CN113390963B - Laser shock peening quality on-line monitoring method based on time window energy attenuation coefficient - Google Patents
Laser shock peening quality on-line monitoring method based on time window energy attenuation coefficient Download PDFInfo
- Publication number
- CN113390963B CN113390963B CN202110513382.8A CN202110513382A CN113390963B CN 113390963 B CN113390963 B CN 113390963B CN 202110513382 A CN202110513382 A CN 202110513382A CN 113390963 B CN113390963 B CN 113390963B
- Authority
- CN
- China
- Prior art keywords
- acoustic emission
- signal
- laser shock
- energy
- emission signals
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/04—Analysing solids
- G01N29/045—Analysing solids by imparting shocks to the workpiece and detecting the vibrations or the acoustic waves caused by the shocks
-
- C—CHEMISTRY; METALLURGY
- C21—METALLURGY OF IRON
- C21D—MODIFYING THE PHYSICAL STRUCTURE OF FERROUS METALS; GENERAL DEVICES FOR HEAT TREATMENT OF FERROUS OR NON-FERROUS METALS OR ALLOYS; MAKING METAL MALLEABLE, e.g. BY DECARBURISATION OR TEMPERING
- C21D10/00—Modifying the physical properties by methods other than heat treatment or deformation
- C21D10/005—Modifying the physical properties by methods other than heat treatment or deformation by laser shock processing
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/04—Analysing solids
- G01N29/11—Analysing solids by measuring attenuation of acoustic waves
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/04—Analysing solids
- G01N29/12—Analysing solids by measuring frequency or resonance of acoustic waves
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2291/00—Indexing codes associated with group G01N29/00
- G01N2291/02—Indexing codes associated with the analysed material
- G01N2291/023—Solids
- G01N2291/0234—Metals, e.g. steel
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P10/00—Technologies related to metal processing
- Y02P10/20—Recycling
Landscapes
- Physics & Mathematics (AREA)
- Chemical & Material Sciences (AREA)
- Pathology (AREA)
- Health & Medical Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Acoustics & Sound (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Optics & Photonics (AREA)
- Thermal Sciences (AREA)
- Crystallography & Structural Chemistry (AREA)
- Mechanical Engineering (AREA)
- Materials Engineering (AREA)
- Metallurgy (AREA)
- Organic Chemistry (AREA)
- Investigating Or Analyzing Materials By The Use Of Ultrasonic Waves (AREA)
Abstract
The invention discloses a laser shock peening quality on-line monitoring method based on time window energy attenuation coefficient, which utilizes dynamic acoustic emission signals generated in the laser shock processing process to fuse 2-channel acoustic emission signals which are synchronously collected and take arithmetic mean value; on the other hand, by means of the acoustic signal attenuation theory, time domain windowing is carried out on the acoustic emission signal, window signal energy is calculated, and an exponential attenuation function y = ae is adopted bx The acoustic emission signal is fitted, the exponential decay rule of the acoustic emission signal in a workpiece material can be revealed, the physical significance of the acoustic emission signal is improved, the fitting parameter b is extracted as a characteristic parameter, the acoustic emission signal has strong representation capability and robustness, and the accuracy and stability in actual production application are improved. The method has the advantages of simple and rapid characteristic extraction, good state response, stability, reliability, lower cost and strong engineering practicability, and provides an efficient technical realization way for realizing the online monitoring of the laser shock peening quality.
Description
Technical Field
The invention belongs to the technical field of laser shock peening and intelligent detection, and particularly relates to a laser shock peening quality online monitoring method based on a time window energy attenuation coefficient.
Background
The Laser Shock Peening (LSP) is a novel process technology for metal surface strengthening. The laser shock strengthening process technology has the outstanding advantages of no contact, no heat influence area, good strengthening effect, strong controllability and the like compared with the traditional surface modification technologies such as shot blasting, rolling and the like, and has huge application prospects in the fields of aerospace, marine ships, petrochemical engineering and the like.
In the laser shock peening process, factors such as laser energy, spot diameter, laser shock frequency and the like all influence the laser shock peening quality. The quality of laser shock peening can be measured by the magnitude of residual stress on the surface of a machined workpiece, however, the existing residual stress detection method mainly adopts a series of off-line destructive detection methods, such as: in the engineering stage, factors such as processing environment, efficiency, workpiece cost and the like are considered, and the traditional detection methods have great defects. Therefore, in order to realize the industrial application and actual production of the laser shock peening technology, the online real-time nondestructive monitoring technology of the process technology must be developed.
Aiming at the existing laser shock peening on-line monitoring method, the Chinese patent No. CN 108956782A discloses a laser shock peening on-line detection method based on acoustic frequency, and realizes the on-line detection of the laser shock effect by detecting and comparing the acoustic frequency signal in the laser shock process and the acoustic frequency signal in a signal library in real time. Chinese patent No. CN 101482542A discloses an on-line detection method and device based on shock wave waveform characteristics, which compares the amplitude and pulse width of shock waves propagating in the air with standard amplitude and pulse width, thereby realizing on-line detection of laser shock peening quality.
In the dynamic laser shock peening process, the generated acoustic emission signal is gradually attenuated along with the phenomena of absorption, refraction, reflection and the like of the workpiece material structure in the propagation process, so that the dynamic change information contained in the acoustic emission signal can reflect the change of the processed workpiece material structure. The existing online monitoring method does not theoretically analyze the dynamic change relationship between an acoustic emission signal and a processed workpiece tissue, extracts the characteristics capable of reflecting the dynamic attenuation of the acoustic emission signal to characterize the laser shock peening quality, but directly extracts the characteristics such as the amplitude, the frequency and the like of the acoustic signal generated in the laser shock process, so that the online monitoring method is easily interfered by noise in the online monitoring process, has low reliability and accuracy, has weak robustness and is difficult to popularize and apply in actual production.
Disclosure of Invention
The invention aims to overcome the defects and provide an online monitoring method for laser shock peening quality based on a time window energy attenuation coefficient. According to the method, the acoustic emission signals generated in the laser shock processing process are fully utilized, time domain windowing processing is carried out on the acoustic emission signals by means of an acoustic signal attenuation theory, window signal energy characteristics are extracted and fitted by adopting an exponential function, and laser shock residual compressive stress is represented on the basis of the fitting parameter b.
In order to achieve the purpose, the invention adopts the technical scheme that:
the laser shock peening quality on-line monitoring method based on the time window energy attenuation coefficient comprises the following steps:
the method comprises the following steps: sequentially connecting acoustic emission signal acquisition equipment such as an acoustic emission piezoelectric sensor, a preamplifier, an A/D data acquisition card, an industrial personal computer and the like, closely attaching a ceramic surface at the acquisition end of the acoustic emission piezoelectric sensor to the surface of the metal to be processed through an industrial coupling agent, and keeping a set distance from the center of an impact area; in the laser impact processing process, 2 acoustic emission sensors which are arranged at two sides of an impact point and are equidistant to a laser processing center complete synchronous real-time acquisition of acoustic emission signals;
step two: carrying out noise reduction treatment on the acoustic emission signal by adopting a db4 wavelet hard threshold noise reduction method so as to eliminate low-frequency noise interference of the acoustic emission signal in the acquisition process and obtain a noise-reduced acoustic emission signal with a high signal-to-noise ratio;
step three: fusing the acoustic emission signals subjected to the noise reduction of the double channels, and taking an arithmetic mean value to obtain acoustic emission signals X (t) subjected to mean value fusion;
step four: windowing the two-channel mean value fusion acoustic emission signal X (t) in a time domain, wherein the size of a window is 1000 sampling points, the windows are not overlapped, 10 windows are divided in total, and a windowed window signal X is obtained n (t), wherein n =1,2,3 8230;, 10;
step five: from the time domain of the signalEnergy calculation formula for calculating each time domain window signal X n (t) energy value and using an exponential function y = ae bx And fitting the energy of 10 time windows to obtain a fitted attenuation parameter b, representing the residual compressive stress on the surface of the workpiece in the laser shock peening process, and monitoring the peening quality in real time.
The invention is further improved in that in the step one, a sensor used for collecting the acoustic emission signals in the laser shock process is an RS-2A type acoustic emission piezoelectric sensor, the sensitivity of the sensor is 80dB +/-5 dB, the frequency response range is 50 Hz-400 kHz, the amplification gain of a preamplifier is set to be 20dB, the sampling frequency of an A/D data acquisition card is set to be 3MHz, and the data acquisition card is used for filtering, collecting and storing the acoustic emission signals.
The invention has the further improvement that in the second step, db4 wavelet is adopted to perform wavelet de-noising on the acoustic emission signal, specifically, db4 wavelet is used to perform 6-layer wavelet decomposition on the acoustic emission signal, the frequency range corresponding to the first node (6, 0) at the bottommost layer is 0-23437.5 Hz, a threshold value is set, wavelet coefficients larger than the threshold value in the wavelet coefficients corresponding to the nodes (6, 0) are reserved, the wavelet coefficients smaller than the threshold value are set to be 0, and finally, signal reconstruction is performed on each decomposition layer in sequence, so that the wavelet de-noising acoustic emission signal is obtained.
The further improvement of the invention is that in the third step, in order to improve the signal anti-interference capability, the 2 channels of fused acoustic emission signals X (t) are obtained by fusing and averaging the noise reduction acoustic emission signals at the same laser impact point synchronously acquired by the 2 channels.
The further improvement of the invention is that in the fourth step, the 2-channel fusion acoustic emission signal X (t) is subjected to windowing treatment in the time domain, the window size is 1000 sampling points, no overlapping exists between the windows, 10 windows are divided in total, and the windowed window signal X is obtained n (t) wherein n =1,2,3 8230;, 10.
The invention is further improved in that in step five, a formula is calculated according to the signal time domain energy
Where n is the number of signal samples, y k The amplitude of the corresponding sampling point is obtained; extracting each time domain window signal X n Energy value E of (t) n (t) and using an exponential function y = ae bx And fitting the energy of 10 time windows to obtain a fitted attenuation parameter b.
The further improvement of the invention is that in the fifth step, based on the attenuation parameter b after the time window energy index attenuation fitting of the laser shock acoustic emission signal, the residual compressive stress on the surface of the workpiece in the laser shock strengthening process is represented, and the strengthening quality is monitored in real time.
Compared with the prior art, the method fully utilizes the dynamic acoustic emission signals generated in the laser impact processing process, and fuses the 2-channel acoustic emission signals which are synchronously acquired to obtain an arithmetic mean value, so that the anti-interference capability of the acoustic emission signals is improved; on the other hand, the invention extracts the energy characteristic which can reflect the dynamic change process of the acoustic emission signal most after the time domain windowing processing is carried out on the acoustic emission signal by means of the acoustic signal attenuation theory and adopts the exponential function y = ae bx The method is fitted, and the fitting parameter b is adopted to represent the laser shock residual compressive stress, so that the method is simple and rapid, good in real-time performance, high in robustness and strong in engineering practicability.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a schematic diagram illustrating installation of an acoustic emission piezoelectric sensor and acquisition of an acoustic emission signal inside a material in the laser shock peening process in the embodiment of the invention;
FIG. 3 is a view showing the shape and size of a metal material to be impact-worked in the embodiment of the present invention; wherein a is a front view, b is a side view, and c is a top view;
FIG. 4 is a time domain waveform before and after denoising an acoustic emission signal using a wavelet threshold in an embodiment of the present invention; wherein a is a time domain image before denoising, and b is a time domain image after denoising;
FIG. 5 is a magnitude spectrogram before and after denoising an acoustic emission signal by using a wavelet threshold in an embodiment of the present invention; wherein a is a denoised amplitude spectrum, and b is a denoised amplitude spectrum;
FIG. 6 is a time domain windowing diagram of an acoustic emission signal after 2 channels are fused in the embodiment of the present invention;
FIG. 7 is a bar graph of window energy of acoustic emission signals at different impact times in an embodiment of the present invention;
FIG. 8 is a fitting graph of window energy indexes of acoustic emission signals at different impact times according to an embodiment of the present invention;
FIG. 9 is a graph showing the relationship between the exponential fitting parameter b and the variation of the laser shock frequency in the embodiment of the present invention;
description of reference numerals:
1-an industrial personal computer, 2-an/D data acquisition card, 3-a preamplifier, 4-an acoustic emission piezoelectric sensor, 5-a water constraint layer, 6-an energy absorption layer, 7-a metal plate to be processed and 8-a laser impact point.
Detailed Description
In order to make the technical problems, technical schemes and data analysis methods solved by the present invention clearer, the present invention is further described with reference to the accompanying drawings and embodiments.
The acoustic emission signal acquisition technology is the prior art, and only key equipment and model parameters of an acquisition system are briefly described here. In the laser shock strengthening process, 2 RS-2A acoustic emission piezoelectric sensors 4 are equidistantly arranged on two sides of a laser shock point, the sensitivity of the sensors is 80dB +/-5 dB, the frequency response range is 50 Hz-400 kHz, and the sensors are used for collecting acoustic emission signals in real time. And the acoustic emission signal acquisition equipment such as a preamplifier 3, an A/D data acquisition card 2, an industrial personal computer 1 and the like are sequentially connected, wherein the amplification gain of the preamplifier 3 is set to be 20dB and is used for signal amplification, analog-to-digital conversion and noise reduction, the A/D data acquisition card 2 finishes data acquisition, the sampling frequency is set to be 3MHz, and the industrial personal computer 1 finishes data storage and analysis.
Referring to fig. 1, the laser shock peening quality online monitoring method based on the time window energy attenuation coefficient provided by the invention comprises the following steps:
firstly, acoustic emission signal acquisition equipment such as an acoustic emission piezoelectric sensor, a preamplifier, an A/D data acquisition card and an industrial personal computer are sequentially connected, and the ceramic surface at the acquisition end of the acoustic emission piezoelectric sensor is tightly attached to the surface of the metal to be processed through an industrial coupling agent and keeps a certain distance from the center of an impact area; in the laser impact processing process, 2 acoustic emission sensors which are positioned on two sides of an impact point and are equidistant to a laser processing center complete synchronous real-time acquisition of acoustic emission signals; fig. 2 is a schematic connection diagram of a metal workpiece to be processed and an acoustic emission signal acquisition system in a laser shock peening process.
And secondly, acquiring real-time acoustic emission signals generated in the laser shock processing process at a sampling rate of 3MHz, in order to eliminate noise interference in the acoustic emission signal acquisition process, improve the signal-to-noise ratio of the signals and obtain noise reduction acoustic emission signals without low-frequency noise interference, performing wavelet denoising on the acoustic emission signals by adopting db4 wavelets, specifically, performing 6-layer wavelet decomposition on the acoustic emission signals by using db4 wavelets, setting corresponding threshold values for 0-23437.5 Hz of the frequency band range corresponding to the first node (6, 0) at the bottommost layer, reserving the wavelet coefficients larger than the threshold values in the wavelet coefficients corresponding to the nodes (6, 0), setting the wavelet coefficients smaller than the threshold values to be 0, and finally completing signal reconstruction on each decomposition layer in sequence so as to obtain the wavelet noise reduction acoustic emission signals.
And step three, in order to improve the signal anti-interference capability, fusing and averaging the noise reduction acoustic emission signals at the same laser impact point synchronously acquired by the 2 channels obtained in the step two, thereby obtaining the acoustic emission signal X (t) after the 2 channels are fused.
Step four, windowing the 2-channel fusion acoustic emission signal X (t) obtained in the step three in the time domain, wherein the window size is 1000 sampling points, the windows are not overlapped, 10 windows are divided in total, and the windowed window signal X is obtained n (t), wherein n =1,2,3 8230;, 10;
step five, according to the signal time domain energy calculation formula
Where n is the number of signal samples, y k The amplitude of the corresponding sampling point is obtained; extracting each time domain window signal X obtained in the fourth step n Energy value E of (t) n (t) and using an exponential functiony＝ae bx Fitting the energy of 10 time windows to obtain a fitted attenuation parameter b, representing the residual compressive stress on the surface of the workpiece in the laser shock peening process, and monitoring the peening quality in real time.
Example (b):
fig. 2 is a schematic view showing the installation and connection of the metal workpiece to be impacted and the acoustic emission collection system in this embodiment. In the embodiment, acoustic emission signal acquisition equipment such as an acoustic emission piezoelectric sensor, a preamplifier, an A/D data acquisition card and an industrial personal computer are sequentially connected, and acquisition ends of 2 acoustic emission sensors of the same type are equidistantly installed on two sides of a laser impact point through an industrial coupling agent to finish real-time synchronous acquisition of acoustic emission signals, wherein the distance between the acquisition ends and the impact center is 60mm, and the sampling rate is set to be 3MHz. The laser impact process parameters adopted in this embodiment are as follows: the single pulse laser energy is 3J, the diameter of a light spot is 3mm, the restraint layer 5 is stable flowing water, and the energy absorption layer 6 adopts a black adhesive tape. In the embodiment, the metal workpiece to be processed by impact is impacted by single points for 1 to 3 times respectively.
Fig. 3 is a schematic diagram showing the shape and size of the metal plate to be processed in this embodiment, wherein (a) is a front view, (b) is a side view, and (c) is a top view. The metal plate used in the examples was square, 300mm long, 50mm wide and 4mm thick.
In the embodiment, short-pulse and high-power-density laser beams emitted by a laser penetrate through the water restraint layer 5 and then irradiate the to-be-impacted area 8, the energy absorption layer black adhesive tape 6 adhered to the to-be-impacted area absorbs laser energy and is rapidly gasified to generate high-temperature and high-pressure plasma, the high-temperature and high-pressure plasma is propagated to the inside of a workpiece under the restraint of the water restraint layer to excite an internal elastic wave signal, and the internal elastic wave signal is collected by acoustic emission sensors arranged on two sides of an impact point and stored in an industrial personal computer. And according to the second step of the invention, the db4 wavelet hard threshold denoising processing of the original acoustic emission signal is completed, as shown in fig. 4, a time domain waveform diagram of the acoustic emission signal after the original acoustic emission signal and the db4 wavelet hard threshold denoising processing is shown, and as shown in fig. 5, a frequency domain amplitude diagram of the original acoustic emission signal and the db4 wavelet hard threshold denoising processing is shown. According to the third step and the fourth step of the invention, 2-way of noise reduction acoustic emission signals is completedAnd (3) performing channel fusion and finishing windowing processing of the fusion acoustic emission signal in a time domain, wherein a 2-channel fusion acoustic emission signal time domain windowing graph is shown in fig. 6. According to a calculation formula of time domain signal energy in the fifth step of the invention, calculating energy values of time domain windows of 1,2 and 3 times of laser impact, and using an exponential function y = ae bx And respectively performing fitting, wherein the energy of 10 windows corresponds to 1,2 and 3 impacts respectively as shown in table 1, the energy histograms of 10 windows correspond to 1,2 and 3 impact acoustic emission signals as shown in fig. 7, and the energy exponential fitting curve graphs of 1,2 and 3 impact windows as shown in fig. 8.
Table 1 the energy of 10 time domain windows corresponding to 1 st, 2 nd and 3 rd laser impacts
In the present embodiment, the exponential function y = ae bx And respectively fitting the window energy of the denoising acoustic emission signal of the laser shock for 1,2 and 3 times to obtain a fitting coefficient b reflecting the attenuation degree of the acoustic emission signal, and combining the change relation between the laser shock times and the residual stress to establish the change relation between the fitting coefficient b and the residual stress. The fitting coefficient b is shown in table 2 for different laser shock times, and is shown in fig. 9 as a graph of the variation of the fitting coefficient b with the laser shock times.
TABLE 2 fitting coefficient as a function of laser shock times
According to the experiment and the embodiment, the dynamic acoustic emission signals generated in the laser shock processing process are fully analyzed and utilized, and the 2-channel acoustic emission signals which are synchronously collected are fused to obtain an arithmetic mean value, so that the anti-interference capability of the acoustic emission signals is improved; on the other hand, the invention extracts the energy characteristic which can reflect the dynamic change process of the acoustic emission signal most and adopts the index after the time domain windowing processing is carried out on the acoustic emission signal by means of the acoustic signal attenuation theoryFunction y = ae bx The method is fitted, and the fitting parameter b is adopted to represent the laser shock residual compressive stress, so that the method is simple and rapid, good in real-time performance, high in robustness and strong in engineering practicability.
Claims (1)
1. The laser shock peening quality on-line monitoring method based on the time window energy attenuation coefficient is characterized by comprising the following steps of:
the method comprises the following steps: sequentially connecting acoustic emission signal acquisition equipment such as an acoustic emission piezoelectric sensor, a preamplifier, an A/D data acquisition card and an industrial personal computer, closely attaching a ceramic surface at an acquisition end of the acoustic emission piezoelectric sensor to the surface of the metal to be processed through an industrial coupling agent, and keeping a set distance from the center of an impact area; in the laser shock processing process, 2 acoustic emission sensors which are arranged at two sides of a shock point and are equidistant to a laser processing center complete synchronous real-time acquisition of acoustic emission signals; the sensor for collecting the acoustic emission signals in the laser shock process is an RS-2A acoustic emission piezoelectric sensor, the sensitivity of the sensor is 80dB +/-5 dB, the frequency response range is 50 Hz-400 kHz, the amplification gain of a preamplifier is set to be 20dB, the sampling frequency of an A/D data acquisition card is set to be 3MHz, and the data acquisition card is used for filtering, collecting and storing the acoustic emission signals;
step two: carrying out noise reduction processing on the acoustic emission signals by adopting a db4 wavelet hard threshold noise reduction method so as to eliminate low-frequency noise interference of the acoustic emission signals in the acquisition process and obtain noise reduction acoustic emission signals with high signal-to-noise ratio; performing wavelet denoising on the acoustic emission signals by adopting db4 wavelets, specifically performing 6-layer wavelet decomposition on the acoustic emission signals by using the db4 wavelets, setting a threshold value in a frequency band range corresponding to a first node (6, 0) at the bottommost layer, reserving wavelet coefficients larger than the threshold value in the wavelet coefficients corresponding to the nodes (6, 0), setting the wavelet coefficients smaller than the threshold value to be 0, and finally sequentially performing signal reconstruction on each decomposition layer to obtain the wavelet denoising acoustic emission signals;
step three: in order to improve the signal anti-interference capability, the fusion mean value of the noise reduction acoustic emission signals at the same laser impact point synchronously acquired by 2 channels is obtained, so that 2-channel fusion acoustic emission signals X (t) are obtained;
step four: windowing the two-channel mean value fusion acoustic emission signal X (t) in a time domain, wherein the size of a window is 1000 sampling points, the windows are not overlapped, 10 windows are divided in total, and a windowed window signal X is obtained n (t), wherein n =1,2,3 8230;, 10;
step five: calculating each time domain window signal X according to a signal time domain energy calculation formula n (t) energy value and using an exponential function y = ae bx Fitting the energy of 10 time windows to obtain a fitted attenuation parameter b, representing the residual compressive stress on the surface of the workpiece in the laser shock peening process, and monitoring the peening quality in real time; according to the signal time domain energy calculation formula
Where n is the number of signal samples, y k The amplitude of the corresponding sampling point is obtained; extracting each time domain window signal X n Energy value E of (t) n (t) and using an exponential function y = ae bx Fitting the energy of 10 time windows to obtain a fitted attenuation parameter b;
and characterizing the residual compressive stress on the surface of the workpiece in the laser shock peening process based on the attenuation parameter b after the laser shock acoustic emission signal time window energy exponential attenuation fitting, and monitoring the peening quality in real time.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110513382.8A CN113390963B (en) | 2021-05-11 | 2021-05-11 | Laser shock peening quality on-line monitoring method based on time window energy attenuation coefficient |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110513382.8A CN113390963B (en) | 2021-05-11 | 2021-05-11 | Laser shock peening quality on-line monitoring method based on time window energy attenuation coefficient |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113390963A CN113390963A (en) | 2021-09-14 |
| CN113390963B true CN113390963B (en) | 2023-03-31 |
Family
ID=77616791
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110513382.8A Active CN113390963B (en) | 2021-05-11 | 2021-05-11 | Laser shock peening quality on-line monitoring method based on time window energy attenuation coefficient |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113390963B (en) |
Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6914215B2 (en) * | 2003-06-27 | 2005-07-05 | General Electric Company | Real time laser shock peening quality assurance by natural frequency analysis |
| US8222567B2 (en) * | 2010-05-12 | 2012-07-17 | General Electric Company | System and method for laser shock peening |
| CN103143126B (en) * | 2013-04-03 | 2015-11-18 | 南京大学 | The method that the non-linear HIFU sound field of biological tissue is determined |
| CN104347068B (en) * | 2013-08-08 | 2020-05-22 | 索尼公司 | Audio signal processing device and method and monitoring system |
| CN106814402B (en) * | 2016-12-22 | 2019-08-23 | 中石化石油工程技术服务有限公司 | Transient electromagnetic signal Prestack Noise Suppression Methods |
| CN107462635A (en) * | 2017-09-13 | 2017-12-12 | 上海海事大学 | A kind of effect of vibration stress relief online rating system and method based on more acoustic emission sensor information fusions |
| CN110715981B (en) * | 2018-07-13 | 2021-09-24 | 中国科学院沈阳自动化研究所 | Laser shock peening on-line detection method and device based on acoustic emission signals |
-
2021
- 2021-05-11 CN CN202110513382.8A patent/CN113390963B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN113390963A (en) | 2021-09-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Michaels et al. | Detection of structural damage from the local temporal coherence of diffuse ultrasonic signals | |
| CN110879254B (en) | Steel rail crack acoustic emission signal detection method based on improved least square generation type countermeasure network | |
| Shi et al. | Non-destructive testing of full-length bonded rock bolts based on HHT signal analysis | |
| CN110018517B (en) | Multi-scale ground micro-seismic reverse-time interference positioning method | |
| CN110967409A (en) | Method for extracting and identifying original data features based on multi-channel ultrasonic flaw detection | |
| CN109649432B (en) | System and method for monitoring integrity of steel rail of cloud platform based on guided wave technology | |
| CN111487315A (en) | Audio frequency nondestructive testing method for tunnel lining thickness and void | |
| CN107678064B (en) | Real-time extraction method for sound wave time difference | |
| CN110286155B (en) | Damage detection method and system for multilayer composite material | |
| Zuo et al. | Noise suppression method of microseismic signal based on complementary ensemble empirical mode decomposition and wavelet packet threshold | |
| Chen et al. | A novel method for enhanced demodulation of bearing fault signals based on acoustic metamaterials | |
| CN113390963B (en) | Laser shock peening quality on-line monitoring method based on time window energy attenuation coefficient | |
| CN113533510B (en) | Rail fatigue micro-crack identification method and device | |
| He et al. | Quantitative detection of surface defect using laser-generated Rayleigh wave with broadband local wavenumber estimation | |
| CN110412129A (en) | A kind of microscopic defect ultrasound detection signal processing method considering surface roughness | |
| CN101126744A (en) | Ceramic carrier embrittlement detection method in ternary catalytic converter assembly | |
| Yang et al. | Feature extraction of ultrasonic guided wave weld detection based on group sparse wavelet transform with tunable Q-factor | |
| CN113091973B (en) | Laser shock peening real-time monitoring method based on internal elastic wave nonlinear characteristics | |
| Zhang et al. | Electromagnetic ultrasonic signal processing and imaging for debonding detection of bonded structures | |
| CN113569799B (en) | Method for extracting characteristics of honeycomb structure air-coupled ultrasonic signals | |
| CN113340493B (en) | Laser impact strengthening quality on-line monitoring method based on modal acoustic emission spectrum ratio | |
| CN104502968B (en) | Controlled source geological data detection method based on threshold value multistage median filtering | |
| CN113340494B (en) | Laser shock strengthening quality on-line monitoring method based on harmonic wavelet frequency band energy | |
| Bose et al. | Acoustic emission signal analysis and event extraction through tuned wavelet packet transform and continuous wavelet transform while tensile testing the AA 2219 coupon | |
| CN113340995A (en) | Acoustic emission signal frequency band selection method for real-time detection of laser shock peening defects |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |