阅读说明：本技术 一种基于超声兰姆波缺陷检测的成像方法及装置 (Imaging method and device based on ultrasonic lamb wave defect detection ) 是由 阎守国 黄娟 阚婷婷 张碧星 于 2021-09-15 设计创作，主要内容包括：本申请涉及一种基于超声兰姆波缺陷检测的成像方法,包括：获取待检测板状结构的缺陷回波信号,缺陷回波信号至少包括第一模式的兰姆波回波信号和第二模式的兰姆波回波信号；对第一模式的兰姆波回波信号和第二模式的兰姆波回波信号进行聚焦处理,确定聚焦回波信号；基于聚焦回波信号,确定第一距离,第一距离表征缺陷回波信号对应的传感器所在位置与所述缺陷所在位置之间的距离；基于N个缺陷回波信号对应的第一距离,确定待检测板状结构的缺陷检测图像。本申请提供的基于超声兰姆波缺陷检测的成像方法可以实现对二维板状结构中缺陷的高精度成像。(The application relates to an imaging method based on ultrasonic lamb wave defect detection, which comprises the following steps: acquiring a defect echo signal of a plate-shaped structure to be detected, wherein the defect echo signal at least comprises a lamb wave echo signal in a first mode and a lamb wave echo signal in a second mode; focusing the lamb wave echo signals in the first mode and the lamb wave echo signals in the second mode to determine focused echo signals; determining a first distance based on the focused echo signal, wherein the first distance represents the distance between the position of the sensor corresponding to the defect echo signal and the position of the defect; and determining a defect detection image of the plate-shaped structure to be detected based on the first distances corresponding to the N defect echo signals. The imaging method based on ultrasonic lamb wave defect detection can realize high-precision imaging of defects in a two-dimensional plate-shaped structure.)

1. An imaging method based on ultrasonic lamb wave defect detection is characterized by comprising the following steps:

acquiring a defect echo signal of a plate-shaped structure to be detected, wherein the defect echo signal at least comprises a lamb wave echo signal in a first mode and a lamb wave echo signal in a second mode, the defect echo signal is an echo signal received by any one of N sensors, the N sensors are arranged in a region to be detected of the plate-shaped structure to be detected, and N is a positive integer greater than or equal to 3;

focusing the lamb wave echo signals in the first mode and the lamb wave echo signals in the second mode to determine focused echo signals;

determining a first distance based on the focusing echo signal, wherein the first distance represents the distance between the position of the sensor corresponding to the defect echo signal and the position of the defect;

and determining a defect detection image of the plate-shaped structure to be detected based on the first distances corresponding to the N defect echo signals.

2. The imaging method according to claim 1, wherein the performing a focusing process on the lamb wave echo signals of the first mode and the lamb wave echo signals of the second mode to determine focused echo signals comprises:

determining phase change of lamb wave echo signals in a first mode and phase change of lamb wave echo signals in a second mode based on the thickness of the plate-shaped structure to be detected, the frequency dispersion characteristic of ultrasonic lamb waves and a preset first distance, wherein the frequency dispersion characteristic of the ultrasonic lamb waves comprises signal angular frequency of the ultrasonic lamb waves, the propagation speed of the lamb waves in the first mode and the propagation speed of the lamb waves in the second mode;

determining a frequency dispersion compensation coefficient based on the phase change of the lamb wave echo signal in the first mode and the phase change of the lamb wave echo signal in the second mode;

and determining the focusing echo signal based on the frequency dispersion compensation coefficient and the defect echo signal.

3. The imaging method of claim 2, wherein said determining the focused echo signal based on the dispersion compensation coefficient and the defect echo signal comprises:

determining a frequency domain representation of a dispersion compensation signal based on the dispersion compensation coefficients and the defect echo signal;

converting a frequency domain representation of the dispersion compensated signal to a time domain representation of the dispersion compensated signal;

determining the focused echo signal based on a target time window and a time domain representation of the dispersion compensation signal, the target time window being determined based on a time length of a sound source excitation signal, a propagation velocity of the lamb wave in the first mode, and a propagation velocity of the lamb wave in the second mode.

4. The imaging method of claim 2 or 3, wherein said determining a first distance based on the focused echo signal comprises:

and determining the preset first distance corresponding to the focus echo signal with the maximum amplitude as the first distance.

5. The imaging method according to any one of claims 1 to 4, wherein determining a defect detection image of the plate-like structure to be detected based on the first distances corresponding to the N defect echo signals comprises:

acquiring second distance information, wherein the second distance information comprises distances between each pixel coordinate in a pixel coordinate system and position coordinates of each sensor in the N sensors in the pixel coordinate system, and the pixel coordinate system is determined based on the surface of the plate-shaped structure to be detected;

determining a pixel value of each pixel coordinate in the pixel coordinate system based on the second distance information and the first distances corresponding to the N defect echo signals;

and generating a defect detection image of the plate-shaped structure to be detected based on the pixel value of each pixel coordinate in the pixel coordinate system.

6. An imaging device based on ultrasonic lamb wave defect detection, comprising:

the system comprises N sensors, a signal processing module and a signal processing module, wherein the N sensors are arranged in a to-be-detected area of a to-be-detected platy structure and used for receiving a defect echo signal of the to-be-detected platy structure, and N is a positive integer greater than or equal to 3;

the communication interface is used for receiving defect echo signals received by the N sensors, and the defect echo signals at least comprise lamb wave echo signals in a first mode and lamb wave echo signals in a second mode;

a memory storing computer instructions;

a processor executing the computer instructions to perform the steps of:

focusing the lamb wave echo signals in the first mode and the lamb wave echo signals in the second mode to determine focused echo signals;

determining a first distance based on the focusing echo signal, wherein the first distance represents the distance between the position of the sensor corresponding to the defect echo signal and the position of the defect;

and determining a defect detection image of the plate-shaped structure to be detected based on the first distances corresponding to the N defect echo signals.

7. The imaging apparatus according to claim 6, wherein the performing a focusing process on the lamb wave echo signals of the first mode and the lamb wave echo signals of the second mode to determine focused echo signals includes:

determining phase change of lamb wave echo signals in a first mode and phase change of lamb wave echo signals in a second mode based on the thickness of the plate-shaped structure to be detected, the frequency dispersion characteristic of ultrasonic lamb waves and a preset first distance, wherein the frequency dispersion characteristic of the ultrasonic lamb waves comprises signal angular frequency of the ultrasonic lamb waves, the propagation speed of the lamb waves in the first mode and the propagation speed of the lamb waves in the second mode;

determining a frequency dispersion compensation coefficient based on the phase change of the lamb wave echo signal in the first mode and the phase change of the lamb wave echo signal in the second mode;

and determining the focusing echo signal based on the frequency dispersion compensation coefficient and the defect echo signal.

8. The imaging apparatus of claim 7, wherein said determining the focused echo signal based on the dispersion compensation coefficient and the defect echo signal comprises:

determining a frequency domain representation of a dispersion compensation signal based on the dispersion compensation coefficients and the defect echo signal;

converting a frequency domain representation of the dispersion compensated signal to a time domain representation of the dispersion compensated signal;

determining the focused echo signal based on a target time window and a time domain representation of the dispersion compensation signal, the target time window being determined based on a time length of a sound source excitation signal, a propagation velocity of the lamb wave in the first mode, and a propagation velocity of the lamb wave in the second mode.

9. The imaging apparatus of claim 7 or 8, wherein the determining a first distance based on the focused echo signal comprises:

and determining the preset first distance corresponding to the focus echo signal with the maximum amplitude as the first distance.

10. The imaging apparatus according to any one of claims 6 to 9, wherein said determining a defect detection image of the plate-like structure to be detected based on the first distances corresponding to the N defect echo signals comprises:

acquiring second distance information, wherein the second distance information comprises distances between each pixel coordinate in a pixel coordinate system and position coordinates of each sensor in the N sensors in the pixel coordinate system, and the pixel coordinate system is determined based on the surface of the plate-shaped structure to be detected;

determining a pixel value of each pixel coordinate in the pixel coordinate system based on the second distance information and the first distances corresponding to the N defect echo signals;

and generating a defect detection image of the plate-shaped structure to be detected based on the pixel value of each pixel coordinate in the pixel coordinate system.

Technical Field

The application relates to the technical field of nondestructive testing, in particular to an imaging method and device based on ultrasonic lamb wave defect detection.

Background

The ultrasonic Lamb wave (Lamb wave) detection technology is concerned with due to the characteristics of large detection range and high detection efficiency, is a quick and effective nondestructive detection method suitable for long-distance large-area structures, and is widely applied to the detection and evaluation of engineering structures along with the deep research on Lamb wave theory. However, since the influence of the dispersion of lamb waves and the multimode characteristics is usually avoided when lamb waves are used for detection, a high-resolution detection image cannot be formed.

In general, when a lamb wave is used for defect detection, a single mode lamb wave is selectively excited for detection, but dispersion and multi-mode phenomena generated when the wave propagates to a defect position and interacts with the defect cannot be avoided. The conventional imaging algorithm generally only extracts lamb wave signals of a certain mode for imaging, ignores useful information contained among waves of a plurality of mode dispersion, and therefore cannot form a detection image with high resolution.

Disclosure of Invention

The application provides an imaging method based on ultrasonic lamb wave defect detection, and a high-resolution detection image can be obtained by applying the method.

In a first aspect, the present application provides an imaging method based on ultrasonic lamb wave defect detection, including: acquiring a defect echo signal of a plate-shaped structure to be detected, wherein the defect echo signal at least comprises a lamb wave echo signal in a first mode and a lamb wave echo signal in a second mode, the defect echo signal is an echo signal received by any one of N sensors, the N sensors are arranged in a region to be detected of the plate-shaped structure to be detected, and N is a positive integer greater than or equal to 3; focusing the lamb wave echo signals in the first mode and the lamb wave echo signals in the second mode to determine focused echo signals; determining a first distance based on the focusing echo signal, wherein the first distance represents the distance between the position of the sensor corresponding to the defect echo signal and the position of the defect; and determining a defect detection image of the plate-shaped structure to be detected based on the first distances corresponding to the N defect echo signals.

In another possible implementation, the performing a focusing process on the lamb wave echo signals in the first mode and the lamb wave echo signals in the second mode to determine focused echo signals includes:

determining phase change of lamb wave echo signals in a first mode and phase change of lamb wave echo signals in a second mode based on the thickness of the plate-shaped structure to be detected, the frequency dispersion characteristic of ultrasonic lamb waves and a preset first distance, wherein the frequency dispersion characteristic of the ultrasonic lamb waves comprises signal angular frequency of the ultrasonic lamb waves, the propagation speed of the lamb waves in the first mode and the propagation speed of the lamb waves in the second mode;

determining a frequency dispersion compensation coefficient based on the phase change of the lamb wave echo signal in the first mode and the phase change of the lamb wave echo signal in the second mode;

and determining the focusing echo signal based on the frequency dispersion compensation coefficient and the defect echo signal.

In another possible implementation, the determining the focused echo signal based on the dispersion compensation coefficient and the defect echo signal includes:

determining a frequency domain representation of a dispersion compensation signal based on the dispersion compensation coefficients and the defect echo signal;

converting a frequency domain representation of the dispersion compensated signal to a time domain representation of the dispersion compensated signal;

determining the focused echo signal based on a target time window and a time domain representation of the dispersion compensation signal, the target time window being determined based on a time length of a sound source excitation signal, a propagation velocity of the lamb wave in the first mode, and a propagation velocity of the lamb wave in the second mode.

In another possible implementation, the determining a first distance based on the focused echo signal includes:

and determining the preset first distance corresponding to the focus echo signal with the maximum amplitude as the first distance.

In another possible implementation, the determining a defect detection image of the plate-like structure to be detected based on the first distances corresponding to the N defect echo signals includes:

acquiring second distance information, wherein the second distance information comprises distances between each pixel coordinate in a pixel coordinate system and position coordinates of each sensor in the N sensors in the pixel coordinate system, and the pixel coordinate system is determined based on the surface of the plate-shaped structure to be detected;

determining a pixel value of each pixel coordinate in the pixel coordinate system based on the second distance information and the first distances corresponding to the N defect echo signals;

and generating a defect detection image of the plate-shaped structure to be detected based on the pixel value of each pixel coordinate in the pixel coordinate system.

In a second aspect, the present application provides an imaging device based on ultrasonic lamb wave defect detection, including:

the system comprises N sensors, a signal processing module and a signal processing module, wherein the N sensors are arranged in a to-be-detected area of a to-be-detected platy structure and used for receiving a defect echo signal of the to-be-detected platy structure, and N is a positive integer greater than or equal to 3;

the communication interface is used for receiving defect echo signals received by the N sensors, and the defect echo signals at least comprise lamb wave echo signals in a first mode and lamb wave echo signals in a second mode;

a memory storing computer instructions;

a processor executing the computer instructions to perform the steps of:

focusing the lamb wave echo signals in the first mode and the lamb wave echo signals in the second mode to determine focused echo signals;

determining a first distance based on the focusing echo signal, wherein the first distance represents the distance between the position of the sensor corresponding to the defect echo signal and the position of the defect;

and determining a defect detection image of the plate-shaped structure to be detected based on the first distances corresponding to the N defect echo signals.

In another possible implementation, the performing a focusing process on the lamb wave echo signals in the first mode and the lamb wave echo signals in the second mode to determine focused echo signals includes:

determining phase change of lamb wave echo signals in a first mode and phase change of lamb wave echo signals in a second mode based on the thickness of the plate-shaped structure to be detected, the frequency dispersion characteristic of ultrasonic lamb waves and a preset first distance, wherein the frequency dispersion characteristic of the ultrasonic lamb waves comprises signal angular frequency of the ultrasonic lamb waves, the propagation speed of the lamb waves in the first mode and the propagation speed of the lamb waves in the second mode;

determining a frequency dispersion compensation coefficient based on the phase change of the lamb wave echo signal in the first mode and the phase change of the lamb wave echo signal in the second mode;

and determining the focusing echo signal based on the frequency dispersion compensation coefficient and the defect echo signal.

In another possible implementation, the determining the focused echo signal based on the dispersion compensation coefficient and the defect echo signal includes:

determining a frequency domain representation of a dispersion compensation signal based on the dispersion compensation coefficients and the defect echo signal;

converting a frequency domain representation of the dispersion compensated signal to a time domain representation of the dispersion compensated signal;

determining the focused echo signal based on a target time window and a time domain representation of the dispersion compensation signal, the target time window being determined based on a time length of a sound source excitation signal, a propagation velocity of the lamb wave in the first mode, and a propagation velocity of the lamb wave in the second mode.

In another possible implementation, the determining a first distance based on the focused echo signal includes:

and determining the preset first distance corresponding to the focus echo signal with the maximum amplitude as the first distance.

In another possible implementation, the determining a defect detection image of the plate-like structure to be detected based on the first distances corresponding to the N defect echo signals includes:

acquiring second distance information, wherein the second distance information comprises distances between each pixel coordinate in a pixel coordinate system and position coordinates of each sensor in the N sensors in the pixel coordinate system, and the pixel coordinate system is determined based on the surface of the plate-shaped structure to be detected;

determining a pixel value of each pixel coordinate in the pixel coordinate system based on the second distance information and the first distances corresponding to the N defect echo signals;

and generating a defect detection image of the plate-shaped structure to be detected based on the pixel value of each pixel coordinate in the pixel coordinate system.

According to the imaging method based on ultrasonic lamb wave defect detection, the problem of positioning the defect is converted into the problem of searching a compensated signal peak value through a frequency dispersion compensation means, and the method has very important significance and application value for positioning and imaging the defect.

Drawings

Fig. 1 is a flowchart of an imaging method based on ultrasonic lamb wave defect detection according to an embodiment of the present disclosure;

fig. 2 is a schematic structural diagram of an imaging device based on ultrasonic lamb wave defect detection according to an embodiment of the present application.

Detailed Description

The technical solution of the present application is further described in detail by the accompanying drawings and examples.

Fig. 1 is a flowchart of an imaging method based on ultrasonic lamb wave defect detection according to an embodiment of the present disclosure. As shown in fig. 1, the method includes steps S101 to S104.

In step S101, a defect echo signal of a plate-like structure to be detected is acquired.

Illustratively, a probe is fixed on a plate-shaped structure to be detected, N sensors are arranged in an area of interest of the plate-shaped structure to be detected (namely, the area to be detected), ultrasonic lamb waves are generated through excitation of the probe, when a defect exists in the plate-shaped structure to be detected, the N sensors receive defect echo signals, and the defect echo signals of the plate-shaped structure to be detected are obtained through obtaining the defect echo signals received by the N sensors.

It should be noted that the defect echo signals include lamb wave echo signals of multiple modes, for example, a lamb wave echo signal of a first mode and a lamb wave echo signal of a second mode, N is a positive integer greater than or equal to 3, and a specific scheme of the ultrasonic lamb wave defect detection-based imaging method of the present application is described below by taking the lamb wave echo signals of multiple modes as lamb wave signals of two modes (that is, the lamb wave echo signals of the first mode and the lamb wave echo signals of the second mode) as an example.

In step S102 and step S103, the lamb wave echo signal in the first mode and the lamb wave echo signal in the second mode are focused to determine a focused echo signal, and then a first distance is determined based on the focused echo signal, where the first distance represents a distance between a position where a sensor corresponding to the defect echo signal is located and a position where the defect is located.

Illustratively, in defect detection, the spectrum of the incident signal propagating to the defect is assumed to be S (r)₀ω), the distance between the receiving point (i.e. the position of one of the N sensors) and the defect is r, and the spectrum of the defect echo signal can be represented as r if the defect scattered signal contains two lamb wave modes

Wherein S (r)₀ω) represents the spectrum of the acoustic vibration signal at the defect, ω being the angular frequency of the signal, a₁And a₂Corresponding to the amplitudes of the two modes of the lamb wave,andthe phase change of the two modes from the defect to the receiving point, respectively, is the distance r from the defect to the receiving point. On the premise of knowing the thickness H of the plate, the propagation velocity c of the i-th mode lamb wave when the frequency is omega can be calculated through a lamb wave frequency dispersion theoretical formula_iThe phase change of the different modes propagating from the defect to the reception point can be calculated by the following formula:

according to the phase variation relation, the phase can be subjected to inverse compensation, and the compensated frequency domain signal function is as follows:

wherein the content of the first and second substances,andi.e. the dispersion compensation coefficients, in other words, the frequency domain representation of the dispersion compensation signal is determined based on the dispersion compensation coefficients and the received defect echo signal.

And performing Fourier transform on the signal function after the frequency dispersion compensation to obtain a time domain down frequency dispersion compensation signal A (t), namely time domain expression of the frequency dispersion compensation signal:

A(t)＝(a₁+a₂)S(r₀,t)+S′₁+S′₂ (3)

wherein S (r)₀T) is S (r)₀ω) of the signal, S ', S), also to obtain a fully dispersion compensated mode signal, S' and S₂' denotes the interference term which is not fully compensated.

In formula (3), S (r)₀T) is a completely compensated signal of the two mode signals, independent of the position of the receiving pointThe last two terms in the formula (3) are interference terms related to the position r of the receiving point and are S (r) in the arrival time of the waveform₀T) on both sides. Therefore, we can intercept the fully compensated time signal (a) in time by controlling the appropriate time window (i.e. the target time window)₁+a₂)S(r₀T), the length of the time window Δ T is related to the time length T of the acoustic source excitation signal, and the dispersion characteristics of the different modes propagating to the defect:

Δt＝T+(r₀/c_min-r₀/c_max)

wherein c is_minAnd c_maxFor different modes of lamb wave propagation velocity c_iI.e. when the plurality of mode lamb waves comprises a first mode lamb wave and a second mode lamb wave, c_minAnd c_maxThe propagation velocity of the first mode lamb wave and the propagation velocity of the second mode lamb wave are respectively the propagation velocity with smaller propagation velocity and the propagation velocity with larger propagation velocity.

(a₁+a₂)S(r₀T) is a focusing signal obtained when the defect scattering echo signal contains two lamb wave modes, and the focusing signal is an original incident signal at the defect.

When a plurality of modes are contained in the defect scattering echo signal, the original incident signal at the defect can be intercepted by adopting a method similar to the above method.

In the defect detection process, the distance r between the receiving point and the defect is unknown, so when the received defect echo signal is subjected to focusing reception, a preset distance r 'is adopted to calculate a focusing receiving signal A (t), and when the preset distance r' is closer to the actual distance r between the defect and the receiving point, the better the dispersion compensation effect is, and the larger the peak value of the obtained focusing receiving signal is. Therefore, the preset distance r 'is continuously changed to obtain the focus echo signal with the maximum peak value, so as to obtain the actual position of the defect, that is, to position the defect, that is, the preset distance r' corresponding to the maximum focus echo signal is the actual distance r, that is, the first distance, between the receiving point and the defect.

It is easy to understand that, the predetermined first distance (r ') corresponding to the maximum focused echo signal means that the focused echo signal a (t) with the maximum amplitude in the plurality of focused echo signals a (t) is correspondingly substituted r', which is the actual distance r between the defect and the receiving point, i.e. the first distance.

The predetermined first distance r 'is arranged in relation to the structure of the plate-like structure to be inspected, for example the predetermined first distance r' is 10-50 cm.

In step S104, a defect detection image of the plate-like structure to be detected is determined based on the first distances corresponding to the N defect echo signals.

Exemplarily, a pixel coordinate system is determined based on a two-dimensional plane (x, y) of lamb wave propagation, namely, the surface of a plate-shaped structure to be detected, N sensors are arranged in an interested imaging area, and for a defect echo signal received by each sensor, the method for positioning the defect in the previous step is applied to obtain the distance r between the defect and the sensor_i(i ═ 1, 2.., N) (i.e., first distance), we propose the following lamb wave imaging algorithm

Where H (x, y) represents the pixel value at the pixel point (x, y), L_iIndicating the distance (i.e., the second distance) between the pixel (x, y) and the ith sensor. Based on the pixel values of the respective pixel coordinates (i.e., pixel points) in the respective pixel coordinate systems, a defect detection image of the plate-like structure to be detected is generated.

The position of the maximum value of the pixel values obtained through calculation is selected as the position of the defect, and the imaging algorithm can realize high-precision imaging of the defect in the two-dimensional plate-shaped structure.

Based on the same concept as the foregoing method embodiment, the embodiment of the present application further provides an ultrasonic lamb wave defect detection-based imaging device 200, where the ultrasonic lamb wave defect detection-based imaging device 200 includes units or means for implementing each step in the ultrasonic lamb wave defect detection-based imaging method shown in fig. 1.

Fig. 2 is a schematic structural diagram of an imaging device based on ultrasonic lamb wave defect detection according to an embodiment of the present application. As shown in fig. 2, the imaging apparatus 200 based on ultrasonic lamb wave defect detection at least includes:

the system comprises N sensors 201, a central processing unit and a central processing unit, wherein the N sensors 201 are arranged in a to-be-detected area of a to-be-detected plate-shaped structure and are used for receiving defect echo signals of the to-be-detected plate-shaped structure, and N is a positive integer greater than or equal to 3;

a communication interface 202, configured to receive defect echo signals received by the N sensors, where the defect echo signals at least include a lamb wave echo signal in a first mode and a lamb wave echo signal in a second mode;

a memory 203 storing computer instructions;

the processor 204, executing the computer instructions, performs the following steps:

focusing the lamb wave echo signals in the first mode and the lamb wave echo signals in the second mode to determine focused echo signals;

determining a first distance based on the focusing echo signal, wherein the first distance represents the distance between the position of the sensor corresponding to the defect echo signal and the position of the defect;

and determining a defect detection image of the plate-shaped structure to be detected based on the first distances corresponding to the N defect echo signals.

In another possible implementation, the performing a focusing process on the lamb wave echo signals in the first mode and the lamb wave echo signals in the second mode to determine focused echo signals includes:

determining phase change of lamb wave echo signals in a first mode and phase change of lamb wave echo signals in a second mode based on the thickness of the plate-shaped structure to be detected, the frequency dispersion characteristic of ultrasonic lamb waves and a preset first distance, wherein the frequency dispersion characteristic of the ultrasonic lamb waves comprises signal angular frequency of the ultrasonic lamb waves, the propagation speed of the lamb waves in the first mode and the propagation speed of the lamb waves in the second mode;

determining a frequency dispersion compensation coefficient based on the phase change of the lamb wave echo signal in the first mode and the phase change of the lamb wave echo signal in the second mode;

and determining the focusing echo signal based on the frequency dispersion compensation coefficient and the defect echo signal.

In another possible implementation, the determining the focused echo signal based on the dispersion compensation coefficient and the defect echo signal includes:

determining a frequency domain representation of a dispersion compensation signal based on the dispersion compensation coefficients and the defect echo signal;

converting a frequency domain representation of the dispersion compensated signal to a time domain representation of the dispersion compensated signal;

determining the focused echo signal based on a target time window and a time domain representation of the dispersion compensation signal, the target time window being determined based on a time length of a sound source excitation signal, a propagation velocity of the lamb wave in the first mode, and a propagation velocity of the lamb wave in the second mode.

In another possible implementation, the determining a first distance based on the focused echo signal includes:

and determining the preset first distance corresponding to the focus echo signal with the maximum amplitude as the first distance.

In another possible implementation, the determining a defect detection image of the plate-like structure to be detected based on the first distances corresponding to the N defect echo signals includes:

acquiring second distance information, wherein the second distance information comprises distances between each pixel coordinate in a pixel coordinate system and position coordinates of each sensor in the N sensors in the pixel coordinate system, and the pixel coordinate system is determined based on the surface of the plate-shaped structure to be detected;

determining a pixel value of each pixel coordinate in the pixel coordinate system based on the second distance information and the first distances corresponding to the N defect echo signals;

and generating a defect detection image of the plate-shaped structure to be detected based on the pixel value of each pixel coordinate in the pixel coordinate system.

It should be understood that, in the embodiment of the present application, the processor 204 may be a central processing unit CPU, and the processor 204 may also be other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, and the like. A general purpose processor may be a microprocessor or any conventional processor or the like.

The memory 203 may include both read-only memory and random access memory, and provides instructions and data to the processor 204. The memory 203 may also include non-volatile random access memory. For example, the memory 203 may also store computer instructions that are executed by the processor to implement the above-described ultrasonic lamb wave defect detection-based imaging method.

The memory 203 may be either volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The non-volatile memory may be a read-only memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an electrically Erasable EPROM (EEPROM), or a flash memory. Volatile memory can be Random Access Memory (RAM), which acts as external cache memory. By way of example but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous SDRAM (ESDRAM), synchlink DRAM (SLDRAM), and direct memory bus RAM (DR RAM).

It should be understood that the imaging apparatus 200 based on ultrasonic lamb wave defect detection according to the embodiment of the present application may correspond to a corresponding subject for executing the method shown in fig. 1 according to the embodiment of the present application, and the above and other operations and/or functions of each device in the imaging apparatus 200 based on ultrasonic lamb wave defect detection are respectively for realizing the corresponding flow of the method of fig. 1, and are not repeated herein for brevity.

It will be further appreciated by those of ordinary skill in the art that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be embodied in electronic hardware, computer software, or combinations of both, and that the components and steps of the examples have been described in a functional general in the foregoing description for the purpose of illustrating clearly the interchangeability of hardware and software. Whether these functions are performed in hardware or software depends on the particular application of the solution and design constraints. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied in hardware, a software module executed by a processor, or a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

The above-mentioned embodiments, objects, technical solutions and advantages of the present application are described in further detail, it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present application and are not intended to limit the scope of the present application, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present application should be included in the scope of the present application.