CN113819851A - Strain monitoring system of airborne radome based on distributed fiber bragg grating - Google Patents

Strain monitoring system of airborne radome based on distributed fiber bragg grating Download PDF

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CN113819851A
CN113819851A CN202111112229.0A CN202111112229A CN113819851A CN 113819851 A CN113819851 A CN 113819851A CN 202111112229 A CN202111112229 A CN 202111112229A CN 113819851 A CN113819851 A CN 113819851A
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CN113819851B (en
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刘春川
宋馥鑫
王阳绵
陈涛
傅康
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G01B11/16—Measuring arrangements characterised by the use of optical techniques for measuring the deformation in a solid, e.g. optical strain gauge
    • G01B11/18—Measuring arrangements characterised by the use of optical techniques for measuring the deformation in a solid, e.g. optical strain gauge using photoelastic elements
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
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Abstract

A strain monitoring system of an airborne radome based on distributed fiber bragg gratings belongs to the technical field of airborne radome health monitoring. The invention aims to solve the problems that damage cannot be found in time in health detection of the existing composite material radome and loss is caused by damage to the internal structure of the radome. The monitoring unit comprises a distributed optical fiber sensor and a temperature compensation sensor; the distributed optical fiber sensor is used for obtaining an actual strain signal at a corresponding position of the radar cover; the temperature compensation sensor is used for acquiring a temperature signal; the central processing unit is used for carrying out temperature compensation on the actual strain signal to obtain a compensated strain signal; the early warning unit is used for judging the compensated strain signal by adopting a machine learning model to obtain a radar cover state judgment result and sending an alarm signal when the radar cover state judgment result is abnormal; the narrow-band Internet of things communication module is used for sending the alarm signal to the airplane control platform. According to the method, the damage to the internal structure of the radar cover can be effectively avoided through damage prediction.

Description

Strain monitoring system of airborne radome based on distributed fiber bragg grating
Technical Field
The invention relates to a strain monitoring system of an airborne radome based on a distributed fiber bragg grating, and belongs to the technical field of airborne radome health monitoring.
Background
Composite radomes are widely used for their good performance. When the airplane is used for daily coping with complex working conditions such as severe weather, alternating stress, mechanical vibration and chemical corrosion, debonding damage, fatigue damage, structural corrosion and the like are easy to generate between the quartz fiber pavements of the radar cover. If the damage to airborne radome is not in time overhauled, mar and crackle enlarge gradually, can lead to near lacquer layer to drop, and then bring inner structure's damage or cause radar received signal's deviation, cause the loss. Therefore, the nondestructive health detection of the airborne radome composite material is indispensable in the service and maintenance processes of the airplane.
The distributed Brillouin optical time domain reflection technology is commonly used in foundation engineering such as slope engineering, bridge engineering and tunnel engineering, and is applied to various engineering fields such as mine overlying rock deformation monitoring, tunnel lining deformation and leakage monitoring, pile foundation detection, concrete internal temperature monitoring, pipe internal pressure bearing capacity monitoring, slide-resistant pile internal force and deformation monitoring and the like. Compared with a tedious monitoring process of an infrared thermal imaging technology or an X-ray detection method, the Brillouin distributed fiber grating has the unique advantages that: the sensor has the advantages of high monitoring sensitivity, corrosion resistance, high temperature resistance, small size, good electromagnetic insulation, adaptability to extremely severe environment, passivity, easiness in networking, sensing and communication transmission integration. Based on the method, the Brillouin distributed fiber bragg grating has wide application prospect in the aspect of aviation structure health monitoring.
Disclosure of Invention
The invention provides a strain monitoring system of an airborne radome based on distributed fiber bragg gratings, aiming at the problems that damage cannot be found in time in the health detection of the existing composite radome and loss is caused by damage of the internal structure of the radome.
The invention relates to a strain monitoring system of an airborne radome based on a distributed fiber bragg grating, which comprises,
the monitoring unit comprises a distributed optical fiber sensor and a temperature compensation sensor; uniformly selecting 12 measurement sections on the radome, burying a strain measurement optical fiber in the 3 rd layer of each measurement section, and respectively arranging strain sensors on the 12 strain measurement optical fibers as distributed optical fiber sensors; arranging 1 temperature compensation optical fiber between two adjacent strain measurement optical fibers to enable the temperature compensation optical fiber to be in a loose state, and arranging a temperature compensation sensor on the temperature compensation optical fiber;
the distributed optical fiber sensor acquires an actual strain signal at a corresponding position of the radome by monitoring the Brillouin center frequency shift change; the temperature compensation sensor is used for acquiring a temperature signal;
the central processing unit is used for carrying out temperature compensation on the actual strain signal according to the temperature signal to obtain a compensated strain signal;
the early warning unit is used for judging the compensated strain signal by adopting a machine learning model, obtaining a radome state judgment result and sending an alarm signal when the radome state is judged to be abnormal;
and the narrow-band Internet of things communication module is used for sending the alarm signal to the airplane control platform.
According to the strain monitoring system of the airborne radome based on the distributed fiber bragg grating, the central processing unit is further used for generating a strain cloud picture according to the compensated strain signals and by combining with 3D modeling, and the strain cloud picture is transmitted to the narrow-band Internet of things communication module through the early warning unit and finally transmitted to the aircraft control platform.
According to the strain monitoring system of the airborne radome based on the distributed fiber bragg grating, the machine learning model adopts a support vector machine classification algorithm optimized by an improved chicken swarm algorithm to judge the compensated strain signal;
the optimized support vector machine classification algorithm is formed by training a material and structure database of the radome, and the normalized compensated strain signal is used as input to identify the state of the radome, so that a radome state judgment result is obtained.
According to the strain monitoring system of the airborne radome based on the distributed fiber bragg grating, the signal measurement process of the distributed fiber sensor and the temperature compensation sensor comprises the following steps:
setting a laser to be in a single-frequency emission working mode; enabling the laser to send a laser signal to the circulator and then enter the modulator, and enabling the modulator to be biased at a zero power point through the adjustment of the bias controller; an electric pulse signal sent by the modulator drives the photoelectric modulator through the driver to obtain an optical pulse signal, and the optical pulse signal enters the optical fiber after being gained by the amplifier;
and the Brillouin backscattering signals in the optical fiber are processed by the photoelectric detector after noise is filtered by the filter, and the obtained result is used as an actual strain signal or a temperature signal.
According to the strain monitoring system of the airborne radome based on the distributed fiber bragg grating, the strain signal after compensation is obtained by calculation according to the strain variation delta epsilon; the strain variation Δ ∈ is calculated according to the following formula:
ΔB＝TkΔT+EkΔε，
where Δ B is the variation of Brillouin center frequency shift, TkIs the intrinsic Brillouin frequency shift temperature coefficient of the optical fiber,. DELTA.T is the temperature variation of the optical fiber, EkThe intrinsic Brillouin frequency shift strain coefficient of the optical fiber is obtained;
the optical fiber temperature variation delta T is obtained by making a difference between a temperature signal obtained by the temperature compensation sensor and the optical fiber calibration temperature.
According to the strain monitoring system of the airborne radome based on the distributed fiber bragg grating, the early warning unit comprises a radome abnormal state decision scheme, and the decision scheme is used for obtaining the strain abnormal position and the damage degree of the radome.
According to the strain monitoring system of the airborne radome based on the distributed fiber bragg grating, the central processing unit and the early warning unit are AB central processing units with models of 1769-L33 ER.
According to the strain monitoring system of the airborne radome based on the distributed fiber bragg grating, the narrow-band internet-of-things communication module adopts Boudica of Huashi 5G series.
The invention has the beneficial effects that: the monitoring unit can realize long-distance continuous data acquisition, further realize accurate calculation of data such as strain, temperature and the like at a certain position, and form dynamic real-time monitoring of a network-shaped large-scale area. By using the temperature compensation fiber in a relaxed state for temperature compensation, the result of the compensated strain signal can be made more accurate.
The strain and temperature monitoring system can quickly, accurately and real-timely monitor the strain and temperature of the conical-shell type quartz fiber composite airborne radome, has strong anti-interference capability, good continuity, high accuracy and strong positioning performance of monitoring results, can reflect the internal force change rule of the radome, and can effectively discover interlayer inclusions and crack damage of the quartz fiber composite, thereby realizing damage identification prediction and overall health monitoring of the airborne radome. Damage to the internal structure of the radar cover can be effectively avoided through damage prediction, and therefore loss is reduced.
Drawings
FIG. 1 is a flow chart of a strain monitoring system of a distributed fiber grating-based airborne radome of the present invention;
FIG. 2 is a schematic view of a radome embedded fiber; wherein P is a temperature compensation optical fiber, and Q is a strain measurement optical fiber;
FIG. 3 is a schematic cross-sectional view of FIG. 2; where W represents the 3 rd ply of the measurement section.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict.
The invention is further described with reference to the following drawings and specific examples, which are not intended to be limiting.
First embodiment, as shown in fig. 1 to 3, the present invention provides a strain monitoring system for a distributed fiber grating-based airborne radome, including,
the monitoring unit comprises a distributed optical fiber sensor and a temperature compensation sensor; uniformly selecting 12 measurement sections on the radome, burying a strain measurement optical fiber in the 3 rd layer of each measurement section, and respectively arranging strain sensors on the 12 strain measurement optical fibers as distributed optical fiber sensors; arranging 1 temperature compensation optical fiber between two adjacent strain measurement optical fibers to enable the temperature compensation optical fiber to be in a loose state, and arranging a temperature compensation sensor on the temperature compensation optical fiber;
the distributed optical fiber sensor acquires an actual strain signal at a corresponding position of the radome by monitoring the Brillouin center frequency shift change; the temperature compensation sensor is used for acquiring a temperature signal;
the central processing unit is used for carrying out temperature compensation on the actual strain signal according to the temperature signal to obtain a compensated strain signal;
the early warning unit is used for judging the compensated strain signal by adopting a machine learning model, obtaining a radome state judgment result and sending an alarm signal when the radome state is judged to be abnormal;
and the narrow-band Internet of things communication module is used for sending the alarm signal to the airplane control platform.
The narrow-band Internet of things communication module is used as a communication technology specially designed for the Internet of things, has performance superior to other wireless communication technologies in the fields of sensing, monitoring and the like, and can receive the state diagram and various signals of the radome sent by the central processing unit in real time and send the state diagram and various signals to the aircraft control platform.
In this embodiment, all the pigtails of the optical fibers can be connected to the brillouin optical time domain reflectometer after being collected by the collection box, and the brillouin optical time domain reflectometer collects corresponding signals and then transmits the signals to the central processing unit.
The early warning unit can be connected with an alarm, and when the machine learning model judges that the state of the radome is abnormal, the alarm can be started to give an alarm. The machine learning model can judge the normal position of the variation and the damage degree.
The embodiment uses the distributed optical fiber sensor and the temperature compensation optical fiber at the same time, so that the measured strain is more accurate.
Furthermore, the central processing unit is also used for generating a strain cloud picture and a radar picture by combining 3D modeling according to the compensated strain signals, and the strain cloud picture and the radar picture are transmitted to the narrow-band Internet of things communication module through the early warning unit and are finally transmitted to the airplane control platform.
The central processing unit may store the received temperature signal, the actual strain signal, and the compensated strain signal.
Further, the machine learning model judges the compensated strain signals by adopting a support vector machine classification algorithm optimized by an improved chicken flock algorithm;
the optimized support vector machine classification algorithm is formed by training different materials and a structural database of the radome, and the normalized compensated strain signal is used as input to identify the state of the radome, so that a radome state judgment result is obtained. The optimized support vector machine classification algorithm can identify the real-time state of the radome, and can judge the strain abnormal position and the damage degree once the radome is abnormal in state.
In the standard chicken flock algorithm, the position of the chicken particle is only determined by the chicken particle in the subgroup, and the position shift formula is as follows:
xm,n(t+1)＝xm,n(t)+L[xp,n(t)-xm,n(t)]，
in the formula xm,n(t +1) and xm,n(t) respectively represents the position of the mth chicken in the nth dimensional space at the t +1 th time and the t-th time, L is the walking step length of the chicken particles following the hen particles to search food, and specifically takes [0, 2 [ ]]A random number of intervals, xp,n(t) represents the position of the maternal particle followed by the chick particle.
The algorithm is improved to solve the problem of chicken particlesOnly following mothers in the subgroup to search food, and the searching capability is poor. Introducing a following coefficient S3And S4The chick searching method has the advantages that the chick can follow the cock particles in the subgroup and the cock particles in other subgroups to search for food besides the mother, so that even if the mother particles are locally optimal, the situation that the chick only follows the mother and then is locally optimal can be avoided, and meanwhile, the learning efficiency of the chick and the convergence speed of an algorithm are improved. The position of the modified chick granules is shifted according to the following formula:
Figure BDA0003271232700000051
in the formula S3A tracking coefficient, S, representing the movement of the chicks following the cock particles of the subgroup in which they are located4A tracking coefficient representing the movement of the chicks following the cock particulates in the other subgroups,
Figure BDA0003271232700000052
representing the position of the cock microgranules in the subgroup of chicks,
Figure BDA0003271232700000053
representing the location of the other subgroup of cock particulates.
Aiming at the actual situation and the data characteristics of the invention, the European radial basis function RBF is defined as follows:
RBF(hi,hj)＝exp(-ρ||hi-hj||2),ρ＞0，
wherein h isiIs an input sample, i.e., the compensated strain signal in this embodiment, hjFor the training samples, ρ is a parameter controlling the degree of non-linearity of the gaussian kernel.
The model needs to set a penalty coefficient, namely error tolerance, which is recorded as lambda. The nonlinear parameters rho and punishment coefficients lambda of different combinations can influence the classification precision of the algorithm, and in order to obtain the optimal rho and lambda array, the parameter combination is optimized by combining a circular estimation method and a grid search method to find the parameter with the best model classification effectCombination rho0And λ0。
The machine learning model can be specifically divided into eight steps:
the first step is as follows: setting the size K of the chicken flock population, the update frequency G of the population, the iteration times M, the percentage of various particles, and the following coefficient S3And S4A value of (d); setting the range of a punishment coefficient lambda and a nonlinear parameter rho of a support vector machine, and setting the cycle estimation cycle number;
the second step is that: according to fitness function
Figure BDA0003271232700000054
Determining the fitness value and the optimal position of each particle;
the third step: when the iteration time t/G is 1, sorting the fitness values, establishing a grading system among the particles, and determining the relationship between the hen particles and the chick particles and the cock particles;
the fourth step: the position of the cock particles is updated,
xm,n(t+1)＝xm,n(t)[1+Randn(0,σ2)]，
Figure BDA0003271232700000055
Randn(0,σ2) Is a random number following a Gaussian distribution, the mean is 0, and the standard deviation is σ2；fmrAnd fkrThe fitness values of the m and k cock particles are respectively, and m and k are not equal; ε is a very small constant;
the fifth step: the position of the hen particles is updated,
Figure BDA0003271232700000061
S1＝exp{(fmq-f)/[abs(fm+ε)]}，
Figure BDA0003271232700000062
S1is a hen particle relativeThe ratio of the group S2Is the proportion of the hen motes located in other search populations,
Figure BDA0003271232700000063
a location of the cock microgranule representing a population in which the hen microgranule is located, and
Figure BDA0003271232700000064
representing the positions of the cock particulates of other populations;
and a sixth step: the position of the chicken particles is updated,
Figure BDA0003271232700000065
the seventh step: calculating a particle fitness function value after updating;
eighth step: and finding the optimal fitness value and the global optimal fitness value of the particles, and the optimal position and the global optimal position of the particles at present. And judging whether the constraint conditions are met, if so, outputting the optimal parameters, and if not, returning to the third step for continuous execution.
Through the improvement and the parameter optimization, the obtained support vector machine adopts the improved chicken flock algorithm, the optimal kernel function RBF and the optimal parameter combination rho0And λ0The classification performance is very good.
Still further, the signal measurement process of the distributed optical fiber sensor and the temperature compensation sensor comprises the following steps:
setting a laser to be in a single-frequency emission working mode; enabling the laser to send a laser signal to the circulator and then enter the modulator, and enabling the modulator to be biased at a zero power point through the adjustment of the bias controller; an electric pulse signal sent by the modulator drives the photoelectric modulator through the driver to obtain an optical pulse signal, and the optical pulse signal enters the optical fiber after being gained by the amplifier;
and the Brillouin backscattering signals in the optical fiber are processed by the photoelectric detector after noise is filtered by the filter, and the obtained result is used as an actual strain signal or a temperature signal.
The temperature compensation optical fiber is required to be in a loose state and not stressed in the composite material laying layer.
Further, the compensated strain signal is obtained by calculation according to the strain variation delta epsilon; the strain variation Δ ∈ is calculated according to the following formula:
ΔB＝TkΔT+EkΔε，
where Δ B is the variation of Brillouin center frequency shift, TkIs the intrinsic Brillouin frequency shift temperature coefficient of the optical fiber,. DELTA.T is the temperature variation of the optical fiber, EkThe intrinsic Brillouin frequency shift strain coefficient of the optical fiber is obtained;
the optical fiber temperature variation delta T is obtained by making a difference between a temperature signal obtained by the temperature compensation sensor and the optical fiber calibration temperature.
The Brillouin frequency shift linearly changes along with the changes of strain and temperature in the environment, and the strain condition of the radar cover can be calculated through the formula.
Still further, the early warning unit comprises a radar cover abnormal state decision scheme, and the decision scheme is used for obtaining the strain abnormal position and the damage degree of the radar cover.
If the aircraft control platform has a mature decision scheme (such as return maintenance or continuous task execution) for different abnormal states of the radome, the decision scheme can be preset in the early warning unit, so that the early warning unit can provide the decision scheme while alarming the abnormal state, and the decision efficiency of a pilot can be improved. And the information of the early warning unit is sent to the airplane control platform through the narrow-band Internet of things communication module.
As an example, the central processing unit and the early warning unit are AB central processing units with models of 1769-L33 ER.
By way of example, the narrow-band internet of things communication module adopts Boudica of Haisi 5G series.
In the invention, the number of the strain measurement optical fibers is not limited to 12, and the strain measurement optical fibers can be selected according to requirements; the temperature compensation optical fibers can also be multiple, and the temperature compensation optical fibers are uniformly arranged on the radar cover and are respectively arranged between two adjacent strain measurement optical fibers.
Although the invention herein has been described with reference to particular embodiments, it is to be understood that these embodiments are merely illustrative of the principles and applications of the present invention. It is therefore to be understood that numerous modifications may be made to the illustrative embodiments and that other arrangements may be devised without departing from the spirit and scope of the present invention as defined by the appended claims. It should be understood that features described in different dependent claims and herein may be combined in ways different from those described in the original claims. It is also to be understood that features described in connection with individual embodiments may be used in other described embodiments.

Claims (8)

1. A strain monitoring system of an airborne radome based on a distributed fiber bragg grating is characterized by comprising,
the monitoring unit comprises a distributed optical fiber sensor and a temperature compensation sensor; uniformly selecting 12 measurement sections on the radome, burying a strain measurement optical fiber in the 3 rd layer of each measurement section, and respectively arranging strain sensors on the 12 strain measurement optical fibers as distributed optical fiber sensors; arranging 1 temperature compensation optical fiber between two adjacent strain measurement optical fibers to enable the temperature compensation optical fiber to be in a loose state, and arranging a temperature compensation sensor on the temperature compensation optical fiber;
the distributed optical fiber sensor acquires an actual strain signal at a corresponding position of the radome by monitoring the Brillouin center frequency shift change; the temperature compensation sensor is used for acquiring a temperature signal;
the central processing unit is used for carrying out temperature compensation on the actual strain signal according to the temperature signal to obtain a compensated strain signal;
the early warning unit is used for judging the compensated strain signal by adopting a machine learning model, obtaining a radome state judgment result and sending an alarm signal when the radome state is judged to be abnormal;
and the narrow-band Internet of things communication module is used for sending the alarm signal to the airplane control platform.
2. The distributed fiber grating-based airborne radome strain monitoring system of claim 1,
the central processing unit is further used for generating a strain cloud picture by combining the compensated strain signal with 3D modeling, and the strain cloud picture is transmitted to the narrow-band Internet of things communication module through the early warning unit and is finally transmitted to the airplane control platform.
3. The strain monitoring system of the distributed fiber grating-based airborne radome of claim 1 or 2, wherein the machine learning model adopts a support vector machine classification algorithm optimized by an improved chicken swarm algorithm to judge the compensated strain signal;
the optimized support vector machine classification algorithm is formed by training a material and structure database of the radome, and the normalized compensated strain signal is used as input to identify the state of the radome, so that a radome state judgment result is obtained.
4. The distributed fiber grating-based strain monitoring system for an airborne radome of claim 3 wherein the signal measurement process of the distributed fiber sensor and the temperature compensation sensor comprises:
setting a laser to be in a single-frequency emission working mode; enabling the laser to send a laser signal to the circulator and then enter the modulator, and enabling the modulator to be biased at a zero power point through the adjustment of the bias controller; an electric pulse signal sent by the modulator drives the photoelectric modulator through the driver to obtain an optical pulse signal, and the optical pulse signal enters the optical fiber after being gained by the amplifier;
and the Brillouin backscattering signals in the optical fiber are processed by the photoelectric detector after noise is filtered by the filter, and the obtained result is used as an actual strain signal or a temperature signal.
5. The distributed fiber grating-based strain monitoring system for an airborne radome of claim 4, wherein the compensated strain signal is obtained by calculation according to a strain variation Δ ∈; the strain variation Δ ∈ is calculated according to the following formula:
ΔB＝TkΔT+EkΔε，
where Δ B is the variation of Brillouin center frequency shift, TkIs the intrinsic Brillouin frequency shift temperature coefficient of the optical fiber,. DELTA.T is the temperature variation of the optical fiber, EkThe intrinsic Brillouin frequency shift strain coefficient of the optical fiber is obtained;
the optical fiber temperature variation delta T is obtained by making a difference between a temperature signal obtained by the temperature compensation sensor and the optical fiber calibration temperature.
6. The distributed fiber grating-based strain monitoring system for an airborne radome of claim 5, wherein the early warning unit comprises a radome abnormal state decision scheme, and the decision scheme is used for obtaining the strain abnormal position and the damage degree of the radome.
7. The strain monitoring system of the distributed fiber grating-based airborne radome of claim 6, wherein the central processing unit and the early warning unit are AB central processing units of models 1769-L33 ER.
8. The strain monitoring system of the airborne radome based on the distributed fiber grating as recited in claim 7, wherein the narrowband internet of things communication module adopts Boudica of Hassi 5G series.
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