CN113340997A - Laser shock peening defect online detection method based on acoustic emission dual-channel range - Google Patents
Laser shock peening defect online detection method based on acoustic emission dual-channel range Download PDFInfo
- Publication number
- CN113340997A CN113340997A CN202110525309.2A CN202110525309A CN113340997A CN 113340997 A CN113340997 A CN 113340997A CN 202110525309 A CN202110525309 A CN 202110525309A CN 113340997 A CN113340997 A CN 113340997A
- Authority
- CN
- China
- Prior art keywords
- defect
- acoustic emission
- shock peening
- laser shock
- plate
- 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.)
- Granted
Links
- 230000007547 defect Effects 0.000 title claims abstract description 133
- 230000035939 shock Effects 0.000 title claims abstract description 70
- 238000001514 detection method Methods 0.000 title claims abstract description 49
- 238000000034 method Methods 0.000 claims abstract description 32
- 230000004927 fusion Effects 0.000 claims abstract description 20
- 230000008569 process Effects 0.000 claims abstract description 17
- 239000000463 material Substances 0.000 claims description 19
- 238000005070 sampling Methods 0.000 claims description 19
- 238000012545 processing Methods 0.000 claims description 14
- 238000004458 analytical method Methods 0.000 claims description 13
- 238000001914 filtration Methods 0.000 claims description 10
- 239000000523 sample Substances 0.000 claims description 9
- 230000002950 deficient Effects 0.000 claims description 8
- 230000003595 spectral effect Effects 0.000 claims description 6
- 238000010183 spectrum analysis Methods 0.000 claims description 6
- 238000012360 testing method Methods 0.000 claims description 6
- BTCSSZJGUNDROE-UHFFFAOYSA-N gamma-aminobutyric acid Chemical compound NCCCC(O)=O BTCSSZJGUNDROE-UHFFFAOYSA-N 0.000 claims description 5
- 238000006243 chemical reaction Methods 0.000 claims description 4
- 238000004364 calculation method Methods 0.000 claims description 3
- 229910052779 Neodymium Inorganic materials 0.000 claims description 2
- 230000008859 change Effects 0.000 claims description 2
- 230000002708 enhancing effect Effects 0.000 claims description 2
- 239000011521 glass Substances 0.000 claims description 2
- 230000010354 integration Effects 0.000 claims description 2
- QEFYFXOXNSNQGX-UHFFFAOYSA-N neodymium atom Chemical compound [Nd] QEFYFXOXNSNQGX-UHFFFAOYSA-N 0.000 claims description 2
- 230000009466 transformation Effects 0.000 claims description 2
- 238000012512 characterization method Methods 0.000 claims 1
- 238000005516 engineering process Methods 0.000 abstract description 11
- 238000005728 strengthening Methods 0.000 description 14
- 238000010586 diagram Methods 0.000 description 9
- 239000010410 layer Substances 0.000 description 9
- 230000006872 improvement Effects 0.000 description 8
- 238000010521 absorption reaction Methods 0.000 description 5
- 230000000694 effects Effects 0.000 description 5
- 239000002390 adhesive tape Substances 0.000 description 4
- 230000005284 excitation Effects 0.000 description 4
- 229910052751 metal Inorganic materials 0.000 description 3
- 239000002184 metal Substances 0.000 description 3
- 239000007769 metal material Substances 0.000 description 3
- 238000001228 spectrum Methods 0.000 description 3
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 3
- 238000002474 experimental method Methods 0.000 description 2
- 238000003754 machining Methods 0.000 description 2
- 238000009659 non-destructive testing Methods 0.000 description 2
- 230000002035 prolonged effect Effects 0.000 description 2
- 238000011897 real-time detection Methods 0.000 description 2
- 238000004381 surface treatment Methods 0.000 description 2
- 230000009471 action Effects 0.000 description 1
- 230000004888 barrier function Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000006835 compression Effects 0.000 description 1
- 238000007906 compression Methods 0.000 description 1
- 239000007822 coupling agent Substances 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000009977 dual effect Effects 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 230000003631 expected effect Effects 0.000 description 1
- 239000003302 ferromagnetic material Substances 0.000 description 1
- 230000006698 induction Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 239000011241 protective layer Substances 0.000 description 1
- 238000004451 qualitative analysis Methods 0.000 description 1
- 238000004445 quantitative analysis Methods 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
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
- G01N29/14—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 using acoustic emission techniques
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/1702—Systems in which incident light is modified in accordance with the properties of the material investigated with opto-acoustic detection, e.g. for gases or analysing solids
-
- 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
- G01N29/44—Processing the detected response signal, e.g. electronic circuits specially adapted therefor
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/14—Fourier, Walsh or analogous domain transformations, e.g. Laplace, Hilbert, Karhunen-Loeve, transforms
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/1702—Systems in which incident light is modified in accordance with the properties of the material investigated with opto-acoustic detection, e.g. for gases or analysing solids
- G01N2021/1706—Systems in which incident light is modified in accordance with the properties of the material investigated with opto-acoustic detection, e.g. for gases or analysing solids in solids
-
- 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
Abstract
The invention discloses an online detection method for a laser shock peening defect based on an acoustic emission double-channel range, which realizes the combination of a laser shock peening process and a defect detection process, wherein an online defect detection system adopts an acoustic emission technology and can more clearly detect a tiny defect in a plate. After the acoustic emission signals are transmitted and analyzed in the plate, sensor signals at different positions are subjected to range fusion, so that the fused signal characteristics can represent defect information more completely and clearly, and the accuracy of defect detection is improved. The method provided by the invention has the advantages of simple algorithm, high feature discrimination, easy explanation, high robustness and strong engineering applicability, and provides an effective implementation way for realizing the on-line detection of the defects in the laser shock peening process.
Description
Technical Field
The invention belongs to the field of laser shock peening, and particularly relates to an online detection method for a laser shock peening defect based on acoustic emission dual-channel range.
Background
Laser shock peening is a novel surface treatment technology for strengthening a metal material by using shock waves generated by high-energy pulse laser induction. The technical principle is that high-energy pulse laser penetrates through a transparent constraint layer and irradiates on metal coated with an absorption protection layer, and under the limitation of the constraint layer, high-temperature and high-pressure plasma clusters generated after the absorption protection layer absorbs laser energy propagate high-pressure shock waves to the interior of a material, so that the surface of the material is modified, and various physical and chemical properties of the metal material are enhanced. Compared with other traditional surface treatment processes, the laser shock peening has the characteristics of good controllability, obvious strengthening effect and the like.
In actual engineering, for a defect-free plate, a good strengthening effect can be achieved after laser shock strengthening, and the service life of the part is greatly prolonged. However, through experimental comparison, after laser shock strengthening is performed on a defective plate, the service life of the part is slightly prolonged, and the expected effect can be achieved only after post-treatment or strengthening treatment again. At present, in laser shock peening, a defective plate and a non-defective plate cannot be effectively distinguished, so that the plate after laser shock has a good and uneven machining effect, and a certain barrier effect is generated on the popularization and application of a laser shock peening technology. Therefore, in order to promote the development of the laser shock peening technology, the problem of online detection of defects in the laser shock process needs to be solved.
Chinese patent CN102680580A proposes an acoustic emission detection method for a folded coil, which arranges the folded coil above the detection area, utilizes the excitation voltage of energy focusing to generate high-energy eddy current on the detection area, and excites the acoustic emission signal after the interaction between the characteristics of ferromagnetic material and the defect, thereby realizing the nondestructive detection and evaluation of the defect. Chinese patent CN103760243A proposes a microcrack nondestructive testing device and method, which combines ultrasonic technology and acoustic emission technology, utilizes an ultrasonic probe to generate an excitation signal, and then uses an acoustic emission acquisition processing system to acquire, amplify and process the signal for analysis, thereby detecting whether there is a microcrack defect in the component.
The above patents, which have been published or granted, all propose detection methods that require a separate excitation device to detect defects of the material, and cannot perform real-time detection during the LSP processing.
Disclosure of Invention
The defect detection purpose in the laser shock peening process is realized by fusing information of the dual-channel acoustic emission sensor. The method is characterized in that the arrangement positions of the acoustic emission sensors are determined through the propagation analysis of the acoustic emission signals in the defect plate, after laser shock strengthening is carried out, range fusion is carried out on the acoustic emission signals of the double sensors, characteristic parameters of a fusion channel are obtained, defect information is represented, and the method is based on the range of the acoustic emission double channels.
The technical scheme adopted by the invention is as follows:
the laser shock peening defect on-line detection method based on the acoustic emission double-channel range is characterized by comprising the following steps of:
fixing a plate to be processed on a laser shock peening test bed, adjusting the position of the plate to enable a focusing device to be opposite to the center of an impact area of the plate, then installing a dual-channel acoustic emission sensor probe on the surface of the plate to be processed, and acquiring an acoustic emission signal x (t) in the material in real time while carrying out shock peening on a blank plate and a defect plate;
secondly, the sampling rate of the original acoustic emission signals x (t) is extremely high, and in order to improve the processing speed of data, the acoustic emission signals of all channels are processed according to Shannon's sampling theorem to obtain down-sampling signals x1 (t);
performing Fourier spectrum analysis on the down-sampled signal x1(t), filtering the signal according to the frequency band of each spectral peak, and extracting kurtosis K, a pulse factor I and a margin factor C from the filtered signal of each sensoreThree-dimensional time domain characteristic parameters;
and fourthly, performing range operation on the three-dimensional time domain characteristic parameters of the signals of the sensors to obtain fusion time domain characteristic parameters based on the dual-channel information, wherein the fusion time domain characteristic parameters are used for representing defect information and realizing the defect online detection of the laser shock peening workpiece material.
The invention is further improved in that in the first step, the laser shock peening test bed comprises four parts, namely a control system, a laser generator, a light guide device and a focusing device, the focusing device is used for realizing the accurate positioning of the laser shock position, the laser generator is a high-power neodymium glass pulse laser, the laser wavelength is 1064nm, the pulse width is 18ns, the single pulse energy is 2-8J, the repetition frequency is 1Hz, and the control system is used for controlling the laser generator to complete the shock work and controlling the focusing device to realize the shock positioning.
The further improvement of the invention is that in the first step, the selected acoustic emission acquisition equipment comprises an acoustic emission sensor probe, a preamplifier and an acoustic emission signal acquisition and analysis system, an RS-2A type narrow-band resonant acoustic emission sensor is selected to acquire an acoustic emission signal, the preamplifier with the gain of 20dB is used for enhancing the signal, and the signal acquisition and analysis system is used for realizing the conversion, integration, display, storage and analysis of signal data;
aiming at the flat plate material, two acoustic emission probes are symmetrically arranged.
The further improvement of the invention is that in the second step, the initial sampling rate of the acoustic emission signal is too high, the data length is large, and in order to improve the signal processing rate, the original signal is subjected to down-sampling processing on the premise of meeting the Shannon sampling theorem to obtain a down-sampled signal.
The further improvement of the invention is that in the third step, the signal after down sampling is subjected to Fourier spectrum analysis, the frequency band of the same spectral peak in the two sensor signals is determined, the signal is subjected to filtering processing, and the three-dimensional dimensionless time domain characteristic parameters are further extracted: kurtosis
Pulse factor
Sum margin factor
The further improvement of the invention is that in the third step, aiming at the flat plate material, the kurtosis K of the filtering signal, the pulse factor I and the margin factor C are extractedeAnd (3) three-dimensional time domain characteristic parameters.
The invention has the further improvement that the acoustic emission elastic wave can be mutually coupled with the defects in the internal propagation process of the material, so that modal transformation and propagation path change occur; when the plate is not defective, the signals received by the sensor are direct surface waves and plate boundary reflected waves; when the plate has a prefabricated defect, the direct surface wave interacts with the defect, mode conversion occurs to generate a defect launching surface wave, and a propagation path is changed to generate a defect diffraction surface wave; the analysis shows that the signal modes carrying the defect information are a defect launching surface wave and a defect diffraction surface wave, so that the defect information can be obtained by analyzing the signals of the two modes.
The further improvement of the invention is that in the fourth step, the arrangement position of the sensor is obtained by analyzing the propagation of the acoustic emission signal in the defect plate; due to the existence of the prefabricated defects, sensors are respectively arranged on two sides of the defects, one sensor and a laser impact area are positioned on one side of the defects, and the sensors receive direct surface waves and reflected surface waves of the defects; the other sensor and the laser impact area are positioned at two sides of the defect, and the sensor receives the diffraction surface wave and the boundary reflection surface wave of the defect; since the defect information exists in the defect reflection surface wave and the defect diffraction surface wave, the defect information can be clearly and completely reflected by fusing the two sensors.
The further improvement of the invention is that in the fourth step, the time domain characteristic parameter calculation formula after the two-channel information fusion is as follows:
in the formula:
is the time domain characteristic parameter of the No. 1 sensor at the same side of the impact area,
is the time domain characteristic parameter of No. 2 sensor at the opposite side of the impact region, i is the three-dimensional dimensionless time domain characteristic parameter, respectively is the kurtosis
Pulse factor
Sum margin factor
The invention has the further improvement that in the fourth step, the defect information representation is carried out by utilizing the time domain characteristic parameters of the double-channel information fusion, and the online detection of the laser shock peening defect is realized.
The invention realizes the combination of the laser shock strengthening process and the defect detection process, and compared with the prior art, the invention has the following advantages:
(1) the defect detection system adopts an acoustic emission technology, the acoustic emission technology belongs to a passive detection technology, the tiny defects in the plate can be clearly detected, in addition, an acoustic emission signal is generated by elastic waves in the material during laser shock strengthening, an external excitation source is not needed, and the information utilization rate of the laser shock strengthening is improved.
(2) The sensors positioned on two sides of the defect are adopted for defect detection, the analysis of the transmission path of the acoustic emission signal in the plate can be known, and compared with a single sensing probe, the time domain characteristics of the information of the fusion multi-sensor can represent defect information more clearly and completely, the sensitivity of the defect characteristics can be greatly enhanced through the simple range operation of the double probes, and the accuracy of the defect detection is improved.
The method provided by the invention has the advantages of simple algorithm, high feature discrimination, strong interpretability, high robustness and strong engineering applicability, and provides an effective implementation way for realizing the on-line detection of defects in the laser shock peening process.
Drawings
FIG. 1 is a schematic diagram of laser shock peening defect on-line detection in an embodiment of the present invention;
FIG. 2 is a flow chart of an embodiment of the present invention;
FIG. 3 is a layout diagram of acoustic emission sensors in an embodiment of the present invention; wherein a is a blank plate and b is a defective plate;
FIG. 4 is a diagram of the shape and size of a blank plate and a defect plate in an embodiment of the present invention; wherein a is a blank plate and b is a defective plate;
FIG. 5 is a frequency spectrum diagram before and after a blank panel and a defect panel sensor acoustic emission signal downsampling process in an embodiment of the invention; wherein, a and b are respectively blank panel 1# and 2# sensor down-sampled acoustic emission signal spectrograms, c and d are respectively defect panel 1# and 2# sensor down-sampled acoustic emission signal spectrograms;
FIG. 6 is a time domain diagram of the filtered signals of the blank plate and the defect plate according to an embodiment of the present invention; wherein a and b are respectively blank panel 1# and 2# sensor filtering signal time domain diagrams, and c and d are respectively defect panel 1# and 2# sensor filtering signal time domain diagrams;
FIG. 7 is a comparison graph of the fused dual-channel information time domain characteristic parameters of the blank plate and the defect plate in the embodiment of the present invention.
Wherein: 1-a control system, 2-a laser generator, 3-a light guide device, 4-a focusing device, 5-a transparent water restraint layer, 6-a black adhesive tape absorption protection layer, 7-a metal plate, 8-an acoustic emission sensor, 9-a preamplifier, 10-an acoustic emission signal acquisition and analysis system, 11-a laser impact area and 12-a prefabricated defect.
Detailed Description
In order to clearly explain the application field of the present invention, the present invention will be further explained with reference to the drawings and examples.
As shown in FIG. 1, it can be seen that the online detection of laser shock peening defects can be divided into two parts, a laser shock peening part and a defect online detection part. The laser shock strengthening part selects a high repetition frequency laser to generate pulse laser, and shock strengthening of the metal material is realized through a series of matched devices. The main structure of the laser shock peening part comprises a control system 1, a laser generator 2, a light guide device 3, a focusing device 4, a transparent constraint layer 5, an absorption protective layer 6 and a metal plate 7. The defect on-line detection part selects an acoustic emission technology to carry out qualitative and quantitative analysis on the defects of the material, and mainly comprises the following three parts, namely an acoustic emission sensor 8, a preamplifier 9 and an acoustic emission signal acquisition and analysis system 10.
The invention provides an online detection method for laser shock peening defects based on acoustic emission dual-channel range, a flow chart of the technical scheme is shown in figure 2, and the method mainly comprises the following steps:
fixing a plate to be processed on a laser shock peening test bed, and adjusting the position of the plate to enable a focusing device to be over against the center of a plate shock area. High-energy pulse laser is generated by a laser generator and is irradiated on an impact area of the plate through a light guide device and a focusing device. And then, correctly installing the acoustic emission sensor on the plate to be processed according to requirements, respectively performing impact strengthening on the blank plate and the defect plate, and acquiring an acoustic emission signal in real time. The position of the sensor on the test plate is shown in fig. 3.
Secondly, performing down-sampling processing on the acoustic emission signals acquired by each channel according to Shannon sampling theorem, and ensuring that the down-sampled signals after data length compression are obtained under the condition that the signals are not distorted, so that the data processing speed is increased;
and step three, performing frequency spectrum analysis on the down-sampling acoustic emission signals received by the sensors, determining the frequency band of each spectral peak on the frequency spectrum, performing filtering processing on the signals according to the frequency band, and then extracting time domain characteristic parameters of the filtered signals of the sensors. Selecting three-dimensional dimensionless parameters commonly used in defect detection by time domain characteristics, mainly kurtosis
Pulse factor
Sum margin factor
And fourthly, performing range operation on the three-dimensional time domain characteristic parameters of the signals of the sensors to obtain fusion time domain characteristic parameters based on the dual-channel information, wherein the fusion time domain characteristic parameters are used for representing defect information and realizing the defect online detection of the laser shock peening workpiece material.
The fusion time domain characteristic parameter calculation formula based on the two-channel information is as follows:
in the formula:
is the time domain characteristic parameter of the No. 1 sensor at the same side of the impact area,
is a time domain characteristic parameter of a No. 2 sensor on the opposite side of the impact region, I is a three-dimensional dimensionless time domain characteristic parameter which is respectively kurtosis K, an impulse factor I and a margin factor Ce。
Example (b):
the laser shock peening defect online detection method adopted by the embodiment can be divided into a laser shock peening part and a defect online detection part. The laser shock peening adopts the following processing technological parameters: the transparent restraint layer is restrained by water, the absorption protection layer is made of black adhesive tape, pulse laser is 4J, the diameter of a light spot is 3mm, and the repetition frequency is 0.5 Hz. In the defect on-line detection part, the acoustic emission sensor is a resonant narrow-band sensor, the gain multiple of a preamplifier is 20dB, and an industrial coupling agent is adopted to ensure that the sensor is tightly attached to the plate
In this example, the effectiveness of the method proposed by the invention was experimentally verified by prefabricating defects on a flat plate for simulating a defective plate in machining. FIG. 3 is a sensor layout diagram, and adopts double sensors to detect defects, the No. 1 sensor and the laser impact area are located on the same side of the defect, the No. 2 sensor and the laser impact area are located on two sides of the defect, and complete defect information is obtained by performing information fusion on the No. 1 sensor and the No. 2 sensor. Fig. 4 shows the dimensions of the blank plate and the defect plate, with a length, width and height of 300mm x 50mm x 4mm, respectively, wherein the defect size is 20mm x 2mm and the defect position is 110mm from the plate boundary.
In this example, according to the first step of the present invention, after a flat plate to be processed is fixed on a laser impact experiment table, a focusing device is adjusted to focus on the center of an impact area of a plate, a controller 1 controls a laser generator 2 to generate high-energy pulse laser, the high-energy pulse laser is irradiated on the plate to be processed attached with a black adhesive tape 6 through a light guide device 3 and a focusing device 4, and the black adhesive tape 6 generates high-pressure plasma after absorbing laser energy, and further gathers to generate a high-temperature high-pressure plasma cluster; then, under the action of the water restraint 5, high-pressure shock waves are generated and transmitted to the interior of the material, so that the material is subjected to micro deformation, a strengthening effect is generated, and meanwhile, an acoustic emission signal is generated. An acoustic emission sensor is arranged according to the requirement of fig. 3, and acoustic emission signals generated during laser shock peening are received, stored and analyzed in real time, wherein the sampling rate of a blank flat plate is 5MHz, and the sampling rate of a defect flat plate is 3 MHz. According to the second step of the invention, the original acoustic emission signals are down-sampled according to the sampling theorem, wherein the blank flat plate is reduced by 5 times, and the defect flat plate is reduced by 3 times, so that the sampling rate of the down-sampled signals is 1 MHz. Fig. 5 is a graph showing the down-sampled signal spectra of each sensor for the blank plate and the defect plate. According to the third step of the invention, the frequency spectrum analysis is carried out on the down-sampled signals of each channel, the frequency band where the spectral peak is located is selected to carry out filtering processing on the signals, and the three-dimensional dimensionless time domain characteristic parameters of the filtered signals are extracted. Fig. 6 is a time domain diagram of the filtered signals of the sensors of the blank plate and the defect plate, and table 1 shows the time domain characteristic parameters of the filtered signals of the sensors of the blank plate and the defect plate. According to the fourth step of the invention, the time domain characteristic parameters of different sensors obtained in the third step are fused to obtain fused time domain characteristic parameters based on the dual-channel information, the fused time domain characteristic parameters are used for representing the defect information and realizing the laser shock peening defect on-line detection, the three-dimensional time domain characteristic parameters of the fused dual-channel information are shown in the table 2, and a fused time domain characteristic comparison graph of a blank panel and a defect panel based on the dual-channel information is shown in the figure 7.
TABLE 1 time-domain characteristic parameters of the filtered signals of each sensor of the blank and defect plates
TABLE 2 fusion time domain feature parameters based on dual channel information
From the experiment and the embodiment results, the real-time detection method for the internal defects of the laser shock peening target based on the acoustic emission dual-channel range fusion combines the laser shock peening process and the defect detection process, adopts the sound emission technology developed in nondestructive testing as a means to collect the acoustic emission signals generated in the laser shock peening process in real time, and realizes the detection target of the material defects. Through the propagation path of the analog acoustic emission signal in the plate, the sensors positioned on two sides of the defect can both receive certain defect information, and the two sensors are subjected to range fusion so as to represent the defect information more completely. The embodiment result shows that the fusion time domain characteristic based on the dual-channel information has strong distinguishability on a blank flat plate and a defect flat plate, and can well detect the defect information. The method has the advantages of simple process, high characteristic representation degree, strong robustness and strong engineering applicability.
Claims (10)
1. The laser shock peening defect on-line detection method based on the acoustic emission double-channel range is characterized by comprising the following steps of:
fixing a plate to be processed on a laser shock peening test bed, adjusting the position of the plate to enable a focusing device to be opposite to the center of an impact area of the plate, then installing a dual-channel acoustic emission sensor probe on the surface of the plate to be processed, and acquiring an acoustic emission signal x (t) in the material in real time while carrying out shock peening on a blank plate and a defect plate;
secondly, the sampling rate of the original acoustic emission signals x (t) is extremely high, and in order to improve the processing speed of data, the acoustic emission signals of all channels are processed according to Shannon's sampling theorem to obtain down-sampling signals x1 (t);
performing Fourier spectrum analysis on the down-sampled signal x1(t), filtering the signal according to the frequency band of each spectral peak, and extracting kurtosis K, a pulse factor I and a margin factor C from the filtered signal of each sensoreThree-dimensional time domain characteristic parameters;
and fourthly, performing range operation on the three-dimensional time domain characteristic parameters of the signals of the sensors to obtain fusion time domain characteristic parameters based on the dual-channel information, wherein the fusion time domain characteristic parameters are used for representing defect information and realizing the defect online detection of the laser shock peening workpiece material.
2. The method for on-line detection of laser shock peening defect based on acoustic emission dual-channel range, according to claim 1, wherein in the first step, the laser shock peening test bench comprises four parts, namely a control system, a laser generator, a light guide device and a focusing device, the focusing device is used for achieving accurate positioning of a laser shock position, the laser generator is a high-power neodymium glass pulse laser, the laser wavelength is 1064nm, the pulse width is 18ns, the single pulse energy is 2-8J, the repetition frequency is 1Hz, the control system is used for controlling the laser generator to complete shock work, and the focusing device is controlled to achieve shock positioning.
3. The online detection method for the laser shock peening defect based on the acoustic emission double-channel range difference is characterized in that in the first step, the selected acoustic emission acquisition equipment comprises an acoustic emission sensor probe, a preamplifier and an acoustic emission signal acquisition and analysis system, an RS-2A type narrow-band resonant acoustic emission sensor is selected to acquire an acoustic emission signal, the preamplifier with the gain of 20dB is used for enhancing the signal, and the signal acquisition and analysis system is used for realizing conversion integration, display, storage and analysis of signal data;
aiming at the flat plate material, two acoustic emission probes are symmetrically arranged.
4. The method for on-line detection of the laser shock peening defect based on the acoustic emission double-channel range difference as recited in claim 1, wherein in the second step, the initial sampling rate of the acoustic emission signal is too high, the data length is large, and in order to increase the signal processing rate, the original signal is down-sampled to obtain a down-sampled signal on the premise of satisfying shannon's sampling theorem.
5. The on-line detection method for the laser shock peening defect based on the acoustic emission double-channel range difference as claimed in claim 1, wherein in the third step, Fourier spectrum analysis is performed on the down-sampled signals, the frequency bands of the same spectral peak in the two sensor signals are determined, the signals are subjected to filtering processing, and three-dimensional dimensionless time domain characteristic parameters are further extracted: kurtosis
Pulse factor
Sum margin factor
6. The method for on-line detection of laser shock peening defect based on acoustic emission two-channel range according to claim 1, wherein in step three, a filtering signal kurtosis K, a pulse factor I and a margin factor C are extracted for a flat materialeAnd (3) three-dimensional time domain characteristic parameters.
7. The method for the on-line detection of the laser shock peening defect based on the acoustic emission double-channel range difference as claimed in claim 1, wherein the acoustic emission elastic wave is mutually coupled with the defect during the internal propagation process of the material, and modal transformation and propagation path change occur; when the plate is not defective, the signals received by the sensor are direct surface waves and plate boundary reflected waves; when the plate has a prefabricated defect, the direct surface wave interacts with the defect, mode conversion occurs to generate a defect launching surface wave, and a propagation path is changed to generate a defect diffraction surface wave; the analysis shows that the signal modes carrying the defect information are a defect launching surface wave and a defect diffraction surface wave, so that the defect information can be obtained by analyzing the signals of the two modes.
8. The method for the on-line detection of the laser shock peening defect based on the acoustic emission double-channel range difference as claimed in claim 1, wherein in the fourth step, the arrangement position of the sensor is obtained by analyzing the propagation of the acoustic emission signal in the defect plate; due to the existence of the prefabricated defects, sensors are respectively arranged on two sides of the defects, one sensor and a laser impact area are positioned on one side of the defects, and the sensors receive direct surface waves and reflected surface waves of the defects; the other sensor and the laser impact area are positioned at two sides of the defect, and the sensor receives the diffraction surface wave and the boundary reflection surface wave of the defect; since the defect information exists in the defect reflection surface wave and the defect diffraction surface wave, the defect information can be clearly and completely reflected by fusing the two sensors.
9. The on-line detection method for the laser shock peening defect based on the acoustic emission double-channel range according to claim 1, characterized in that in the fourth step, a time domain characteristic parameter calculation formula after double-channel information fusion is as follows:
in the formula:
is the time domain characteristic parameter of the No. 1 sensor at the same side of the impact area,
is the time domain characteristic parameter of No. 2 sensor at the opposite side of the impact region, i is the three-dimensional dimensionless time domain characteristic parameter, respectively is the kurtosis
Pulse factor
Sum margin factor
10. The method for the online detection of the laser shock peening defect based on the acoustic emission double-channel range according to claim 1, wherein in the fourth step, the defect information characterization is performed by using the time domain characteristic parameters of the double-channel information fusion, so that the online detection of the laser shock peening defect is realized.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110525309.2A CN113340997B (en) | 2021-05-11 | 2021-05-11 | Online detection method for laser shock peening defect based on acoustic emission double-channel range |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110525309.2A CN113340997B (en) | 2021-05-11 | 2021-05-11 | Online detection method for laser shock peening defect based on acoustic emission double-channel range |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113340997A true CN113340997A (en) | 2021-09-03 |
| CN113340997B CN113340997B (en) | 2024-01-12 |
Family
ID=77468797
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110525309.2A Active CN113340997B (en) | 2021-05-11 | 2021-05-11 | Online detection method for laser shock peening defect based on acoustic emission double-channel range |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113340997B (en) |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101198861A (en) * | 2005-04-13 | 2008-06-11 | 传感器公司 | Method for determining impact position with acoustics imaging |
| CN104391046A (en) * | 2014-11-17 | 2015-03-04 | 西安交通大学 | Optimum rolling bearing lubricating grease amount determining method based on acoustic emission |
| CN107153728A (en) * | 2017-04-26 | 2017-09-12 | 西安交通大学 | A kind of abrasion of grinding wheel state feature extracting method based on bispectrum amplitude distribution entropy |
| EP3435044A1 (en) * | 2017-07-27 | 2019-01-30 | Aif Management Bvba | Apparatus and method for performing an impact excitation technique |
| CN109827081A (en) * | 2019-02-28 | 2019-05-31 | 昆明理工大学 | A kind of buried drain pipe road plugging fault and branch pipe tee connection part diagnostic method based on acoustics active detecting |
| CN112067696A (en) * | 2020-09-30 | 2020-12-11 | 北京石油化工学院 | System for detecting surface defects of pipeline based on laser ultrasonic |
| CN112199996A (en) * | 2020-09-04 | 2021-01-08 | 西安交通大学 | Rolling bearing diagnosis method based on parameter self-adaptive VMD and fast Hoyer spectrogram indexes |
| CN112232400A (en) * | 2020-10-12 | 2021-01-15 | 太原科技大学 | Stainless steel weld ultrasonic defect detection method based on depth feature fusion |
| CN112668382A (en) * | 2020-07-21 | 2021-04-16 | 北京工业大学 | Support vector machine-based ultrasonic signal identification method for defects in steel ingot |
-
2021
- 2021-05-11 CN CN202110525309.2A patent/CN113340997B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101198861A (en) * | 2005-04-13 | 2008-06-11 | 传感器公司 | Method for determining impact position with acoustics imaging |
| CN104391046A (en) * | 2014-11-17 | 2015-03-04 | 西安交通大学 | Optimum rolling bearing lubricating grease amount determining method based on acoustic emission |
| CN107153728A (en) * | 2017-04-26 | 2017-09-12 | 西安交通大学 | A kind of abrasion of grinding wheel state feature extracting method based on bispectrum amplitude distribution entropy |
| EP3435044A1 (en) * | 2017-07-27 | 2019-01-30 | Aif Management Bvba | Apparatus and method for performing an impact excitation technique |
| CN109827081A (en) * | 2019-02-28 | 2019-05-31 | 昆明理工大学 | A kind of buried drain pipe road plugging fault and branch pipe tee connection part diagnostic method based on acoustics active detecting |
| CN112668382A (en) * | 2020-07-21 | 2021-04-16 | 北京工业大学 | Support vector machine-based ultrasonic signal identification method for defects in steel ingot |
| CN112199996A (en) * | 2020-09-04 | 2021-01-08 | 西安交通大学 | Rolling bearing diagnosis method based on parameter self-adaptive VMD and fast Hoyer spectrogram indexes |
| CN112067696A (en) * | 2020-09-30 | 2020-12-11 | 北京石油化工学院 | System for detecting surface defects of pipeline based on laser ultrasonic |
| CN112232400A (en) * | 2020-10-12 | 2021-01-15 | 太原科技大学 | Stainless steel weld ultrasonic defect detection method based on depth feature fusion |
Non-Patent Citations (2)
| Title |
|---|
| JIAJUN WU等: "Acoustic wave detection of laser shock peering", 《OPTO-ELECTRONIC ADVANCES》 * |
| 张志芬等: "航空航天用铝合金机器人焊接内部气孔缺陷在线检测", 《航空制造技术》 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113340997B (en) | 2024-01-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Lv et al. | Automated control of welding penetration based on audio sensing technology | |
| CN113231651B (en) | Additive manufacturing apparatus and method | |
| CN109387567B (en) | Additive manufacturing laser ultrasonic detection data processing method based on wave speed correction | |
| US6823736B1 (en) | Nondestructive acoustic emission testing system using electromagnetic excitation and method for using same | |
| US20100131210A1 (en) | Method and system for non-destructive inspection of a colony of stress corrosion cracks | |
| CN112098526B (en) | Near-surface defect feature extraction method for additive product based on laser ultrasonic technology | |
| JP2012032404A (en) | Structure/material measurement system | |
| US9488623B2 (en) | Guided wave mode sweep technique for optimal mode and frequency excitation | |
| CN112157368B (en) | Laser non-penetration welding seam penetration nondestructive testing method | |
| Luo et al. | Monitoring of laser welding using source localization and tracking processing by microphone array | |
| Yusof et al. | Weld depth estimation during pulse mode laser welding process by the analysis of the acquired sound using feature extraction analysis and artificial neural network | |
| CN111174894B (en) | Laser ultrasonic transverse wave sound velocity measurement method | |
| CN215375237U (en) | Nondestructive testing system for improving laser ultrasonic signal based on beam shaping | |
| CN108956782B (en) | Laser shock online detection method and device based on sound wave frequency characteristics | |
| CN113340997A (en) | Laser shock peening defect online detection method based on acoustic emission dual-channel range | |
| Zhang et al. | Multisensory data fusion technique and its application to welding process monitoring | |
| CN112280968B (en) | High-energy pulse laser processing and measuring integrated system and method | |
| Sattar et al. | Exploring the potential and recent advancement in laser Opto-ultrasonic detection for material characterization: A state-of-the-art review | |
| Masserey et al. | IN‐SITU MONITORING OF FATIGUE CRACK GROWTH AT FASTENER HOLES USING RAYLEIGH‐LIKE WAVES | |
| US5466910A (en) | Method of testing weld seams using an eddy-current technique | |
| Tian et al. | Phased array ultrasonic S-scan testing of near-detection-surface defects based on a background subtraction algorithm | |
| Meng et al. | Spectral analysis for crack detection during TIG welding using acoustic emission techniques | |
| Sampath et al. | Depth profiling of residual stress distribution in surface treated metallic structures using nonlinear ultrasonics | |
| Zhang et al. | Ultrasonic flaw recognition by multi-angle phased array data integration | |
| CN113953271B (en) | Laser cleaning and nondestructive testing system and method |
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 |