阅读说明：本技术 用于蜂窝夹层结构飞机蒙皮检测的仿真分析方法 (Simulation analysis method for honeycomb sandwich structure aircraft skin detection ) 是由 李慧娟 石亮 张祥春 张方洲 王俊涛 刘志毅 于 2021-07-23 设计创作，主要内容包括：本发明提供了一种蜂窝夹层结构飞机蒙皮检测的仿真分析方法,S1、获取蜂窝夹层结构飞机蒙皮红外锁相热成像缺陷并构建解析模型；S2、对蜂窝夹层结构飞机蒙皮红外锁相热成像缺陷进行有限元分析；S3、对解析模型进行瞬态过程分析,进行载荷加载和信号处理,获得温度信号的幅值和相位,并确定有缺陷处与无缺陷处的幅值极差与相位极差；S4、获得有缺陷处的温度变化幅值和相位分别与无缺陷处温度变化幅值和相位之间最大差值；S5、通过对铝蒙皮蜂窝夹层结构模拟缺陷的仿真分析,确定检测参数范围。其能够基于缺陷特征,开展蜂窝夹层结构红外锁相热成像检测有限元分析,确定是否能根据红外锁相热成像检测技术进行缺陷检测,并确定合理的检测参数范围。(The invention provides a simulation analysis method for detecting a honeycomb sandwich structure aircraft skin, which comprises the steps of S1, acquiring infrared phase-locked thermal imaging defects of the honeycomb sandwich structure aircraft skin and constructing an analytic model; s2, carrying out finite element analysis on the infrared phase locking thermal imaging defects of the honeycomb sandwich structure aircraft skin; s3, carrying out transient process analysis on the analytic model, carrying out load loading and signal processing to obtain the amplitude and phase of the temperature signal, and determining the amplitude range and the phase range of the defect position and the defect-free position; s4, obtaining the maximum difference value between the amplitude and the phase of the temperature change at the position with the defect and the amplitude and the phase of the temperature change at the position without the defect respectively; and S5, determining the detection parameter range through simulation analysis of the simulation defects of the aluminum skin honeycomb sandwich structure. The method can be used for developing the infrared phase-locking thermal imaging detection finite element analysis of the honeycomb sandwich structure based on defect characteristics, determining whether the defect detection can be carried out according to the infrared phase-locking thermal imaging detection technology, and determining a reasonable detection parameter range.)

1. A simulation analysis method for detecting the skin of an aircraft with a honeycomb sandwich structure is characterized by comprising the following steps:

s1, acquiring infrared phase-locking thermal imaging defects of the honeycomb sandwich structure aircraft skin and constructing an analytic model;

s2, carrying out finite element analysis on the infrared phase locking thermal imaging defects of the honeycomb sandwich structure aircraft skin, and specifically comprising the following substeps:

s21, under the action of periodic heat flow, the transient heat conduction process of the honeycomb sandwich structure aircraft skin test piece is represented by the constitutive equation of the heat transfer process:

wherein: k is a radical of_ix，k_iy，k_izThe thermal conductivity or thermal conductivity of the ith interlayer material in the X, Y, Z direction is expressed in the unit of w/kg · m; rho_ix，ρ_iy，ρ_izDenotes the density of the i-th sandwich material in the direction X, Y, Z in kg/m³；c_ix，c_iy，c_izThe specific heat of the ith interlayer material in the direction of X, Y, Z is expressed as J/kg DEG C;to calculate the partial derivative, T is time and T is temperature;

s22, determining initial conditions of the analytical model:

T(X,Y,Z,t＝0)＝T_am (2)

s23, in order to solve the analytical model, the CFRP material and the foam material are assumed to have uniform thermal property, and because the area of each layer in the aircraft skin test piece is larger than the thickness, the transverse diffusion of heat flow is neglected on the boundary, the boundary condition is divided into two heat exchange upper surfaces and lower surfaces and a second surface meeting the heat insulation condition;

for the upper surface:

wherein: h is_topRepresents the heat transfer coefficient (J/m) of the upper surface²DEG C.); i represents the excitation heat flow;

for the lower surface:

wherein: h is_bottomRepresents the heat transfer coefficient (J/m) of the lower surface²·℃)；L_zRepresents the length of the test piece in the Z direction;

the adiabatic condition is satisfied for the second surface:

wherein: l is_x，L_yLength indicating the direction of the test piece X, Y;

s24, for each layer of material in the test piece, the continuity conditions of temperature and heat flow are met;

T_i(X,Y,Z,t)＝T_i+1(X,Y,Z,t) (7)

s3, carrying out transient process analysis on the analytic model, carrying out load loading and signal processing to obtain the amplitude and phase of the temperature signal, and determining the amplitude range and the phase range of the defect position and the defect-free position;

s4, obtaining the maximum difference value between the amplitude and the phase of the temperature change at the defect and the amplitude and the phase of the temperature change at the defect respectively:

ΔA_max＝A_defmax-A_nondefmax (11)

wherein: delta A_maxIndicating a very poor amplitude; a. the_defmaxRepresenting the amplitude of the defect; a. the_nondefmaxRepresenting the amplitude of the defect-free region;

ΔPh_max＝Ph_defmax-Ph_nondefmax (12)

wherein: delta Ph_maxIndicating a phase pole difference; ph_defmaxRepresenting the phase at the defect; ph_nondefmaxIndicating a phase without defects;

s5, determining whether defect detection can be carried out according to an amplitude diagram and a phase diagram of the infrared phase-locked thermal imaging detection method or not through simulation analysis of the simulated defects of the honeycomb sandwich structure skin, and determining the detection parameter range.

2. The simulation analysis method for honeycomb sandwich structure aircraft skin inspection according to claim 1,

step S1 specifically includes the following steps:

s11, constructing an analysis model of temperature change and distribution of the aircraft skin test piece based on Fourier one-dimensional heat conduction model analysis by adopting an infrared phase-locked thermal imaging detection technology;

and S12, extracting amplitude and phase information of a steady-state or quasi-steady-state process in the temperature signal by adopting a digital phase locking method, and obtaining defect characteristics by utilizing the influence of defects on the phase information.

3. The simulation analysis method for honeycomb sandwich structure aircraft skin inspection according to claim 2,

step S11 can obtain the temperature change history and distribution of the test piece under the sine-law change heat flow excitation condition:

the formula provides an analytic model of temperature change and distribution of a test piece based on Fourier one-dimensional heat conduction model analysis under the excitation of sine regular change heat flow, and the temperature history of the test piece and the temperature distribution condition along the heat flow transmission direction are analyzed through the model.

4. The simulation analysis method for honeycomb sandwich structure aircraft skin inspection according to claim 1,

in step S5, when the skin thickness hd is less than or equal to 0.5mm, the simulated defect inside the test piece can be accurately detected, where when the skin thickness hd is 0.3mm, the modulation frequency fe is 0.36Hz to 0.37Hz, and when the skin thickness hd is 0.5mm, the modulation frequency fe is 0.34Hz to 0.35Hz in order to obtain a better detection result;

when the skin thickness hd is more than or equal to 0.8mm, the defect diameter phi can be detected as 8mm, wherein when the skin thickness hd is 0.8mm, the modulation frequency fe is 0.17 Hz-0.18 Hz, and when the skin thickness hd is 1.0mm, the modulation frequency fe is 0.09 Hz-0.11 Hz.

5. The simulation analysis method for honeycomb sandwich structure aircraft skin inspection according to claim 1 or 4,

the aircraft skin and the honeycomb sandwich structure are bonded by adopting the glue layer, and when the thickness of the skin is increased and the honeycomb sandwich structure under the glue layer is detected, the modulation frequency value detected by adopting infrared phase-locked thermal imaging is correspondingly reduced.

Technical Field

The invention belongs to the technical field of nondestructive testing, and particularly relates to a simulation analysis method for testing a honeycomb sandwich structure aircraft skin.

Background

Honeycomb sandwich structures are emerging and rapidly used in a wide variety of fields, are much lighter and more rigid than conventional materials and structures, and have a significant weight reduction effect on products. Because various process parameters are difficult to accurately control in the manufacturing process, the honeycomb sandwich structure is easy to cause unstable quality and large discreteness, and various defect types such as debonding, layering, poor bonding, air holes, inclusion, honeycomb core deformation and the like appear, and the detection effect and efficiency of the traditional detection methods such as ray, ultrasonic and the like are not good and need to be improved urgently.

Under the background, the infrared thermal imaging detection method is popularized and applied, but the infrared thermal imaging detection is influenced by various factors, such as material performance, defect characteristics, detection requirements and the like. When the infrared thermal imaging detection technology is used for detecting defects, a large number of tests are required to determine the optimal detection parameters. The infrared phase-locked thermal imaging detection method comprises the steps that an external excitation source with energy changing according to a sine rule is adopted to excite and load a component or a material, when heat flow is transmitted inside a test piece, the temperature changes according to the rule, when thermal characteristics are uneven or defects exist inside the test piece, thermal wave signals on the surface of the test piece can change, particularly, due to attenuation of the heat flow, the amplitude of the thermal wave signals changes, meanwhile, the phase can also be delayed or advanced, and the characteristics of the defects inside the test piece are analyzed by using the amplitude and the phase information of the thermal wave signals on the surface of the test piece.

The thermal imaging has the influence on the detection process due to the excitation frequency, the excitation loading period and the excitation loading energy, and a large amount of tests are required to be carried out for determining the influence rule of the parameters, so that the cost is very high. Therefore, a simulation analysis method for infrared thermal imaging detection is urgently needed. Currently, simulation techniques for infrared thermal imaging detection mainly focus on pulse and transient excitation conditions, and perform thermal analysis on the premise of certain simplification and assumption. The phase-locked infrared thermal imaging detection technology has few simulation technologies, and mainly because the phase-locked infrared thermal imaging detection method is periodically excited, the heat conduction process and the internal heat transfer process are more complex, and a large amount of information is contained in a temperature signal. The invention establishes a simulation analysis method for the infrared thermal imaging detection of the honeycomb sandwich structure aircraft skin through the system, thereby greatly reducing the test cost and improving the detection efficiency.

The defect types of the honeycomb sandwich structure are numerous, the accuracy of the detection result needs to be verified, and a simulation analysis method for detecting the skin of the aircraft with the honeycomb sandwich structure is urgently needed to perform simulation verification on the detection result.

Disclosure of Invention

Aiming at the defects in the prior art, the invention provides a simulation analysis method for detecting the aircraft skin with the honeycomb sandwich structure. The method can be used for developing the finite element analysis of the infrared phase-locking thermal imaging detection of the honeycomb sandwich structure based on defect characteristics, determining whether the defect detection can be carried out according to an amplitude diagram and a phase diagram of the infrared phase-locking thermal imaging detection technology, and determining a reasonable detection parameter range. The invention fully considers the constant heat flow and the alternating heat flow and the influence of transverse heat diffusion in the honeycomb sandwich structure, and is very effective for the detection process range of defects of different types and different depths and the detection of different defects.

The invention provides a simulation analysis method for detecting a honeycomb sandwich structure aircraft skin, which comprises the following steps:

s1, acquiring infrared phase-locking thermal imaging defects of the honeycomb sandwich structure aircraft skin and constructing an analytic model;

s2, carrying out finite element analysis on the infrared phase locking thermal imaging defects of the honeycomb sandwich structure aircraft skin, and specifically comprising the following substeps:

s21, under the action of periodic heat flow, the transient heat conduction process of the honeycomb sandwich structure aircraft skin test piece is represented by the constitutive equation of the heat transfer process:

wherein: k is a radical of_ix，k_iy，k_izThe thermal conductivity or thermal conductivity of the ith interlayer material in the X, Y, Z direction is expressed in the unit of w/kg · m; rho_ix，ρ_iy，ρ_izDenotes the density of the i-th sandwich material in the direction X, Y, Z in kg/m³；c_ix，c_iy，c_izThe specific heat of the ith interlayer material in the direction of X, Y, Z is expressed as J/kg DEG C;to calculate the partial derivative, T is time and T is temperature;

s22, determining initial conditions of the analytical model:

T(X,Y,Z,t＝0)＝T_am (2)

s23, in order to solve the analytical model, the CFRP material and the foam material are assumed to have uniform thermal property, and because the area of each layer in the aircraft skin test piece is larger than the thickness, the transverse diffusion of heat flow is neglected on the boundary, the boundary condition is divided into two heat exchange upper surfaces and lower surfaces and a second surface meeting the heat insulation condition;

for the upper surface:

wherein: h is_topRepresents the heat transfer coefficient (J/m) of the upper surface²DEG C.); i represents the excitation heat flow;

for the lower surface:

wherein: h is_bottomRepresents the heat transfer coefficient (J/m) of the lower surface²·℃)；L_zRepresents the length of the test piece in the Z direction;

the adiabatic condition is satisfied for the second surface:

wherein: l is_x，L_yLength indicating the direction of the test piece X, Y;

s24, for each layer of material in the test piece, the continuity conditions of temperature and heat flow are met;

T_i(X,Y,Z,t)＝T_i+1(X,Y,Z,t) (7)

s3, carrying out transient process analysis on the analytic model, carrying out load loading and signal processing to obtain the amplitude and phase of the temperature signal, and determining the amplitude range and the phase range of the defect position and the defect-free position;

s4, obtaining the maximum difference value between the amplitude and the phase of the temperature change at the defect and the amplitude and the phase of the temperature change at the defect respectively:

ΔA_max＝A_defmax-A_nondefmax (11)

wherein: delta A_maxIndicating a very poor amplitude; a. the_defmaxRepresenting the amplitude of the defect; a. the_nondefmaxRepresenting the amplitude of the defect-free region;

ΔPh_max＝Ph_defmax-Ph_nondefmax (12)

wherein: delta Ph_maxIndicating a phase pole difference; ph_defmaxRepresenting the phase at the defect; ph_nondefmaxIndicating a phase without defects;

s5, determining whether defect detection can be carried out according to an amplitude diagram and a phase diagram of the infrared phase-locked thermal imaging detection method or not through simulation analysis of the simulated defects of the honeycomb sandwich structure skin, and determining the detection parameter range.

Preferably, step S1 specifically includes the following steps:

s11, constructing an analysis model of temperature change and distribution of the aircraft skin test piece based on Fourier one-dimensional heat conduction model analysis by adopting an infrared phase-locked thermal imaging detection technology;

and S12, extracting amplitude and phase information of a steady-state or quasi-steady-state process in the temperature signal by adopting a digital phase locking method, and obtaining defect characteristics by utilizing the influence of defects on the phase information.

Preferably, step S11 can obtain the temperature change history and distribution of the test piece under the excitation condition of the sinusoidal regularly changing heat flow:

the formula provides an analytic model of temperature change and distribution of a test piece based on Fourier one-dimensional heat conduction model analysis under the excitation of sine regular change heat flow, and the temperature history of the test piece and the temperature distribution condition along the heat flow transmission direction are analyzed through the model.

Preferably, in step S5, when the skin thickness hd is less than or equal to 0.5mm, the simulated defect inside the test piece can be accurately detected, where when the skin thickness hd is 0.3mm, the modulation frequency fe is 0.36Hz to 0.37Hz, and when the skin thickness hd is 0.5mm, the modulation frequency fe should be 0.34Hz to 0.35Hz in order to obtain a good detection result;

when the skin thickness hd is more than or equal to 0.8mm, the defect diameter phi can be detected as 8mm, wherein when the skin thickness hd is 0.8mm, the modulation frequency fe is 0.17 Hz-0.18 Hz, and when the skin thickness hd is 1.0mm, the modulation frequency fe is 0.09 Hz-0.11 Hz.

Preferably, the aircraft skin and the honeycomb sandwich structure are bonded by adopting a glue layer, and when the thickness of the skin is increased and the honeycomb sandwich structure below the glue layer is detected, the modulation frequency value detected by adopting infrared phase-locked thermal imaging is correspondingly reduced.

Compared with the prior art, the invention has the technical effects that:

1. the simulation analysis method for detecting the honeycomb sandwich structure aircraft skin, which is designed by the invention, can perform finite element analysis of infrared phase-locked thermal imaging detection of the honeycomb sandwich structure based on defect characteristics, determine whether the defect detection can be performed according to an amplitude diagram and a phase diagram of an infrared phase-locked thermal imaging detection technology, and determine a reasonable detection parameter range. The invention fully considers the constant heat flow and the alternating heat flow and the influence of transverse heat diffusion in the honeycomb sandwich structure, and is very effective for the detection process range of defects of different types and different depths and the detection of different defects. And performing transient process solution on the model by adopting a display integration method, performing load loading and signal processing, solving the amplitude and phase of the temperature signal, and determining the amplitude range and the phase range of the defective and non-defective positions.

2. The invention designs a simulation analysis method for detecting a honeycomb sandwich structure aircraft skin, which defines that the temperature of a test piece is gradually attenuated along with the increase of the transfer depth along the heat flow transfer direction under the heat flow excitation condition of a sine rule, and the thermal diffusion length exists, and the size of the thermal diffusion length is related to the heat conductivity coefficient, specific heat, density and heat flow excitation loading frequency of a material; it is clear that for air defects, reasonable heat flow excitation loading frequency and sampling analysis period number are needed to accurately determine defect characteristics so that the amplitude and phase difference are large.

Drawings

Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings.

FIG. 1 is a schematic flow diagram of the present invention;

FIG. 2 is a schematic diagram of an Matlab/Simulink thermal and electrical equivalent simulation model for infrared lock-in thermography inspection according to the present invention;

FIG. 3 is a schematic three-dimensional structure of a honeycomb sandwich structure test piece and defect of the present invention;

FIG. 4 is a schematic diagram of the solution process of the present invention;

FIG. 5 is a schematic diagram of finite element meshing according to the present invention;

FIG. 6 is a graph of the simulation calculation result of the aluminum skin thickness h of the present invention at 0.3mm and frequency 0.2 Hz;

FIG. 7 is a graph of the simulation calculation result of the aluminum skin thickness h of the present invention at 0.5mm and frequency 0.2 Hz;

FIG. 8 is a graph of the simulation calculation result of the aluminum skin thickness h of the present invention at 0.8mm and frequency 0.2 Hz;

FIG. 9 is a graph of the simulation calculation result of the aluminum skin thickness h of the present invention at 1.0mm frequency 0.2 Hz;

FIG. 10 is a schematic of the amplitude and phase of an aluminum skin of the present invention with a thickness of 0.8mm on glue φ 10 defect;

FIG. 11 is a schematic view of the amplitude and phase of an aluminum skin 1.0mm thick under glue φ 5 defect of the present invention;

FIG. 12 is a schematic view of a carbon fiber skin honeycomb sandwich structure simulated defect test piece according to the present invention;

FIG. 13 is a schematic view of a test piece for simulating defects of an aluminum skin honeycomb sandwich structure according to the present invention;

FIG. 14 is a schematic view of a defect simulation test piece of a carbon fiber and aluminum skin honeycomb sandwich structure according to the present invention;

FIG. 15 is a schematic view of a defect simulation test piece of a carbon fiber and aluminum skin honeycomb sandwich structure according to the present invention;

FIG. 16 is a schematic structural diagram of a defect simulation test piece of a carbon fiber skin variable-thickness honeycomb sandwich structure according to the invention;

FIG. 17 is a schematic diagram of adjusting the excitation angle of incidence of a light source according to the present invention;

FIG. 18 is a schematic view of a simulated defect analysis point of the present invention;

FIG. 19 is an infrared phase-locked thermographic inspection result of different light source excitation thermal incident angles of the present invention;

FIG. 20 is a graph of the sequence-1.0-5-p detection result of the present invention at 0.165Hz splice phase;

FIG. 21 is a schematic of the phase distribution of line 1 for sequence-1.0-4-f of the present invention;

FIG. 22 is a schematic of the phase distribution of line 2 for sequence-1.0-4-f of the present invention;

FIG. 23 is a spliced phase diagram of the sequence-0.5-4-w of the present invention;

FIG. 24 is a schematic phase distribution diagram for line 1 at sequence-0.5-4-w of the present invention;

FIG. 25 is a schematic of the phase distribution of line 2 at sequence-0.5-4-w of the present invention;

FIG. 26 is a schematic of the phase distribution of line 3 at sequence-0.5-4-w of the present invention;

FIG. 27 is a schematic of the phase distribution of line 4 at sequence-0.5-4-w of the present invention.

Detailed Description

The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant invention and not restrictive of the invention. It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings.

It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.

The invention develops finite element analysis of the infrared phase-locking thermal imaging detection of the honeycomb sandwich structure, determines whether the amplitude diagram and the phase diagram of the infrared phase-locking thermal imaging detection technology can be used for defect detection, and determines a reasonable detection parameter range.

The infrared thermal imaging technology is used as a novel nondestructive testing technology and is widely applied to detecting defects of aerospace materials. At present, the infrared pulse thermal imaging detection technology and the infrared phase-locking thermal imaging detection technology are relatively mature. The infrared phase-locked thermal imaging detection technology has the advantages of large detection depth range, high signal-to-noise ratio and the like, is particularly suitable for nondestructive detection of composite materials and sandwich structures, and is widely applied to the fields of foreign aerospace and the like. In order to carry out nondestructive testing on the honeycomb sandwich structure by applying an infrared phase-locking thermal imaging technology, a three-dimensional heat conduction model for transferring heat flow in a test piece is established, a finite element method is adopted to carry out analog simulation research on the model, and the influence rule of heat flow excitation frequency and excitation loading period on defect judgment is analyzed.

The detection result of the infrared phase-locking thermal imaging detection of the honeycomb sandwich structure aircraft skin is obtained according to the following steps:

an infrared phase-locked thermal imaging detection technology is adopted, and an analytic model of temperature change and distribution of the aircraft skin test piece is constructed based on Fourier one-dimensional thermal conduction model analysis. The method comprises the following specific steps:

the infrared phase-locking thermal imaging detection technology is an active infrared thermal wave detection technology, and adopts the infrared phase-locking thermal imaging detection technology, and the heat flow of external excitation changes according to the sine rule:

wherein: i (t) represents the intensity of external excitation loading heat flow, and the unit is W; p represents the power loaded by external excitation, and the unit is W; f. of_eRepresents the modulation excitation loading frequency in Hz;

the heat flow with sine regular change is injected into a flat plate with limited thickness, when the area is much larger than the thickness, the transverse diffusion of the heat flow can be ignored, and only the transmission in the thickness direction is considered, so that the problem of one-dimensional heat conduction can be converted, as shown in figure 1.

When heat flow is transferred in a flat plate with finite thickness, the transfer process is described by a fourier one-dimensional heat conduction model:

wherein: c represents the specific heat of the test piece material; ρ represents the density of the specimen material; k represents the thermal conductivity of the test piece material;

the given heat flow conditions described therein include two components, one is a constant heat flow component which causes heat to build up in the test piece, causing the temperature to rise; the second is the alternating heat flow portion, which will cause temperature oscillation with a frequency consistent with the heat flow excitation loading frequency.

Assuming that the material is isotropic, and considering the heat accumulation caused by the constant heat flow part, the equation (2) is solved analytically to obtain the temperature change along with the time and the thickness under the stable or quasi-stable state:

wherein:represents the thermal diffusion length; am represents an amplitude gain factor of the temperature signal;

the formula describes the change condition of the test piece under the heat flow loading condition of sine regular change and under the stable or quasi-stable state of the temperature of the test piece, so that the length of heat flow which can be transmitted to the interior of the test piece is related to the thermal characteristics of the material and the heat flow excitation loading frequency, and the frequency of the temperature change of the test piece is consistent with the heat flow excitation modulation frequency in the stable or quasi-stable state; when the thermal characteristics of the test piece material change or defects exist in the test piece material, the amplitude of the test piece material changes due to the surface temperature of the test piece under the condition of a stable or quasi-stable state, phase difference can also be generated, whether defects exist in the test piece material or not can be judged through the information, and defect characteristics can be determined, so that a theoretical basis is laid for nondestructive testing by adopting an infrared phase-locking thermal imaging detection technology.

The temperature of the test piece is increased instantaneously due to the heat accumulation of the test piece caused by the constant heat flow part, and the temperature change of the whole test piece caused by the constant heat flow satisfies the following differential equation:

wherein: r_thIndicating the thermal resistance of the test piece material; t is_amRepresents the ambient temperature;

when the initial boundary condition is satisfied, i.e. T (0, ∞) ═ T is satisfied_amUnder the condition, solving the following formula:

T(0,t)＝T_am+ΔT(1-e^-t/τ)

wherein: τ denotes a time constant, τ ═ ρ cR_th；

The above equation describes the process by which the test piece causes a momentary temperature rise under thermal flow excitation conditions, resulting in: the time for the temperature change of the test piece to reach a stable or quasi-stable state is related to the specific heat, density and thermal resistance of the material, namely the thermal characteristics of the material.

Obtaining the temperature change history and distribution of the test piece under the sine-law change heat flow excitation condition:

the formula provides an analytic model of temperature change and distribution of a test piece based on Fourier one-dimensional heat conduction model analysis under the excitation of sine regular change heat flow, and the temperature history of the test piece and the temperature distribution condition along the heat flow transmission direction are analyzed through the model.

And then, extracting amplitude and phase information of a steady-state or quasi-steady-state process in the temperature signal by adopting a digital phase locking method, and obtaining defect characteristics by utilizing the influence of defects on the phase information so as to finish the detection of the honeycomb interlayer. For a given time constant, the temperature course is changed into two processes, namely a transient course process and a steady-state course process, the transient process is mainly determined by the time constant, the shorter the time constant is, the shorter the time for reaching the steady process is, the faster the speed is, the time constant is determined by the thermal characteristics of materials, the time constant of heat transfer is different for different thermal characteristics materials, and whether defects exist in the test piece or not and the characteristics are determined by analyzing the speed of the signal reaching the steady-state process.

In the steady state or quasi-steady state process, the temperature process oscillates according to the sine change along with the time, along the heat flow transmission direction, along with the increase of the transmission depth, the temperature gradually attenuates, namely the energy is attenuated continuously, if the depth of the defect in the test piece is deep, if the energy cannot be transmitted to the depth of the defect, the temperature signal cannot contain the influence information of the defect on the temperature change, and at the moment, the defect detection cannot be carried out. For sine heat flow excitation, the point temperature history and distribution of a test piece in the heat flow excitation process are very complex, but the temperature signals contain a large amount of information, amplitude and phase information of a steady state or quasi-steady state process in the temperature signals can be extracted by adopting a digital phase locking method, and defect characteristics can be accurately obtained by utilizing the influence of defects on the information, so that nondestructive detection is realized.

And finally, starting finite element analysis on the detection result of the honeycomb sandwich layer based on the defect characteristics obtained in the steps, and specifically comprising the following steps of:

s1, carrying out finite element analysis of the infrared phase-locking thermal imaging detection of the honeycomb sandwich structure;

formula (II)The heat flow of the external thermal excitation source is shown to vary sinusoidally with time, i.e. the intensity of the heat flow of the heating source is a sinusoidal function with time. The test piece is of a solid skin-honeycomb-skin three-layer sandwich structure, the interior of the test piece has a manual hole digging defect, and simulation defects are manufactured at the upper position and the lower position of the interior in a glued joint mode. Fig. 2 shows a three-dimensional structure diagram of a test piece and a defect.

The finite element analysis comprises the following specific steps:

s11, under the action of periodic heat flow, the transient heat conduction process of the test piece is obtained by a heat transfer process constitutive equation:

wherein: k is a radical of_ix，k_iy，k_izThe thermal conductivity or the thermal conductivity coefficient of the ith layer material in the X, Y, Z direction is expressed in the unit of w/kg · m; rho_ix，ρ_iy，ρ_izThe density of the i-th layer material in the X, Y, Z direction is shown in kg/m³；c_ix，c_iy，c_izThe specific heat of the ith material in the direction of X, Y, Z is expressed in J/kg DEG.C.

S12, determining the initial conditions of the model:

T(X,Y,Z,t＝0)＝T_am (2)

s13, in order to simplify the solution of the model, the CFRP material and the foam material are assumed to have uniform thermal material characteristics, and because the area of each layer in the test piece is far larger than the thickness, the transverse (X and Y directions) diffusion of heat flow can be ignored on the boundary, and the boundary conditions are mainly divided into an upper heat exchange surface, a lower heat exchange surface and a second surface meeting the heat insulation condition.

For the upper surface:

wherein: h is_topRepresents the heat transfer coefficient (J/m) of the upper surface²·℃)；

For the lower surface:

wherein: h is_bottomRepresents the heat transfer coefficient (J/m) of the lower surface²·℃)；L_zRepresents the length of the test piece in the Z direction;

the adiabatic condition is satisfied for the second surface:

wherein: l is_x，L_yLength indicating the direction of the test piece X, Y;

s14, the continuity conditions of temperature and heat flow should be satisfied for each layer of material inside the test piece.

T_i(X,Y,Z,t)＝T_i+1(X,Y,Z,t) (7)

The formula (1) to the formula (10) describe a temperature field distribution model of the sine regular change heat flow excitation test piece, and the model lays a theoretical foundation for carrying out nondestructive testing on defects of different depths and types in the test piece by adopting an infrared phase-locked thermal imaging detection technology. Because the three-dimensional heat conduction model is difficult to realize by adopting analytical analysis, in order to research the influence of the selection of the heat flow excitation source loading parameters and analysis parameters which change in a sine rule on defect characteristic analysis, a finite element method is adopted to solve the process, and the amplitude and the phase of the temperature signal are extracted in the transient process.

S2, in the finite element analysis process, the constitutive equation, the initial condition, the boundary condition and the continuity condition of the test piece three-dimensional heat conduction finite element model are given by the formula (1) to the formula (10), the model is subjected to transient process solution by adopting commercial finite element software COMSOLMulti-Physics, the solution method adopts a display integration method, a subprogram is applied to load loading and signal processing, the amplitude and the phase of a temperature signal are solved, the amplitude range and the phase range of a defective part and a non-defective part are determined, and the solution process is shown in figure 3.

The geometry of the honeycomb sandwich structure of finite element analysis is 26mm × 26mm × 2.1mm (the skin thickness is H ═ 0.3, 0.5, 0.8, 1.0mm respectively), the defect type is set to be air, and the defect sizes of the upper and lower surfaces of the glue line are Φ 10 × 0.1mm and Φ 5 × 0.1mm respectively. Finite element meshing is shown in figure 4.

The material thermophysical parameter selection is given in table 1, the boundary condition parameters and initial conditions for finite element model analysis are given in table 2, and the simulation analysis parameters are given in table 3.

TABLE 1

TABLE 2

TABLE 3

S3, in order to research the relation between the surface temperature signal and the defect characteristics, calculating the maximum difference between the amplitude and the phase of the temperature change at the defect and the amplitude and the phase of the temperature change at the defect respectively:

ΔA_max＝A_defmax-A_nondefmax (11)

wherein: delta A_maxIndicating a very poor amplitude; a. the_defmaxRepresenting the amplitude of the defect; a. the_nondefmaxIndicating the amplitude of the defect-free spot.

ΔPh_max＝Ph_defmax-Ph_nondefmax (12)

Wherein: delta Ph_maxIndicating a phase pole difference; ph_defmaxRepresenting the phase at the defect; ph_nondefmaxIndicating a phase without defects.

Fig. 5-8 show simulation calculation results of the amplitude and phase distribution of the surface temperature change of the test piece of the aluminum skin honeycomb sandwich structure with different skin thicknesses under the condition of 2 sampling analysis periods.

As can be seen from fig. 5 to 8, under the condition of a given modulation frequency and analysis period, due to the influence of the lateral thermal diffusion of the honeycomb core, the geometric shape of the defect is difficult to identify in both the amplitude diagram and the phase diagram, the resolution range of the amplitude diagram is small, the geometric feature of the defect is difficult to actually reflect, the phase diagram has high resolution, but as the thickness of the skin increases, the geometric feature of the defect is difficult to identify, and particularly, the small defect under the gel can hardly be determined.

Fig. 9-10 show two graphs of the simulation results of the influence of the heat flow excitation loading frequency and the sampling analysis period number on the amplitude difference and the phase difference of the defect (air).

As can be seen from the figure, for the honeycomb sandwich structure with different aluminum skin thicknesses, excitation parameters (modulation frequency and analysis cycle number) have great influence on the detection result, and as the skin thickness increases, within a given parameter range, the amplitude difference and the phase difference gradually decrease, the skin thickness increases (the defect depth increases), so that the transmission attenuation of the thermal wave in the test piece increases, the difference between the amplitude of the thermal wave at the defective part and the amplitude of the thermal wave at the non-defective part is smaller, and meanwhile, the phase difference value of the thermal wave also decreases. And when the amplitude difference is less than 0.001 ℃, determining that the defect cannot be detected by using the amplitude diagram, and when the phase difference is less than 0.2 ℃, determining that the defect cannot be detected by using the phase diagram.

S4, determining whether defect detection can be carried out according to an amplitude diagram and a phase diagram of an infrared phase-locked thermal imaging detection technology through simulation analysis of the aluminum skin honeycomb sandwich structure simulation defect, and determining a reasonable detection parameter range, wherein a specific analysis result shows

Table 4.

X-undetectable; check the check rate; -indicating absence

TABLE 4

The present invention will be described in further detail with reference to specific examples.

And manufacturing corresponding simulated defect test pieces aiming at different materials and defect types, carrying out nondestructive testing on the simulated defect test pieces by adopting an infrared phase-locking thermal imaging detection technology, and determining the influence of different thermal wave signal processing methods on the detection result and the infrared phase-locking thermal imaging detection modulation frequency ranges of different materials. Corresponding simulation defect test pieces are manufactured aiming at the honeycomb sandwich structure material for aerospace, and the debonding defect between the interfaces in the composite materials is simulated. Fig. 11 to 15 show schematic structural diagrams of different simulated defect test pieces.

FIG. 13 shows that 2 PTFE films are adhered to the adhesive layer in row 1, 2 PTFE films are adhered to the adhesive layer in row 2 after the adhesive layer is removed, and the adhesive layer in row 3 simulates a defect, and the minimum defect is formed at the connection position of the honeycomb sandwich. FIG. 14 shows a 2-layer polytetrafluoroethylene film applied to a glue layer. FIG. 15 shows a test piece structure of a carbon fiber skin with a variable thickness simulated defect, wherein 2 layers of polytetrafluoroethylene films are attached to the glue layer for simulating the defect. The specific simulated defect specimens and structural parameters are shown in table 5.

TABLE 5

1. Nondestructive testing test of defect simulation test piece of carbon fiber skin honeycomb sandwich structure

The carbon fiber skin honeycomb sandwich structure is an important structural material for aerospace, the skins are mainly connected with the honeycomb by bonding, debonding defects are easily generated between the skins and the honeycomb, and the test piece for simulating the defects of the carbon fiber skin honeycomb sandwich structure is detected by adopting an infrared phase-locking method thermal wave detection technology in this chapter to determine the detection capability of the defects with different skin thicknesses (defect depths). Table 6 gives the experimental parameters.

TABLE 6

As can be seen from fig. 16, for the test piece with the thin carbon fiber skin thickness, the minimum size of the simulated defect (diameter Φ 6mm) can be identified, while for the test piece with the thick skin, the minimum size of the simulated defect has a certain difficulty to be identified. When the skin thickness h_d>At 1.0mm, the resolution of the minimum spacing of the simulated defects is difficult, but some also meet the predetermined requirements. By simulating the design and manufacturing conditions of the defect test piece, the large-size defects in the test pieces with different skin thicknesses can be detected, the effect is satisfactory, and the skin thickness h is_d<1.0mm, the defect with smaller size can be detected, and the effect is satisfactory. When the skin thickness is thicker, the amplitude diagram is difficult to judge the defects.

When the infrared phase-locked thermal imaging detection is adopted, the surface of the test piece can influence the detection result on the reflection of other heating or luminous bodies, and the influence of the surface of the test piece on the reflection of the light source and other objects is reduced by adjusting the included angle theta between the light source and the test piece, namely the excitation incident angle of the light source.

In order to research the influence of the incidence angle of the excitation light source on the detection result, different incidence angles of the excitation light source are respectively adopted to excite the carbon fiber skin honeycomb sandwich structure simulated defect test piece, the image signal to noise ratio of a given simulated defect area in the test piece is calculated, and the influence of the incidence angle of the excitation light source on the detection effect is analyzed. Fig. 17 shows the area of the analysis simulated defect.

The phase and amplitude image signal-to-noise ratio of the simulated defect specimen can be calculated by the following formula.

Wherein: SNA_phaseRepresenting the phase image signal-to-noise ratio;a phase average value representing a defective region;represents the mean value of the phases of the defect-free region; sigma (Ph)_NondefectIndicating the standard deviation of the phase distribution of a non-defective region; SNA_AmRepresenting the amplitude image signal-to-noise ratio;an amplitude average value representing a defective region;represents the mean value of the amplitudes of the defect-free regions; sigma (Am)_NondefectIndicating the standard deviation of the amplitude distribution for a defect-free region.

Carbon fiber skin thickness h by adopting infrared phase-locked thermal imaging detection technology_dAnd (3) simulating a defect test piece for detecting test research by using the honeycomb sandwich structure of 0.5 mm. The parameters of the test are shown in Table 7.

TABLE 7

FIG. 18/shows the detection results of infrared phase-locked thermal imaging of different light source excitation thermal incident angles. As can be seen from fig. 18, under the given detection parameter conditions, changing the excitation incident angle of the light source has a large influence on the amplitude diagram, which indicates that uneven heating of the test piece may affect the detection effect of the amplitude diagram. In the phase diagram, the resolution of the simulated defects is not greatly influenced by the excitation incident angles of different light sources, which also shows that the sensitivity to uneven heating of the surface of the test piece of the phase diagram is low. FIG. 19 shows the effect of the light source excitation angle on the amplitude and phase image signal-to-noise ratio for a given local simulated defect region.

As can be seen from fig. 19, the signal-to-noise ratio of the amplitude image of the local simulated defect region decreases with increasing excitation incident angle of the light source, and the signal-to-noise ratio of the amplitude image of the simulated defect region with smaller size is lower under the condition of the given excitation incident angle of the light source. Under the condition of different light source excitation incident angles, the signal-to-noise ratio of the phase diagram of the local simulation defect area is much higher than that of the amplitude image, and the signal-to-noise ratio of the phase diagram is known, so that when the infrared phase-locked thermal imaging detection is adopted for an actual test piece, the light source excitation incident angle is selected within the range of theta <60 degrees, and a better detection effect can be obtained.

In order to analyze the detection capability of the infrared phase-locking thermal imaging detection technology on defects in the carbon fiber composite material skin honeycomb structure and the influence of the detection distance (the distance between a thermal imager and a detection test piece) on the detection effect, the infrared phase-locking thermal imaging technology is adopted to perform a detection test on the carbon fiber composite material skin honeycomb sandwich structure simulation defect test piece. And determining reasonable modulation frequency through parameter analysis and calibration test in the early stage. By shortening the detection distance, the size resolution of the defects in the simulated defect test piece in the field of view can be improved, the defect detection parameters of different carbon fiber composite material skin thicknesses can be determined through a calibration test, phase diagrams obtained by infrared phase-locked thermal imaging detection under different modulation frequency conditions are spliced by using an image splicing technology, and the detection of defects at different depths can be realized. For a simulated defect test piece with the skin thickness of 0.5mm, all simulated defects can be detected by adopting an infrared phase-locked thermal imaging technology under the conditions of given modulation frequency and detection distance.

For a simulated defect test piece with the skin thickness of 1.0mm, when the test piece is detected in a full-view field, the defect with a smaller size is difficult to determine from a phase diagram, the space resolution in the view field is improved after the block detection is carried out by shortening the detection distance, and the defect with the smaller size can be judged through the difference between the phase of a suspected defect and the phase around the suspected defect. Because the phase difference between the defect position and the non-defect position is obvious, the defect judgment is easily carried out through the phase difference, and the adjacent nearest defect is conveniently identified by reducing the detection distance, improving the field space resolution and adopting the image splicing technology.

Fig. 20 shows phase diagram results obtained by adopting different modulation frequency excitations for different carbon fiber composite material skin thicknesses, the phase diagram obtained by using the image stitching technology can determine the defects existing inside, and the minimum defect size phi 6mm can also be determined and identified.

2. Nondestructive testing test of aluminum skin honeycomb sandwich structure simulation defect test piece

The aluminum skin honeycomb sandwich structure is also an important structural material for aerospace, and has the characteristics of light weight, high specific stiffness, high specific strength, high bending strength and the like, so that the aluminum skin honeycomb sandwich structure is widely applied to satellite structures. The aluminum skin and the honeycomb are generally connected by bonding, debonding defects are easily generated between the skin and the honeycomb, and the honeycomb core grids also have the defects of core grid breakage, node separation, core shrinkage, wrinkle, insufficient foam glue or cavities and the like. The test piece with the simulated defects of the aluminum skin honeycomb sandwich structure is detected by adopting an infrared phase-locked thermal imaging detection technology, the detection capability and the modulation frequency selection range of the defects with different skin thicknesses are determined, and test parameters are given in a table 8.

TABLE 8

Thickness h of aluminum skin_dLess than or equal to 0.5mm, the simulation defect inside the test piece can be detected and distinguished, and the thickness h of the aluminum skin_d0.3mm, the modulation frequency is f_eSatisfactory detection results were obtained at 0.36Hz to 0.37 Hz. Thickness h of aluminum skin_d0.5mm, the modulation frequency should be f to obtain a good detection result_e0.34Hz to 0.35 Hz. Thickness h of aluminum skin_dThe defect of the minimum size (the diameter phi 6mm) in the test piece is difficult to distinguish and distinguish, but the defect diameter phi of 8mm can be detected. For aluminum skin thickness h_d0.8mm, the modulation frequency should be f_e＝0.17Hz～018Hz, aluminum skin thickness h_d1.0mm, the modulation frequency should be f_e0.09Hz to 0.11 Hz. Because the aluminum skin and the honeycomb are bonded by adopting glue, the glue with certain thickness has great influence on the detection of the simulation defects on the lower surface of the aluminum skin, and when the thickness of the skin is increased and the condition of the honeycomb under the glue layer is detected, the modulation frequency value detected by adopting the infrared phase-locked thermal imaging is reduced.

In order to analyze the influence of the detection capability and the detection distance of the infrared phase-locking thermal imaging detection technology on the defects in the aluminum skin honeycomb structure on the detection effect, the infrared phase-locking thermal imaging technology is adopted to carry out a detection test on a test piece with the simulated defects of the aluminum skin honeycomb sandwich structure. And determining reasonable modulation frequency through parameter analysis and calibration test in the early stage.

By shortening the detection distance, block detection is carried out, and the phase diagram is spliced by using an image splicing technology, so that the size resolution of the defects in the simulation defect test piece in the view field is improved.

For a simulation defect test piece with the aluminum skin thickness of 0.5mm and 1.0mm, under the conditions of given modulation frequency and detection distance, the infrared phase-locked thermal imaging technology is adopted to realize the detection of all simulation defects, the detection distance is shortened, the field-of-view spatial resolution is improved, the minimum defect size phi 6mm can be realized, but for a honeycomb sandwich structure with the skin thickness of 1.0mm, due to the influence of the transverse thermal diffusion of the aluminum skin, the defect contrast is reduced, namely the signal-to-noise ratio is reduced, the simulation defect edge in a phase diagram becomes fuzzy, and the defect boundary is difficult to accurately identify.

For a given test piece simulating defects, due to the influence of the transverse thermal diffusion of the aluminum skin, the defect contrast in a phase diagram obtained by adopting an infrared phase-locking thermal imaging technology is very low, the defects are difficult to judge, and meanwhile, the nearest adjacent defects can not be distinguished almost.

For a given simulated defect test piece, the detection distance is shortened, after block detection is carried out, the spatial resolution in a view field is improved, defects with smaller sizes can be judged, the nearest adjacent defects are difficult to distinguish, and the defects with the center distance of 15mm and the side length of 10mm can be distinguished from a spliced phase diagram and phase distribution. For a simulated defect test piece with a given defect shape, the geometrical shape of the defect can be accurately determined by adopting a phase diagram of an infrared phase-locked thermal imaging technology under the condition of giving reasonable detection parameters. The overall test results are shown in Table 9.

TABLE 9

FIGS. 20 to 27 are phase diagrams of the results of the tests, wherein FIG. 20 is a phase diagram of the sequence-1.0-5-p test result of the present invention at 0.165Hz stitching; FIG. 21 is a schematic of the phase distribution of line 1 for sequence-1.0-4-f of the present invention; FIG. 22 is a schematic of the phase distribution of line 2 for sequence-1.0-4-f of the present invention; FIG. 23 is a spliced phase diagram of the sequence-0.5-4-w of the present invention; FIG. 24 is a schematic phase distribution diagram for line 1 at sequence-0.5-4-w of the present invention; FIG. 25 is a schematic of the phase distribution of line 2 at sequence-0.5-4-w of the present invention; FIG. 26 is a schematic of the phase distribution of line 3 at sequence-0.5-4-w of the present invention; FIG. 27 is a schematic of the phase distribution of line 4 at sequence-0.5-4-w of the present invention.

The invention designs a simulation analysis method for detecting a honeycomb sandwich structure aircraft skin, which is different from a conventional infrared phase-locked thermal imaging detection simulation method by adopting a one-dimensional conduction model, fully considers constant heat flow and alternating heat flow, simultaneously considers the transverse heat diffusion influence in a honeycomb sandwich structure, and establishes a three-layer structure heat conduction model; performing transient process solution on the model by adopting a display integration method, performing load loading and signal processing, solving the amplitude and phase of the temperature signal, and determining the amplitude range and the phase range of the defective and non-defective positions; under the sine heat flow excitation condition, the temperature of the test piece is along the heat flow transfer direction, the temperature is gradually attenuated along with the increase of the transfer depth, and the thermal diffusion length exists, and the size of the thermal diffusion length is related to the heat conductivity coefficient, specific heat, density and heat flow excitation loading frequency of the material; it is clear that for air defects, reasonable heat flow excitation loading frequency and sampling analysis period number are needed to accurately determine defect characteristics so that the amplitude and phase difference are large.

Finally, it should be noted that: although the present invention has been described in detail with reference to the above embodiments, it should be understood by those skilled in the art that: modifications and equivalents may be made thereto without departing from the spirit and scope of the invention and it is intended to cover in the claims the invention as defined in the appended claims.