CN103048356B - The many materials associating recognition methods successively focused on based on ultra broadband phased array and device - Google Patents
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Abstract
The invention discloses the many materials associating recognition methods and device that successively focus on based on ultra broadband phased array, device comprises device control module, signal transmitting and receiving module, signal processing module and parameter of curve extraction module, wherein signal transmitting and receiving module is connected with signal processing module, signal processing module is connected with parameter of curve extraction module, and signal transmitting and receiving module, signal processing module are all connected with device control module with parameter of curve extraction module; Recognition methods utilizes the reflection coefficient curve measured value and intrinsic reflection coefficient empirical curve that record, can extract the electromagnetic parameter of each layer material, realize the identification of material.Apparatus structure of the present invention is simple, has high, safe, the portable feature of accuracy of identification.The present invention can realize the Material Identification of determinand multi-section, multi-angle, many degree of depth, and can realize dynamic focusing adjustment.The present invention, except for except the identification of industrial materials, also can be used for the quality check of agricultural product.
Description
Technical Field
The invention relates to the technical field of material identification, in particular to a multi-material joint identification method and device based on ultra wide band phased array layer-by-layer focusing.
Background
Material identification and quality identification are important issues in the field of industrial material quality detection. For an object composed of multiple materials, the category of each material needs to be identified respectively, so as to draw conclusions on the material composition and quality identification of the whole object. For example, how to detect the internal layered structure of an object and the material of each layer, how to identify the authenticity and quality of the internal material of a wooden product, a metal product, or the like, how to identify whether or not other components are mixed in the material, and how to identify the material type of the other components.
The current common methods for material identification include photothermal identification, color identification, electromagnetic identification, echo signal identification, eddy current identification and the like. The photothermal method identification and the color identification can not identify the material inside the object, and the electromagnetic identification is only suitable for identifying the electromagnetic material. Echo signal identification, such as material identification based on echo data feature extraction combined with neural network (patent No. CN 1595195A), is based on the principle that ultra-wideband signals are transmitted to a material to be detected, and then feature values of echo typical data are extracted from received echoes, and training and identification of the neural network are performed, so as to complete material identification. The eddy current identification method, such as identifying the metal material based on the eddy current identification composite material (patent No. CN 101413921A), utilizes the eddy current characteristic of the metal conductor, and can realize the material identification of the upper and lower layers of composite material and the positioning of the critical plane by adjusting the detection depth. The above method cannot identify the material of each layer of an object containing multiple layers of materials, and the specific disadvantages are as follows:
1. the identification of multilayer materials cannot be effectively realized, and the quality of the internal materials of the object to be detected cannot be identified. The photothermal method identification and the color identification only identify the surface material, and the precision is not high. The extraction of the echo characteristic value identifies the object to be detected as a whole, and the information of materials of all layers cannot be distinguished. The eddy current method can only identify the material of the objects made of the upper and lower layers of metal materials.
2. The method for extracting the echo characteristic value does not take the factors influencing the echo characteristics into full consideration, so the accuracy of material identification is restricted. When the material does not satisfy the semi-infinite condition, the reflection coefficient curve is related to the thickness of the material, and the change of the thickness of the material can cause the error identification of the material. In addition, when the material has multiple layers of media, the change of some media can also change the equivalent electromagnetic parameters of the whole material, so that the reflection coefficient curve is changed. The extraction of the characteristic value of the single surface reflection signal cannot find the changes, but the material is identified as another material as a whole.
3. The traditional material identification method has fewer measuring points and can not comprehensively reflect the material types of various depths of various positions of a measured object. If the measured object is measured at multiple points, mechanical movement of the transmitting device is required, which increases the complexity and manufacturing cost of the device.
For material identification of the object, its intrinsic properties, such as permittivity σ, conductivity, permeability μ among electromagnetic parameters, can be considered. When a signal is transmitted in a substance, the signal is reflected when the electromagnetic parameters sigma and mu are changed, namely the signal is reflected at the critical surface of the two materials. According to the electromagnetic theory, under the condition of satisfying semi-infinite conditions, the reflection coefficient is determined by the signal frequency f, the characteristic impedance eta of materials on two sides of a critical surface and the propagation constant gamma. Whereas η and γ are determined by the electromagnetic parameters σ, and μ. Therefore, the curve of the reflection coefficients of different substances changing along with the signal frequency has uniqueness due to the carried electromagnetic parameter information, and the electromagnetic parameter information can be extracted through the reflection coefficient curve to realize the identification of the material.
For an object containing multiple layers of materials, the media on two sides of the critical surface do not meet the semi-infinite condition any more, and the reflection coefficient curve is related to the electromagnetic parameters of the media on two sides of the critical surface, other electromagnetic parameters of each layer of media and the thickness of each layer of media. Therefore, the electromagnetic parameters sigma and mu of the materials of each layer can be jointly extracted through the curve of the reflection coefficient of each layer.
In order to accurately identify the material of each layer of an object containing multiple layers of materials, enough reflection coefficients and frequency relation information are needed, so that the material identification of the object can be carried out by utilizing an ultra-wideband signal carrying rich frequency band information. In order to improve the speed of material identification, phased arrays are used to transmit and receive ultra-wideband signals. Because the phased array has a plurality of independent radiation wave beams and receiving wave beams, the phased array has the characteristics of rapid change of wave beam direction and flexible change of wave beam shape, can enable the scanning range to comprehensively cover the detected part of the object to be detected, and realizes comprehensive identification of materials in various depths of the position of the object to be detected. Therefore, ultra-wideband detection and phased array are combined, and accurate and comprehensive scanning and detection of materials can be achieved. The method can also be applied to quality inspection of agricultural products and daily necessities.
Disclosure of Invention
In order to realize the identification of the material, including the identification of the material types of the surface layer and each layer inside the object to be detected and the quality inspection, the invention provides a multi-material combined identification method and a device based on ultra wide band phased array layer-by-layer focusing. The method is based on different materials with different dielectric constants sigma, conductivity and permeability mu, establishes the relation function of each reflection coefficient curve and the electromagnetic parameters sigma and mu of each layer of material by extracting each layer of interstrational reflection echoes, and realizes the identification of the material by jointly solving the relation function of each interstrational reflection coefficient and the electromagnetic parameters. Specifically, the electromagnetic parameters of the materials of each layer can be extracted by using the measured reflection coefficient curve and the inherent reflection coefficient empirical curve, so as to realize the identification of the materials. The technical scheme of the invention is as follows.
The multi-material combined identification device based on ultra-wideband phased array layer-by-layer focusing comprises an equipment control module, a signal transceiving module, a signal processing module and a curve parameter extraction module, wherein the signal transceiving module is connected with the signal processing module, the signal processing module is connected with the curve parameter extraction module, and the signal transceiving module, the signal processing module and the curve parameter extraction module are all connected with the equipment control module; the device control module controls the module connected with the device control module and outputs a processing result, and comprises a central control unit, a data memory and a display device, wherein the data memory and the display device are respectively connected with the central control unit, and the central control unit is used for controlling the work of the signal transceiving module, the signal processing module and the curve parameter extraction module and the data transmission among the modules; the data memory is used for storing the processing results of the modules and providing input data required by the signal processing module; the display equipment displays the processing progress and the result; the signal receiving and transmitting module is a full-duplex signal transceiver and transmits an ultra-wideband signal to the object to be detected and receives reflection echoes of each layer of the object to be detected; the signal processing module is used for collecting echo signals, processing the echo signals in time domain and frequency domain and extracting a reflection coefficient curve measured value; the curve parameter extraction module is used for solving the electromagnetic parameter information of each layer of material and transmitting the solved result to the equipment control module.
Preferably, the signal transceiver module comprises an ultra-wideband transmitter, a power divider, a beam controller, P beam sub-array transceivers and a beam former; the ultra-wideband transmitter, the power distributor, the beam controller, the P beam subarray transceivers and the beam former are sequentially connected; the power divider couples the power of the ultra-wideband transmitter and averagely distributes the power to each beam subarray; the beam controller is used for realizing beam deflection and focusing at different angles and different depths and obtaining thickness information of materials of each layer at each position through depth change of layer-by-layer focusing; p wave beam sub-array transceivers form a phased array transceiver, transmit ultra-wideband signals to a focusing point and receive echo signals of a reflecting point; the wave beam forming device carries out phase compensation on the echo signals received by each sub-array and synthesizes the echo signals into receiving wave beams, and P is larger than or equal to 2.
Preferably, the signal processing module comprises a data sampler, a signal preprocessor, a guided wave signal processor and a signal processor, wherein the signal processor comprises a wave band extraction device, a power estimator, an amplitude-frequency analysis device and a divider; the data sampler, the signal preprocessor and the signal processor are connected in sequence; the signal preprocessor is connected with the guided wave signal processor, and the guided wave signal processor is connected with a data memory in the equipment control module; the wave band extraction device, the power estimator, the amplitude-frequency analysis device and the divider are sequentially connected, and the divisor of the divider is provided by a data memory in the equipment control module; the data sampler is used for realizing the analog-to-digital conversion of the transmitting signals and the echo signals, and the signal preprocessor is used for respectively realizing the time averaging of the multiple transmitting signals and the echo signals of the same focusing point and respectively obtaining average transmitting signals and average echo signals; the guided wave signal processor obtains the preliminary information of the category, the shape and the layer number of the measured object by recording the echo time delay and the wave peak number of the guided wave, and transmits the result to the data memory; the signal processor carries out time domain and frequency domain processing on the average echo signal and extracts a reflection coefficient curve measured value, wherein the wave band extraction device extracts a reflection wave band of the average echo signal at a focus point in the time domain, so as to avoid errors of reflected waves at other positions in subsequent processing on the reflection coefficient curve measured value at the focus position; however, the amplitude-frequency characteristic curve of the transfer function obtained at this time is not a reflection coefficient curve of the signal, and the amplitude-frequency characteristic curve is a combined result of the transmission of the reflecting surface and the materials of the layers above the reflecting surface. Therefore, the divider divides the amplitude-frequency characteristic curve by the transmission coefficient of each layer of material on the reflecting surface (critical surface) to obtain a measured value of the reflection coefficient curve, and the result is transmitted to a curve parameter extraction module and a data memory in an equipment control module; when calculating the reflectance curve measurement for the next layer of media, the data storage in the device control module provides the reflectance measurements for the layers of media above it.
Further preferably, the curve parameter extraction module comprises an analyzer and a characteristic database which are sequentially connected, the analyzer is also connected with a data memory in the equipment control module, and the analyzer obtains the electromagnetic parameter information of each layer of material according to the measured value of each layer of reflection coefficient curve and the reflection coefficient empirical curve; the characteristic database matches the calculation result, transmits the final material identification result to the equipment control module, and displays the identification result by the display equipment; the individual layer reflectance profile measurements comprise a sequence of frequency and amplitude pairs.
Preferably, the device control module further comprises an operation device connected to the central control unit, and the operation device is configured to turn on and off the device, name and store a processing result of a certain recognition.
The invention provides a multi-material joint identification method based on ultra wide band phased array layer-by-layer focusing, which comprises the following steps:
the method comprises the following steps that firstly, an object to be measured is placed under P wave beam sub-array transceivers, the P wave beam sub-arrays are arranged in a central scattering line shape, a scattering center is located on a central axis extension line in the vertical direction of the object to be measured, and each wave beam sub-array is composed of K receiving and transmitting wave beams;
step two, transmitting guide wave beams to obtain the information of the category, the shape and the layer number of the measured object: p is the wave beam of K and launches the single pulse to guide the wave beam vertically downward at the same time, obtain the appearance information of the measured object according to the time delay of the echo signal of each point, according to the wave crest number of the echo, obtain the classification of the measured object and layer number information of each point; the category of the measured object is divided into a low-loss material and a good-conductivity material;
step three, transmitting a focused beam: the ultra-wideband transmitter adopts frequency stepping signals or linear frequency modulation signals, each beam sub-array transmitter independently transmits focused beams to form multi-section scanning, and each beam sub-array starts to focus from the surface of an object to receive echo signals;
the position of a focal point at the critical plane of the (n-1) th layer and the nth layer at a certain position a where the p-th beam subarray is focused is recorded as ap，nSetting the object to be measured to contain N layers of materials, and collecting the focus point a of each critical surfacep,1、ap,2、…、ap,NIs marked as Ap(ii) a At ap，nFocusing M times, and averaging the M times of transmitted signals to obtain an average transmitted signalThe time average of the M times of echo signals is taken to obtain an average echo signal
Step four, calculating an amplitude-frequency characteristic curve of the transfer function at a certain focus point: will be provided withAndthe amplitude spectrum on each frequency domain is obtained by carrying out power spectrum estimation and amplitude-frequency characteristic analysis through the signal processing moduleAndfurther obtain ap，nAmplitude-frequency characteristic curve of point transfer function
Step five, extracting the measured value of the reflection coefficient curve of the boundary critical surface of a certain layer at a certain position: for a focused beam, the reflected echo of the critical plane after the focusing point is suppressed, and the reflection coefficient is the ratio of the amplitude of the reflected wave to the amplitude of the incident wave; when the incident wave is a single-frequency signal, the reflection coefficient is a constant, and when the incident wave is an ultra-wideband signal, the reflection coefficient is a curve changing along with the frequency; the (n-1) th layer and the nth layer boundary ap，nMeasured value of reflection coefficient curve
The critical surface between the air and the surface layer of the measured object,i.e. the focusing point a of the boundary between air and layer 1p，1The measured value of the reflection coefficient curve is directly incident, soAnd for the critical surface of the 1 st layer and the 2 nd layer, the transmission of the transmitting signal and the echo signal occurs when penetrating the air and the critical surface of the 1 st layer, ap，2Measured in a reflectance curve ofBy adopting a recursion method, the critical surface a of the (n-1) th layer and the nth layerp，nMeasured value of reflection coefficient curve <math>
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</math> Wherein,representing curves of transmission coefficients of incident wave and reflected wave at the critical plane between (i-1) th layer and i-th layer before and after reflectionThe measured value of the reflection coefficient curve for the critical surface of the (n +1) th layer and the n-th layerExtracting;
step six, focusing at different depths: a isp，nAfter the solution of the reflection coefficient curve is completed, the reflection coefficient curve gradually enters the object to be focused, and when the signal transceiver module receives a stronger echo again, the signal transceiver module focuses to the point set ApPoint a at the boundary between the lower nth layer and the (n +1) th layerp，n+1From a to ap，nTo ap，n+1Can obtain the position ap，nMaterial thickness of lower n-th layerReturning to the step three, analyzing and processing the echo signal until the echo signal is focused on the bottom surface of the object; and sets d obtained by each change of depth of focusp，1、dp,2、…、dp,NIs marked as
Step seven, curve parameter extraction, namely the joint solution of electromagnetic parameters of each layer of medium: n reflection coefficient curve measurementsForm a matrixAccording to the multi-layer material objectAccording to the reflection principle, a reflection coefficient empirical curve is obtained, wherein the empirical curve is a function group of electromagnetic parameters of materials of all layers; from empirical curves of reflection coefficients between layersThe equality relationship of the two sets of equations establishes an equation set, and jointly solves ApElectromagnetic parameters of materials of middle layersWherein N =1,2, …, N; the signal also has propagation loss in propagation, and the empirical curve of the reflection coefficient also has a propagation loss factorAfter multiplication, it is combined withAnd wherein, in the case of the same,andrespectively represent ApThe attenuation constant and the thickness of the material of the ith layer; for a material with a low loss, the material is, <math>
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</math> multiplying corresponding propagation loss factors on corresponding frequency points;
step eight, focusing at different angles: and (3) simultaneously focusing each group of beams from one end of the section of the material to be detected, gradually changing the deflection angle of the beams after the identification of the material at each depth under the angle is finished, and gradually deflecting for 7.5 degrees to focus at other positions to form multi-angle scanning, returning to the step three, and analyzing and processing each layer of echo signals under the angle until the other end of the material is scanned.
And step nine, matching the solving result with a material parameter library to realize the identification of the material. And outputting the material type identification and quality identification results.
Further preferably, after the step eight and before the step nine, the method further comprises: and rotating the beam subarray by a set angle by taking the central point as an axis, returning to the step three, and identifying the materials of other sections of the materials to realize the omnibearing material identification of the measured object.
Further optimized, M is more than or equal to 1000.
Compared with the prior art, the invention has the following advantages and technical effects:
1. the ultra-wideband signal measurement is adopted, the echo carries rich frequency information, and the reflected power has larger fluctuation trend along with the change of the frequency. More information volume for calculating the electromagnetic parameters is thus available.
2. Phased array technology is used. The electronic technology is used for adjusting the focal position and the focusing direction, the scanning range completely covers the object to be detected, the material identification of the object to be detected in multiple sections, multiple angles and multiple depths is realized, and the dynamic focusing adjustment can be realized.
3. The material identification method determines the material type through electromagnetic parameters. The electromagnetic parameters are intrinsic parameters of the material and do not change along with the change of the environment. The material is identified through electromagnetic parameters, and the accuracy is stronger.
4. And the material identification precision is high. All factors influencing the reflection coefficient are considered comprehensively, so that the reflection coefficient empirical curve is more accurate. The formula considers the influence of the electromagnetic parameters of the thickness of each layer material and the inner layer material on the equivalent electromagnetic parameters of both sides of each critical surface under the semi-infinite condition, and the calculation accuracy of the solved electromagnetic parameters is higher.
5. And the material identification of various substances can be realized. The measured objects are different in types, such as low-loss materials and good-conductivity materials, and the reflection coefficient empirical curves are different, and the power loss in propagation is also different. The method firstly emits the guided first wave, judges the type of the material, and then adopts the corresponding reflection coefficient empirical curve to solve according to the judgment result, thereby realizing the accurate identification of various substances.
6. The device has the characteristics of safety and portability. The equipment selected by the scheme consists of a plurality of basic modules, each module chip is connected with the phased array, and the device is light. By adopting the ultra-wideband phased array technology, the ultra-wideband signal has the characteristic of low average power, and each wave beam of the phased array further equally divides the power. For low loss materials, lower transmit power may also be selected. The power radiation of the device is therefore small.
7. The material identification method can be used for identifying industrial materials and quality inspection of agricultural products.
Drawings
FIG. 1 is a structural block diagram of a material joint identification device based on ultra wide band phased array layer-by-layer focusing reflection in the embodiment.
Fig. 2 is an internal structural view of the signal transceiver module.
Fig. 3 is an internal configuration diagram of the signal processor.
Fig. 4 is an internal structural view of the curve parameter extraction module.
FIG. 5 is a flow chart of a material joint identification method based on ultra wide band phased array layer-by-layer focusing reflection.
Fig. 6 is a schematic diagram of a multi-section scanning position using 6 sets of beam subarray transceivers as an example.
FIG. 7 is a schematic view of the incident and reflected multi-layer material of the example.
FIG. 8 is a schematic diagram of multi-angle scanning in an example.
Detailed Description
The present invention will be described in further detail with reference to examples and drawings, but the present invention is not limited thereto. In this embodiment, 6 beam sub-arrays are taken as an example, i.e., P =6, and an object to be measured containing N layers of materials is taken as an example, i.e., N =1,2, …, N.
As shown in fig. 1, the apparatus includes a device control module, a signal transceiver module, a signal processing module, and a curve fitting module.
The equipment control module of the device consists of a central control unit, a data memory, display equipment and operating equipment. The central control unit is used for controlling the work of peripheral equipment such as the ultra-wideband signal transceiving module, the digital signal processing module, the curve parameter extraction module and the like and data transmission among all the modules. The data memory is used for storing the reflection coefficient empirical curve, the processing result of each module, the input parameters required by each module and the final identification result. The display equipment is used for displaying a processing process and an operation result, the processing process comprises the shape of each section, the layer number information and a signal oscillogram of a reflection coefficient curve measured value at each focus point, and the operation result comprises electromagnetic parameters of materials of each layer at each position(p =1,2, …,6, N =1,2, …, N), the identification result of the type of each layer material and the overall quality identification conclusion, i.e. the conclusion whether the measured object meets the quality requirement. The operation equipment is used for providing an operation platform for a user, and comprises a device for opening and closing, naming and storing a processing result identified at a certain time, and selecting and calling out an existing measurement result for comparison.
The ultra-wideband signal transceiver module is used for transmitting and receiving ultra-wideband signals. As shown in fig. 1 and fig. 2, the module is composed of an ultra-wideband transmitter, a power divider, a beam controller, 1 st to 6 th beam sub-array transceivers (in this embodiment, 6 beam sub-arrays are taken as an example), and a beam former. The ultra-wideband transmitter is used for vertically and downwards transmitting a single-pulse guided first wave at low power and high power respectively and then transmitting M times of single-pulse guided wave beams in a guided wave transmitting stage; in the focusing stage, at each focusing point ap，nAnd transmitting the ultra-wideband step signal or the linear frequency modulation signal for M times (M is more than or equal to 1000). Because the phased array focusing of the ultra-wideband pulse signal has the frequency offset problem, a frequency stepping signal or a linear frequency modulation signal is required to replace the pulse signal, so that the frequency offset of focusing is avoided. A power divider for coupling and equally dividing the ultra-wideband transmission signal6 beam sub-arrays. The beam controller realizes beam deflection and focusing through the time delay device and the phase shifter. The 1 st to 6 th wave beam sub-array transceivers respectively and independently transmit ultra-wideband signals, form wave beam scanning of 6 cross sections and receive echo signals reflected by materials. The beam former respectively performs phase compensation on the echo signals received by the 6 sub-arrays, and synthesizes the echo signals into 6 receiving beams, namely echoes received by 6 points on 6 cross sections.
The signal processing module is used for sampling the analog signal and obtaining the same measuring point ap，nThe time average of the M transmit signals and the time average of the M echo signals, and then a reflection coefficient curve is obtained by a signal processing method. As shown in fig. 1 and 3, the module is composed of a data sampler, a signal preprocessor, a guided wave signal processor, a band extracting device, a power estimator, an amplitude-frequency analyzing device and a divider. The data sampler converts the analog echo signal into a digital signal through a sample and hold (S/H) circuit and an A/D converter, and the signal preprocessor processes the position ap，nAnd respectively carrying out time averaging on the M times of emission signal sampling results and the M times of echo sampling results to remove white noise and random errors. The echo signal of the guided wave passes through a guided wave signal processor, and the guided wave signal processor records the wave crest number of the guided wave echo through a level comparator and a counter to obtain the information of the category and the layer number of the measured object; and recording the echo time delay by a timer to obtain the shape information of the measured object, namely the distance between each point of the surface layer and the transceiver. The average echo signal at the measuring point is obviously enhanced in power due to the action of phased array focusing, echoes at other positions are suppressed, but the average echo signal still contains reflection clutter of other critical surfaces at the moment, so that the wave band extracting device cuts off the signal at the zero-point junction of the wave band with stronger echo power and other wave bands, and extracts the echo signal at the focusing point. The power estimator can adopt a welch power estimation algorithm to respectively solve the power spectrums of the average transmitting signal and the average echo signal. Because the echo signals are random signals, a power estimation is required to replace a Fourier transform equal frequency spectrum analysis means. Amplitude-frequency analysis apparatus using power spectrum and average of average transmission signalAnd respectively obtaining the average transmitting signal and the amplitude spectrum on the frequency domain of the average echo signal by the power spectrum of the echo signal, and further obtaining the amplitude-frequency characteristic of the transfer function. The divider divides the amplitude-frequency characteristic curve by the transmission coefficient curve of each critical surface above the critical surface, i.e. divides by coefficientTo obtain ap，nThe reflection coefficient of the material is measured according to the curve of the relation of the reflection coefficient of the material and the frequency.
The curve parameter extraction module utilizes the input material reflection coefficient curve measured value and the reflection coefficient empirical curve to solve A by a method of solving the minimum value of the cost functionpElectromagnetic parameters of the material of the middle and lower layersAnd(N =1,2, …, N), and matching with the feature database to realize the identification of the material quality. As shown in fig. 4, the module consists of an analyzer, a feature database. Empirical curve of reflection coefficientAndand material thicknessThe relation of (A) is known, and at the same time, because of the existence of measurement error and random error, all frequencies and amplitude sequences of the measured value of the reflection coefficient curve can be obtained by the analyzer under the condition that the mean square error is minimumAndreflectionRequired for empirical curve of coefficientsInformation is passed from the data store to the analyser. In order to simplify the calculation, fewer measurement value sequence pairs can be selected to participate in the calculation, but in order to ensure accuracy, the number of selected sequence pairs should be greater than 10. The analyzer passes the solution results to a data store.
As shown in fig. 5, it is a flow chart of signal transmission and echo signal processing and analysis of the present invention, which specifically includes the following steps:
step one, the object to be measured is placed under 6 wave beam sub-array transceivers. The 6 linear wave beam sub-arrays are distributed in a central scattering line shape, the scattering center is positioned on the extension line of the central axis of the object to be measured in the vertical direction, and each wave beam sub-array transceiver consists of K transceiving wave beams.
And step two, the 6 wave beam subarray transceivers vertically downwards transmit single pulse guide wave beams. Firstly, a wave beam positioned in the center of a scattered ray in a phased array transmits two guide head waves with low power and high power respectively, and the material type is judged by comparing the wave crest number of two echoes. If the number of echo peaks under high power is larger than that under low power, the measured object is a good conductive material. Otherwise, the measured object is made of low-loss material. The power loss of the signal transmitted in the good conductive material is large, and the skin effect can occur in the low-power signal, so that the energy is completely lost when the signal does not penetrate through the measured object, and the return wave is only the reflected wave of the critical surface between the first layers, so that the number of wave peaks is less than that of the wave peaks under the high power. If the material is good conductive material, the subsequent guide beam and focusing beam are transmitted with high power; otherwise, the transmission is performed with low power. Then the 6 x K beams of the 6 beam sub-array transceivers simultaneously transmit M times the single pulse steered beam vertically downwards. Based on average time delay of each echo signalObtaining the distance between each point of the surface layer of the measured object and the subarray transceiver to determine the focusing position of the surface layer; the number of wave peaks of each echo signal is the layer number signal of the corresponding positionTo determine a location set ApThe number of times the depth of focus needs to be adjusted.
And step three, transmitting the focused beam. The 6 groups of linear beam sub-arrays independently transmit signals, focus on a certain point on an intersection line of a vertical plane where each beam sub-array is located and a certain critical plane of a measured object, and form multi-section scanning, as shown in fig. 6. The phased array transmit beams may employ frequency stepping signals or chirp signals. Each group of beam sub-arrays focuses from the surface of the object and receives the echo signal. At a focusing point ap，nFor example, the same measuring point ap，nThe M measurements are averaged to reduce the effects of random errors and white noise. After the focusing is finished, focusing at other positions is carried out.
And step four, calculating an amplitude-frequency characteristic curve of the transfer function at each focusing point. Will average the transmitted signalAnd averaging the echo signalsRespectively processing the power spectrum estimation and the amplitude-frequency characteristic analysis in sequence through a signal processing module to obtain an amplitude spectrumAndfurther obtaining the amplitude-frequency characteristic of the transfer function
And step five, extracting the reflection coefficient curve measured values of different interstratified critical surfaces at a certain position. For a focused beam, the reflected echoes of critical surfaces behind the focal point are suppressed. And the reflection coefficient is the ratio of the reflected wave amplitude to the incident wave amplitude. When the incident wave is a single frequency signal, the reflection coefficient is constant, and when the incident wave is an ultra-wideband signal, the reflection coefficient is varied with the frequencyA curve. Will be provided withDivision by coefficientWherein n is more than or equal to 2 to obtain ap，nReflectance curve measurements at pointsAnd n =1, namely the reflection coefficient curve measured value of the critical surface between the air and the measured object surface layer, because the reflection coefficient curve is directly incident,
the derivation procedure is as follows (see fig. 7): for a certain focus point ap，n，The measured values of the incident wave signal and the reflected wave signal before and after the reflection are recorded as the measured values respectivelyAndboth can pass through respectivelyAnd (4) calculating. Transmitting signalAt propagation to point ap，nBefore, the transmission occurs in turn at each critical surface between the air, layer 1, … and (n-1) above, thereforeIs equal toMultiplied by the transmission coefficients of the layers above it. Similarly, the received echo signalIs a reflected wave signalSuccessive transmission results at the critical surfaces of the layers above it, and thusDividing by the transmission coefficient of the critical surface of each layer thereon to obtainAccording to the law of conservation of energy, the sum of the transmission coefficient and the reflection coefficient is 1, so that the position apThe transmission coefficient between the lower (i-1) th layer and the ith layer isThe total transmission coefficient between air, layer 1, layer 2 to layer (n-1) isFrom which a can be deducedp，nMeasured value of reflection coefficient curve
And step six, focusing at different depths. Position ap，nAfter the solution of the reflection coefficient curve is completed, the reflection coefficient curve gradually goes deep into the object to be focused, and when a strong echo is received again, the focusing point is the position apThe lower nth layer and the (n +1) th layer, i.e. ap，n+1And calculating the position a by changing the depth of focusp,nMaterial thickness of lower n-th layerAnd returning to the step three, and analyzing and processing the echo signal at the moment. Until the focus is on the bottom surface of the measured object, the A is solvedpAnd (4) measuring the reflection coefficient curve among the materials of the middle and lower layers.
And seventhly, extracting curve parameters, namely performing combined solution on the electromagnetic parameters of each layer of medium.
1. From the principle of reflection of a substance, an empirical curve of the reflection coefficient can be derived, which is a function of the electromagnetic parameters. The specific formula and derivation are as follows:
when the media 1 and 2 on both sides of the critical plane satisfy a semi-infinite condition, the reflection coefficient isWherein eta is1、η2The characteristic impedances of medium 1 and medium 2, respectively. But the actual material does not meet the semi-infinite conditions. Therefore, the total input impedance of all layer media on the critical surface side is required to replace the characteristic impedance of a single medium. To be provided withThe reflection coefficient of (a) is taken as an example,
WhereinIndicates position ap，nThe equivalent characteristic impedance of the lower nth layer and the lower (N +1), (N +2), …, N layers as a whole,indicates position ap，nThe upper (n-1) th layer and the (n-2), …, 1 st layer, air thereon are considered as a whole.
The total equivalent characteristic impedance of the nth layer and the (N +1), (N +2), …, and N layers thereunder is derived from the equivalent transmission line theory
Wherein,is the characteristic impedance of the material of the nth layer,is a propagation constant of the material, and,representing the equivalent characteristic impedance of the (n +1) th layer and all layers therebelow, the method andthe same applies to the method. The equivalent characteristic impedance of the last layer of material, i.e. the Nth layer and the air thereunder as a whole is,
Wherein the characteristic impedance of the air under the Nth layer of the object to be measured is 1. Thus, from bottom to top, each layer and the layers below it andthe air under the bottom layer is regarded as an integral equivalent characteristic impedanceWhere N =1,2, …, N.
Similarly, the equivalent characteristic impedance of the (n-1) th layer and the layers thereon considered as a whole can be derived
The equivalent characteristic impedance of layer 1 taken as a whole with the air above is
Equivalent characteristic impedance from layer 1Recursion downwards to obtain the equivalent characteristic impedance of the (n-1) th layer and the layers above the layer as a whole, and the characteristic impedance of the air layer above the surface layer is 1, i.e. the characteristic impedance of the air layer above the surface layer is 1From this, can obtainWhere N =1,2, …, N.
Will be provided withAnd substituting the obtained result into the formula 1 to obtain the reflection coefficient empirical curve between the nth layer and the (n-1) th layer.
Wherein, according to the electromagnetic theory, for the low loss material,
because σ < 2 π f, it is thus possible to use <math>
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2. Signal propagating in mediumAt a propagation loss of a propagation loss factor ofThe focus point a is thus obtained without taking into account measurement errors and random noisep，nMeasured value of reflection coefficient curveEmpirical curve of reflection coefficientIn a relationship of
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Propagation loss factorAnd (equation 6) are derived as follows: in the propagation process, the signal may be represented as E (z) = E0e-γd=E0e-αde-jβdThe loss when the signal propagation distance is d is e-αd. And the focal point ap，nThe incident wave at (a) is the result of the transmission of the emission signal from layer 1 to layer (n-1), so the total loss of the emission signal is:similarly, the echo signal is also the result of the transmission of the reflected wave layer by layer, and since the path is the same as the incident wave and the total loss is the same, the echo signal should be compensated, i.e. divided by the total loss to be the focusing point ap，nThe reflected wave of (c):
thus a propagation loss factor ofWill contain parametersMoves to the same side of the equation, and gets (equation 6).
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That is, 3N electromagnetic parameters of each layer of material are jointly solved through 3N equations, and A with the minimum error sum of squares can be obtainedpOf material of lower layers at intermediate positionsAnd
step eight, focusing at different angles, as shown in fig. 8. And each group of beams starts to focus from one end of the section of the material to be measured, and after the material identification of each depth under the angle is completed, the deflection angle of the beams is gradually changed, for example, the beams are gradually deflected by 7.5 degrees to focus at other positions, so that multi-angle scanning is formed. And returning to the step three, analyzing and processing the echo signals of each layer under the angle until the echo signals of each layer are scanned to the other end of the section.
And step nine, the beam subarray can rotate for a certain angle by taking the center as an axis, and the material identification of other sections is carried out. After the six beam sub-arrays complete the focusing of each point of the cross section where the beam sub-array is located, the beam sub-arrays rotate by a certain angle, such as 10 degrees, the step three is returned, and the material identification of each point of other cross sections is carried out. Therefore, the omnibearing material identification of the measured object is realized.
Step ten, solving results, namely the material of each layer of each position of the measured objectAndand matching the calculation result with a material parameter library to realize the identification of the material. And outputting a material type identification result, which comprises the identification result of each layer of material at each position and a quality identification result, namely an identification conclusion whether the detected object meets the quality requirement.
Claims (7)
1. The multi-material combined identification device based on ultra-wideband phased array layer-by-layer focusing is characterized by comprising an equipment control module, a signal transceiving module, a signal processing module and a curve parameter extraction module, wherein the signal transceiving module is connected with the signal processing module, the signal processing module is connected with the curve parameter extraction module, and the signal transceiving module, the signal processing module and the curve parameter extraction module are all connected with the equipment control module; the device control module controls each module connected with the device control module and outputs a processing result, and comprises a central control unit, a data memory and a display device, wherein the data memory and the display device are respectively connected with the central control unit, and the central control unit is used for controlling the work of the signal transceiving module, the signal processing module and the curve parameter extraction module and the data transmission among the modules; the data memory is used for storing the processing results of the modules and providing input data required by the signal processing module; the display equipment displays the processing progress and the result; the signal receiving and transmitting module is a full-duplex signal transceiver and transmits an ultra-wideband signal to the object to be detected and receives reflection echoes of each layer of the object to be detected; the signal processing module is used for collecting echo signals, processing the echo signals in time domain and frequency domain and extracting a reflection coefficient curve measured value; the curve parameter extraction module is used for solving the electromagnetic parameter information of each layer of material and transmitting the solved result to the equipment control module; the signal transceiving module comprises an ultra-wideband transmitter, a power divider, a beam controller, P beam subarray transceivers and a beam former; the ultra-wideband transmitter, the power distributor, the beam controller, the P beam subarray transceivers and the beam former are sequentially connected; the power divider couples the power of the ultra-wideband transmitter and averagely distributes the power to each beam subarray; the beam controller is used for realizing beam deflection and focusing at different angles and different depths and obtaining thickness information of each layer of material through depth change of layer-by-layer focusing; p wave beam sub-array transceivers form a phased array transceiver, transmit ultra-wideband signals to a focusing point and receive echo signals of a reflecting point; the wave beam forming device carries out phase compensation on the echo signals received by each sub-array and synthesizes the echo signals into receiving wave beams, and P is larger than or equal to 2.
2. The device for multi-material joint identification based on ultra wide band phased array layer-by-layer focusing of claim 1, wherein the signal processing module comprises a data sampler, a signal preprocessor, a guided wave signal processor and a signal processor, wherein the signal processor comprises a wave band extraction device, a power estimator, an amplitude-frequency analysis device and a divider; the data sampler, the signal preprocessor and the signal processor are connected in sequence; the signal preprocessor is connected with the guided wave signal processor, and the guided wave signal processor is connected with a data memory in the equipment control module; the wave band extraction device, the power estimator, the amplitude-frequency analysis device and the divider are sequentially connected, and the divisor of the divider is provided by a data memory in the equipment control module; the data sampler is used for realizing the analog-to-digital conversion of the transmitting signals and the echo signals, and the signal preprocessor is used for respectively realizing the time averaging of the multiple transmitting signals and the echo signals of the same focusing point and respectively obtaining average transmitting signals and average echo signals; the guided wave signal processor obtains the preliminary information of the category, the shape and the layer number of the measured object by recording the echo time delay and the wave peak number of the guided wave, and transmits the result to the data memory; the signal processor processes the time domain and the frequency domain of the average echo signal, and extracts a reflection coefficient curve measured value, wherein a wave band extraction device extracts a reflection wave band of the average echo signal at a focus point in the time domain, a power estimator respectively carries out power spectrum estimation on the average emission signal and the average echo signal, and an amplitude-frequency analysis device is used for acquiring an amplitude spectrum on the average emission signal and the average echo signal in the frequency domain, so as to obtain an amplitude-frequency characteristic curve; the divider divides the amplitude-frequency characteristic curve and the transmission coefficient of each layer of material above the critical surface to obtain a reflection coefficient curve measured value, and the result is transmitted to a curve parameter extraction module and a data memory in the equipment control module; when calculating the reflectance curve measurement for the next layer of media, the data storage in the device control module provides the reflectance measurements for the layers of media above it.
3. The multi-material combined identification device based on ultra wide band phased array layer-by-layer focusing of claim 1, wherein the curve parameter extraction module comprises an analyzer and a characteristic database which are connected in sequence, the analyzer is also connected with a data memory in the equipment control module, and the analyzer is used for solving the electromagnetic parameter information of each layer of material according to the measured value of each layer of reflection coefficient curve and the reflection coefficient empirical curve; and the characteristic database matches the calculation result, transmits the final material identification result to the equipment control module, and displays the identification result by the display equipment.
4. The device for multi-material joint identification based on ultra wide band phased array layer-by-layer focusing of claim 1, wherein the device control module further comprises an operation device connected with the central control unit for turning on and off the device, naming and storing the processing result of a certain identification.
5. The multi-material joint identification method based on ultra wide band phased array layer-by-layer focusing is characterized by comprising the following steps of:
the method comprises the following steps that firstly, an object to be measured is placed under P wave beam sub-array transceivers, the P wave beam sub-arrays are arranged in a central scattering line shape, a scattering center is located on a central axis extension line in the vertical direction of the object to be measured, and each wave beam sub-array is composed of K receiving and transmitting wave beams;
step two, transmitting guide wave beams to obtain the information of the category, the shape and the layer number of the measured object: p is the wave beam of K and launches the single pulse to guide the wave beam vertically downward at the same time, obtain the appearance information of the measured object according to the time delay of the echo signal of each point, according to the wave crest number of the echo, obtain the classification of the measured object and layer number information of each point; the category of the measured object is divided into a low-loss material and a good-conductivity material;
step three, transmitting a focused beam: the ultra-wideband transmitter adopts frequency stepping signals or linear frequency modulation signals, each beam sub-array transmitter independently transmits focused beams to form multi-section scanning, and each beam sub-array starts to focus from the surface of an object to receive echo signals;
the position of a focal point at the critical plane of the (n-1) th layer and the nth layer at a certain position a where the p-th beam subarray is focused is recorded as ap,nSetting the object to be measured to contain N layers of materials, and collecting the focus point a of each critical surfacep,1、ap,2、…、ap,NIs marked as Ap(ii) a At ap,nFocusing M times, and averaging the M times of transmitted signals to obtain an average transmitted signal xap,n(t) averaging the time of the M echo signals to obtain an average echo signal yap,n(t)；
Step four, calculating a certain focusAmplitude-frequency characteristic curve of the transfer function at the focus: x is to beap,n(t) and yap,n(t) obtaining amplitude spectrum x on respective frequency domain by power spectrum estimation and amplitude-frequency characteristic analysis of the signal processing moduleap,n(f) And yap,n(f) Further obtain ap,nAmplitude-frequency characteristic curve of point transfer function
Step five, extracting the measured value of the reflection coefficient curve of the boundary critical surface of a certain layer at a certain position: for a focused beam, the reflected echo of the critical plane after the focusing point is suppressed, and the reflection coefficient is the ratio of the amplitude of the reflected wave to the amplitude of the incident wave; when the incident wave is a single-frequency signal, the reflection coefficient is a constant, and when the incident wave is an ultra-wideband signal, the reflection coefficient is a curve changing along with the frequency; the (n-1) th layer and the nth layer boundary ap,nMeasured value of reflection coefficient curve
The critical surface between the air and the surface layer of the object to be measured, namely the focusing point a of the critical surface between the air and the 1 st layerp,1The measured value of the reflection coefficient curve is directly incident, soAnd for the boundary between the layer 1 and the layer 2, the transmitting signal and the echo signal are at the boundary between the penetrating air and the layer 1When all the transmission occurs, ap,2Measured in a reflectance curve ofBy recursion, the critical plane a of the (n-1) th layer and the n-th layerp,nTo Wherein,representing curves of transmission coefficients of incident wave and reflected wave at the critical plane between (i-1) th layer and i-th layer before and after reflectionThe measured value of the reflection coefficient curve for the critical surface of the (n +1) th layer and the n-th layerExtracting;
step six, focusing at different depths: a isp,nAfter the solution of the reflection coefficient curve is completed, the reflection coefficient curve gradually enters the object to be focused, and when the signal transceiver module receives a stronger echo again, the signal transceiver module focuses to the point set ApPoint a at the boundary between the lower nth layer and the (n +1) th layerp,n+1From a to ap,nTo ap,n+1Can obtain the position ap,nMaterial thickness d of lower n-th layerap,n(ii) a Returning to the step three, analyzing and processing the echo signal until the echo signal is focused on the bottom surface of the object; and sets d obtained by each change of depth of focusp,1、dp,2、…、dp,NRecording as Dap;
step seven, curve parameter extraction, namely the joint solution of electromagnetic parameters of each layer of medium: n reflection coefficient curve measurementsForm a matrixObtaining a reflection coefficient empirical curve which is a function group of electromagnetic parameters of materials of each layer according to the reflection principle of the object made of the materials of the plurality of layers; from empirical curves of reflection coefficients between layersThe equality relationship of the two sets of equations establishes an equation set, and jointly solves ApElectromagnetic parameter mu of medium layer material(ap,n)、σ(ap,n)、(ap,n)Wherein N is 1,2, …, N; the signal also has propagation loss in propagation, and the empirical curve of the reflection coefficient also has a propagation loss factorAfter multiplication, it is combined withAre equal to each other, whereinap,iAnd dap,iRespectively represent ApThe attenuation constant and the thickness of the material of the ith layer; for a material with a low loss, the material is,for the material with good conductivity, the material is,multiplying corresponding propagation loss factors on corresponding frequency points;
step eight, focusing at different angles: focusing each group of wave beams from one end of the section of the material to be measured, gradually changing the deflection angle of the wave beams to focus at other positions after the material identification of each depth under the angle is completed, forming multi-angle scanning, returning to the step three, analyzing and processing echo signals of each layer under the angle until the other end of the material is scanned;
matching the solving result with a material parameter library to realize the identification of the material; and outputting the material type identification and quality identification results.
6. The method for identifying the combination of the multi-materials based on the ultra-wideband phased array layer-by-layer focusing according to claim 5, wherein the method further comprises the following steps after the step eight and before the step nine: and rotating the beam subarray by a set angle by taking the central point as an axis, returning to the step three, and identifying the materials of other sections of the materials to realize the omnibearing material identification of the measured object.
7. The method for multi-material joint identification based on ultra wide band phased array layer-by-layer focusing according to claim 5, wherein M is more than or equal to 1000.
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| CN104459679A (en) * | 2014-12-01 | 2015-03-25 | 西安电子工程研究所 | Target medium-band high-resolution processing system of azimuth rotation scanning mechanism surveillance radar |
| CN106896355B (en) * | 2016-12-29 | 2019-07-05 | 湖北工业大学 | Barrier Material Identification and range error bearing calibration based on UWB time reversal |
| CN107169469B (en) * | 2017-06-02 | 2020-06-19 | 南京理工大学 | Material identification method of MIMO radar based on machine learning |
| CN108872387A (en) * | 2018-04-23 | 2018-11-23 | 江苏省特种设备安全监督检验研究院 | Ultrasonic phased array inspection imaging system |
| CN111398968B (en) * | 2018-12-28 | 2022-10-18 | 浙江舜宇智能光学技术有限公司 | TOF precision detection system and precision detection method thereof |
| CN111256574B (en) * | 2020-03-25 | 2021-01-01 | 北京理工大学 | Method and system for measuring thickness of metal pipeline |
| CN111665293B (en) * | 2020-07-20 | 2023-12-19 | 浙江树人学院（浙江树人大学） | Eddy current detection method for defects of double-layer pipe column of weak magnetic oil pipe of high-sulfur-content gas field |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1777513A1 (en) * | 2005-10-20 | 2007-04-25 | General Electric Company | Phased array ultrasonic methods and systems for generator rotor teeth inspection |
| EP2233921A1 (en) * | 2009-03-25 | 2010-09-29 | Olympus NDT | A method and system for transducer element fault detection for phased array ultrasonic instruments |
| CN101936756A (en) * | 2010-08-31 | 2011-01-05 | 华南理工大学 | Multifrequency phased array ultrasonic Doppler flow detection system and method |
| US20110083512A1 (en) * | 2009-10-09 | 2011-04-14 | Christophe Claude Imbert | Weld seam tracking system using phased array ultrasonic devices |
| CN202057631U (en) * | 2011-03-03 | 2011-11-30 | 中国电子科技集团公司第五十研究所 | Recognition and detection instrument of metal materials in shoes |
| CN202216721U (en) * | 2011-09-23 | 2012-05-09 | 华南理工大学 | Object internal information nondestructive testing system based on ultra wide band |
| CN102809610A (en) * | 2012-06-04 | 2012-12-05 | 北京航空航天大学 | Phased array ultrasonic testing method based on improved dynamic depth focusing |
| CN203083961U (en) * | 2012-12-15 | 2013-07-24 | 华南理工大学 | Multi-material combined recognition device based on ultra-wide band phased array layer-by-layer focusing |
-
2012
- 2012-12-15 CN CN201210545447.8A patent/CN103048356B/en not_active Expired - Fee Related
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1777513A1 (en) * | 2005-10-20 | 2007-04-25 | General Electric Company | Phased array ultrasonic methods and systems for generator rotor teeth inspection |
| EP2233921A1 (en) * | 2009-03-25 | 2010-09-29 | Olympus NDT | A method and system for transducer element fault detection for phased array ultrasonic instruments |
| US20110083512A1 (en) * | 2009-10-09 | 2011-04-14 | Christophe Claude Imbert | Weld seam tracking system using phased array ultrasonic devices |
| CN101936756A (en) * | 2010-08-31 | 2011-01-05 | 华南理工大学 | Multifrequency phased array ultrasonic Doppler flow detection system and method |
| CN202057631U (en) * | 2011-03-03 | 2011-11-30 | 中国电子科技集团公司第五十研究所 | Recognition and detection instrument of metal materials in shoes |
| CN202216721U (en) * | 2011-09-23 | 2012-05-09 | 华南理工大学 | Object internal information nondestructive testing system based on ultra wide band |
| CN102809610A (en) * | 2012-06-04 | 2012-12-05 | 北京航空航天大学 | Phased array ultrasonic testing method based on improved dynamic depth focusing |
| CN203083961U (en) * | 2012-12-15 | 2013-07-24 | 华南理工大学 | Multi-material combined recognition device based on ultra-wide band phased array layer-by-layer focusing |
Non-Patent Citations (6)
| Title |
|---|
| 《超声相控阵钢轨探伤方法研究》;邬以三;《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》;20111231;全文 * |
| Rectangular Slot Antenna with Patch Stub for Ultra Wideband Applications and Phased Array Systems;Eldek A. et al.;《Progress in Electromagnetics Research》;20051231;全文 * |
| Secure Localization and Authentication in Ultra-wideband Sensor Networks;Zhang Yanchao et al.;《IEEE Journal on Selected Areas in Communications》;20060430;第24卷(第4期);全文 * |
| 相控阵多普勒测速技术研究;刘逸豪;《中国优秀硕士学位论文全文数据库 信息科技辑》;20111231;全文 * |
| 超声波相控阵技术原理及特点;刘长福 等;《河北电力技术》;20080625;第27卷(第3期);全文 * |
| 超声相控阵技术在复合材料检测上的应用;李怀富;《玻璃钢/复合材料》;20100328;全文 * |
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