwich layer structures with low profile, high directivity, and wide bandwidth.
GRIN MS lenses are composed of metamaterial units of different refractive indices that vary gradually along the lens diameter. Assuming that the lens has a diameter D, a thickness T and a focal distance S, to ensure that each optical path from the source to the GRIN lens surface has an equal phase delay, certain conditions are satisfied:
where r denotes the radial distance from the center of the lens to a point, n (r) denotes the refractive index function as a function of radial distance r, and n 0 is the maximum refractive index at the center of the lens.
As shown in fig. 1, designing a metamaterial unit structure with a wide variation range of refractive index is advantageous in reducing the lens thickness. But a higher metamaterial index requires a larger relative permittivity. And electromagnetic wave reflection caused by the change of dielectric constant at the interface of the lens and air is a key factor affecting the antenna efficiency. In order to reduce reflection loss and maintain wide variation of refractive index of the metamaterial unit, a sandwich layer structure formed by a core layer CL and an impedance matching layer IML is adopted to design the lens.
The refractive indexes of the core layer, the impedance matching layer and the whole lens are n CL、nIML and n respectively, the whole thickness of the lens is T, the thickness of the core layer is T CL, the thickness of the impedance matching layer is T IML, and all parameters need to be satisfied:
wherein, From this equation, the refractive index of each cell of the core layer and the impedance matching layer can be calculated.
Further, the lens-related parameters include: lens diameter d=106.25 mm, focal length f=60 mm, lens period length p=4.25 mm, and lens total thickness t=8.75 mm. Lens core layer thickness T CL = 3.15mm, lens impedance matching layer thickness T IML = 2.8mm.
Further, as shown in fig. 2, the core layer unit UCcore is composed of three dielectric layers, and the length, width and height dimensions are as follows: 4.25mm x 1.05mm, the middle layer is made of Roger 3003 as a substrate material, the thickness h core1 = 0.508mm, and a rectangular ring and two C-shaped structures are respectively printed on the upper side and the lower side of the substrate by metal copper wires. Both top and bottom layers of UCcore were Roger 5880 as substrate material, thickness h core2 = 0.254mm. Other relevant structural parameters include ：acore=0.6mm,dcore=3.5mm,ccore=0.775,score=0.3mm,aw=0.3mm,aw2=0.32mm,t=0.017mm,P=4.25mm,TCL=1.05mm.
Further, as shown in fig. 3, the impedance matching layer unit UCIML is also composed of three dielectric layers, and the dimensions of the length, width and height are: the base materials of the top and bottom layers of 4.25mm×4.25mm×1.05mm, UCIML were composed of Foam material, h IMl2 =1 mm, the middle layer of uci ml was composed of Roger 5880 as the substrate, and h IMl1 = 2.237mm. Other relevant structural parameters include ：aIML = 0.6mm,dIML=3.5mm,cIML=0.775mm,sIML=0.3mm,aw=0.1mm,aw2=0.2mm,t=0.0065mm,P=4.25mm,TIML=2.8mm.
Since the thickness of the core layer unit UCcore is 1.05mm, the thickness of the impedance matching layer unit UCIML is 2.8mm. To meet the design requirements of T CL and T IML, the lens core layer CL is composed of three core layer units UCcore stacked together, and the lens impedance matching layer IML is composed of a single UCIML.
2. The designed GRIN MS lens is loaded with an open rectangular waveguide to collect S 11 signals.
As shown in fig. 4, a standard open rectangular waveguide is currently a common option for material internal defect detection with non-resonant sensors. However, such sensors have a disadvantage: the beams are not sufficiently concentrated, resulting in poor detection accuracy. To overcome this problem, the present invention employs an open rectangular waveguide of model WR-90, which is combined with a designed GRIN MS lens, which is integrated as a sensor with an operating band of 8GHz-12GHz. The design can realize the focusing of wave beams, so that the electric field distribution is more concentrated, and the sensitivity of the sensor can be obviously improved. The improvement makes up for the defect detection precision of the traditional open rectangular waveguide, and provides an effective solution for improving the detection precision.
The method comprises the steps of keeping a constant distance between a sensor and the surface of an object to be measured, firstly collecting 201S 11 discrete spectrum response points which have the same thickness and the same material as the object to be measured and are free of defects, and converting the discrete spectrum response points into S 11 time domain signals which are used as reference S 11 time domain signals for subsequent discrimination. Then, 201S 11 discrete spectrum response points of the sensor at a certain position of the X-Y plane in the Z direction of the object to be detected are acquired and converted into S 11 time domain signals, which are used as acquired detected S 11 time domain signals.
3. And a defect burial depth quantitative detection algorithm based on a characteristic parameter extraction algorithm.
As shown in fig. 5, first, the frequency domain signal of S 11 is converted into the time domain signal of S 11 by inverse fourier transform, so that the reference S 11 time domain signal corresponding to the reference S 11 frequency domain signal and the detected S 11 time domain signal can be obtained. Then, quantifying the similarity between the reference S 11 time domain signal and the detected S 11 time domain signal within a certain time window based on the time window and using the normalized cross-correlation coefficient; the formula of normalized cross-correlation coefficient is:
Wherein x is the S 11 time domain signal detected in a certain time window, y is the reference S 11 time domain signal in the same time window, i is the sequence number of the discrete signal in the time window, For the mean value of the S 11 time domain signal detected in this time window,For the mean value of the reference S 11 time domain signal within the time window,，R xy is the calculated cross-correlation coefficient, that is, the similarity between x and y, and a local similarity sequence in the whole time can be obtained by sliding the time window in a certain step.
The obtained local similarity sequence consists of discrete points, and in order to more accurately locate the position where the similarity is reduced to the threshold value M for the first time, the smooth interpolation is considered while the local characteristics of the data are kept, and a (PIECEWISE CUBIC HERMITE INTERPOLATING POLYNOMIAL) method, namely a piecewise three-order Hermite interpolation polynomial method, is adopted. The method can interpolate between discrete points of the similarity curve to form a continuous and smooth curve. The application of such a continuous curve makes it possible to precisely locate the value of the transverse axis N when the similarity first falls to the threshold value M, as a key characteristic parameter. Finally, the N values are linearly fitted with different defect burial depths h, so that the relation between the N values and the h is established.
The foregoing is merely a preferred embodiment of the invention, and it is to be understood that the invention is not limited to the form disclosed herein but is not to be construed as excluding other embodiments, but is capable of numerous other combinations, modifications and adaptations, and of being modified within the scope of the inventive concept described herein, by the foregoing teachings or by the skilled person or knowledge of the relevant art. And that modifications and variations which do not depart from the spirit and scope of the invention are intended to be within the scope of the appended claims.
Claims (1)
1. A high-precision quantitative detection method for the embedded depth of internal defects of a nonmetallic material is characterized by comprising the following steps of: the detection method comprises the following steps:
placing the designed GRIN MS lens on one side of the open rectangular waveguide facing the object to be detected, forming a sensor with the open rectangular waveguide, and keeping a constant distance between the sensor and the surface of the object to be detected;
collecting a plurality of S 11 discrete spectrum response points which have the same thickness and the same material as the object to be measured and have no defects through a sensor, and converting the discrete spectrum response points into S 11 time domain signals which are used as reference S 11 time domain signals for subsequent discrimination;
Collecting a plurality of S 11 discrete spectrum response points of a sensor at a certain position of an X-Y plane in the Z direction of an object to be detected, and converting the discrete spectrum response points into S 11 time domain signals which are used as acquired detected S 11 time domain signals;
based on a feature extraction algorithm of S 11 time domain signal analysis, the relation between the feature parameter and the defect burial depth is established by carrying out linear fitting on the feature parameter, so that the quantitative detection of the defect burial depth is realized;
The feature extraction algorithm based on S 11 time domain signal analysis establishes a relation between the feature parameter and the defect burial depth by performing linear fitting on the feature parameter, so as to realize quantitative detection of the defect burial depth, and specifically comprises the following steps:
Converting the S 11 frequency domain signal into an S 11 time domain signal through Fourier inversion to obtain a reference S 11 time domain signal corresponding to the reference S 11 frequency domain signal and a detected S 11 time domain signal;
Based on a time window and by utilizing a normalized correlation quantity, quantifying the similarity between a reference S 11 time domain signal and a detected S 11 time domain signal in a certain time window, and sliding the time window in a set step to obtain a local similarity sequence in the whole time;
the local similarity sequence consists of a plurality of discrete points, and interpolation is carried out among the discrete points by adopting a piecewise three-time Hermite interpolation polynomial method to form a continuous curve;
The horizontal axis N value when the similarity is first reduced to the threshold value M is positioned through the continuous curve and is used as a key characteristic parameter;
Performing linear fitting on the N values and different defect burial depths h, and establishing a relation between the N values and the h to realize quantitative detection of the defect burial depths;
The GRIN MS lens consists of metamaterial units with different refractive indexes, the refractive indexes of the metamaterial units gradually change along the diameter of the GRIN MS lens, the diameter of the GRIN MS lens is D, the thickness of the GRIN MS lens is T, the focal distance is S, and the requirements are met To ensure that each optical path of the wave source to the GRIN MS lens surface has an equal phase delay, r represents the radial distance from the lens center to a point, n (r) represents the refractive index function as a function of radial distance r, and n 0 is the maximum refractive index at the lens center;
The GRIN MS lens comprises a core layer and an impedance matching layer, wherein the upper surface and the lower surface of the core layer are respectively provided with an impedance matching layer, the refractive indexes of the core layer, the impedance matching layer and the GRIN MS lens are respectively n CL、nIML and n, the thicknesses of the core layer, the impedance matching layer and the GRIN MS lens are respectively T CL、TIML and T, and the requirements are met ；
The core layer is formed by superposing three core layer units, each core layer unit comprises three dielectric layers, the thicknesses of the upper dielectric layer and the lower dielectric layer are the same and are smaller than those of the middle dielectric layer, rectangular rings and two C-shaped structures are respectively printed on the upper side and the lower side of the middle dielectric layer, and the rectangular rings are printed in the middle of the two C-shaped structures;
the length, width and height dimensions of the core layer unit comprise 4.25mm multiplied by 1.05mm, the thickness of the middle dielectric layer is 0.508mm by adopting Roger 3003 as a substrate material, the thickness of the upper dielectric layer and the lower dielectric layer is 0.254mm by adopting Roger 5880 as a substrate material, and the thicknesses of the rectangular ring and the C-shaped structure are 0.017mm;
The impedance matching layer comprises an impedance matching layer unit, the impedance matching layer unit comprises three dielectric layers, the thicknesses of the upper dielectric layer and the lower dielectric layer are the same and smaller than the thickness of the middle dielectric layer, rectangular rings and two C-shaped structures are respectively printed on the upper side and the lower side of the middle dielectric layer, and the rectangular rings are printed in the middle of the two C-shaped structures;
The length, width and height dimensions of the impedance matching layer unit comprise 4.25mm multiplied by 1.05mm, the middle dielectric layer adopts Roger 5880 as a substrate material, the thickness of the middle dielectric layer is 2.237mm, the upper dielectric layer and the lower dielectric layer adopt Foam materials as substrate materials, the thickness of the upper dielectric layer is 1mm, and the thicknesses of the rectangular ring and the C-shaped structure are 0.0065mm.
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| JP2012112805A (en) * | 2010-11-25 | 2012-06-14 | Nippon Telegr & Teleph Corp <Ntt> | Wood imaging device and wood inspection method |
| CN117388286A (en) * | 2023-12-07 | 2024-01-12 | 成都信息工程大学 | Nonmetal internal defect detection method based on microwave near-field time domain reflection |
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