Automatic dead pixel identification method of laser vibration meter based on return light intensity and signal-to-noise ratio analysis

Abstract

The invention discloses an automatic dead pixel identification method for a laser vibration meter based on return light intensity and signal-to-noise ratio analysis, and aims to improve the return light signal quality of the laser vibration meter on a rough surface sample. According to the technical scheme, in the field scanning process of a laser vibration meter through an electric displacement sliding table, the signal quality of a scanning position is judged according to the intensity of return light, if the intensity of the return light does not exceed a set threshold value, a signal of a position with a high signal-to-noise ratio is found nearby again to replace an original position signal, and the signal quality is improved. And the detection capability of the laser vibration meter on the sample with the rough surface is improved.

Description

Technical Field

[0001] The present invention belongs to the field of laser ultrasonic non-destructive testing, and relates to a method for automatically identifying defective points of a laser vibrometer based on the analysis of return light intensity and signal-to-noise ratio. Background Technique

[0002] Laser ultrasonic technology is a disruptive non-destructive testing technology developed in the late 20th century. Through a non-contact photo-acoustic energy conversion mechanism, it realizes high-precision dynamic characterization of internal defects, mechanical properties, and microstructures of materials. Traditional piezoelectric ultrasonic testing technology is limited by the use of mechanical couplants, probe size, and frequency band range, and it is difficult to meet the high-resolution, full-life-cycle monitoring requirements of modern industries for complex components (such as aerospace composite materials, microelectronic packaging structures). Laser ultrasonic, with photo-induced ultrasonic waves as the core, combined with advanced optical sensing and intelligent signal processing technologies, has gradually become a key enabling tool in the fields of intelligent manufacturing, new energy, and biomedicine.

[0003] From a physical mechanism perspective, the birth of laser ultrasonic stems from theoretical breakthroughs in the photoacoustic effect and photoelastic effect. In 1963, White first established a mathematical model of laser-induced thermoelastic acoustic waves, revealing the acoustic response law of the interaction between short-pulse lasers and materials. Since then, with the maturity of high-power pulsed lasers and high-sensitivity interferometers, laser ultrasonic technology has gradually moved from the laboratory to industrial sites. In the 1990s, the EU's "LASERULTRA" project first applied it to the monitoring of nuclear power plant pressure vessels, demonstrating its stability in high-temperature (>500°C), high-radiation environments; while the case of delamination detection of the carbon fiber skin of the Airbus A380 wing marked the large-scale implementation of this technology in the aerospace field. In recent years, the deep integration of ultrafast optical technology and artificial intelligence algorithms has further promoted the evolution of laser ultrasonic towards sub-micron resolution and multi-physical field coupling (thermal-acoustic-optical joint inversion), opening up new paths for its application in frontier fields such as the mechanical characterization of two-dimensional materials and elastic imaging of biological tissues.

[0004] However, in actual industrial scenarios, the serious attenuation of the signal-to-noise ratio caused by complex material surfaces (such as low-reflectivity composite materials, rough metals) and environmental interference has become the core bottleneck restricting the wide application of this technology. According to statistics, in the detection of carbon fiber reinforced polymers, due to the surface reflectivity being less than 5%, the signal-to-noise ratio of ultrasonic echo signals is usually lower than 20 dB, resulting in a missed detection rate of sub-millimeter defects as high as over 30%. Therefore, how to improve the signal-to-noise ratio of laser ultrasonic signals has become the focus of common concern in the academic and industrial communities. Summary of the Invention

[0005] In view of this, in order to solve the deficiencies of the prior art, the present invention proposes a method for automatically identifying bad points of a laser vibrometer based on the analysis of the return light intensity and the signal-to-noise ratio, so as to improve the signal-to-noise ratio of the signals obtained by the laser vibrometer from complex surfaces.

[0006] To achieve the above object, a method for automatically identifying bad points of a laser vibrometer based on the analysis of the return light intensity and the signal-to-noise ratio is provided. The method is executed by a detection device, and the detection device includes a pulsed laser, an electric displacement stage, a laser vibrometer, and a computer. The pulsed laser is used to emit excitation light to the surface of a metal plate to excite laser ultrasonic signals. The electric displacement stage fixes and moves the metal plate for laser scanning. The laser vibrometer is used to emit detection light to the surface of the metal plate, receive the laser ultrasonic signals excited by the excitation light, and convert the return light intensity into a DC voltage signal and output it to the computer together. The computer is used to control the movement of the displacement stage and store and process the obtained laser ultrasonic signals.

[0007] The method includes the following steps:

[0008] Step 1: Set up the metal plate stably on the electric displacement stage, place and start the laser vibrometer on one side of the metal plate, and adjust the position, laser incident angle, and energy output of the laser vibrometer until the laser vibrometer obtains a stable DC voltage signal with the highest amplitude.

[0009] Step 2: Start the pulsed laser, make the excitation light and the detection light incident on the same side of the metal plate, and control the electric displacement stage through the computer to perform laser scanning on the surface of the metal plate.

[0010] Step 3: The computer detects the intensity of the DC voltage signal at each position on the metal plate during the laser scanning process and records the abnormal positions where the intensity of the DC voltage signal is lower than the preset voltage threshold. After the laser scanning is completed, re-laser scan the vicinity of the above abnormal positions until the intensity of the DC voltage signal is higher than the preset voltage threshold; the abnormal positions correspond to bad points; each position refers to the position where the detection light passes on the metal plate during the laser scanning.

[0011] Step 4: The computer performs wavelet transform filtering on the laser ultrasonic signals at the positions of the re-laser scanning, then performs Fourier transform on the time component of the laser ultrasonic signals after the wavelet transform filtering, changes the time-domain signal into a frequency-domain signal, determines the preset bandwidth range before and after the wave peak with the largest amplitude in the spectrum corresponding to the frequency-domain signal as the signal main frequency band, so as to calculate the signal power of the laser ultrasonic signal corresponding to the abnormal position and further obtain the signal-to-noise ratio of the signal power. The signal-to-noise ratio calculation formula is as follows:

[0012]

[0013] Among them, SNR is the signal-to-noise ratio, P signal is the signal power, P noise is the noise power;

[0014] If the signal-to-noise ratio is greater than the preset signal-to-noise ratio threshold, the newly obtained laser ultrasonic signal by re-laser scanning field will replace the original laser ultrasonic signal corresponding to the abnormal position, otherwise return to execute step 3.

[0015] Furthermore, in step 1, the output power of the laser vibrometer is 0 - 100 mW.

[0016] Furthermore, in steps 2 and 3, the laser scanning field obtains matrix data of M×N rows and L columns. M is the number of spatial sampling points in the x direction, N is the number of spatial sampling points in the y direction, L is the number of time sampling points, the scanning field step length is 5 mm, the step length of re-scanning field is 1 mm, and the radius of the excitation light spot is 1 mm.

[0017] Furthermore, in step 3, the amplitude of the DC signal output by the laser vibrometer reflects the received intensity of the returned light.

[0018] Furthermore, in step 4, the signal power is the sum of the squares of the spectral amplitudes within the signal frequency band, the noise power is the sum of the squares of the spectral amplitudes within the noise frequency band, and the noise frequency band is from 50 MHz to 70 MHz.

[0019] Furthermore, in step 4, the preset signal-to-noise ratio threshold is 40 dB.

[0020] Furthermore, the preset voltage threshold is 200 mv.

[0021] Furthermore, the range corresponding to the vicinity of the abnormal position is less than half of the scanning field step length during the first scanning field.

[0022] Furthermore, the abscissa of the laser ultrasonic signal represents the time component.

[0023] Furthermore, the preset bandwidth is 10 MHz.

[0024] The above technical solution has the following beneficial technical effects:

[0025] The present invention combines the dual criteria of the intensity of the returned light (amplitude of the DC signal) and the signal-to-noise ratio, and can accurately identify the measurement bad points caused by optical path deviation, surface defects or environmental interference. For the bad point area, high-precision re-scanning at the 1 mm level + combined wavelet-Fourier denoising is adopted, and the effective data utilization rate is improved by separating the power in the high-frequency noise band and reconstructing the signal segment, and the success rate of repairing abnormal signals is increased. Description of the Drawings

[0026] The accompanying drawings are used to better understand the present invention and do not constitute an undue limitation on the present invention. Among them:

[0027] Figure 1 is a schematic diagram of the algorithm principle of an embodiment of the present invention;

[0028] Figure 2 is a schematic diagram of the device connection of an embodiment of the present invention;

[0029] Figure 3 is a flowchart of a schematic diagram of the laser rescan path for the bad point position in an embodiment of the present invention;

[0030] Figure 4 is a functional block diagram of a computer system of an embodiment of the present invention. Detailed implementation manners

[0031] The following describes exemplary embodiments of the present invention with reference to the accompanying drawings. Various details of the embodiments of the present invention are included to facilitate understanding, and they should be considered merely exemplary. Therefore, those of ordinary skill in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present invention. Similarly, for clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0032] To solve the deficiencies of the prior art, an embodiment of the present invention proposes a method for automatically identifying bad points of a laser vibrometer based on the analysis of the return light intensity and signal-to-noise ratio, which improves the signal-to-noise ratio of the signals obtained by the laser vibrometer from complex surfaces. The present invention discloses a method for automatically identifying bad points of a laser vibrometer based on the analysis of the return light intensity and signal-to-noise ratio, and its purpose is to improve the quality of the return light signal of the laser vibrometer on a rough surface specimen (sample). Its technical solution is that during the process of the laser vibrometer using an electric displacement stage to perform a scanning field, the signal quality of the scanning position is judged according to the return light intensity. If the return light intensity fails to exceed the set threshold, a signal at a position with a high signal-to-noise ratio will be found nearby to replace the original position signal, improving the detection ability of the laser vibrometer for surface rough specimens. The samples to be detected are not limited to metal plates. Although a metal plate is mentioned in the following embodiments, its principle and method can be applied to other materials or structures as long as these materials can perform effective vibration detection through laser ultrasonic signals. Other materials such as plastics, composite materials, ceramics, thin films, glass, etc., and even some composite structures, as long as they have suitable optical and vibration response characteristics, can all apply this method for anomaly detection.

[0033] As Figures 1 to 3 shown, this embodiment provides a method for automatically identifying bad points of a laser vibrometer based on the analysis of the return light intensity and signal-to-noise ratio. The method is performed by Figure 2It is executed by the detection device shown. The detection device includes a pulsed laser, an electric displacement stage, a laser vibrometer, and a computer. The pulsed laser is used to emit excitation light onto the surface of the metal plate to excite laser ultrasonic signals. The electric displacement stage fixes and moves the metal plate for laser scanning. The laser vibrometer is used to emit detection light onto the surface of the metal plate to receive the laser ultrasonic signals excited by the excitation light and convert the intensity of the returned light into a DC voltage signal and output it to the computer. The computer is used to control the movement of the displacement stage and store and process the obtained laser ultrasonic signals;

[0034] Referring to Figures 1 to 3 , the method includes the following steps:

[0035] Step 1: Mount the metal plate stably on the electric displacement stage. Place and start the laser vibrometer on one side of the metal plate. Adjust the position, laser incident angle, and energy output of the laser vibrometer until the laser vibrometer obtains a stable and maximum-amplitude DC voltage signal;

[0036] Step 2: Start the pulsed laser, and make the excitation light and the detection light incident on the same side of the metal plate. Control the electric displacement stage through the computer to perform laser scanning on the surface of the metal plate. The metal plate has two sides. Incident on the same side means that the two beams of light are incident on the same surface of the metal plate rather than on different surfaces;

[0037] Step 3: The computer detects the intensity of the DC voltage signal at each position on the metal plate during the laser scanning process and records the abnormal positions where the intensity of the DC voltage signal is lower than the preset voltage threshold. After the laser scanning is completed, re-laser scan (laser rescan) the vicinity of the above-mentioned abnormal positions until the intensity of the DC voltage signal is higher than the preset voltage threshold; The abnormal positions correspond to bad points; Each position refers to the position where the detection light passes through on the metal plate during the laser scanning; In Figure 3 , the laser scanning position, bad point position, and laser rescan position are shown. Among them, the laser rescan position is at 8 points around the abnormal position corresponding to the bad point, and the step length of the laser rescan is 1 mm.

[0038] Step 4: The computer performs wavelet transform filtering on the laser ultrasonic signals at the positions of the re-laser scan (i.e., laser rescan), and then performs Fourier transform on the time component of the laser ultrasonic signals after the wavelet transform filtering to change the time-domain signal into a frequency-domain signal. Determine the preset bandwidth range before and after the wave peak with the largest amplitude in the spectrum corresponding to the frequency-domain signal as the signal main frequency band to calculate the signal power of the laser ultrasonic signal corresponding to the abnormal position and then obtain the signal-to-noise ratio of the signal power. The signal-to-noise ratio calculation formula is as follows:

[0039]

[0040] Among them, SNR is the signal-to-noise ratio, P signal is the signal power, P noise is the noise power;

[0041] If the signal-to-noise ratio is greater than the preset signal-to-noise ratio threshold, the newly obtained laser ultrasonic signal by re-laser scanning field will replace the original laser ultrasonic signal corresponding to the abnormal position, otherwise return to execute step 3.

[0042] In step 4, the computer performs wavelet transform on the laser ultrasonic signal at the re-scanned position to remove the low-frequency components and reduce the low-frequency noise interference, which is to filter the ultrasonic signal.

[0043] Further, in step 1, the output power of the laser vibrometer is 0 - 100 mW.

[0044] Further, in steps 2 and 3, the laser scanning field obtains matrix data of M×N rows and L columns. M is the number of spatial sampling points in the x direction, N is the number of spatial sampling points in the y direction, and L is the number of time sampling points. The scanning field step length is 5 mm, the re-scanning field step length is 1 mm, and the excitation light spot radius is 1 mm. This technical solution significantly improves the detection accuracy of abnormal positions on the metal plate surface by precisely controlling the step lengths of laser scanning field and re-scanning field. By setting the step length of the original laser scanning field to 5 mm and performing re-scanning field with a 1 mm step after detecting the abnormal position, the signal changes can be captured and analyzed with higher accuracy within a local range, so as to obtain a better-quality ultrasonic signal to replace the ultrasonic signal at the abnormal point position. The purpose of the re-scanning field here is to find a normal point near the abnormal point to replace the abnormal point, so it cannot be too far from the abnormal point. In addition, the precise control of the excitation light spot radius further enhances the signal stability and accuracy, thereby improving the quality of the laser ultrasonic signal, making the calculation of the signal-to-noise ratio and signal update more reliable, and effectively improving the sensitivity and accuracy of fault detection.

[0045] Further, in step 3, the amplitude of the DC signal output by the laser vibrometer reflects the received light return intensity.

[0046] Furthermore, in the step 4, the signal power is the sum of the squared spectral amplitudes within the signal frequency band, the noise power is the sum of the squared spectral amplitudes within the noise frequency band, and the noise frequency band is from 50 MHz to 70 MHz. This technical solution improves the calculation accuracy of the signal-to-noise ratio by clearly distinguishing the processing methods for the signal frequency band and the noise frequency band. The signal power is calculated by summing the squared spectral amplitudes within the signal frequency band, while the noise power is calculated by summing the squared spectral amplitudes within the noise frequency band from 50 MHz to 70 MHz, effectively separating the noise from the useful signal and avoiding the influence of noise interference on the calculation result of the signal-to-noise ratio. This method makes the calculation of the signal power and the noise power more accurate, thereby improving the reliability of the signal-to-noise ratio, and further enhancing the sensitivity of anomaly detection and the accuracy of positioning.

[0047] Furthermore, in the step 4, the preset signal-to-noise ratio threshold is 40 dB. This technical solution further improves the detection accuracy and reliability of the abnormal signal by setting the preset signal-to-noise ratio threshold to 40 dB. The threshold of 40 dB ensures that only signals with a relatively high signal-to-noise ratio are considered valid signals, thus effectively filtering out signals with high noise. This setting helps to ensure that only high-quality signals after optimization and processing are used to replace the original abnormal signals, avoiding the interference of noise on subsequent analysis. In addition, by setting a relatively high signal-to-noise ratio threshold, it can be ensured that the detected abnormal positions are obvious and reliable, thereby improving the accuracy and stability of the overall system in fault detection and positioning.

[0048] Furthermore, the preset voltage threshold is 200 mV. This technical solution helps to ensure that only when the DC voltage signal strength is significantly lower than this threshold is the position considered an abnormal point, thereby reducing the possibility of misjudgment. The threshold setting of 200 mV can effectively distinguish normal signals from abnormal signals, ensuring that the detected abnormal positions are the areas that truly need further analysis. This setting further improves the stability and accuracy of the system, making the steps of re-scanning the field and subsequent signal processing more targeted, avoiding the interference of irrelevant signals, and thus enhancing the efficiency and accuracy of the overall detection process.

[0049] Further, the corresponding range near the abnormal position is less than half of the sweep step length during the first field sweep. By setting the re-sweeping range near the abnormal position to be less than half of the step length during the first field sweep (i.e., less than 2.5 mm), this technical solution effectively improves the detection accuracy in the local area. Such a setting ensures that after the abnormal position is detected, a more detailed re-scan can be performed within a finer spatial range, thereby capturing more subtle signal changes and enhancing the sensitivity of abnormal detection. At the same time, this approach avoids unnecessary extensive re-sweeping, optimizes the detection efficiency and the utilization of computing resources, and further improves the overall detection performance and positioning accuracy.

[0050] Further, the abscissa of the laser ultrasonic signal represents the time component.

[0051] Further, the preset bandwidth is 10 MHz. By setting the preset bandwidth to 10 MHz, this technical solution further optimizes the process of determining the main frequency band of the signal. The 10 MHz bandwidth range helps to accurately capture the signal components around the peak with the largest amplitude in the spectrum, ensures more accurate calculation of the signal power, and reduces the uncertainty in the selection of the frequency range. In addition, the appropriate bandwidth selection balances the signal resolution and the influence of noise, avoiding signal omission or noise interference that may be caused by too wide or too narrow bandwidths, thereby improving the reliability of the signal-to-noise ratio and the accuracy of abnormal detection. This processing method helps to improve the stability and efficiency of the system and ensures the accuracy of the signal analysis results.

[0052] Compared with the prior art, the present invention has the following advantages: By combining the double criteria of the return light intensity (DC signal amplitude) and the signal-to-noise ratio, measurement bad points caused by optical path deviation, surface defects, or environmental interference can be accurately identified. For the bad point area, high-precision re-scanning at the 1 mm level + combined wavelet-Fourier denoising is adopted. By separating the power in the high-frequency noise segment and reconstructing the signal segment, the utilization rate of effective data is improved, and the success rate of abnormal signal repair is increased.

[0053] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the above-mentioned division of each functional unit and module is used as an example. In actual applications, the above functions can be allocated to different functional units and modules as needed, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiments can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit. In addition, the specific names of each functional unit and module are only for the convenience of mutual distinction and do not limit the protection scope of this application. The specific working processes of the units and modules in the above system can refer to the corresponding processes in the foregoing method embodiments and will not be repeated here.

[0054] An embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the following method is implemented:

[0055] a) Control the electric displacement stage through the computer, start the pulsed laser, make the excitation light and the detection light enter on the same side of the metal plate, and perform laser field scanning on the surface of the metal plate;

[0056] b) The computer detects the intensity of the DC voltage signal at each position during the laser field scanning process and records the abnormal positions where the intensity is lower than the preset voltage threshold;

[0057] c) After the laser field scanning is completed, the computer re-performs laser field scanning near the abnormal positions until the intensity of the DC voltage signal at the abnormal positions is higher than the preset voltage threshold;

[0058] d) The computer performs wavelet transform filtering on the laser ultrasonic signal obtained by the re-laser field scanning, and then performs Fourier transform on the laser ultrasonic signal after wavelet transform filtering to obtain a frequency-domain signal;

[0059] e) The computer extracts the preset bandwidth range before and after the wave peak with the largest amplitude in the spectrum from the frequency-domain signal, determines it as the signal main frequency band, and calculates the signal power of the signal main frequency band;

[0060] f) The computer calculates the signal-to-noise ratio according to the signal power. If the signal-to-noise ratio is greater than the preset signal-to-noise ratio threshold, the original laser ultrasonic signal corresponding to the abnormal position is updated and replaced with the laser ultrasonic signal obtained by the re-laser field scanning;

[0061] g) Otherwise, the computer returns to step b) and continues to perform laser field scanning of the abnormal positions.

[0062] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the above-described embodiment methods of the present invention, it can also be completed by a computer program instructing relevant hardware. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-described method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal, and software distribution medium, etc. Of course, there are other ways of readable storage media, such as quantum memory, graphene memory, and so on. It should be noted that the content included in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice within the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0063] The present invention also provides an electronic device. The electronic device according to the embodiment of the present invention includes: one or more processors; a storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the method provided by the present invention as follows:

[0064] a) Control the electric displacement stage, start the pulsed laser, make the excitation light and the probe light incident on the same side of the metal plate, and perform laser scanning on the surface of the metal plate;

[0065] b) Detect the intensity of the DC voltage signal at each position during the laser scanning process, and record the abnormal positions where the intensity is lower than the preset voltage threshold;

[0066] c) After the laser scanning is completed, re-perform laser scanning near the abnormal positions until the intensity of the DC voltage signal at the abnormal positions is higher than the preset voltage threshold;

[0067] d) Perform wavelet transform filtering on the laser ultrasonic signal obtained by the re-laser scanning, and then perform Fourier transform on the laser ultrasonic signal after wavelet transform filtering to obtain a frequency-domain signal;

[0068] e) Extract the preset bandwidth range before and after the peak with the largest amplitude in the spectrum from the frequency-domain signal, determine it as the signal main frequency band, and calculate the signal power of the signal main frequency band;

[0069] f) Calculate the signal-to-noise ratio based on the signal power. If the signal-to-noise ratio is greater than the preset signal-to-noise ratio threshold, update the original laser ultrasonic signal corresponding to the abnormal position and replace it with the laser ultrasonic signal obtained by re-scanning the laser field;

[0070] g) Otherwise, return to step b) and continue the laser field scanning at the abnormal position.

[0071] Next, refer to Figure 4 , which shows a schematic structural diagram of a computer system 800 of an electronic device suitable for implementing the embodiments of the present invention. Figure 4 The shown electronic device is only an example and should not bring any restrictions to the functions and usage scopes of the embodiments of the present invention.

[0072] As Figure 4 shown, the computer system 800 includes a central processing unit (CPU) 801, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 802 or the program loaded from the storage section 808 into the random access memory (RAM) 803. In the RAM 803, various programs and data required for the operation of the computer system 800 are also stored. The CPU 801, ROM 802, and RAM 803 are connected to each other via a bus 804. The input / output (I / O) interface 805 is also connected to the bus 804.

[0073] The following components are connected to the I / O interface 805: an input section 806 including a keyboard, a mouse, etc.; an output section 807 including such as a cathode ray tube (CRT), a liquid crystal display (LCD), etc. and a speaker, etc.; a storage section 808 including a hard disk, etc.; and a communication section 809 including a network interface card such as a LAN card, a modem, etc. The communication section 809 performs communication processing via a network such as the Internet. A drive 810 is also connected to the I / O interface 805 as needed. A removable medium 811, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 810 as needed so that the computer program read from it is installed into the storage section 808 as needed.

[0074] In particular, according to the embodiments disclosed in the present invention, the process described in the above main step diagram can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program codes for executing the method shown in the main step diagram. In the above embodiment, the computer program can be downloaded and installed from the network through the communication part 809, and / or installed from the removable medium 811. When the computer program is executed by the central processing unit 801, the above functions defined in the system of the present invention are executed.

[0075] It should be noted that the computer-readable medium shown in the present invention can be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, the computer-readable storage medium can be any tangible medium that contains or stores a program, and the program can be used by or in combination with an instruction execution system, apparatus, or device. In the present invention, the computer-readable signal medium can include a data signal propagated in a baseband or as part of a carrier wave, which carries computer-readable program codes. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium can also be any computer-readable medium other than the computer-readable storage medium, and the computer-readable medium can send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device. The program codes contained on the computer-readable medium can be transmitted by any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0076] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagram may represent a module, a segment of a program, or a part of code, which contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram or flowchart, as well as the combinations of blocks in the block diagram or flowchart, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0077] The units involved in the embodiments of the present invention can be implemented in software or in hardware. Among them, the names of these units do not constitute a limitation to the units themselves in some cases.

[0078] The above specific embodiments do not constitute a limitation to the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions may occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for automatically identifying bad points of a laser vibrometer based on analysis of retroreflection intensity and signal-to-noise ratio, characterized in that, The method is executed by a detection device, which includes a pulsed laser, an electric displacement stage, a laser vibrometer, and a computer. The pulsed laser is used to emit excitation light onto the surface of the metal plate to excite laser ultrasonic signals. The electric displacement stage fixes and moves the metal plate for laser scanning. The laser vibrometer is used to emit detection light onto the surface of the metal plate to receive the laser ultrasonic signals excited by the excitation light and convert the intensity of the reflected light into a DC voltage signal and output it to the computer. The computer is used to control the movement of the displacement stage and store and process the obtained laser ultrasonic signals; The method includes the following steps: Step 1: Mount the metal plate stably on the electric displacement stage, place and start the laser vibrometer on one side of the metal plate, and adjust the position, laser incident angle, and energy output of the laser vibrometer until the laser vibrometer obtains a stable DC voltage signal with the highest amplitude; Step 2: Start the pulsed laser, make the excitation light and the detection light incident on the same side of the metal plate, and control the electric displacement stage through the computer to perform laser scanning on the surface of the metal plate; Step 3: The computer detects the intensity of the DC voltage signal at each position on the metal plate during the laser scanning process and records the abnormal positions where the intensity of the DC voltage signal is lower than the preset voltage threshold. After the laser scanning is completed, re-scan the vicinity of the above abnormal positions until the intensity of the DC voltage signal is higher than the preset voltage threshold; The abnormal positions correspond to bad points; Each position refers to the position where the detection light passes through on the metal plate during laser scanning; Step 4: The computer performs wavelet transform filtering on the laser ultrasonic signals at the positions of the re-scanned laser, then performs Fourier transform on the time component of the laser ultrasonic signals after wavelet transform filtering to change the time-domain signal into a frequency-domain signal, determines the main signal band as the preset bandwidth range before and after the wave peak with the largest amplitude in the spectrum corresponding to the frequency-domain signal, calculates the signal power of the laser ultrasonic signal corresponding to the abnormal position, and further obtains the signal-to-noise ratio of the signal power. The signal-to-noise ratio calculation formula is as follows: Among them, SNR is the signal-to-noise ratio, P signal is the signal power, P noise is the noise power; If the signal-to-noise ratio is greater than the preset signal-to-noise ratio threshold, replace the original laser ultrasonic signal corresponding to the abnormal position with the newly obtained laser ultrasonic signal from the re-scanned laser, otherwise return to execute Step 3.

2. The method according to claim 1, wherein: In Step 1, the output power of the laser vibrometer is 0 - 100 mW.

3. The method according to claim 1, wherein: In Steps 2 and 3, the laser scanning obtains matrix data of M×N rows and L columns. M is the number of spatial sampling points in the x direction, N is the number of spatial sampling points in the y direction, L is the number of time sampling points, the scanning step length is 5 mm, the re-scanning step length is 1 mm, and the radius of the excitation light spot is 1 mm.

4. The method according to claim 1, characterized in that: In Step 3, the amplitude of the DC signal output by the laser vibrometer reflects the intensity of the received reflected light.

5. The method according to claim 1, characterized in that: In Step 4, the signal power is the sum of the squares of the spectral amplitudes within the signal frequency band, the noise power is the sum of the squares of the spectral amplitudes within the noise frequency band, and the noise frequency band is from 50 MHz to 70 MHz.

6. The method according to claim 1, characterized in that: In Step 4, the preset signal-to-noise ratio threshold is 40 dB.

7. The method according to claim 1, wherein: The preset voltage threshold is 200 mv.

8. The method according to claim 1, characterized in that: The corresponding range near the abnormal position is less than half of the sweep field step length during the first sweep field.

9. The method according to claim 1, wherein: The abscissa of the laser ultrasonic signal represents the time component.

10. The method according to claim 1, characterized in that: The preset bandwidth is 10 MHz.

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