CN113688544B - Active and passive combined quantitative identification method for damage of composite material - Google Patents
Active and passive combined quantitative identification method for damage of composite material Download PDFInfo
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Abstract
The invention discloses a quantitative identification method of active and passive combined composite material damage, which comprises the steps of firstly constructing a structure virtual numerical model based on an undamaged structure through measurement information such as geometry, quality, static characteristics, dynamic response and the like, and measuring corresponding basic signals; secondly, aiming at a damaged structure, judging the occurrence position of the damage by using an active excitation signal of a piezoelectric sensor and adopting a time reversal imaging method; and finally, constructing a damage variable based on rigidity reduction based on damage mechanics for the position where the damage occurs, and quantitatively identifying the damage by utilizing a passive static response signal and a passive dynamic response signal. Based on the method, quantitative identification can be performed on damage of the composite material, and the obtained identification result can more accurately reflect the residual mechanical properties of the structure, so that guidance is provided for a control strategy and a maintenance strategy of a subsequent structure.
Description
Technical Field
The invention relates to the technical field of aerospace, in particular to a method for quantitatively identifying damage of a composite material by active and passive combination.
Background
In aerospace engineering, due to design requirements of advanced aircrafts such as aerospace shuttle aircrafts, new generation fighters and the like, which are set forth by working environments such as long endurance, light weight, large overload, wide Mach, multi-task section, strong robustness and high reliability, composite materials with high specific strength and high specific stiffness are widely applied. However, advanced aircrafts are inevitably influenced by unsafe factors such as fatigue, large overload, impact and the like in the long-term service process, so that the composite material engine body structure is damaged.
In order to reduce further loss caused by damage and destruction and ensure the structural safety performance of the advanced aircraft, the structural health state needs to be detected or monitored in real time. The traditional nondestructive testing method has the limitations of equipment and use environment, has long testing period and requires equipment to be stopped; the active monitoring method based on the fluctuation theory can only estimate the damage position, and can not further judge the damage degree; monitoring methods based on vibration theory face the challenges of multiple damage variables and strong problem discomfort.
Disclosure of Invention
The invention aims to solve the technical problems that: the method overcomes the defects that the damage degree cannot be judged and the discomfort is strong in the prior art, provides a composite material damage quantitative identification method based on active and passive combination, comprehensively adopts an active monitoring method based on a fluctuation theory and a passive monitoring method based on a static response and a vibration theory, comprehensively uses various sensors such as a piezoelectric sheet sensor, a resistance strain sensor and the like, quantitatively identifies the damage of the composite material, and can more accurately reflect the residual mechanical property of the structure according to the identification result, and provides guidance for a control strategy and a maintenance strategy of a subsequent structure.
The invention adopts the technical scheme that: a method for quantitatively identifying damage of a composite material by active and passive combination comprises the following implementation steps:
the first step: establishing a damage identification basic numerical model of a composite material identification object in a damage-free state, establishing the geometric shape of the damage identification basic numerical model by geometric shape measurement on the identification object, determining the material density of the damage identification basic numerical model by weight measurement on the identification object, correcting the material rigidity of the damage identification basic numerical model by stress response measurement of static load test on the identification object, and correcting the boundary rigidity loaded by the numerical model structure by natural frequency measurement of dynamic response test on the identification object;
and a second step of: arranging piezoelectric sensors and resistive strain sensors on the identification object, wherein the piezoelectric sensors are distributed uniformly in a monitoring area for the arrangement of active sensors, and surround the area where damage is likely to occur; the resistive strain sensor is a passive sensor, the resistive strain sensor is arranged in each area where damage is likely to occur, and the resistive strain sensor is additionally arranged in the area where damage is likely to occur due to stress concentration or large load;
and a third step of: the piezoelectric sensor and the resistance strain sensor which are arranged in the second step are adopted to measure a basic signal in a non-damaged state, wherein the basic signal comprises a piezoelectric sensor signal generated by excitation of structural Lamb waves (namely Lamb waves) in a non-load state, a piezoelectric sensor signal generated by excitation of the structural Lamb waves in a rated load state, a structural strain sensor signal in the rated load state and a dynamic response signal of a free vibration strain sensor excited under the action of force hammer striking;
fourth step: the piezoelectric sensor arranged in the second step is adopted to measure an active excitation signal after damage occurs, wherein the active excitation comprises a piezoelectric sensor signal generated by structural Lamb wave excitation in a non-load state after damage occurs and a piezoelectric sensor signal generated by structural Lamb wave excitation in a rated load state after damage occurs;
fifth step: the resistive strain sensor arranged in the second step is adopted to measure a static response signal and a dynamic response signal of the structure after the damage occurs, and specifically refers to a static response strain sensor signal of the structure under a rated load state after the damage occurs and a free vibration strain sensor signal under the force hammer striking excitation;
sixth step: determining the damage position of the identification object by adopting a time reversal focusing imaging method based on the basic signal obtained by the measurement in the third step and the active excitation signal obtained by the measurement in the fourth step;
seventh step: based on the damage identification basic numerical model established in the first step, carrying out parameterization modification on the rigidity parameters of the finite element units at the damage occurrence position according to the damage position determined in the sixth step through a damage quantification model to obtain a damage identification correction model; the damage identification correction model has the following characteristics: (1) In the region where the damage occurs, the finite element stiffness parameters of the damage model can be modified; (2) When the damage variable is set to 0, i.e. no damage occurs, the structural static strain response and the free vibration excitation response are consistent with the basic signal measurement result;
eighth step: and obtaining the situation that the analysis result is closest to the measured damage result by using a differential format gradient iteration method or a gradient-free mode search method, wherein the obtained damage variable is the damage quantification result.
In the third step, the basic signal in the undamaged state and the measured response signals after damage in the fourth step and the fifth step are generated by active excitation of piezoelectric sensors, lamb wave signals (the piezoelectric sensors are not only one, and other piezoelectric sensors are not excited when one is excited), static load generated by loading of a static testing machine, static response signals measured by a resistance strain gauge and dynamic response signals measured by a force sensor and a resistance strain sensor are generated by knocking; wherein Lamb wave signals are active excitation signals, static response signals and passive response signals are passive response signals, and one of active and passive combination features means that the two signals are combined.
In the sixth step, the time reversal focusing imaging method is specifically as follows:
(1) The measured signal response after damage is differenced with the measured signal response before damage to obtain a difference signal;
(2) Inverting the time phase of the difference signal;
(3) Selecting one point in the monitoring area, calculating a signal phase translation distance according to the position of the selected monitoring point and the distance between the sensor and the received signal, and carrying out phase translation on the signal;
(4) Superposing a plurality of groups of signals after phase shift, and square integrating the superposed signals;
(5) Selecting another point in the monitoring area and repeating (3) - (4) until all points in the area are calculated;
(6) Normalizing the signal calculated value in the detection area, imaging the result as the pixel value of the point, and obtaining the area with the maximum pixel value as the identification damage area.
In the seventh step, based on the damage identification basic model, the rigidity performance of the finite element unit of the damage identification basic model at the damage occurrence position is recalculated and modified according to the damage quantification model to obtain the relation between the rigidity matrix of the damage unit and the damage variable, the modified finite element model is the damage identification correction model, the damage quantification model adopts the theory of damage mechanics, the rigidity reduction amount is used as the damage variable to quantitatively identify the residual characterization rigidity of the damage unit in the finite element model, and the quantitative description and the identification characterization rigidity description of the damage of the composite material are realized by the following formula:
E d ＝E m (1-d)
in E d To damage stiffness, i.e. characterize stiffness, E m For stiffness of isotropic material when no damage occurs, d is a damage variable, and for constitutive relation of the symmetrically-paved composite laminated plate, the complete expression is as follows:
B＝0
wherein A is the tensile stiffness matrix of the laminated plate, B is the stretch bending coupling stiffness matrix of the laminated plate, D is the bending stiffness matrix of the laminated plate, H is the shearing stiffness matrix of the laminated plate, and D 1 ～d 14 For the lesion variable to be identified, A ij (i，j＝1，2，6)，D ij (i，j＝1，2，6)，H ij (i, j=4, 5) represents the in-plane stiffness coefficient, the bending stiffness coefficient, and the shear stiffness coefficient of the laminate, respectively.
Compared with the prior art, the invention has the advantages that: the invention comprehensively utilizes the active excitation type piezoelectric sensor signal and the passive resistance strain sensor signal, combines the Lamb wave imaging positioning method based on the fluctuation method and the rigidity reduction type damage quantification method based on model reconstruction, and realizes the damage quantification identification method for the composite material structure. Compared with the traditional damage identification method based on the fluctuation method, the method adopts the subsequent damage quantification method, breaks through the barrier that damage quantification identification cannot be performed, and realizes damage quantification identification; compared with the traditional vibration modeling method, the method has the advantages that the quantity of parameters to be identified is reduced by adopting the pre-positioning damage, and the barriers of low solving precision and low solving efficiency caused by high discomfort in the solving process are broken through.
Drawings
FIG. 1 is a flow chart of a method for quantitatively identifying damage to a composite material by active and passive combination according to the present invention;
FIG. 2 is a schematic diagram of a time-reversal imaging method used in the present invention.
Detailed Description
The invention is further described below with reference to the drawings and detailed description.
As shown in fig. 1, the invention relates to a method for quantitatively identifying damage of a composite material by active and passive combination, which mainly comprises the following steps:
(1) A lesion recognition model is determined. And establishing a damage identification basic numerical model when the identification object is in a damage state, wherein the numerical model takes the finite element model as a main object. The method comprises the steps of measuring and correcting the geometric shape of a finite element model through the geometric shape of an identification object, measuring and correcting the density of a material through the weight of the identification object, measuring and correcting the rigidity of the material through the stress response of the identification object through a static load test, and measuring and correcting the rigidity of the boundary of a structure through the natural frequency of the identification object through a dynamic response test.
The geometric dimension is directly obtained through measurement, the material density is obtained through the established geometric model dimension and the measured weight, and the material rigidity and the boundary rigidity are subjected to inverse problem identification through a finite element operation optimization method.
find E m ，E b
s.t.min∑λ(ε c -ε m ) 2
Wherein E is m Refers to material stiffness, E b Refer to boundary stiffness, ε c Refers to finite element analysis strain results, ε m Refers to the measurement of strain results, λ being the weight coefficient.
According to the geometric dimension of structure measurement, a corresponding geometric dimension model is established in a finite element software preprocessor, a two-dimensional finite element model is established for a composite material laminated board structure, a SHELL181 unit type is selected, anisotropic material properties are given to the composite material laminated board structure to simulate composite material properties, material properties rigidity is given by a material processing side, material density properties are given by weighing an electronic scale, a structure clamped boundary is not completely clamped, a spring unit is added to simulate the non-completely clamped boundary condition, a dynamic identification system is used for identifying structural modal frequency, and an optimization analysis method is used for calculating the structure boundary clamped rigidity and the material rigidity properties.
(2) A sensor arrangement is determined. The active piezoelectric sensors are arranged in the area to be identified, the distribution is basically uniform, the arrangement distance of the sensors is determined by measuring the elastic wave velocity of the structure, the area where damage is likely to occur is surrounded by the piezoelectric sensors, necessary strain sensors are arranged in each area, and the strain sensors are additionally arranged in the area with high damage possibility for the stress state caused by the structural characteristics.
The method comprises the steps of carrying out finite element analysis on a structural model, selecting a point with higher strain level or stress level in the first few modes as a resistive strain sensor arrangement point, calculating the stress state of the structure in the working state, and arranging a resistive strain sensor in a high strain level or high stress level region in the working state; the piezoelectric sensors are uniformly arranged on the surface of the structure, the propagation speed of Lamb on the surface of the structure is obtained through simulation analysis and calculation or through experimental measurement, and the distance of the arrangement of the piezoelectric sensors is determined, so that the propagation time of Lamb waves is longer than the excitation time of a complete excitation signal, and the complete reception of the signal is ensured.
(3) The basal signal in the undamaged state is measured. The basic signal comprises a piezoelectric sensor signal generated by excitation of structural Lamb waves in a no-load state; piezoelectric sensing signals generated by excitation of structural Lamb waves under a rated load state; structural strain sensor signals under rated load conditions; free vibration strain sensor signal excited by the force hammer strike.
(4) The active excitation signal after the occurrence of the injury is measured. The active excitation signals after the damage comprises piezoelectric sensor signals generated by structural Lamb wave excitation in a non-load state after the damage and piezoelectric sensor signals generated by structural Lamb wave excitation in a rated load state after the damage.
(5) And measuring structural static response and dynamic response signals after damage occurs. The static response signal and the dynamic response signal of the structure after the damage occurs refer to a static response strain sensor signal of the structure under the rated load state after the damage occurs and a free vibration strain sensor signal under the force hammer striking excitation.
(6) And determining the damage position by using a time reversal focusing imaging method according to the basic signal and the active excitation signal.
As shown in FIG. 2, PZT1-PZT4 are arranged piezoelectric sensors, damage is the position where damage occurs, and monitoring points are scanned point by point in a damage monitoring area; the time reversal focusing imaging method is to use the reversibility of wave propagation to perform time reversal on elastic wave signals measured by piezoelectric sensors, consider the multi-measuring point signals as signal sources to be propagated out, and perform point-by-point phase synthesis on a monitoring area, so that the multi-measuring point signals are focused at the signal generating position, namely the position where the damage is generated. And finally, completing the identification of the damage position, and regarding the finite element unit at the detected damage position as a damage unit for subsequent operation. The specific operation of the time reversal focusing imaging method is as follows:
1) The measured signal response after damage is differenced with the measured signal response before damage to obtain a difference signal, namely a piezoelectric signal caused by damage;
2) Carrying out shannon wavelet transformation on the difference signal to obtain a time sequence of energy transmission after piezoelectric excitation, and carrying out time phase inversion on the processed signal;
3) Selecting one point in the monitoring area, calculating a signal phase shift distance according to the position of the selected monitoring point and the distance between the sensor and the received signal, and carrying out phase shift on the signal:
in c m (t) is the translated signal, c r And (t) is a signal before translation, l is the distance between a monitoring point and a receiving signal sensor, and v is the Lamb wave propagation speed.
4) Superposing a plurality of groups of signals after phase shift, and square integrating the superposed signals:
where cwt (x, y) is the superimposed signal intensity at coordinates (x, y) in the monitored region, c i For signals translated with respect to the ith channel at the (x, y) position of coordinates in the monitored area, n is the number of channels, t 0 t 1 Is the signal start time and end time.
5) Selecting another point in the monitoring area and repeating 3-4 until all points in the area are calculated;
6) Normalizing the signal calculated value in the detection area, imaging the result as the pixel value of the point, and obtaining the area with the maximum pixel value as the identification damage area.
(7) And according to the damage position determined in the previous step and the damage identification basic numerical model established in the first step, establishing a damage identification correction model based on the damage. The damage identification correction model has the following characteristics: the first is in the area where damage occurs, the damage unit stiffness parameters of the damage model can be modified, and the unit stiffness and damage variable remain corresponding. And secondly, when the damage variable is set to 0, namely no damage occurs, the structural static strain response and the free vibration excitation response are consistent with the basic signal measurement result.
Wherein the damage variable is expressed in terms of a stiffness fold-down amount, i.e., the characterization stiffness can be expressed as a function of the stiffness of the material, as follows:
E d ＝E m (1-d)
in E d To damage stiffness, i.e. characterize stiffness, E m Stiffness of the isotropic material when no damage occurs, and d is a damage variable. For a symmetrically-laid composite laminate, E in the above formula is expressed as a stiffness parameter of the composite laminate, specifically expressed as:
B＝0
wherein A is a tensile stiffness matrix of the composite laminated plate, B is a stretch bending coupling stiffness matrix of the composite laminated plate, D is a bending stiffness matrix of the composite laminated plate, and H is a shearing stiffness matrix of the composite laminated plate.
And recalculating and modifying the unit rigidity of the damaged position in the finite element model according to the damage quantification model to obtain the relation between the rigidity matrix of the damaged unit and the damage variable, wherein the modified finite element model is the damage identification correction model.
(8) Setting the damage quantification degree of the damage unit, and responding to a finite element model containing a damage structure through finite element simulation analysis. The analysis content comprises static strain response and free vibration dynamic response under the rated load, the simulation analysis result is compared with the structural static response and dynamic response signals under the damage state obtained by measurement in the fifth step, if the results are consistent, the damage degree of the unit is considered to be the set quantization degree, and if the damage degree is inconsistent, the step (9) is executed. To evaluate the degree of signal agreement, it is described by the following formula:
where n is the number of strain measurement points, l is the number of modal measurements, λ 1i For the magnification coefficient of the ith strain measurement point epsilon ci Strain results, ε, are analyzed for the finite element at the ith measurement point mi For the strain results obtained by experimental measurement of the ith measuring point, lambda 2j An amplification factor of the j-th order mode, f cj For the j-th order modal frequency, f obtained by finite element analysis mj For the j-th order modal frequency obtained by experimental measurement, the smaller the result is, the higher the degree of agreement between the calculation model and the experimental model is.
(9) And obtaining a response by carrying out small variable change on the damage quantification degree of the damage unit, and obtaining the relation between the response change and the damage degree change of the damage unit. Modifying the damage quantification degree of the damage unit along the direction of enabling the static response and the dynamic response of the structure to be closer to each other, and repeating the step (8). This process can be expressed in an optimized form:
find d i (i＝1，2，...，14)
s.t.min err
where err is the assessment of the degree of signal agreement in step (8). And optimizing and solving to obtain the value of the damage variable set after damage positioning and identification, namely the damage quantification degree.
In summary, the invention provides a method for quantitatively identifying damage of a composite material by active and passive combination. Firstly, establishing a corresponding numerical model according to the identified composite material laminated plate object, and correcting the model to ensure that the numerical model can reproduce the load and the response result in the test; secondly, measuring basic signals aiming at an undamaged structure, wherein the basic signals comprise but are not limited to static strain, lamb wave signals, natural frequencies, modes and the like; then, after the structure is damaged, the damage signal is measured on the structure, and the damage signal is the same as the signal type of the basic signal and the measuring method; then, aiming at the guided wave signal, realizing structural damage positioning by using a time reversal imaging method, and positioning damage in a numerical model; and finally, analyzing the numerical model of the damaged structure, determining the rigidity reduction degree of the damaged unit, realizing the quantification of the damage degree of the structure, and providing guidance and reference for the control strategy and the maintenance strategy of the subsequent structure.
The above is only a specific step of the present invention, and does not limit the protection scope of the present invention; the method can be applied to the field of damage identification, and all technical schemes formed by equivalent transformation or equivalent replacement fall within the scope of the invention.
The present invention is not described in detail in part as being well known to those skilled in the art.
Claims (4)
1. The quantitative identification method for the damage of the composite material by active and passive combination is characterized by comprising the following steps of:
the first step: establishing a damage identification basic numerical model of a composite material identification object in a damage-free state, establishing the geometric shape of the damage identification basic numerical model by geometric shape measurement on the identification object, determining the material density of the damage identification basic numerical model by weight measurement on the identification object, correcting the material rigidity of the damage identification basic numerical model by stress response measurement of static load test on the identification object, and correcting the boundary rigidity loaded by the numerical model structure by natural frequency measurement of dynamic response test on the identification object;
and a second step of: arranging piezoelectric sensors and resistive strain sensors on the identification object, wherein the piezoelectric sensors are distributed uniformly in a monitoring area for the arrangement of active sensors, and surround the area where damage is likely to occur; the resistive strain sensor is a passive sensor, the resistive strain sensor is arranged in each area where damage is likely to occur, and the resistive strain sensor is additionally arranged in the area where damage is likely to occur due to stress concentration or large load;
and a third step of: the piezoelectric sensor and the resistance strain sensor which are arranged in the second step are adopted to measure a basic signal in a non-damaged state, wherein the basic signal comprises a piezoelectric sensor signal generated by excitation of structural Lamb waves in a non-load state, namely Lamb waves, a piezoelectric sensing signal generated by excitation of the structural Lamb waves in a rated load state, a structural strain sensor signal in the rated load state and a dynamic response signal of a free vibration strain sensor excited under the action of force hammer striking;
fourth step: the piezoelectric sensor arranged in the second step is adopted to measure an active excitation signal after damage occurs, wherein the active excitation comprises a piezoelectric sensor signal generated by structural Lamb wave excitation in a non-load state after damage occurs and a piezoelectric sensor signal generated by structural Lamb wave excitation in a rated load state after damage occurs;
fifth step: the resistive strain sensor arranged in the second step is adopted to measure a static response signal and a dynamic response signal of the structure after the damage occurs, and specifically refers to a static response strain sensor signal of the structure under a rated load state after the damage occurs and a free vibration strain sensor signal under the force hammer striking excitation;
sixth step: determining the damage position of the identification object by adopting a time reversal focusing imaging method based on the basic signal obtained by the measurement in the third step and the active excitation signal obtained by the measurement in the fourth step;
seventh step: based on the damage identification basic numerical model established in the first step, carrying out parameterization modification on the rigidity parameters of the finite element units at the damage occurrence position according to the damage position determined in the sixth step through a damage quantification model to obtain a damage identification correction model; the damage identification correction model has the following characteristics: (1) In the region where the damage occurs, the finite element stiffness parameters of the damage model can be modified; (2) When the damage variable is set to 0, i.e. no damage occurs, the structural static strain response and the free vibration excitation response are consistent with the basic signal measurement result;
eighth step: and obtaining the situation that the analysis result is closest to the measured damage result by using a differential format gradient iteration method or a gradient-free mode search method, wherein the obtained damage variable is the damage quantification result.
2. The method for quantitatively identifying damage to active-passive composite material according to claim 1, wherein the method comprises the steps of: in the third step, the basic signal in the undamaged state and the measurement response signals after damage in the fourth step and the fifth step comprise Lamb wave signals which are actively excited by piezoelectric sensors and are received by other piezoelectric sensors, static load which is loaded by a static testing machine, static response signals which are measured by a resistance strain gauge and dynamic response signals which are measured by a force sensor and a resistance strain sensor, wherein excitation is generated by knocking by a force hammer; wherein Lamb wave signals are active excitation signals, static response signals and passive response signals are passive response signals, and one of active and passive combination features means that the two signals are combined; wherein more than one piezoelectric sensor, when one is energized, no other piezoelectric sensor is energized.
3. The method for quantitatively identifying damage to active-passive composite material according to claim 1, wherein the method comprises the steps of: in the sixth step, the time reversal focusing imaging method is specifically as follows:
(1) The measured signal response after damage is differenced with the measured signal response before damage to obtain a difference signal;
(2) Inverting the time phase of the difference signal;
(3) Selecting one point in the monitoring area, calculating a signal phase translation distance according to the position of the selected monitoring point and the distance between the sensor and the received signal, and carrying out phase translation on the signal;
(4) Superposing a plurality of groups of signals after phase shift, and square integrating the superposed signals;
(5) Selecting another point in the monitoring area and repeating (3) - (4) until all points in the area are calculated;
(6) Normalizing the signal calculated value in the detection area, imaging the result as the pixel value of the point, and obtaining the area with the maximum pixel value as the identification damage area.
4. The method for quantitatively identifying damage to active-passive composite material according to claim 1, wherein the method comprises the steps of: in the seventh step, based on the damage identification basic model, the rigidity performance of the finite element unit of the damage identification basic model at the damage occurrence position is recalculated and modified according to the damage quantification model to obtain the relation between the rigidity matrix of the damage unit and the damage variable, the modified finite element model is the damage identification correction model, the damage quantification model adopts the theory of damage mechanics, the rigidity reduction amount is used as the damage variable to quantitatively identify the residual characterization rigidity of the damage unit in the finite element model, and the quantitative description and the identification characterization rigidity description of the damage of the composite material are realized by the following formula:
E d ＝E m (1-d)
in E d To damage stiffness, i.e. characterize stiffness, E m For stiffness of isotropic material when no damage occurs, d is a damage variable, and for constitutive relation of the symmetrically-paved composite laminated plate, the complete expression is as follows:
B＝0
wherein A is the tensile stiffness matrix of the laminated plate, B is the stretch bending coupling stiffness matrix of the laminated plate, D is the bending stiffness matrix of the laminated plate, H is the shearing stiffness matrix of the laminated plate, and D 1 ～d 14 For the lesion variable to be identified, A ij ，D ij ，H ij Respectively represent the in-plane stiffness coefficient, the bending stiffness coefficient and the shearing stiffness coefficient of the laminated plate.
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