Damage mechanism test method of glass fiber / epoxy composite material

Abstract

The invention provides a damage mechanism test method of a glass fiber / epoxy composite material. The damage mechanism test method comprises the following steps: acquiring an original acoustic emission signal of a whole damage process of a to-be-tested material sample; carrying out clustering analysis on data of three types of signal characteristics including amplitude, center frequency and average frequency in the original acoustic emission signals to obtain a characteristic distribution diagram of the three types of acoustic emission signals; according to the characteristic distribution diagram of the three types of acoustic emission signals, classifying and identifying defect modes of the material sample; and acquiring an accumulative count-load-time change curve of each defect category, dividing damage development stages of the to-be-detected material sample according to development characteristics of each defect, and determining distribution positions and development rules of different defects in the damage process. According to the method, three different defect modes of matrix damage, fiber-matrix interface layering and fiber fracture can be identified more accurately, damage development stages are accurately divided according to defect development characteristics, and an accurate scientific basis is provided for maintenance and replacement of materials.

Description

Technical Field

[0001] The invention relates to the technical field of insulating material detection, and in particular to a damage mechanism test method for a glass fiber / epoxy composite material. Background Art

[0002] The loads, mechanical vibrations and complex external environmental factors that composite insulators bear during service can cause defects or even damage. Severe defects can cause material damage and may lead to economic losses. Research on the damage mechanism of glass fiber / epoxy composite materials for composite insulator core rods can help operation and maintenance personnel evaluate their overall performance and understand the operating status of the equipment in a timely manner, thereby preventing the overall performance degradation of composite insulators caused by internal defects and effectively ensuring the safety of the power grid.

[0003] As a nondestructive testing technology, acoustic emission (AE) has the characteristics of high precision, real-time performance, and versatility, meeting the requirements of nondestructive testing of defects in composite glass fiber / epoxy composite materials. Compared with conventional composite material nondestructive testing methods, acoustic emission testing technology has a wide range of applications, can effectively detect dynamic defects, and conduct real-time observation of the damage process. In addition, dynamic information about the damage defects can be obtained in this process. It is an efficient nondestructive dynamic damage detection technology.

[0004] Matrix damage, fiber-matrix interface separation, delamination and fiber breakage are common defects in glass fiber / epoxy composites. A large number of studies have shown that although the failure mechanism of composite insulation materials is very complex, the acoustic emission signals corresponding to different defects show obvious differences, which can effectively distinguish the various failure modes of composite insulation materials.

[0005] However, there is still a lack of reliable methods for studying the mechanism of the entire dynamic damage process of composite materials. When many researchers use acoustic emission technology to detect defects in composite insulation materials, they rarely use it as a core method for material defect identification and damage mechanism research, and lack effective means to verify the accuracy of defect identification. In addition, the research on acoustic emission parameters is mainly based on the analysis of a single parameter, and there is a lack of damage mechanism research methods that combine the analysis of multiple parameters. Summary of the invention

[0006] In view of this, the present invention proposes a damage mechanism test method for glass fiber / epoxy composite materials, aiming to solve the above technical problems existing in the prior art.

[0007] The present invention provides a damage mechanism test method for glass fiber / epoxy composite materials, comprising:

[0008] Step 1, applying a load to the material sample to be tested to perform a damage experiment, so as to collect the original acoustic emission signal of the whole damage process of the material sample to be tested;

[0009] Step 2, performing cluster analysis on the data of three types of signal features including amplitude, center frequency and average frequency in the original acoustic emission signal to obtain characteristic distribution diagrams of the three types of acoustic emission signals;

[0010] Step 3, classifying and identifying the defect mode of the material sample to be tested according to the characteristic distribution diagrams of the above three types of acoustic emission signals;

[0011] Step 4, obtaining the cumulative count-load-time variation curve of each defect type, and dividing the damage development stage of the material sample to be tested according to the development characteristics of each defect;

[0012] Step 5, combining the acoustic emission positioning results of the material sample to be tested during the entire damage process, to obtain the distribution positions and development laws of different defects in the material sample to be tested during the damage process.

[0013] Furthermore, in the damage mechanism test method of the glass fiber / epoxy composite material, after step 1 and before step 2, the original acoustic emission signal is subjected to noise reduction processing.

[0014] Furthermore, in the above-mentioned damage mechanism test method of glass fiber / epoxy composite materials, in step 2, the K-means clustering algorithm is used to cluster and classify the data containing three types of acoustic emission signal characteristics, namely amplitude, center frequency and average frequency, and obtain the probability density map of amplitude, center frequency and average frequency.

[0015] Furthermore, in the above-mentioned damage mechanism test method for glass fiber / epoxy composite materials, in the step 3, an acoustic emission signal with a lower amplitude, a lower average frequency and a relatively low center frequency is identified as a matrix damage signal; an acoustic emission signal with a higher amplitude, a lower average frequency and a center frequency is identified as an interface delamination signal; and an acoustic emission signal with a lower amplitude, a higher average frequency and a center frequency is identified as a fiber breakage signal.

[0016] Furthermore, in the above-mentioned damage mechanism test method of glass fiber / epoxy composite material, in step 4, the damage development stage of the material sample to be tested is divided into three stages:

[0017] In the initial damage stage, there are very few signals of the three types of defects;

[0018] In the damage development stage, matrix damage and fiber breakage signals begin to appear and continue to appear throughout the damage development stage, and interface delamination signals are rare;

[0019] The damage intensifies to the stage of overall failure, and the matrix damage and fiber breakage signals continue to appear throughout the damage development stage; the interface delamination signal appears and surges until the overall failure of the material sample to be tested.

[0020] Furthermore, in the damage mechanism test method of the above-mentioned glass fiber / epoxy composite material, the duration of the initial damage stage is in the range of 0-100s; the duration of the damage development stage is in the range of 100-300s; and the duration of the damage aggravation to the overall failure stage is in the range of 300-400s.

[0021] Furthermore, the damage mechanism test method of the glass fiber / epoxy composite material further includes:

[0022] Step 6, taking a plurality of control samples that have not been damaged, applying a load to each of the control samples until each of the control samples reaches a different damage stage divided in step 4, thereby obtaining control samples at different damage development stages; the control samples have the same properties as the material sample to be tested;

[0023] Step 7, observing the defects inside the control samples at different damage stages, comparing the observed defects with the results of defect pattern recognition in step 3, and verifying whether the defect pattern recognition results are accurate.

[0024] Furthermore, in the damage mechanism test method of the glass fiber / epoxy composite material, the load applied to each of the control samples is consistent with the load applied to the sample of the material to be tested.

[0025] Furthermore, in the damage mechanism test method of the glass fiber / epoxy composite material, the surface and cross-sectional morphologies of each of the control samples at different damage development stages are observed by SEM to obtain the defect distribution inside each of the control samples at different damage development stages.

[0026] Furthermore, in the damage mechanism test method of the glass fiber / epoxy composite material, a lead breaking test is performed before step 1 to ensure that a valid original acoustic emission signal is collected.

[0027] The damage mechanism test method of the glass fiber / epoxy composite material in the present invention obtains characteristic distribution diagrams of three types of acoustic emission signals by clustering analysis using data of three types of signal characteristics, namely amplitude, center frequency and average frequency, so as to more accurately identify three different defect modes, namely matrix damage, fiber-matrix interface delamination and fiber fracture, and by obtaining the cumulative count-load-time variation curve of each defect category, the present invention can accurately divide the stage of damage development according to the defect development characteristics. This division helps to deeply understand the damage mechanism and provides an accurate scientific basis for the maintenance and replacement of materials. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0029] Figure 1 A schematic flow chart of a damage mechanism test method for a glass fiber / epoxy composite material provided in an embodiment of the present invention;

[0030] Figure 2 A schematic diagram of a lead interruption experiment for a damage mechanism test method of a glass fiber / epoxy composite material provided in an embodiment of the present invention;

[0031] Figure 3 Schematic diagram of an experimental device for performing tensile acoustic emission analysis in an embodiment of the present invention;

[0032] Figure 4 This is a graph of acoustic emission signal amplitude-load-time for a damage experiment of a glass fiber / epoxy composite material to be tested in an embodiment of the present invention;

[0033] Figure 5 It is a hierarchical clustering dendrogram of the embodiment of the present invention ((a) epoxy resin matrix (b) glass fiber bundle (c) glass fiber / epoxy composite material tensile sample diagram);

[0034] Figure 6 It is a probability density diagram of the amplitude, center frequency and average frequency of the damage experiment of the glass fiber / epoxy composite material to be tested in the embodiment of the present invention;

[0035] Figure 7 Probability density diagram of the tensile damage test amplitude (a), average frequency (b), and center frequency (c) of epoxy resin;

[0036] Figure 8 The probability density diagram of the tensile damage test amplitude (a), average frequency (b), and center frequency (c) of glass fiber;

[0037] Fig. 9 The probability density diagram of the tensile damage test amplitude (a), average frequency (b), and center frequency (c) of the tested glass fiber / epoxy composite material;

[0038] Fig.10 It is the cumulative count-load-time curve of matrix damage signal in the tensile damage experiment of the glass fiber / epoxy composite material to be tested;

[0039] Fig.11It is the cumulative count-load-time curve of the fiber-matrix interface delamination signal in the tensile damage experiment of the glass fiber / epoxy composite material to be tested;

[0040] Fig.12 It is the cumulative count-load-time curve of fiber fracture signal in the tensile damage test of the glass fiber / epoxy composite material to be tested;

[0041] Fig.13 The macroscopic morphology of the sample before stretching (a), during the test (b), and after stretching (c) during the damage test of the control sample;

[0042] Fig.14 The cross-sectional SEM images of the glass fiber / epoxy composite control sample to be tested were stretched for 100s and 300s;

[0043] Fig.15 Surface SEM images of the glass fiber / epoxy composite control sample to be tested after stretching for 100s and 300s. DETAILED DESCRIPTION

[0044] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present disclosure and to be able to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features described in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0045] See also Figure 1 The damage mechanism test method of the glass fiber / epoxy composite material of the embodiment of the present invention includes:

[0046] Step S1, applying a load to the material sample to be tested to perform a damage experiment, so as to collect the original acoustic emission signal of the whole damage process of the material sample to be tested.

[0047] Specifically, the material sample to be tested can be a brand new, undamaged sample or a damaged sample, and this embodiment does not impose any limitation on it. In this embodiment, a glass fiber / epoxy composite material is used as the material sample to be tested.

[0048] The damage test may be a tensile test, a compression test, a fatigue test, an impact test, etc., which may be selected according to actual needs. In this embodiment, the damage test is performed on the material sample to be tested until the material sample to be tested is completely broken or destroyed, and then the test is stopped.

[0049] This embodiment mainly uses the acoustic emission principle to collect and record the elastic waves generated in the acoustic emission phenomenon and convert them into electrical signals. After the electrical signals are amplified and collected, the acoustic emission characteristic parameters are obtained, recorded, displayed, and finally the data is analyzed.

[0050] See also Figure 3 The acoustic emission acquisition system can be composed of an acoustic emission sensor 5, a preamplifier 9 and a detection system 10. Multiple acoustic emission sensors 5 and preamplifiers 9 can be set. Taking two acoustic emission sensors 5 and two preamplifiers 9 as an example, the two acoustic emission sensors 5 are installed on the test piece 8, and the two preamplifiers 9 are correspondingly connected between the acoustic emission sensor and the detection system 10.

[0051] In this embodiment, a lead breaking experiment is performed before step 1 to ensure that a valid original acoustic emission signal is collected.

[0052] See also Figure 2 Before the acoustic emission experiment officially starts signal collection, a lead breaking experiment is required to determine the size of parameters such as the acoustic signal threshold and to verify whether the signal transmission of the entire acoustic emission system is smooth after the sensor is connected. At the same time, the positioning accuracy can be verified. According to the standard guide for determining the reproducibility of the response of acoustic emission sensors in ASTM E976-15, the lead breaking experiment is repeated about 5 times. The first and last breaks should not be used as the standard. Use a pencil lead with a diameter of 0.5mm and a hardness of HB, control the elongation each time between 2-3mm, and keep the angle between the pencil lead and the sample surface at about 30°. Figure 2 In the figure, 1 is the lead of the pencil, 2 is a protective tube for protecting the lead of the pencil, 3 is a support ring for supporting and fixing the protective tube, and 4 is the pencil.

[0053] Continue reading Figure 3 Taking tensile damage as an example, in order to reduce the energy loss caused by the difference in acoustic impedance between the coupling agent and the surface of the acoustic emission sensor 5, the tiny gap between the contact surfaces needs to be effectively compensated. Referring to the standard QJ 2914-97 "Acoustic Emission Detection Method for Composite Structures", vacuum grease is used as an acoustic coupling agent and evenly applied to the position of the sample where the sensor is to be installed. Then, the two sensors are symmetrically fixed on the sample using electrical insulating tape. When installing the specimen 8, pay attention to aligning the center line of the sample with the center line of the upper fixture 6 and the lower fixture 7 to ensure the smooth application of the load. After installation, re-measure the distance between the two sensors. The device for applying the load can be an electronic universal testing machine 11 or a tensile tester.

[0054] In specific implementation, before the damage experiment officially begins, a background noise signal is first measured to determine the threshold value setting parameters to exclude the background noise signal of the material sample to be tested during the loading process.

[0055] Since electromagnetic interference, friction and collision interference caused by experimental instruments, etc., which affect the acoustic emission sensor, exist noise signals, after step 1 and before step 2, the original acoustic emission signal is subjected to noise reduction processing. Noise signals differ significantly from normal signals in some signal features, and data noise reduction can significantly improve the accuracy of acoustic emission source positioning and defect identification. Common noise reduction methods include wavelet analysis, neural networks, adaptive noise reduction, etc.

[0056] This embodiment takes the tensile damage experiment as an example, and conducts tensile damage experiments on the glass fiber / epoxy composite material and the epoxy resin and glass fiber as its component materials, respectively, and collects acoustic emission signals during the experiment to determine the key signal characteristic parameters of the damage development stage of the glass fiber / epoxy composite material.

[0057] The glass fiber / epoxy composite material, epoxy resin and glass fiber can be any commercially available product that meets the tensile test conditions, and this embodiment does not impose any limitation thereto.

[0058] In a specific implementation of the present invention, the epoxy resin sample is processed and prepared according to the requirements of the tensile test sample in the standard GB / T2567-2008 resin casting performance test method, and then vacuum degassing is performed in a vacuum drying oven and heated for curing.

[0059] The glass fiber bundle was pulled straight and clamped on the clamps at both ends of the tensile tester. The effective length of the sample was 500 mm.

[0060] The glass fiber and epoxy resin materials described above were used to prepare glass fiber / epoxy composite material samples by pultrusion process. The curing process was consistent with the curing process of the epoxy resin. The sample size was 240×12×3 mm.

[0061] The acoustic emission sensor used in the damage experiment in the embodiment of the present invention is a Nano30 sensor, the system is Express-8, the sampling signal amplitude is 0-100dB, and the preamplifier gain is 40dB. The acquisition instrument parameters set for the acoustic emission experiment are shown in Table 1. The sampling frequency is 1MSPS, and one acoustic emission signal is collected every microsecond.

[0062] Table 1 Acoustic emission acquisition instrument parameter settings

[0063]

[0064]

[0065] Before the acoustic emission experiment officially started signal collection, lead breaking experiments were carried out at a distance of 30mm from each acoustic emission sensor probe and at the midpoint of the two acoustic emission sensor probes. The results showed that the peak amplitude of each response was greater than 95dB, and the average wave velocity in the glass fiber / epoxy composite material sample was measured to be approximately 2000m / s.

[0066] In the epoxy resin tensile test, the distance between the two acoustic emission sensors is 120 mm, and the sensor probes are installed at 50 mm and 170 mm from the top to the bottom of the sample, symmetrically distributed on the same side. The tensile rate of the electronic universal testing machine is controlled at 1 mm / min.

[0067] In the glass fiber tensile test, the two acoustic emission sensors are installed at the upper and lower clamps of the single-filament tensile tester, that is, at 30mm and 470mm of the effective distance of the sample, with a spacing of 440mm, symmetrically distributed on the same side and keeping the center line perpendicular to the ground. When installing the sample, keep the sample parallel to the center line of the clamp to ensure smooth application of the tensile load. The tensile rate of the single-filament tensile tester is controlled at 1mm / min.

[0068] In the tensile test of the glass fiber / epoxy composite material sample, two acoustic emission sensor probes were arranged at 60mm and 180mm from the top to the bottom of the sample. The installation distance between the two acoustic emission sensors was 120mm and they were symmetrically distributed on the same side. The tensile rate of the electronic universal testing machine was controlled at 1mm / min.

[0069] See also Figure 4 , the figure shows the acoustic emission signal amplitude-load-time diagram of the glass fiber / epoxy composite material to be tested. It can be seen from the figure that: with the increase of load, the amplitude of the acoustic emission signal of the damaged glass fiber / epoxy composite material to be tested increases, and the number of acoustic emission signal events also increases, which also indicates the development of different damages inside the glass fiber / epoxy composite material to be tested.

[0070] Step S2, clustering analysis is performed on the data of three types of signal features, namely, amplitude, center frequency and average frequency, in the original acoustic emission signal to obtain characteristic distribution diagrams of the three types of acoustic emission signals.

[0071] Specifically, the acoustic emission signal parameters involved in the above damage experiment include amplitude, energy, count, center frequency, average frequency, rise time, duration and initial frequency.

[0072] In order to select the weakly correlated acoustic emission signal characteristic parameters from the above parameters for subsequent analysis, the hierarchical clustering feature extraction algorithm is applied to the above characteristic parameters, and the features involved in the extraction are shown in Table 2.

[0073] Table 2 Hierarchical clustering characteristics

[0074]

[0075] See also Figure 5 ,The hierarchical clustering dendrogram is classified according to the correlation between different parameters. Figure 5 In (a)-(c), the horizontal axis represents the eight parameters from 0 to 7 in Table 2, and the vertical axis represents the strength of the correlation. The larger the value, the weaker the correlation. Figure 5 The analysis results of this embodiment are shown. Therefore, the embodiment of the present invention selects amplitude, average frequency and center frequency as research features.

[0076] See also Figure 6 , the K-means clustering algorithm is used to cluster and classify the data containing three types of acoustic emission signal characteristics, namely amplitude, center frequency and average frequency, and the probability density maps of amplitude, center frequency and average frequency are obtained.

[0077] K-means clustering is a commonly used unsupervised learning algorithm for dividing data points into K clusters. The following is the basic process of using K-means clustering analysis to divide into 3 categories:

[0078] (1) The K-means++ method is used to select the initial centroid to reduce the dependence of the clustering results on the selection of the initial centroid;

[0079] (2) For each data point, calculate its Euclidean distance to each centroid and assign the data point to the nearest centroid to form three clusters;

[0080] (3) For each cluster, recalculate the centroid;

[0081] (4) Repeat the allocation and update steps until a certain stopping condition is met, for example, the change in the centroid is less than a certain threshold. The preset number of iterations is reached;

[0082] (5) When the algorithm reaches the stopping condition, it is considered to have converged, and the cluster assignment and centroid position at this time are considered to be the final clustering results.

[0083] Step S3: classify and identify the defect mode of the material sample to be tested according to the characteristic distribution diagrams of the above three types of acoustic emission signals.

[0084] Specifically, the probability density images obtained from the damage experiments on the epoxy resin, glass fiber and glass fiber / epoxy composite material (see Figure 7-9), in each figure: the green curve category No. 1 is valid data, and the red curve category No. 2 is noise data. From the figure, the amplitude, average frequency and center frequency parameter characteristics of various defect signals can be summarized, as shown in Table 3. And the conclusions drawn in this experiment are consistent with the theoretical analysis and experimental research results of other researchers. Studies generally believe that lower amplitudes correspond to brittle damage modes, including matrix cracking and fiber breakage; signals with high center frequency and average frequency values ​​correspond to fiber breakage, and lower center frequency and average frequency values ​​correspond to matrix cracking; larger amplitudes, lower center frequencies and average frequencies correspond to interface damage.

[0085] Therefore, three types of defect modes are identified according to the characteristics described in Table 3.

[0086] Table 3 Defect signal characteristics

[0087]

[0088] That is: according to the probability density diagram of amplitude, center frequency and average frequency, the acoustic emission signal with lower amplitude, lower average frequency and relatively low center frequency is identified as matrix damage signal; the acoustic emission signal with higher amplitude, lower average frequency and center frequency is identified as interface delamination signal; the acoustic emission signal with lower amplitude, higher average frequency and center frequency is identified as fiber breakage signal.

[0089] Specific as Figure 6 In the figure, cluster1 signal (blue curve) has lower amplitude, lower average frequency and relatively low center frequency, which is identified as matrix damage signal; cluster2 signal (red curve) has higher amplitude, lower average frequency and center frequency, which is identified as interface delamination signal; cluster3 signal (yellow curve) has lower amplitude, higher average frequency and center frequency, which is identified as fiber breakage signal.

[0090] Step S4, obtaining the cumulative count-load-time variation curve of each defect type, and dividing the damage development stage of the material sample to be tested according to the development characteristics of each defect.

[0091] Specifically, the damage development stage of the material sample to be tested is divided into three stages:

[0092] In the initial damage stage, there are very few signals of the three types of defects;

[0093] In the damage development stage, matrix damage and fiber breakage signals begin to appear and continue to appear throughout the damage development stage, and interface delamination signals are rare;

[0094] The damage intensifies to the stage of overall failure, and the matrix damage and fiber breakage signals continue to appear throughout the damage development stage; the interface delamination signal appears and surges until the overall failure of the material sample to be tested.

[0095] See also Figure 10-12 It can be seen that: with the increase of load and time, the number of various defect signals increases in different forms: within 0-100s, the matrix damage signal, fiber-matrix interface delamination signal and fiber breakage signal are relatively small; within 100-300s, matrix damage and fiber breakage signals begin to appear and continue to increase throughout the stage; interface delamination signals are very few; 300-400s: matrix damage and fiber breakage signals continue to increase, and interface delamination signals appear and surge.

[0096] Therefore, preferably, the duration of the initial damage stage is in the range of 0-100s; the duration of the damage development stage is in the range of 100-300s; and the duration of the damage aggravation to the overall failure stage is in the range of 300-400s.

[0097] Step S5, combining the acoustic emission positioning results of the material sample to be tested during the entire damage process, to obtain the distribution positions and development rules of different defects in the material sample to be tested during the damage process.

[0098] Specifically, in order to improve the accuracy of acoustic emission signal positioning, it is necessary to arrange at least two acoustic emission sensors in the acoustic emission signal collection experiment, and test the sound velocity of the material through the aforementioned lead breaking experiment, and achieve accurate positioning through the time difference between an acoustic signal reaching different sensors.

[0099] Combine again Figure 4 , the development rules of different defects can be specifically as follows:

[0100] 1. Initial damage stage (0-100s): There are very few signals of the three types of defects.

[0101] 2. Damage development stage (100-300s): Matrix damage and fiber breakage signals begin to appear and continue throughout the entire stage; there are few interface delamination signals.

[0102] 3. Damage intensifies to overall failure stage (300-400s): Matrix damage and fiber breakage signals continue to appear throughout the entire stage; interface delamination signals appear and surge until the overall failure of the material.

[0103] In specific implementation, a series of spherical equations can be constructed based on the time difference of signals received by three or more acoustic emission sensors, and their intersection is the location of the acoustic emission source. The sum of square errors between the time difference and the theoretical value can also be minimized according to the least squares method to solve the location of the acoustic emission source.

[0104] It can be clearly concluded from the above that the damage mechanism test method for glass fiber / epoxy composite materials provided in this embodiment obtains characteristic distribution diagrams of three types of acoustic emission signals by clustering analysis using data of three types of signal characteristics, namely amplitude, center frequency and average frequency, so as to more accurately identify three different defect modes, namely matrix damage, fiber-matrix interface delamination and fiber breakage, and by obtaining the cumulative count-load-time variation curve of each defect category, the present invention can accurately divide the stages of damage development according to the characteristics of defect development. This division helps to deeply understand the damage mechanism and provides an accurate scientific basis for the maintenance and replacement of materials.

[0105] The above embodiment may also include: step S6, taking a plurality of control samples that have not been damaged, applying loads to each of the control samples until each of the control samples reaches a different damage stage divided in step 4, and obtaining control samples at different damage development stages; the control samples have the same properties as the material samples to be tested.

[0106] Specifically, the control sample is guaranteed to have the same state and physical and chemical properties as the material sample to be tested, including shape, material, etc. The control sample can be a product from the same batch as the material sample to be tested. Since there are 3 damage stages, any 3 samples in the selected batch of products except the material sample to be tested can be used as control samples to verify whether the defect pattern recognition result is accurate.

[0107] The load applied to each of the control samples is consistent with the load applied to the material sample to be tested.

[0108] In the specific implementation, take the control sample that has not been damaged, load it until it reaches the different damage stages defined in step S4, and the loading conditions are the same as the original damage process in step S1 to obtain damaged samples at different stages: the material sample to be tested is stretched to 100s and then stretched to 300s and then stopped according to the experimental conditions described in step S1. The macroscopic morphology of the sample before stretching, the experimental process picture, and the macroscopic morphology of the sample after stretching are shown in Figure 1. Fig.13 As shown, Fig.13 (c) shows the states of stretching to fracture, stretching to 100s, and stretching to 300s from left to right.

[0109] Step S7, observe the defects inside the control sample at different damage stages, compare the observed defects with the results of defect pattern recognition in step 3, and verify whether the identification results of the defect pattern are accurate; if the observed results do not correspond to the results of defect pattern recognition in step 3, then improve the damage test method of the material sample to be tested, the noise reduction processing of the original acoustic emission signal, and the data processing method. For example, the friction between the test instrument and the hardware, and between the hardware and the sample can be reduced by improving the design of the experimental hardware, thereby reducing environmental noise.

[0110] It can be seen that the present invention verifies the accuracy of defect identification by observing the defects in samples at different damage stages through SEM and comparing them with the defects identified by pattern recognition. This experimental verification method improves the reliability of damage mechanism testing.

[0111] Combination Fig.14 and Fig.15 Specifically, the surface and cross-sectional morphologies of each of the control samples at different damage development stages are observed by SEM to obtain the defect distribution inside each of the control samples at different damage development stages.

[0112] Specifically, the surface and cross section of the damaged sample were observed respectively to visually observe the defect distribution inside the material at different damage stages. The cross section images of the sample stretched for 100s and 300s under SEM are as follows: Fig.13 As shown in the figure, there is almost no debonding phenomenon. The surface SEM of the sample is as follows Fig.14 The main damage modes observed are fiber breakage and matrix cracking, and only a small amount of resin matrix is ​​observed on the fiber surface, which corresponds to the small amount of fiber / matrix debonding signals in the early stage of stretching in the acoustic emission signal. The debonding phenomenon of the sample stretched for 300s is significantly more than that of the sample stretched for 100s. The observation results are consistent with the defect types of pattern recognition, verifying that the defect identification method is accurate and effective.

[0113] Analysis of the damage mechanism shows that matrix microcracks and fiber breakage appear at the beginning of stretching and continue until the end. This is because the matrix strength in the glass fiber / epoxy composite material is low and the fiber strength is more dispersed. Interfacial interlayer damage occurs more frequently in the middle and late stages of stretching. This is because the interface bonding force between the glass fiber and the resin matrix is ​​strong, and fiber / matrix debonding and fiber pull-out occur relatively late. In the early stage of stretching, less damage is generated inside the material, with only a small number of matrix microcracks and low-strength fibers breaking; in the middle stage of stretching, the number of matrix microcracks and fiber breakages increases rapidly, and interface delamination begins to appear. At this time, more damage begins to occur inside the sample, and the low strength of the matrix will produce a large number of microcracks. Fibers of different strengths are the main load-bearing mode in the stretching process at this time, and damage continues to occur as the stretching process proceeds; interface delamination surges in the middle and late stages of stretching, at which time cracks inside the sample may extend along the matrix / fiber interface, and debonding or fiber pullout occurs between the fibers and the matrix. The matrix loses the ability to transfer load to the fibers, and ultimately an unstable critical fracture surface is formed under the combined action of matrix cracks, fiber breakage, and fiber / matrix debonding until the material fails.

[0114] In summary, the damage mechanism test method of glass fiber / epoxy composite material provided by the present invention has the following beneficial effects:

[0115] 1. Improve the accuracy of damage identification: By using three key acoustic emission parameters, namely amplitude, center frequency and average frequency, for K-means clustering, the present invention can more accurately identify different defect modes such as matrix damage, fiber-matrix interface delamination and fiber breakage. Compared with single parameter analysis, this multi-parameter combined analysis method can more comprehensively capture damage characteristics and improve the accuracy of defect identification.

[0116] 2. Real-time monitoring and analysis of damage process: The method of the present invention can monitor the damage process of composite materials in real time. By acquiring the original acoustic emission signal of the entire damage process and classifying and identifying it in combination with the signal characteristics, real-time observation and analysis of the damage development are achieved. This real-time nature provides timely damage information to operation and maintenance personnel, which helps prevent material performance degradation.

[0117] 3. Accurate division of damage stages: By obtaining the cumulative count-load-time variation curve of each defect category, the present invention can accurately divide the stages of damage development according to the characteristics of defect development. This division helps to deeply understand the damage mechanism and provide a scientific basis for material maintenance and replacement.

[0118] 4. Verify the accuracy of defect identification: The present invention verifies the accuracy of defect identification by observing the defects in samples at different damage stages through SEM and comparing them with the defects identified by pattern recognition. This experimental verification method improves the reliability of damage mechanism research.

[0119] 5. Acquisition of damage distribution location and development law: Combined with the acoustic emission positioning results, the present invention can obtain the distribution location and development law of different defects in the damage process, which is of great significance for understanding the damage mechanism of materials and optimizing material design.

[0120] 6. Experimental data support: The effects of the present invention are not only supported by theoretical deduction, but also verified by the experimental data shown in the examples, which has significant technical progress and practical value.

[0121] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A damage mechanism test method for glass fiber / epoxy composite materials, characterized in that: include: Step 1, applying a load to the material sample to be tested to perform a damage experiment, so as to collect the original acoustic emission signal of the whole damage process of the material sample to be tested; Step 2, performing cluster analysis on the data of three types of signal features including amplitude, center frequency and average frequency in the original acoustic emission signal to obtain characteristic distribution diagrams of the three types of acoustic emission signals; Step 3, classifying and identifying the defect mode of the material sample to be tested according to the characteristic distribution diagrams of the above three types of acoustic emission signals; Step 4, obtaining the cumulative count-load-time variation curve of each defect type, and dividing the damage development stage of the material sample to be tested according to the development characteristics of each defect; Step 5, combining the acoustic emission positioning results of the material sample to be tested during the entire damage process, to obtain the distribution positions and development laws of different defects in the material sample to be tested during the damage process.

2. The damage mechanism test method of glass fiber / epoxy composite material according to claim 1, characterized in that: After step 1 and before step 2, the original acoustic emission signal is subjected to noise reduction processing.

3. The damage mechanism test method of glass fiber / epoxy composite material according to claim 1, characterized in that: In the step 2, a K-means clustering algorithm is used to cluster and classify the data including the three types of acoustic emission signal features, namely, amplitude, center frequency and average frequency, and a probability density map of the amplitude, center frequency and average frequency is obtained.

4. The damage mechanism test method of glass fiber / epoxy composite material according to claim 1, characterized in that: In step 3, an acoustic emission signal with a lower amplitude, a lower average frequency and a relatively lower center frequency is identified as a matrix damage signal; an acoustic emission signal with a higher amplitude, a lower average frequency and a center frequency is identified as an interface delamination signal; and an acoustic emission signal with a lower amplitude, a higher average frequency and a center frequency is identified as a fiber breakage signal.

5. The damage mechanism test method of glass fiber / epoxy composite material according to claim 4, characterized in that: In step 4, the damage development stage of the material sample to be tested is divided into three stages: In the initial damage stage, there are very few signals of the three types of defects; In the damage development stage, matrix damage and fiber breakage signals begin to appear and continue to appear throughout the damage development stage, and interface delamination signals are rare; The damage intensifies to the stage of overall failure, and the matrix damage and fiber breakage signals continue to appear throughout the damage development stage; the interface delamination signal appears and surges until the overall failure of the material sample to be tested.

6. The damage mechanism test method of glass fiber / epoxy composite material according to claim 5, characterized in that: The duration of the initial damage stage is in the range of 0-100s; the duration of the damage development stage is in the range of 100-300s; and the duration of the damage aggravation to the overall failure stage is in the range of 300-400s.

7. The damage mechanism test method of glass fiber / epoxy composite material according to claim 1, characterized in that: Also includes: Step 6, taking a plurality of control samples that have not been damaged, applying a load to each of the control samples until each of the control samples reaches a different damage stage divided in step 4, thereby obtaining control samples at different damage development stages; the control samples have the same properties as the material sample to be tested; Step 7, observing the defects inside the control samples at different damage stages, comparing the observed defects with the results of defect pattern recognition in step 3, and verifying whether the defect pattern recognition results are accurate.

8. The damage mechanism test method of glass fiber / epoxy composite material according to claim 7, characterized in that: The load applied to each of the control samples is consistent with the load applied to the material sample to be tested.

9. The damage mechanism test method of glass fiber / epoxy composite material according to claim 7, characterized in that: The surface and cross-sectional morphologies of each of the control samples at different damage development stages were observed by SEM to obtain the defect distribution inside each of the control samples at different damage development stages.

10. The damage mechanism test method of glass fiber / epoxy composite material according to claim 1, characterized in that: A lead breaking experiment is performed before step 1 to ensure that effective original acoustic emission signals are collected.

Images