CN113011057A - Method and system for predicting performance of aged bonding structure based on gradient degradation of adhesive layer - Google Patents
Method and system for predicting performance of aged bonding structure based on gradient degradation of adhesive layer Download PDFInfo
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Abstract
The invention belongs to the technical field of prediction of mechanical properties of bonding structures, and discloses a method and a system for predicting the performance of a bonding structure after aging based on adhesive layer gradient degradation. According to the invention, through the gradient degradation rule of the performance in the large-area adhesive layer surface under the damp and hot aging environment through the chemical analysis, the failure behavior of the aged composite material honeycomb sandwich bonding structure can be accurately and effectively simulated, and reference is provided for the safety design of the composite material honeycomb sandwich bonding structure.
Description
Technical Field
The invention belongs to the technical field of prediction of mechanical properties of bonding structures, and particularly relates to a method and a system for predicting the performance of an aged bonding structure based on gradient degradation of a glue layer.
Background
At present: the CFRP composite material honeycomb sandwich structure is formed by taking two layers of thin and strong carbon fiber reinforced composite material laminated plates as panels and sandwiching a layer of thick and extremely light honeycomb in the middle. The upper and lower skins and the core are usually bonded together with an adhesive to form an integral rigid bonded structure. The honeycomb sandwich structure has the advantages of light weight, high specific strength, high specific rigidity, vibration resistance, heat insulation, sound insulation and the like, can obtain a flat and smooth appearance by controlling a forming process, has excellent pneumatic performance, and is widely applied to aerospace, ships, buildings, automobiles, rail vehicles and the like. In the long-term service process of automobiles, the bonding structure is often subjected to the effects of environmental factors such as temperature, moisture, ultraviolet rays, salt fog and the like. The adhesive and the CFRP resin matrix are used as high molecular polymers, and the adhesive structure can be aged under the action of a long-term environment, so that the performance of the adhesive structure is reduced, and the safety of the whole vehicle is seriously influenced. At present, an effective means for predicting mechanical property and service life of an aged bonding structure is still lacked. The existing bonded structure durability research mainly adopts an artificial accelerated aging method to carry out aging on a bonded joint in a specific environment and in a specific time, and research on the change rule of the joint performance. Because the bonding area in a bonded joint is usually small, the bond line is generally regarded as reaching the same aging degree after aging, and the same failure condition is adopted by the whole bond line in finite element failure simulation.
However, in practical applications, the composite honeycomb sandwich structure generally has a large area, such as a trunk floor of a passenger car, a fuselage and a wing, a device bay floor of a high-speed motor train unit, an engine cover and the like, and therefore a large bonding area is required. In a hot and humid environment, moisture may penetrate along the bondline, the adhesive-substrate interface, and the composite. Considering that time is required for water to diffuse from the outer surface of the structure to the inside, and chemical reactions such as hydrolysis and plasticization of a high polymer material (an adhesive and a CFRP resin substrate) caused by the existence of water also consume a certain time, at the same aging time, the aging degree of each part in a large-area adhesive layer has a certain difference, and a material performance degradation gradient exists from the outer surface to the center of the adhesive layer. The whole glue layer adopts a unified failure criterion condition, so that the simulation result has errors, the performance of the bonding structure after aging cannot be accurately predicted, and the service life of the composite material honeycomb sandwich structure in practical application cannot be effectively evaluated.
Through the above analysis, the problems and defects of the prior art are as follows: the phenomenon of uneven performance degradation in the large-area adhesive layer surface is ignored by adopting a unified failure criterion condition for the whole adhesive layer at the same time, so that the simulation result has errors, the performance of the bonding structure after aging cannot be accurately predicted, and the service life of the composite material honeycomb sandwich structure in practical application cannot be effectively evaluated.
The difficulty in solving the above problems and defects is: the in-plane performance degradation mechanism of the large-area adhesive structure glue layer under the action of long-term damp and hot environment is complex, the performance change rule is not clear, and the degradation characteristic of the large-area adhesive structure glue layer is not evaluated quantitatively by an effective means at present. The significance of solving the problems and the defects is as follows: by implementing the method, the influence of the non-uniform degradation phenomenon of the performance of the large-area adhesive layer in the damp-heat aging process can be fully considered in the performance prediction of the bonding structure, and the failure behavior of the bonding structure of the honeycomb sandwich layer of the composite material after aging can be accurately and effectively simulated, so that the aging life prediction is realized. The safety problem caused by premature failure of the structure due to aging in the service process can be fully reduced, the material and the manufacturing cost can be saved, and reference is provided for the design of the bonding structure.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a method and a system for predicting the performance of an aged bonding structure based on glue layer gradient degradation.
The invention is realized in such a way that a method for predicting the performance of an aged bonding structure based on the gradient degradation of a glue layer comprises the following steps:
manufacturing a CFRP/aluminum alloy single lap joint and a CFRP honeycomb sandwich bonding structure, wherein the joint and the bonding structure adopt the same CFRP, aluminum alloy and adhesive;
selecting a typical damp-heat aging working condition according to the actual service environment of the vehicle, and carrying out artificial accelerated damp-heat aging on the single lap joint;
performing quasi-static tensile test on the aged bonding joint to obtain failure loads of the bonding joint in different aging times; extracting an adhesive sample from the joint section, performing FTIR test, and obtaining the light absorption intensity of functional groups at different aging times according to a spectrogram;
the joint failure load and the absorbance of the adhesive functional group are normalized by adopting a dispersion standardization method, so that the influence of different data dimensions is eliminated; screening out a characteristic functional group with the maximum correlation with the mechanical property of the joint through correlation analysis between dimensionless data of failure load and absorbance; fitting by adopting a least square method to respectively obtain a curve of the change rule of the joint failure load along with the aging time (called failure load change rule curve for short) and a curve of the change rule of the light absorption intensity of the characteristic functional group along with the aging time (called absorbance change rule curve for short);
taking a joint failure load curve as a target, and basically changing the absorbance of the characteristic functional group to obtain an optimal coincidence state function;
introducing a weight factor, linearly combining the optimal superposition state functions of the characteristic functional groups, and establishing a joint failure load prediction function;
defining a basic degradation factor according to a failure load prediction function;
manually accelerating damp-heat aging of the bonding structure for a specific time, peeling off the CFRP plate after the aging is finished, and calculating equivalent failure load in the adhesive layer surface of the bonding structure after the aging;
establishing a failure load prediction function based on the proportional length; defining a gradient factor and an in-plane degradation factor;
and establishing a bonding structure finite element model based on the cohesion unit, correcting the cohesion parameter according to the in-plane degradation factor, and realizing the aged bonding structure failure behavior simulation.
Further, the method for predicting the performance of the bonding structure after aging based on glue line gradient degradation defines the optimal coincidence state function A 'of all characteristic functional groups'k(t)：
A'k(t)＝akAk(t)+bkt+ck(k＝1,2,3L m)；
Wherein m is the number of characteristic functional groups; a isk、bkAnd ckRespectively corresponding scaling, rotation and translation basic transformation factors of the kth characteristic functional group; t is aging time; a. thek(t) is the absorbance change law curve function;
a functional is established as follows:
wherein F (t) is a joint failure load curve function. And obtaining scaling, rotation and translation factors corresponding to each characteristic functional group according to the extreme value condition of the functional, and determining the optimal superposition state function of each characteristic functional group.
Furthermore, the method for predicting the performance of the aged bonding structure based on the gradient degradation of the glue layer introduces a weight factor lambda to linearly combine the optimal superposition state functions of the characteristic functional groups. Defining a joint failure load prediction function P (t):
wherein the weight factor values are obtained by solving the extremum condition of the following functional.
Further, the method for predicting the performance of the aged bonding structure based on the gradient degradation of the glue layer defines a basic degradation factor according to a failure load prediction function:
further, the method for predicting the performance of the bonding structure after aging based on the gradient degradation of the adhesive layer carries out artificial accelerated damp-heat aging on the bonding structure for a specific time, peels off the CFRP board after aging is finished, takes the center of the adhesive layer as an original point, establishes a rectangular coordinate system, selects i measuring points at fixed intervals along an x axis, extracts an adhesive sample, and carries out FTIR test to obtain the light absorption strength value of a characteristic functional group of each measuring point. Substituting the absorbance intensity and the aging time of the characteristic functional group into a joint failure load prediction function to obtain an equivalent failure load value P corresponding to each point in the adhesive layer surface of the composite material honeycomb sandwich structurei。
Further, the method for predicting the performance of the aged bonding structure based on the gradient degradation of the glue layer establishes a failure load prediction function based on proportional length, and comprises the following steps: suppose a point A in the glue layer surface has a coordinate of (x)a,ya) Then, the coordinate (x) of the intersection point B of the line OA and the boundary of the glue layer is solved according to the following equation systemb,yb)：
Then the argument proportional length is defined:
respectively calculating the proportional length value l of each measuring pointiAccording to liAnd PiCorresponding relation between the two, fitting the failure load prediction function based on the proportional lengthP'(l)；
The method for predicting the performance of the aged bonding structure based on the gradient degradation of the glue layer defines a gradient factor and an in-plane degradation factor, and comprises the following steps: the gradient factor α is:
the in-plane degradation factor is then:
Dp＝αD0；
the cohesion parameter correction comprises the following steps: establishing a bonding structure finite element model based on the cohesion unit, and correcting the cohesion parameter according to the in-plane degradation factor:
P'coh＝DpPcoh＝αD0Pcoh；
wherein P iscohIs an initial cohesion parameter, P'cohCorrected cohesion parameters.
Another object of the present invention is to provide a system for predicting performance of an aged adhesive structure based on glue line gradient degradation, which implements the method for predicting performance of an aged adhesive structure based on glue line gradient degradation, the system comprising:
the structure manufacturing module is used for manufacturing a CFRP/aluminum alloy single lap joint and a CFRP honeycomb sandwich bonding structure, wherein the joint and the bonding structure adopt the same CFRP, aluminum alloy and adhesive;
the artificial accelerated damp-heat aging module is used for selecting a typical damp-heat aging working condition according to the actual service environment of the vehicle and carrying out artificial accelerated damp-heat aging on the single lap joint;
the quasi-static tensile test module is used for performing quasi-static tensile test on the aged bonding joint to obtain failure loads of the bonding joint in different aging times;
the adhesive chemical property testing module extracts an adhesive sample from the joint section, performs FTIR test, and obtains the light absorption intensity of functional groups with different aging times according to a spectrogram;
the correlation analysis module is used for carrying out normalization processing on joint failure load and the absorbance of the functional groups of the adhesive by adopting a dispersion standardization method so as to eliminate the influence of different data dimensions; screening out a characteristic functional group with the maximum correlation with the mechanical property of the joint through correlation analysis between dimensionless data of failure load and absorbance; respectively obtaining a change rule curve of the joint failure load along with the aging time and a change rule curve of the light absorption intensity of the characteristic functional group along with the aging time by adopting least square fitting;
the optimal coincidence state acquisition module is used for basically changing the absorbance of the characteristic functional group by taking a joint failure load curve as a target to acquire an optimal coincidence state function;
the joint failure load prediction function establishing module is used for introducing a weight factor, linearly combining the optimal superposition state functions of the characteristic functional groups and establishing a joint failure load prediction function;
the basic degradation factor definition module is used for defining a basic degradation factor according to the failure load prediction function;
the equivalent failure load calculation module in the adhesive layer surface of the bonding structure after aging is used for carrying out artificial accelerated damp-heat aging on the bonding structure for a specific time, peeling off the CFRP plate after the aging is finished, and calculating the equivalent failure load in the adhesive layer surface of the bonding structure after aging;
the gradient factor and in-plane degradation factor definition module is used for establishing a failure load prediction function based on the proportional length; defining a gradient factor and an in-plane degradation factor;
and the cohesion parameter correction and failure simulation module is used for establishing a cohesion unit-based bonding structure finite element model, correcting the cohesion parameter according to the in-plane degradation factor and realizing the aged bonding structure failure behavior simulation.
By combining all the technical schemes, the invention has the advantages and positive effects that: when the aging bonding structure failure simulation is carried out, assignment is carried out according to the corrected internal cohesion parameter, so that the performance degradation of the in-plane adhesive layer is realized, and the aging behavior of the large-area bonding structure in a damp-heat environment is simulated more accurately and effectively. The method can more accurately and effectively simulate the failure behavior of the composite material honeycomb sandwich bonding structure after aging, and realizes the aging life prediction, thereby providing reference for the life safety design of the composite material bonding structure. The accurate prediction of the service life of the bonding structure not only can fully reduce the safety problem caused by the premature failure of the structure due to aging in the service process, but also can save materials and manufacturing cost.
Drawings
Fig. 1 is a flowchart of a method for predicting performance of an aged bonding structure based on gradient degradation of a glue layer according to an embodiment of the present invention.
FIG. 2 is a schematic view of a single lap joint provided by an embodiment of the present invention;
in fig. 2: 1. an aluminum plate; 2. an adhesive; 3. CFRP.
FIG. 3 is a structural diagram of a CFRP honeycomb sandwich bonding structure provided by an embodiment of the invention;
in fig. 3: 4. an aluminum honeycomb core.
Figure 4 is a graph of single lap joint failure load for different aging times as provided by an embodiment of the present invention.
FIG. 5 is a FTIR spectrum of an adhesive with different aging times provided by an embodiment of the present invention.
FIG. 6 is a plot of the correlation coefficient of adhesive functional group absorbance versus single lap joint failure load provided by an example of the present invention.
Fig. 7 is a schematic diagram of a coordinate system of a glue layer of the bonding structure according to the embodiment of the invention.
FIG. 8 is a diagram of a method for predicting performance of an aged bonding structure based on gradient degradation of a glue layer according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Aiming at the problems in the prior art, the invention provides a method for predicting the performance of an aged bonding structure based on glue line gradient degradation, and the method for predicting the performance of the aged bonding structure based on glue line gradient degradation is described in detail below with reference to the accompanying drawings.
As shown in fig. 1, the method for predicting the performance of the aged bonding structure based on the gradient degradation of the glue layer according to the embodiment of the present invention includes the following steps:
s101: manufacturing a CFRP/aluminum alloy single lap joint and a CFRP honeycomb sandwich bonding structure, wherein the joint and the bonding structure adopt the same CFRP, aluminum alloy and adhesive;
s102: selecting a typical damp-heat aging working condition according to the actual service environment of the vehicle, and carrying out artificial accelerated damp-heat aging on the single lap joint;
s103: performing quasi-static tensile test on the aged bonding joint to obtain failure loads of the bonding joint in different aging times; extracting an adhesive sample from the joint section, performing FTIR test, and obtaining the light absorption intensity of functional groups at different aging times according to a spectrogram;
s104: the joint failure load and the absorbance of the adhesive functional group are normalized by adopting a dispersion standardization method, so that the influence of different data dimensions is eliminated; screening out a characteristic functional group with the maximum correlation with the mechanical property of the joint through correlation analysis between dimensionless data of failure load and absorbance; respectively obtaining a change rule curve of the joint failure load along with the aging time and a change rule curve of the light absorption intensity of the characteristic functional group along with the aging time by adopting least square fitting;
s105: taking a joint failure load curve as a target, and basically changing an absorbance curve of each characteristic functional group to obtain an optimal coincidence state function;
s106: introducing a weight factor, linearly combining the optimal superposition state functions of the characteristic functional groups, and establishing a joint failure load prediction function;
s107: defining a basic degradation factor according to a failure load prediction function;
s108: manually accelerating damp-heat aging of the bonding structure for a specific time, peeling off the CFRP plate after the aging is finished, and calculating equivalent failure load in the adhesive layer surface of the bonding structure after the aging;
s109: establishing a failure load prediction function based on the proportional length; defining a gradient factor and an in-plane degradation factor;
s110: and establishing a bonding structure finite element model based on the cohesion unit, correcting the cohesion parameter according to the in-plane degradation factor, and realizing the aged bonding structure failure behavior simulation.
One skilled in the art can also use other steps to implement the method for predicting the performance of the aged bonding structure based on the glue line gradient degradation, and the method for predicting the performance of the aged bonding structure based on the glue line gradient degradation provided by the present invention shown in fig. 1 is only one specific example.
The technical solution of the present invention is further described below with reference to the accompanying drawings.
As shown in fig. 2 to 3, the single lap joint includes: the aluminum plate comprises an aluminum plate 1, an adhesive 2 and a CFRP 3, wherein the aluminum plate 1 is connected with the CFRP 3 through the adhesive 2; the CFRP honeycomb sandwich bonding structure comprises: adhesive 2, CFRP 3, aluminum honeycomb core 4 passes through adhesive 2 and is connected with CFRP 3. In step S101, the method for manufacturing a CFRP/aluminum alloy single lap joint and a CFRP honeycomb sandwich bonding structure provided in the embodiment of the present invention includes: selecting two-component epoxy resin adhesive
2015. CFRP and 6061 aluminum alloy. Wherein the CFRP model is T300/YPH-23, and the laminating sequence of the laminated plate is [ (0/90)/0/90/0/90/0/90/(0/90)]The thickness of a single layer is about 0.25mm, the number of the single layer is 8, and the sizes of the aluminum plate and the CFRP plate in the single lap joint are 100mm multiplied by 25mm multiplied by 2 mm; the size of the adhesive is 25mm multiplied by 0.2mm, and the size of a CFRP panel in the CFRP honeycomb sandwich bonding structure is 150mm multiplied by 2 mm; the wall thickness of the aluminum honeycomb core is 0.06mm, the height of the aluminum honeycomb core is 20mm, and the side length of the regular hexagonal honeycomb core unit is 6 mm; the size of the adhesive is 150mm multiplied by 0.2mm, in order to ensure effective bonding, the surface of the honeycomb aluminum is subjected to sand blasting, the surface of the CFRP is ground by using sand paper, and the bonding surface is cleaned by using an acetone solvent before bonding. The bonding of the test piece requires curing at a high temperature of 80 ℃ for 2 hours.
In step S102, the joint aging test provided in the embodiment of the present invention includes: and selecting a typical damp-heat aging working condition according to the actual service environment of the vehicle, and carrying out artificial accelerated damp-heat aging on the single lap joint.
As shown in fig. 4 to fig. 5, in step S103, the joint mechanical property test and the adhesive FTIR test provided by the embodiment of the present invention include: and after the aging is finished, the joint is placed in a room temperature environment for 24 hours, then an electronic universal testing machine is used for carrying out quasi-static mechanical property test, the tensile speed of the testing machine is 1mm/min, and each group of the testing machines is repeated for five times to obtain the failure loads of the adhesive joint with different aging times. And extracting an adhesive sample from the joint section, performing FTIR test, and repeating the test for three times in each group of test to obtain FTIR spectrograms of the adhesive with different aging times.
As shown in fig. 6, in step S104, the screening of the feature functional group provided by the embodiment of the present invention includes: and (4) carrying out normalization processing on the joint failure load and the functional group absorbance data by adopting SPSS software, and carrying out correlation analysis. When the absolute value of the correlation coefficient r is greater than 0.8, the corresponding functional group is defined as a characteristic functional group, and is considered to have a significant correlation with the joint failure strength. The results of the correlation analysis are shown in FIG. 6. Characteristic functional groups that are therefore highly correlated with the load to failure of a single lap joint are hydroxyl, ester, carbonyl and epoxy (corresponding to wave numbers of 3325cm each)-1、1736cm-1、1648cm-1And 914cm-1)。
In step S105, the basic transformation of the absorbance curve of the functional group provided in the embodiment of the present invention includes: by writing a FORTRAN program and calculating basic transformation factors in the optimal superposition state function of each characteristic functional group by adopting a trapezoidal and Simpson integration method and the like, the obtained curve function after the transformation of hydroxyl, ester, carbonyl and epoxy absorbance is as follows:
A'1(t)＝-0.8145A1(t)+0.0022t+0.6426；
A'2(t)＝0.8628A2(t)-0.0018t+0.1149；
A'3(t)＝-2.0123A3(t)+0.0209t+0.8149；
A'4(t)＝0.5421A4(t)-0.0092t+0.4079；
in step S106, the establishing of the joint failure load prediction function provided in the embodiment of the present invention includes: and introducing a weight factor lambda, and linearly combining the optimal superposition state functions of the characteristic functional groups. Defining a joint failure load prediction function P (t) as shown in the formula:
wherein the weight factor values are obtained by solving the extremum condition of the following functional.
The final set-up joint failure load prediction function is shown below:
P(t)＝-0.2372A1(t)+2.0384A2(t)+1.3045A3(t)-0.5518A4(t)-0.0079t-0.4849
in step S107, the defining of the basic degradation factor provided in the embodiment of the present invention includes: the time-varying base degradation factor function is:
as shown in fig. 7, in step S108, the calculating the equivalent failure load in the glue layer surface of the aged bonding structure according to the embodiment of the present invention includes: after 60 days of damp heat aging, the bonded structure was left in a room temperature environment for 24 hours, and then the CFRP panel was peeled off. And (3) selecting a measuring point at an interval of 25mm along the x axis in the adhesive layer surface, and extracting an adhesive infrared test sample from 7 measuring points (the numbers of the measuring points along the x axis in the forward direction are respectively 1-7). In order to ensure effectiveness, 5 points are selected near the measuring points for FTIR measurement, the average value is taken as a final result and substituted into a joint failure load prediction function, and equivalent failure load values P corresponding to the measuring points are obtained1＝1.1378、P2＝0.5829、P3＝0.4012、P4＝0.2312、P5＝0.1823、P6＝0.0822、P7＝0.0215。
In step S108, the establishing of the failure load prediction function based on the proportional length provided in the embodiment of the present invention includes: and calculating the proportional length of each measuring point according to the coordinate of each measuring point. Specifically are respectively l1＝0.0000、l2＝0.1667、l3＝0.3333、l4＝0.5000、l5＝0.6667、l6＝0.8333、l71.0000. Fitting by using a quadratic polynomial comparison ratio length and a relation before the equivalent failure load to obtain a failure load prediction function based on the ratio length as follows:
P'(l)＝1.0848l2-2.1261l+1.0869；
in step S109, the defining the gradient factor and the in-plane degradation factor provided in the embodiment of the present invention includes: respectively calculating to obtain a gradient factor and an in-plane degradation factor as follows:
α(l)＝0.9534l2-1.8686l+0.9553；
as shown in fig. 8, in step S111, the cohesion parameter modification provided by the embodiment of the present invention includes: and establishing a bonding structure finite element model based on the cohesion unit, and correcting the cohesion parameter according to the in-plane degradation factor. As shown in the formula:
P'coh＝DpPcoh＝αD0Pcoh；
wherein P iscohIs an initial cohesion parameter, P'cohCorrected cohesion parameters. And when the aging bonding structure is subjected to failure simulation, assigning according to the corrected internal cohesion parameter, thereby realizing the performance degradation of the in-plane adhesive layer. Compared with the test result, the simulation result obtained by the method has higher accuracy (the precision is improved by more than 5%) than that obtained by adopting the unified failure rule in the whole planeThe aging behavior of the large-area bonding structure in a damp and hot environment can be simulated more accurately and effectively.
It should be noted that the embodiments of the present invention can be realized by hardware, software, or a combination of software and hardware. The hardware portion may be implemented using dedicated logic; the software portions may be stored in a memory and executed by a suitable instruction execution system, such as a microprocessor or specially designed hardware. Those skilled in the art will appreciate that the apparatus and methods described above may be implemented using computer executable instructions and/or embodied in processor control code, such code being provided on a carrier medium such as a disk, CD-or DVD-ROM, programmable memory such as read only memory (firmware), or a data carrier such as an optical or electronic signal carrier, for example. The apparatus and its modules of the present invention may be implemented by hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., or by software executed by various types of processors, or by a combination of hardware circuits and software, e.g., firmware.
The above description is only for the purpose of illustrating the present invention and the appended claims are not to be construed as limiting the scope of the invention, which is intended to cover all modifications, equivalents and improvements that are within the spirit and scope of the invention as defined by the appended claims.
Claims (7)
1. The method for predicting the performance of the bonding structure after aging based on the gradient degradation of the glue layer is characterized by comprising the following steps of:
manufacturing a CFRP/aluminum alloy single lap joint and a CFRP honeycomb sandwich bonding structure, wherein the joint and the bonding structure adopt the same CFRP, aluminum alloy and adhesive;
selecting a typical damp-heat aging working condition according to the actual service environment of the vehicle, and carrying out artificial accelerated damp-heat aging on the single lap joint;
performing quasi-static tensile test on the aged bonding joint to obtain failure loads of the bonding joint in different aging times; extracting an adhesive sample from the joint section, performing FTIR test, and obtaining the light absorption intensity of functional groups at different aging times according to a spectrogram;
the joint failure load and the absorbance of the adhesive functional group are normalized by adopting a dispersion standardization method, so that the influence of different data dimensions is eliminated; screening out a characteristic functional group with the maximum correlation with the mechanical property of the joint through correlation analysis between dimensionless data of failure load and absorbance; respectively obtaining a change rule curve of the joint failure load along with the aging time and a change rule curve of the light absorption intensity of the characteristic functional group along with the aging time by adopting least square fitting;
taking a joint failure load curve as a target, and basically changing an absorbance curve of each characteristic functional group to obtain an optimal coincidence state function;
introducing a weight factor, linearly combining the optimal superposition state functions of the characteristic functional groups, and establishing a joint failure load prediction function;
defining a basic degradation factor according to a failure load prediction function;
manually accelerating damp-heat aging of the bonding structure for a specific time, peeling off the CFRP plate after the aging is finished, and calculating equivalent failure load in the adhesive layer surface of the bonding structure after the aging;
establishing a failure load prediction function based on the proportional length; defining a gradient factor and an in-plane degradation factor;
and establishing a bonding structure finite element model based on the cohesion unit, correcting the cohesion parameter according to the in-plane degradation factor, and realizing the aged bonding structure failure behavior simulation.
2. The method for predicting performance of adhesive bonding structure after aging based on glue line gradient degradation as claimed in claim 1, wherein the method for predicting performance of adhesive bonding structure after aging based on glue line gradient degradation defines an optimal coincidence state function A 'of each characteristic functional group'k(t)：
A'k(t)＝akAk(t)+bkt+ck(k＝1,2,3Lm)；
Wherein m is the number of characteristic functional groups; a isk、bkAnd ckRespectively corresponding scaling, rotation and translation basic transformation factors of the kth characteristic functional group; t is aging time; a. thek(t) is the absorbance change law curve function;
a functional is established as follows:
and F (t) is a joint failure load curve function, and the scaling, rotation and translation factors corresponding to each characteristic functional group are obtained according to the functional extreme value condition, so that the optimal coincidence state function of each characteristic functional group is determined.
3. The method for predicting the performance of the bonding structure after aging based on the gradient degradation of the glue layer according to claim 1, wherein a weighting factor λ is introduced into the method for predicting the performance of the bonding structure after aging based on the gradient degradation of the glue layer, the optimal coincidence state functions of the characteristic functional groups are linearly combined, and a joint failure load prediction function P (t) is defined as follows:
wherein the weight factor value is obtained by solving an extremum condition of a functional
4. The method for predicting the performance of the aged bonding structure based on the glue line gradient degradation as claimed in claim 1, wherein the method for predicting the performance of the aged bonding structure based on the glue line gradient degradation defines a basic degradation factor according to a failure load prediction function:
5. the method for predicting the performance of the aged bonding structure based on the glue line gradient degradation as claimed in claim 1, wherein the method for predicting the performance of the aged bonding structure based on the glue line gradient degradation is used for performing artificial accelerated humid heat aging on the bonding structure for a specific time, peeling off a CFRP (carbon fiber reinforced polymer) plate after the aging is completed, establishing a rectangular coordinate system with the center of the glue line as an origin, selecting i measuring points at fixed intervals along an x axis, extracting a glue sample, performing FTIR (infrared spectroscopy) testing to obtain the light absorption intensity value of a characteristic functional group of each measuring point, and substituting the light absorption intensity of the characteristic functional group and the aging time into a joint failure load prediction function to obtain an equivalent failure load value P corresponding to each point in the glue line of the composite material honeycomb sandwich structurei。
6. The method for predicting the performance of the aged bonding structure based on the glue line gradient degradation as claimed in claim 1, wherein the method for predicting the performance of the aged bonding structure based on the glue line gradient degradation establishes a proportional length-based failure load prediction function, and comprises the following steps: suppose a point A in the glue layer surface has a coordinate of (x)a,ya) Then, the coordinate (x) of the intersection point B of the line OA and the boundary of the glue layer is solved according to the following equation systemb,yb)：
Then the argument proportional length is defined:
respectively calculating the proportional length value l of each measuring pointiAccording to liAnd PiFitting a failure load prediction function P' (l) based on the proportional length;
the method for predicting the performance of the aged bonding structure based on the gradient degradation of the glue layer defines a gradient factor and an in-plane degradation factor, and comprises the following steps: the gradient factor α is:
the in-plane degradation factor is then:
Dp＝αD0；
the cohesion parameter correction comprises the following steps: establishing a bonding structure finite element model based on the cohesion unit, and correcting the cohesion parameter according to the in-plane degradation factor:
P′coh＝DpPcoh＝αD0Pcoh；
wherein P iscohIs an initial cohesion parameter, P'cohCorrected cohesion parameters.
7. The system for predicting the performance of the aged bonding structure based on the gradient degradation of the glue layer is characterized by comprising the following steps of:
the structure manufacturing module is used for manufacturing a CFRP/aluminum alloy single lap joint and a CFRP honeycomb sandwich bonding structure, wherein the joint and the bonding structure adopt the same CFRP, aluminum alloy and adhesive;
the artificial accelerated damp-heat aging module is used for selecting a typical damp-heat aging working condition according to the actual service environment of the vehicle and carrying out artificial accelerated damp-heat aging on the single lap joint;
the quasi-static tensile test module is used for performing quasi-static tensile test on the aged bonding joint to obtain failure loads of the bonding joint in different aging times;
the adhesive chemical property testing module extracts an adhesive sample from the joint section, performs FTIR test, and obtains the light absorption intensity of functional groups with different aging times according to a spectrogram;
the correlation analysis module is used for carrying out normalization processing on joint failure load and the absorbance of the functional groups of the adhesive by adopting a dispersion standardization method so as to eliminate the influence of different data dimensions; screening out a characteristic functional group with the maximum correlation with the mechanical property of the joint through correlation analysis between dimensionless data of failure load and absorbance; respectively obtaining a change rule curve of the joint failure load along with the aging time and a change rule curve of the light absorption intensity of the characteristic functional group along with the aging time by adopting least square fitting;
the optimal coincidence state acquisition module is used for basically changing the absorbance of the characteristic functional group by taking a joint failure load curve as a target to acquire an optimal coincidence state function;
the joint failure load prediction function establishing module is used for introducing a weight factor, linearly combining the optimal superposition state functions of the characteristic functional groups and establishing a joint failure load prediction function;
the basic degradation factor definition module is used for defining a basic degradation factor according to the failure load prediction function;
the equivalent failure load calculation module in the adhesive layer surface of the bonding structure after aging is used for carrying out artificial accelerated damp-heat aging on the bonding structure for a specific time, peeling off the CFRP plate after the aging is finished, and calculating the equivalent failure load in the adhesive layer surface of the bonding structure after aging;
the gradient factor and in-plane degradation factor definition module is used for establishing a failure load prediction function based on the proportional length; defining a gradient factor and an in-plane degradation factor;
and the cohesion parameter correction and failure simulation module is used for establishing a cohesion unit-based bonding structure finite element model, correcting the cohesion parameter according to the in-plane degradation factor and realizing the aged bonding structure failure behavior simulation.
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