Aircraft composite material structure health monitoring system and method

Abstract

The invention discloses an aircraft composite material structure health monitoring system and method, and relates to the field of aircraft material health monitoring, and the system comprises a DAS integrated optical module which is used for generating and transmitting an optical pulse pair subjected to heterodyne phase modulation to a single-mode optical fiber sensing network, and converting backward Rayleigh scattering light into an electric signal; the single-mode optical fiber sensing network is arranged on the surface of the aircraft composite material structure and is used for converting an acoustic emission signal containing the physical change of the aircraft composite material structure into an optical phase change signal by utilizing a coherent Rayleigh scattering effect; the digital signal processing module is used for carrying out signal processing on the electric signal by utilizing a heterodyne phase modulation method based on instantaneous frequency tracking so as to identify and position the damage of the aircraft composite material structure; and the alarm output module is used for outputting a damage position, a damage degree grade and an alarm signal of the airplane composite material structure in real time when the structural damage is detected, so that full-distribution and wide-range online accurate monitoring is realized.

Description

Technical Field

[0001] This application relates to the field of aircraft material health monitoring, and in particular to an aircraft composite material structure health monitoring system and method. Background Technology

[0002] With the rapid development of the aviation industry, composite materials, due to their advantages such as high strength, lightweight, and corrosion resistance, are widely used in key structures such as aircraft fuselages and wings, accounting for more than 50% of the structural weight of aircraft. However, during long-term service, aircraft are susceptible to damage such as microcracks and interlaminar delamination caused by factors such as flight loads, airflow impact, temperature cycling, and external collisions. If these damages are not detected in time, they will gradually expand with the increase of flight frequency, seriously threatening flight safety.

[0003] Existing technologies for monitoring the health of aircraft composite structures have several shortcomings: 1) Traditional point-based sensing technologies (such as strain gauges and piezoelectric sensors) require a large number of sensor nodes to be deployed on the structural surface, resulting in blind spots. Furthermore, sensor installation can damage the integrity of the composite structure, and these technologies are ill-suited for large-scale, fully distributed monitoring. 2) Conventional fiber optic sensing technologies (such as fiber Bragg grating (FBG) based sensing schemes) possess some distributed monitoring capabilities, but their demodulation systems are complex and costly, and their dynamic range is limited, making it difficult to capture acoustic emission signals from minute damages. Traditional interferometric fiber optic sensing schemes are constrained by heterodyne frequency and system bandwidth; increasing the heterodyne frequency leads to increased system bandwidth requirements, while airborne system bandwidth resources are limited, making it difficult to balance dynamic range and monitoring sensitivity. 3) Ultrasonic testing and infrared thermal imaging technologies require manual inspection while the aircraft is parked, making online real-time monitoring impossible. They also lack the ability to identify early minute damages, resulting in low detection efficiency and failing to meet the needs of full lifecycle health management for aircraft.

[0004] Therefore, there is an urgent need for a health monitoring technology for aircraft composite material structures that has full-distribution, wide-range online monitoring capabilities and is adaptable to airborne environments. Summary of the Invention

[0005] The purpose of this application is to provide a health monitoring system and method for aircraft composite material structures, which can achieve full-distribution, wide-range online accurate monitoring.

[0006] To achieve the above objectives, this application provides the following solution: In a first aspect, this application provides a health monitoring system for aircraft composite material structures, comprising: The DAS integrated optical module is used to generate and transmit heterodyne phase-modulated optical pulse pairs to a single-mode fiber optic sensing network, and to receive backscattered Rayleigh light carrying optical phase change signals from the single-mode fiber optic sensing network, and convert the backscattered Rayleigh light into an electrical signal. A single-mode fiber optic sensing network is deployed on the surface of an aircraft composite material structure to convert acoustic emission signals containing physical changes in the aircraft composite material structure into optical phase change signals using the coherent Rayleigh scattering effect. A digital signal processing module, electrically connected to the DAS integrated optical module, is used to process the electrical signal using a heterodyne phase modulation method based on instantaneous frequency tracking in order to identify and locate damage to the aircraft composite material structure. The alarm output module is communicatively connected to the digital signal processing module and is used to output the damage location, damage level, and alarm signal of the aircraft composite material structure in real time when structural damage is detected.

[0007] Secondly, this application provides a method for monitoring the health of aircraft composite structures based on the aircraft composite structure health monitoring system described in the first aspect, comprising: The DAS integrated optical module generates and transmits heterodyne phase-modulated optical pulses to a single-mode fiber optic sensing network; using the coherent Rayleigh scattering effect, the acoustic emission signal containing the physical changes of the aircraft composite material structure is converted into an optical phase change signal; and the backscattered Rayleigh light carrying the optical phase change signal is converted into an electrical signal. The electrical signal is processed using a heterodyne phase modulation method based on instantaneous frequency tracking to identify and locate damage to the aircraft composite material structure. When structural damage is detected, the location of the damage, the level of damage, and the alarm signal of the aircraft composite material structure are output in real time.

[0008] According to the specific embodiments provided in this application, this application has the following technical effects: This application provides a health monitoring system and method for aircraft composite material structures. A single-mode fiber optic sensor network is deployed on the surface of the aircraft composite material structure to achieve full-area, blind-spot-free monitoring. The system has a high signal-to-noise ratio and can identify early-stage micro-cracks and interlaminar delamination damage in aircraft composite material structures. High-frequency phase modulation technology is introduced to effectively increase the heterodyne frequency under limited system bandwidth. Combined with an instantaneous frequency tracking algorithm, the phase winding problem is solved, and the upper limit of the dynamic range is improved compared with existing solutions. It can simultaneously meet the monitoring needs of micro-damage and large-amplitude structural deformation. Based on coherent Rayleigh scattering, combined with phase modulation heterodyne demodulation technology and instantaneous frequency tracking algorithm, it achieves full-distribution, wide-range, and accurate online monitoring of damage in aircraft composite material structures. It overcomes the problems of monitoring blind spots, limited dynamic range, and poor airborne adaptability in traditional technologies, providing reliable protection for flight safety. Attached Figure Description

[0009] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0010] Figure 1 This is a structural schematic diagram of an aircraft composite material structure health monitoring system provided in Embodiment 1 of this application.

[0011] Figure 2 This is a schematic diagram of the heterodyne DAS detection principle provided in Embodiment 1 of this application.

[0012] Figure 3 This is a schematic diagram showing the relationship between the first-order and second-order Bessel functions and the modulation coefficient M, as provided in Embodiment 1 of this application.

[0013] Figure 4 This is a flowchart of the IQ demodulation algorithm provided in Embodiment 1 of this application.

[0014] Figure 5 This is a schematic diagram of the phase extraction process of the IQ demodulation algorithm provided in Embodiment 1 of this application.

[0015] Figure 6 This is a schematic diagram of phase winding provided in Embodiment 1 of this application.

[0016] Figure 7 The flowchart of the heterodyne demodulation algorithm based on instantaneous frequency tracking provided in Embodiment 1 of this application is shown.

[0017] Figure 8 This is a schematic diagram of the digital implementation of the digital instantaneous frequency measurement method provided in Embodiment 1 of this application.

[0018] Figure 9 The different sampling delays m provided in Embodiment 1 of this application correspond to Value diagram.

[0019] Figure 10 This is a schematic diagram of the frequency exceeding the threshold, the expected demodulation rotation direction, and the required correction factor provided in Embodiment 1 of this application.

[0020] Figure 11 This is a schematic diagram of the rotation probability of the demodulated output rotation direction given an actual direction, as provided in Embodiment 1 of this application.

[0021] Figure 12 This is a schematic diagram of the phase winding correction factor boundary with the maximum and minimum likelihood demodulation rotation direction provided in Embodiment 1 of this application. Detailed Implementation

[0022] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0023] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0024] Example 1 like Figure 1 As shown, this embodiment provides a health monitoring system for aircraft composite material structures. The system includes an integrated DAS optical module, a single-mode fiber optic sensor network, a digital signal processing module, and an alarm output module. All components are stably connected via standardized interfaces, and the overall structure employs a lightweight design to adapt to airborne environmental requirements.

[0025] The DAS integrated optical module is a heterodyne frequency-enhanced distributed acoustic sensing (DAS) integrated optical module based on an integrated optical modulator (IOC). It is used to generate and transmit heterodyne phase-modulated optical pulse pairs to a single-mode fiber optic sensing network, and receive backscattered Rayleigh light carrying optical phase change signals from the single-mode fiber optic sensing network, converting the backscattered Rayleigh light into an electrical signal.

[0026] A single-mode fiber optic sensor network is a distributed single-mode fiber optic sensor network deployed on the surface of an aircraft composite material structure. It is used to convert acoustic emission signals containing physical changes in the aircraft composite material structure into optical phase change signals by utilizing the coherent Rayleigh scattering effect.

[0027] The digital signal processing module, electrically connected to the DAS integrated optical module, is used to process the electrical signal using a heterodyne phase modulation method based on instantaneous frequency tracking in order to identify and locate damage to the aircraft composite material structure.

[0028] The alarm output module, which is communicatively connected to the digital signal processing module, is used to output the location, severity level, and alarm signal of the aircraft composite material structure in real time when structural damage is detected. It supports multiple interface outputs.

[0029] The DAS integrated optical module includes a narrow linewidth laser (NLL), a semiconductor optical amplifier (SOA), an unbalanced Mach-Zehnder (MZ) interferometer, and a photodetector (PD).

[0030] A narrow-linewidth laser is used to provide a detection light source and emit continuous light; the operating wavelength of the narrow-linewidth laser is set to 1550.92nm, and the output optical power is stabilized at 17mW.

[0031] A semiconductor optical amplifier is used to convert continuous light into pulsed light, thereby generating optical pulses. A PPG (programmable pulse generator) is used to control the semiconductor optical amplifier to generate pulsed light.

[0032] An unbalanced Mach-Zehnder interferometer is used to separately perform frequency shifting and continuous phase modulation on pulsed light, and then synthesize the frequency-shifted and phase-modulated light signals into a single optical pulse pair. This pair is then used to interfere with the backscattered Rayleigh light carrying the phase change signal, resulting in an interference light signal. The unbalanced Mach-Zehnder interferometer achieves the interference superposition of optical signals, converting phase changes into intensity changes.

[0033] The length difference between the two arms of the unbalanced Mach-Zehnder interferometer is set to 50m. One arm of the unbalanced Mach-Zehnder interferometer includes an acousto-optic modulator (AOM), and the other arm includes a first optical circulator CIR1, an integrated optical phase modulator (IOC), a Faraday rotator (FRM), and a fiber delay loop to eliminate polarization fading. One end of the acousto-optic modulator and one end of the first optical circulator CIR1 are connected to a semiconductor optical amplifier via a first single-mode fiber coupler; the other end of the acousto-optic modulator and the other end of the first optical circulator CIR1 are connected to a second optical circulator CIR2 via a second single-mode fiber coupler; the second optical circulator CIR2 is used to connect the DAS integrated optical module, the single-mode fiber sensing network, and the digital signal processing module.

[0034] An acousto-optic modulator is used to frequency-shift pulsed light to generate the heterodyne frequency required for heterodyne detection. It achieves frequency shifting of the optical pulse by approximately 80 MHz, with an extinction ratio of at least 60 dB. Figure 1 In the middle: DC (power supply) provides DC drive signal to the acousto-optic modulator via RF drive.

[0035] An integrated optical phase modulator is used to introduce high-frequency phase modulation, continuously applying phase modulation to pulsed light and reducing the system's bandwidth requirements. The integrated optical phase modulator uses a Y-cut Z-transfer LiNbO3 crystal structure based on titanium diffusion technology, operating at a wavelength of 1550 nm, with an average insertion loss of 3.44 dB, polarization loss of 0.54 dB, output polarization crosstalk of -31.0 dB, half-wave voltage (TE) of 3.75 V, and modulation bandwidth ≥300 MHz. An AFG (Arbitrary Function Generator) is used to generate the modulation signal.

[0036] A photodetector is used to convert interfering optical signals into electrical signals. The photodetector has a bandwidth of 200MHz to ensure efficient conversion of high-frequency signals.

[0037] Single-mode fiber optic sensing network: Employing a specific deployment method, single-mode optical fibers are fixed to the surfaces of critical aircraft composite structures, such as wing spars and fuselage skin joints, using a combination of helical winding and straight bonding. The fiber density is dynamically adjusted based on the stress concentration level of the structure, with a spacing of no more than 5cm in stress concentration areas and no more than 15cm in non-stress concentration areas. The single-mode fiber optic sensing network is connected to the DAS integrated optical module and digital signal processing module via a second optical circulator (CIR2). As an acoustic signal acquisition medium, the single-mode fiber optic sensing network utilizes the coherent Rayleigh scattering effect to convert physical changes such as vibration and crack propagation in the aircraft composite structure into optical phase change signals, achieving fully distributed, blind-zone-free signal acquisition.

[0038] The DAS integrated optical module and the single-mode fiber optic sensing network are connected through the second optical circulator CIR2. The photodetector output of the DAS integrated optical module is connected to the data acquisition card (DAQ) input port of the digital signal processing module. The digital signal processing module transmits data to the alarm output module through the PCIe bus. The power supply for each module is provided by the onboard 28V DC power supply through the voltage regulator module to ensure power supply stability.

[0039] The principle of heterodyne DAS detection is as follows: Figure 2 As shown, the following steps are used to achieve full-distribution, wide-range online acquisition of structural acoustic emission signals and damage identification and localization.

[0040] (1) System initialization and parameter configuration: The integrated airborne structural health monitoring system is started by the signal processing module, and a power-on self-test is performed on the narrow linewidth laser, AOM, IOC, and data acquisition card. After the self-test passes, the operating parameters of the narrow linewidth laser, SOA modulation pulse parameters, AOM frequency shift, IOC modulation parameters, DAQ sampling rate, and initial value of the dynamic threshold are configured. The initial value of the dynamic threshold is set according to the ambient noise level under the static state of the aircraft on the ground, ensuring that the initial threshold is more than 3dB higher than the ambient noise.

[0041] (2) Optical Pulse Generation and Phase Modulation: A narrow-linewidth laser emits continuous light, which is converted into pulsed light after passing through the SOA. The pulsed light then enters the unbalanced Mach-Zehnder interferometer after passing through the polarization-maintaining fiber coupler C1. After passing through the first single-mode fiber coupler C1, the pulsed light is split into two paths. One path undergoes frequency shifting processing through the AOM. The other path is continuously phase-modulated through the IOC, and a delay is generated after passing through the fiber delay loop (the circle between the IOC and the FRM). The phase modulation coefficient is... Set to a small value less than 1. The modulation signal expression is: (1); in, For integrated optical phase modulators The modulated signal generated at a given time; The modulation angular frequency of IOC is set to 55MHz.

[0042] The two optical paths are finally combined into one after passing through the second single-mode fiber coupler C2, generating a pulse pair of a specific frequency, which then enters the single-mode fiber sensing network.

[0043] (3) Acoustic emission signal acquisition and interference conversion: Pulse pairs are transmitted through a single-mode fiber optic sensing network. When damage occurs in the aircraft composite material structure, such as crack propagation or interlayer delamination, the generated acoustic emission signal causes vibration of the medium surrounding the fiber, resulting in a change in the phase of the light transmitted in the fiber (coherent Rayleigh scattering effect). The backscattered light carrying the phase change information returns to the second optical circulator CIR2, where it interferes with the photodetector. The interference light signal is converted into an electrical signal by the photodetector. Its expression is: (2); in, for The electrical signal at a given moment; The amplitude of the AC signal detected by the detector; It is a sine function; The heterodyne frequency generated by the acousto-optic modulator; The phase change caused by the acoustic emission signal; This is the initial phase.

[0044] Substituting equation (1) into equation (2) and performing a Bessel expansion, we can write: (3); in, It is a k-th order Bessel function. It is a 0th-order Bessel function; It is a 2k-order Bessel function; for Bessel function of order.

[0045] Optical methods can be used to reduce the requirements of the system acquisition card. Generally, the sampling frequency of the acquisition card should be 8 times the heterodyne frequency. The higher the heterodyne frequency, the better the detection effect of the DAS system.

[0046] Assuming the modulation coefficient is small, we have Since the higher-order terms are relatively small compared to the first-order and zero-order terms, they can be ignored. Therefore, equation (3) can be approximated as: (4).

[0047] in, This can be expanded as follows: (5); Substituting equation (5) into equation (4), we get: (6); in, It is a first-order Bessel function. From equation (6), it can be seen that... It still carries acoustic wave phase information. The relationship between the first-order and second-order Bessel functions and the modulation coefficient M is as follows: Figure 3 As shown.

[0048] (4) Signal demodulation and phase dewinding: The electrical signal output by the detector is passed through a low-pass filter with a cutoff frequency of 50MHz. After filtering by equation (7), higher-order terms can be ignored, and a simplified signal expression is obtained. The low-frequency component carrying acoustic emission information is extracted by the IQ demodulation algorithm: (7); As can be seen from equation (7), It still carries sound wave phase information, making the intermediate quantity After appropriate low-pass filtering, equation (7) can be written as: (8); In the formula This is the filtered signal. It can be seen that the heterodyne phase modulation method introduces phase modulation into the optical path. The heterodyne frequency in the optical path is the same as the frequency shift of the AOM (Aspect-Order Optimizer), and the heterodyne frequency is not reduced. At the detector end, a first-order carrier is used to demodulate the acoustic signal, and the resulting first-order carrier frequency is the difference between the heterodyne frequency and the phase carrier frequency, rather than the AOM frequency shift, thus reducing the requirements for system bandwidth and sampling rate. In other words, the heterodyne phase modulation method proposed in this example can increase the carrier frequency under the same system bandwidth.

[0049] Equation (7) requires the use of a corresponding demodulation algorithm to extract acoustic wave information. Currently, commonly used heterodyne demodulation algorithms include DCM and IQ demodulation. Both algorithms require mixing and filtering first. Mixing multiplies the acquired signal by a reference signal of an orthogonal signal at the same frequency. The orthogonal reference signal can be obtained from the demodulation hardware. The IQ demodulation algorithm has a higher theoretical dynamic range upper limit than the DCM algorithm; therefore, this embodiment uses the IQ demodulation algorithm to demodulate the acoustic signal. The orthogonal reference signal can be obtained from the demodulation hardware and has the following form: (9); (10); in, and This is an orthogonal reference signal; The amplitude of the reference signal.

[0050] like Figure 4 As shown, by multiplying equation (7) by equations (9) and (10) respectively, we can obtain: (11); (12); After low-pass filtering, equations (11) and (12) yield the following: (13); (14); Dividing equations (13) and (14) to obtain the arctangent directly yields the phase information, where, and These are the first orthogonal signal and the second orthogonal signal, respectively.

[0051] (15); Compared to the DCM algorithm, the IQ algorithm is simpler. The method of directly calculating the arctangent of equation (15) to obtain the acoustic signal has two main problems: 1) Although the arctangent function has a clear mathematical meaning, it lacks a clear calculation formula; 2) The range of the arctangent function is... However, in practical applications, the signal to be measured may exceed this range.

[0052] The first problem concerns the digital implementation of the arctangent function, which is typically solved using approximation algorithms in practical digital signal processing applications. The second problem can usually be improved by combining range expansion with phase dewinding algorithms. The phase extraction process is as follows: Figure 5 As shown, the phase extraction process is divided into three parts, firstly... and The arctangent of the ratio is calculated, and then the range is expanded and the phase is de-wound to obtain the acoustic wave phase information.

[0053] The range of the arctangent function is When the actual acoustic wave phase is outside this range, directly using the arctangent function will not yield the correct demodulation result. The demodulation range can be extended by range expansion. While performing the arctangent operation, determine... and The sign of the signal is used to determine the region where the phase signal is located, and then the phase value is determined based on the region. The specific operation is shown in Table 1.

[0054] Table 1. Range Expansion Execution Comparison Table

[0055] Although the demodulated phase range can be extended after range expansion, However, when the phase exceeds or less than At that time, the phase demodulation result will appear arrive or arrive The jump, that is, the appearance of phase wrapping, as Figure 6 As shown, the phase value suddenly jumps by 2π, disrupting the continuity of the signal.

[0056] Furthermore, to address the phase winding problem, the instantaneous frequency tracking method proposed in this example is adopted. The instantaneous frequency of the signal is calculated using the instantaneous frequency formula, and the phase winding part is compensated and corrected to restore the true phase change information.

[0057] Traditional frequency is a classical physical definition of periodic signals, characterizing the overall features of a signal over a certain time range, and is generally obtained by Fourier transform. Instantaneous frequency, however, differs from the traditional concept of frequency. It can be understood as the reciprocal of the phase of an analytic signal constructed based on the Hilbert Transform (HT). Although the Hilbert Transform requires certain preconditions, such as being applicable only to narrowband signals, the instantaneous frequency based on the Hilbert Transform has a clear physical meaning, and the analytic signal has the same spectrum as the original signal. For real-valued signals… and its corresponding analytical signal The definition is as follows: (16); Among them, the imaginary part The for The Hilbert transform.

[0058] Instantaneous frequency defined based on Hilbert transform It can be expressed by the following formula: (17); Among them, intermediate quantity ; for The first derivative; for The first derivative.

[0059] Based on the hardware configuration, instantaneous frequency measurement can be divided into two types: analog instantaneous frequency measurement and digital instantaneous frequency measurement (DIFM). Currently, the DIFM method is widely used. Figure 8 This diagram illustrates the digital implementation of the DIFM method. The input acoustic signal is split into two paths: one path directly enters the digital multiplier unit. The other path can be viewed as passing through one or more delay units before entering the multiplier. The delay path contains one or more delay elements before sending the signal to the same multiplier. The delay is the ADC sampling time interval. Multiples of, among which This is the sampling frequency for the ADC. Therefore, this path may contain one or more delay registers, the number of which will determine the available frequency detection bandwidth.

[0060] Let the input carrier frequency be... After digitization and mixing, we have: (18); in, The signal after mixing; The carrier amplitude; The number of bits in the ADC; It is the dynamic range of the input voltage; Instantaneous frequency; It is quantization error; This represents the number of samples taken by the ADC due to latency. The above formula can be divided into two parts: one part contains instantaneous frequency information, and the other part is the quantization error magnitude.

[0061] After multiplying the two terms, the instantaneous frequency can be obtained by low-pass filtering. The result of multiplying the two terms and then low-pass filtering is: (19); in, The signal is a low-pass filtered signal; This is the gain of the low-pass filter. Current research indicates that even with a 10-bit ADC, quantization error can be ignored. Since most digital demodulation systems currently use 12-16 bit ADCs, quantization noise is usually negligible, so the instantaneous frequency of the output... This can be expressed as: (20); right Equation (20) can be simplified to: (twenty one); in, The signal is simplified. Equation (20) is actually the peak amplitude output of equation (18). Dividing equation (18) by equation (20) yields an output equation that is independent of amplitude, as follows: (twenty two); Output value It can be directly used in the instantaneous frequency tracking algorithm for the upper limit of dynamic range proposed in this example.

[0062] According to Figure 9 choose The optimal value mainly depends on the instantaneous carrier frequency bandwidth for the normalized carrier frequency. For sinusoidal modulation, there is That is, the instantaneous carrier frequency bandwidth is twice the peak fringe rate of the signal. Assume... . The optimal value is an approximately linear output within the instantaneous carrier bandwidth; furthermore, the output needs to have a large difference. Figure 9 It can be seen that, for The optimal value is ,exist Nearby Within the range, The output values ​​exhibit good linearity and a large difference. However, for... The output is located in the non-linear part of the curve. Nearby The differential outputs within the range are very limited. For Although the output is approximately linear, the output difference is compared to... Small. Therefore, this example takes... .

[0063] (1) Phase winding analysis: When the stripe rate of the demodulated signal exceeds the arc between sampling points, phase winding will occur. Phase winding can usually be divided into the following two cases.

[0064] The first type of phase winding occurs when the demodulated output rotates in the wrong direction. This happens when the phase difference between two sampling points is greater than... At this time, the demodulation algorithm calculates the phase rotation direction based on the shortest path travel, which will produce an error of . The demodulated output. For example, the forward-rotating... Its demodulation output is Therefore, the difference between the true phase and the demodulated output is... In this situation, it is necessary to apply pressure to the demodulator. The correction coefficient is used to correct for obvious phase reversal.

[0065] The second type of phase winding occurs when the demodulated output rotates in the correct direction, but the phase shift of the output still exceeds the demodulation range of the demodulator. This occurs when the phase difference between two sampling points is greater than... This phase winding situation can occur at times. Because the demodulation range of the demodulator is only... ,therefore The phase rotation will cause full-cycle phase winding, which will be effectively subtracted by the demodulator. For example, The phase shift will be demodulated as Therefore, considering the phase winding situation, the demodulator must be modified. The correction factor.

[0066] In summary, improving the phase winding problem requires determining the demodulated phase rotation direction and angular velocity to apply the correct correction factor. The following analysis shows that the angular velocity and actual phase rotation direction can be obtained from the instantaneous frequency to determine whether a correction factor needs to be added and its magnitude.

[0067] (a) Determination of phase rotation direction: In conventional demodulation, the shortest path method is usually used to estimate the phase rotation direction. If the phase of two adjacent sampling points exceeds... Such estimations will lead to errors, resulting in incorrect demodulation results. The instantaneous frequency of the heterodyne interferometer system. for: (twenty three); in, and These are the amplitude and frequency of the sound wave, respectively. Because... Given that the above has already designed the method to find... The algorithm, therefore the intermediate quantity It can be calculated. Right now Then the angular phase rotation direction is positive, if Right now If the angular phase rotation direction is negative, then the instantaneous rotation direction can be determined by the normalized carrier frequency and the magnitude of the instantaneous frequency.

[0068] Determining the direction of angular phase rotation can effectively increase the dynamic range and, to some extent, suppress phase winding. Because the direction of angular phase rotation can be determined directly, [the following applies]. The correction factor can achieve at least a 6dB increase in dynamic range. However, when the phase shift exceeds... At that time, the light has information about angular phase rotation, which cannot eliminate the phase winding phenomenon.

[0069] (b) Determination of angular velocity: Determining the direction of phase rotation can correct phase shifts exceeding [the specified value]. The first phase-wound sampling point, but the phase shift exceeds At that time, phase winding cannot be corrected. For more than In such cases, it is necessary to track the instantaneous frequency to determine the angular velocity. Instantaneous angular velocity can often be used to estimate the phase shift amplitude between demodulation points, which is helpful in determining higher-order phases. Correction factor.

[0070] For instantaneous angular velocity have: (twenty four).

[0071] However, since the carrier frequency is removed from the equations during demodulation, the only significant angular velocity component is the one contributed by the input signal. This has previously been shown to be simply the derivative of the input. Therefore, the instantaneous angular velocity of the sinusoidal signal... for: (25).

[0072] because The unit is Multiplying this by the time step between demodulated sampling points yields an estimate of the phase change between the two samples. However, the accuracy of this estimate depends on several factors. First, since the angular velocity of a signal is essentially sinusoidal, the sampling location is crucial. Sampling in the linear portion of the sine wave will result in a phase estimate that is closer to the mean than samples taken in the nonlinear portion. This leads to the second issue: the time step between samples. A small time step results in a small error, while a large time step results in a large error. Whether the time step is considered small or large depends on the signal frequency relative to the demodulation rate. The higher the signal frequency, the greater the estimation error for a given sampling rate.

[0073] Multiplying the instantaneous angular velocity by the demodulation time step results in a large error in the phase change estimation. Therefore, some form of averaging of the instantaneous angular velocity is needed to improve the estimation. This averaging will reduce the estimation error of the nonlinear components of the input signal, such as at junctions. Assuming the signal's angular velocity is averaged over two or more sampling points, the averaging can be calculated using the following formula: The correction factor, of which It must be added to or subtracted from the demodulated output. The multiple of. The sign in the formula is determined by the instantaneous rotation direction, which can be determined beforehand by the instantaneous frequency, as follows: (26); in, Nominal frequency; The average instantaneous angular velocity.

[0074] Therefore, by calculating the average instantaneous angular velocity, an estimated phase winding correction factor can be obtained, which allows for a phase offset greater than [a certain value]. While this method can increase the dynamic range, it is relatively complex and has a large error. The instantaneous frequency tracking method designed in this example avoids these problems, and the method designed in this example will be described in detail below.

[0075] The above analysis shows that the upper limit of the dynamic range can be improved by obtaining relevant information through the instantaneous carrier frequency. A method has been previously proposed to derive the instantaneous rotation direction and instantaneous angular velocity from the instantaneous frequency and then determine the correction factor; however, this method is complex and contains significant errors. This example proposes a method to directly obtain the correction factor using the instantaneous frequency.

[0076] (2) Heterodyne demodulation algorithm based on instantaneous frequency tracking: If the fringe rate (i.e., angular velocity) of the signal is greater than the fringe rate of the demodulator, phase winding will occur. Phase winding occurs when the fringe rate is equal to... At that time, the peak stripe rate of the demodulator can be divided by... This is converted to an equivalent frequency. Therefore, the first phase winding occurs when the carrier frequency deviates from the nominal frequency instantaneously. It also shows that for each additional increase in the input phase shift, the demodulated output will experience a significant phase reversal.

[0077] The carrier frequencies at which these phase reversals occur are considered to exceed a threshold frequency. The threshold frequency can be obtained using the following formula: (27); in, This refers to the instantaneous carrier frequency exceeding the crossover point. Exceeding the threshold frequency is not only important for determining the appropriate correction factor but also helps in determining the optimal carrier frequency or band within the system bandwidth for tracking. The threshold frequency, the expected demodulation rotation direction, and the required correction factor are as follows: Figure 10 As shown.

[0078] (a) Boundary conditions for the correction factor: The dynamic range extension method proposed in this example mainly relies on determining a suitable correction factor to mitigate the error offset caused by phase winding. As discussed earlier, the first phase winding point requires... A correction factor is used to correct the demodulator output phase reversal. After the second exceedance point, considering the full-cycle phase rotation, an additional correction factor is still needed. Offset. Both the third and fourth phase wrapping points require... For every two frequencies that the instantaneous carrier frequency crosses above the threshold, this form of increasing the correction factor continues. Figure 11 The system's carrier spectrum is displayed, including frequencies exceeding the threshold, correction factors and boundaries, and the direction of demodulation rotation.

[0079] A common method for dynamic range extension is to select a correction factor based on the position of the measured instantaneous carrier frequency within the system spectrum. However, this general extension method does not consider three additional issues: the likelihood probability of the demodulation rotation direction, the tracking frequency, and the frequency averaging method. Addressing these three issues will facilitate improvements to the general dynamic range extension method. This example will consider these three issues and further improve the dynamic range extension method.

[0080] (b) Maximum and minimum likelihood of demodulation rotation direction: when the input phase signal is close to At that time, the demodulation output will be a... Low phase noise centered on the arc, the instantaneous carrier frequency will remain at the nominal value. In the vicinity of the waveform, under these conditions, the probability of the demodulator experiencing a small positive rotation is the same as the probability of it experiencing a small negative rotation. However, if a large-phase signal is input, the probabilities of experiencing a positive or negative rotation will no longer be equal when considering a small portion of the waveform. For the sinusoidal modulation method used in this example, the probability of a positive phase rotation is highest when the waveform slope is positive. The probability of a negative rotation is highest when the waveform slope is negative. At the maximum and minimum values ​​of the waveform slope, the probabilities of positive and negative rotations are again equal.

[0081] What's truly interesting isn't the actual probability of waveform rotation, but rather the probability of the demodulated output rotation direction. Similarly, even without an input signal, the demodulator can still produce an output with either a positive or negative rotation direction. However, considering sinusoidal modulation, as the phase between demodulation points begins to increase in the positive direction, the probability of the demodulator producing a demodulated output with a positive rotation direction also begins to increase. If this probability continues to increase, it will continue until the phase shift between sampling points reaches a certain threshold. Radius. This is the first maximum likelihood point for the demodulated positive rotation. If the phase continues to increase further in the positive direction, the probability will begin to decrease until it reaches the maximum likelihood point again. The probability of equal phase shifts in radians. This is the first over-threshold sampling point of the demodulator. Even if the actual phase rotation direction is positive, if the phase shift is only slightly greater than... The demodulator will produce near- The output value. Therefore, at frequencies exceeding the threshold where a phase reversal of the demodulated output occurs, the probability of the demodulator producing a positive output is the same as the probability of producing a negative output.

[0082] When the first threshold is exceeded, if the input phase leads and continues to increase in the positive direction, the probability of the demodulator producing a positive value will continue to decrease until it leads in the positive phase. The minimum likelihood point for the positive phase rotation is reached. This is the point where the demodulator is most likely to demodulate this positive phase rotation. The point of negative rotation. The additional phase lead from positive rotation will increase the probability of the demodulator producing positive rotation. As the positive phase advances closer to... This probability will again equalize at the second threshold. The maximum and minimum likelihood modes in this demodulation rotation direction will continue to repeat with further phase increases in the given direction. A similar analysis can be performed for the negative rotation direction. The difference between these two cases lies in the location where the maximum and minimum probabilities occur. The equal probability points are the same in both cases and are located above the threshold frequency. The equal probability points occur above the threshold frequency. Similarly, the signal fringe rate equal to the maximum and minimum probabilities can also be obtained by dividing by... Convert to an equivalent instantaneous carrier frequency value. For example... Figure 12 As shown, these frequencies can be compared with... Figure 10The correction factor boundaries overlap.

[0083] from Figure 12 It can be seen that the maximum and minimum likelihood points occur at frequencies exceeding the threshold frequency range. For a given rotation direction, the total bandwidth from one maximum to the next, or from one minimum to the next, is twice the bandwidth between frequencies exceeding the threshold frequency range. When the demodulated output rotation direction is unidirectional, but the measured instantaneous carrier frequency falls between frequencies exceeding the threshold frequency range opposite to the expected rotation direction, the increased bandwidth helps reduce the ambiguity in selecting an appropriate correction factor. Therefore, both the maximum and minimum likelihood frequencies are helpful in determining the correction factor band and the optimal frequency within the system bandwidth to be tracked.

[0084] (1) Determination of tracking frequency: Instantaneous frequency tracking requires the measurement of selected frequencies within the system spectrum. Which frequencies or bands should be tracked depends on the frequency tracking method itself. Frequency tracking methods can be divided into two types: tracking methods for frequencies with a continuous output range and tracking methods for discrete frequencies.

[0085] The instantaneous frequency tracking method proposed in this example tracks frequencies over a continuous range. The output instantaneous frequency is a normalized instantaneous frequency, and the output value is within... The amplitude of the output value is directly related to the instantaneous carrier frequency, and therefore can be used to track any frequency within the detector's design bandwidth. For frequency tracking methods with a continuous output range, the dynamic range extension method places the measured frequency in one of several designated frequency bands associated with a specific correction factor. These frequency bands are typically determined by the over-threshold frequencies. This example uses two specific sets of frequency bands to measure the instantaneous frequency. One set is used to determine the correction factor for a given positive rotation demodulation output, and the other set is used for the negative rotation demodulation output. A positive rotation band is established between the positive rotation minimum likelihood frequencies. A negative rotation band is established between the negative rotation minimum likelihood frequencies. This method of establishing the correction factor boundary based on the demodulation output direction increases the effective bandwidth of the correction factor band by a factor of two compared to using the over-threshold frequencies alone.

[0086] The minimum likelihood frequencies for positive and negative rotations can be determined by equations (28) and (29). These frequencies can then be converted into instantaneous frequency values ​​for the algorithm designed in this example and used directly in the dynamic range extension algorithm.

[0087] (28); (29); in, and These are the minimum likelihood frequencies for positive and negative rotations, respectively.

[0088] (2) Frequency Averaging: Selecting a correction factor solely based on the position of the instantaneous carrier frequency within the spectrum will result in a high error rate. The instantaneous carrier frequency obtained only provides the angular velocity information of the current sampling point, without considering the angular velocity changes since the previous demodulation point. For high stripe rate signals, the angular velocity changes between sampling points can be significant. In particular, for the sinusoidal modulation signal used in this example, there may be large angular velocity changes at the minimum, maximum, and inflection points of the signal. Therefore, such errors can be mitigated by considering the instantaneous frequency or angular velocity of previous demodulation points. Typically, averaging the instantaneous frequencies of two samples with equal weight can significantly reduce potential errors in the selection of correction factors. However, the simple averaging method does not consider frequency dependence. As the input signal frequency increases, the number of demodulation sampling points per cycle decreases. If the number of sampling points becomes too small, the averaging method will not be able to determine the accurate average angular velocity, affecting the selection of correction factors. This will be explained later in this example. For the full dynamic range extension method, at least 8 to 12 sampling points are required per sinusoidal cycle, with the specific number of sampling points depending on the demodulation algorithm used. Using fewer sampling points is beneficial for achieving high-speed demodulation, but it will reduce the range of dynamic range extension.

[0089] Employing more sophisticated averaging methods can further enhance the improved angular velocity tracking capabilities. Since two-point averaging has already achieved good results, this example does not delve into averaging methods in detail. Possible improvements include multi-point and weighted averaging. Weighted three-point averaging may be a promising method, utilizing previous, current, and subsequent demodulation points; however, this method requires selecting a demodulation point delay, which, while easily implemented, may encounter larger fringe rate inflection points.

[0090] (3) Determination of the correction factor: Selecting an appropriate overcorrection factor requires determining the rotation direction of the demodulated output and the position of the average instantaneous carrier frequency within the system bandwidth. However, how to obtain this information depends on the specific instantaneous frequency extraction method.

[0091] (4) Algorithm execution: such as Figure 7 As shown, after the IQ demodulation algorithm, an instantaneous frequency tracking stage is added. The algorithm uses if-else comparison statements to determine the frequency band of the average instantaneous carrier and performs real-time frequency tracking based on this result. Figure 10 Determine the applied correction factor and correct the demodulation results in real time.

[0092] Digital Signal Processing Module: Employing an embedded processor architecture, this module integrates a high-speed data acquisition card (DAQ) with an adjustable sampling rate of 250MHz. A built-in FPGA chip is used for real-time signal preprocessing. The module incorporates a coherent Rayleigh scattering signal demodulation algorithm, phase encoding / decoding logic, an instantaneous frequency tracking algorithm, and an adaptive threshold decision module, enabling real-time analysis and damage identification of the demodulated signal. It acquires electrical signals via a high-speed DAQ, extracts phase change information using the coherent Rayleigh scattering demodulation algorithm, reconstructs damage characteristics using a heterodyne demodulation algorithm, addresses phase entanglement issues in large-signal demodulation using the instantaneous frequency tracking algorithm, and adapts to environmental interference at different flight stages using the adaptive threshold decision module, ultimately achieving damage identification and localization.

[0093] In processing the electrical signal using a heterodyne phase modulation method based on instantaneous frequency tracking, the digital signal processing module is configured to: The electrical signal is low-pass filtered to obtain the filtered signal; The filtered signal is demodulated using IQ to obtain the acoustic phase signal; Calculate the instantaneous frequency of the sound wave signal; Based on the instantaneous frequency, determine the rotation direction of the demodulated output and the correction factor band where the average instantaneous carrier frequency is located; Based on the rotation direction and correction factor frequency band, a correction factor is determined and applied to correct the acoustic wave phase signal obtained by IQ demodulation in order to eliminate phase winding. Based on the corrected phase information, determine whether there is structural damage in the aircraft composite material structure; Based on the deployment location information of the distributed optical fiber sensor network and the time difference of optical pulse transmission, combined with the spatial distribution characteristics of Rayleigh scattering light, the damage location of the aircraft composite material structure is calculated.

[0094] In determining whether there is structural damage in the aircraft composite material structure based on the corrected phase information, the digital signal processing module is used to: perform spectral analysis and feature extraction on the corrected phase information, and calculate the power spectral density and signal-to-noise ratio of the signal; when the signal amplitude exceeds the dynamic threshold and the signal-to-noise ratio is better than the set signal-to-noise ratio value, it is determined that there is structural damage in the aircraft composite material structure.

[0095] Dynamic Threshold Adjustment and Damage Identification: The damage assessment threshold is adjusted in real-time according to the aircraft's flight phase, such as takeoff, cruise, and landing. Using a correlation model of flight parameters, such as flight speed, altitude, load, and environmental noise, the threshold level is dynamically optimized to ensure effective differentiation between environmental noise and damage signals in complex flight environments. Spectral analysis and feature extraction are performed on the demodulated phase change signal to calculate the signal's power spectral density (PSD) and signal-to-noise ratio (SNR). When the signal amplitude exceeds the dynamic threshold and the SNR is better than the set SNR value (set at 40 dB), structural damage is identified.

[0096] The alarm output module enables multi-channel transmission of detection results and alarm notifications, ensuring that the crew and ground maintenance personnel receive timely structural health status information. Equipped with a CAN bus interface, Ethernet interface, and RS485 interface, it can interact with the airborne avionics system, ground monitoring center, and cockpit alarm devices. When structural damage is detected, it can output the damage location, damage level, and alarm signal in real time, including audible and visual alarms and data pop-up notifications.

[0097] Damage Location and Alarm Output: Based on the deployment location information of the distributed fiber optic sensor network (the electrical signal converted by the photodetector through the distributed single-mode fiber optic sensor network carries the deployment location information) and the time difference of optical pulse transmission, combined with the spatial distribution characteristics of Rayleigh scattering light, the precise location of the damage is calculated. The alarm output module synchronously outputs the damage location, damage severity (determined based on the signal amplitude and phase change rate), and alarm level to the airborne avionics system, ground monitoring center, and cockpit alarm devices via CAN bus and Ethernet interface, triggering the corresponding alarm mechanisms.

[0098] Example 2 Based on the same inventive concept, this application also provides a method for monitoring the health of aircraft composite structures based on the aforementioned aircraft composite structure health monitoring system. The solution provided by this method is similar to the implementation scheme described in the above system. Therefore, the specific limitations in one or more embodiments of the aircraft composite structure health monitoring method provided below can be found in the limitations of the aircraft composite structure health monitoring system described above, and will not be repeated here.

[0099] In one exemplary embodiment, a method for monitoring the health of an aircraft composite material structure is provided, comprising the following steps.

[0100] S1: Generate and transmit heterodyne phase-modulated optical pulses through the DAS integrated optical module to the single-mode fiber optic sensing network; utilize the coherent Rayleigh scattering effect to convert the acoustic emission signal containing the physical changes of the aircraft composite material structure into an optical phase change signal; convert the backscattered Rayleigh light carrying the optical phase change signal into an electrical signal.

[0101] S2: The electrical signal is processed using a heterodyne phase modulation method based on instantaneous frequency tracking to identify and locate damage to the aircraft composite material structure.

[0102] S3: When structural damage is detected, output the location of the damage, the level of damage, and the alarm signal of the aircraft composite material structure in real time.

[0103] As an optional implementation, the electrical signal is processed using a heterodyne phase modulation method based on instantaneous frequency tracking to identify and locate damage in the aircraft composite material structure, specifically including: The electrical signal is low-pass filtered to obtain the filtered signal; The filtered signal is demodulated using IQ to obtain the acoustic phase signal; Calculate the instantaneous frequency of the sound wave signal; Based on the instantaneous frequency, determine the rotation direction of the demodulated output and the correction factor band where the average instantaneous carrier frequency is located; Based on the rotation direction and correction factor frequency band, a correction factor is determined and applied to correct the acoustic wave phase signal obtained by IQ demodulation in order to eliminate phase winding. Based on the corrected phase information, determine whether there is structural damage in the aircraft composite material structure; Based on the deployment location information of the distributed optical fiber sensor network and the time difference of optical pulse transmission, combined with the spatial distribution characteristics of Rayleigh scattering light, the damage location of the aircraft composite material structure is calculated.

[0104] This implementation method, based on the corrected phase information, determines whether there is structural damage in the aircraft composite material structure. Specifically, it includes: performing spectral analysis and feature extraction on the corrected phase information, and calculating the power spectral density and signal-to-noise ratio of the signal; when the signal amplitude exceeds the dynamic threshold and the signal-to-noise ratio is better than the set signal-to-noise ratio value, it is determined that there is structural damage in the aircraft composite material structure.

[0105] Related technologies for monitoring damage to aircraft composite structures include quasi-distributed sensing systems based on fiber Bragg gratings (FBGs) and active / passive monitoring systems based on piezoelectric thin film sensor arrays.

[0106] The technical concept of a quasi-distributed sensing system based on fiber Bragg gratings (FBGs) involves using wavelength division multiplexing (WDM) or time division multiplexing (TDM) techniques to embed multiple FBG sensors in series into a single optical fiber, forming a sensing network. Each FBG reflects light of a specific wavelength, and the center wavelength of its reflection drifts linearly with strain or temperature changes at the sensor's location. By monitoring these wavelength shifts using a demodulator, the state changes at various points in the structure can be deduced, thus enabling discrete-point monitoring of key areas. However, this scheme has several insurmountable limitations: First, its monitoring capability is limited by the multiplexing technology, and the number of FBGs that can be connected in series on a single optical fiber is limited (usually no more than 40), making it impossible to achieve large-area full coverage and resulting in significant monitoring blind spots; second, the fixed spacing between sensor nodes makes it difficult to flexibly adapt to the dense monitoring needs of stress-concentrated areas on structures such as wings; third, FBGs have a cross-sensitivity to temperature and strain, requiring complex decoupling algorithms or additional temperature compensation sensors, which increases system complexity and uncertainty; finally, high-precision wavelength demodulation equipment is expensive, and the dynamic range of the system is limited by the physical characteristics of the grating itself, making it difficult to simultaneously and accurately capture minute initial damage signals and severe structural deformations.

[0107] The technical concept of active / passive monitoring systems based on piezoelectric thin-film sensor arrays involves deploying an array of piezoelectric sensors on or inside the surface of composite material structures. These sensors typically utilize flexible materials such as polyvinylidene fluoride (PVDF) and their positive piezoelectric effect to convert vibrations or acoustic emission stress waves generated by the structure into electrical signals. By analyzing the time difference and amplitude attenuation characteristics of signals received from multiple sensors, algorithms such as time reversal and beamforming can be used to identify and locate impact or damage sources. However, this approach also has significant limitations: First, the density and range of the sensor array are limited by installation space, weight, and complex wiring layout, making it difficult to achieve full-area monitoring, and blind spots are unavoidable. Second, the electrical signals output by piezoelectric materials are extremely weak, and the signal-to-noise ratio drops sharply in the complex and strong electromagnetic environment of airborne systems, resulting in poor anti-interference capabilities and insufficient stability. Third, sensors typically require coupling to the structural surface via adhesives; this contact-based installation is invasive and may alter the local mechanical properties of the structure. Furthermore, the adhesive layer is prone to aging and failure under long-term vibration and high / low temperature cycling, leading to data drift or even functional loss, making it difficult to meet the reliability requirements of aircraft lifecycle management.

[0108] The comparison results between the above scheme and the scheme provided in this application are shown in Table 2.

[0109] Table 2 Comparison of existing aircraft composite material structure damage monitoring schemes with the scheme provided in this application

[0110] In summary, while the two aforementioned solutions are feasible in specific application scenarios, they each have inherent limitations in terms of monitoring comprehensiveness, environmental adaptability, system reliability, and cost-effectiveness. Based on a deep understanding of these technical bottlenecks, this application proposes an innovative solution aimed at systematically overcoming these limitations.

[0111] This application has the following beneficial effects: 1. High signal-to-noise ratio damage detection: The system has a high signal-to-noise ratio and can identify early micro-cracks and interlaminar peeling damage in aircraft composite structures. Compared with traditional fiber optic sensing monitoring solutions, the sensitivity is improved by more than 20dB.

[0112] 2. Wide measurement range and large dynamic range: By introducing high-frequency phase modulation technology through IOC, the heterodyne frequency is effectively improved under the condition of limited system bandwidth. Combined with the instantaneous frequency tracking algorithm, the phase winding problem is solved. The upper limit of the dynamic range is improved compared with the existing solution, which can simultaneously meet the monitoring needs of minor damage and large structural deformation.

[0113] 3. Fully Distributed and High-Precision Positioning: Distributed single-mode fiber optic sensor networks enable blind-spot-free monitoring of the entire structure. Based on the time difference of light pulse transmission and the spatial distribution characteristics of Rayleigh scattering, the damage positioning accuracy is high. Compared with traditional point-based sensing solutions, the positioning error is reduced, and there is no need to deploy a large number of sensor nodes on the structure surface.

[0114] 4. Lightweight and highly adaptable to airborne systems: The integrated DAS optical module adopts a lightweight design with a high degree of integration of core components. The overall system weight is ≤5kg, which meets the lightweight requirements of airborne equipment. Each module adopts a vibration-resistant and wide temperature range (-55℃~70℃) design, which can adapt to the complex environment under different operating conditions such as aircraft takeoff, cruise, and landing.

[0115] 5. Real-time response and multi-channel alarms: The digital signal processing module adopts an FPGA + embedded processor architecture, which has low data processing latency and can complete damage identification and location in real time; the alarm output module supports seamless integration with existing airborne systems, ensuring that relevant personnel can obtain alarm information in a timely manner, and providing a guarantee for structural maintenance and flight safety.

[0116] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0117] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A health monitoring system for aircraft composite material structures, characterized in that, The aircraft composite material structure health monitoring system includes: The DAS integrated optical module is used to generate and transmit heterodyne phase-modulated optical pulse pairs to a single-mode fiber optic sensing network, and to receive backscattered Rayleigh light carrying optical phase change signals from the single-mode fiber optic sensing network, and convert the backscattered Rayleigh light into an electrical signal. A single-mode fiber optic sensing network is deployed on the surface of an aircraft composite material structure to convert acoustic emission signals containing physical changes in the aircraft composite material structure into optical phase change signals using the coherent Rayleigh scattering effect. A digital signal processing module, electrically connected to the DAS integrated optical module, is used to process the electrical signal using a heterodyne phase modulation method based on instantaneous frequency tracking in order to identify and locate damage to the aircraft composite material structure. The alarm output module is communicatively connected to the digital signal processing module and is used to output the damage location, damage level, and alarm signal of the aircraft composite material structure in real time when structural damage is detected.

2. The aircraft composite material structure health monitoring system according to claim 1, characterized in that, The integrated DAS optical module includes a narrow linewidth laser, a semiconductor optical amplifier, an unbalanced Mach-Zehnder interferometer, and a photodetector. Narrow linewidth lasers are used to provide a detection light source, emitting continuous light; Semiconductor optical amplifiers are used to convert continuous light into pulsed light; An unbalanced Mach-Zehnder interferometer is used to perform frequency shifting and continuous phase modulation on pulsed light, and to combine the frequency-shifted and phase-modulated light signals into a pair of light pulses. The back-scattered Rayleigh light carrying the phase change signal is then interfered with to obtain the interference light signal. A photodetector is used to convert interfering optical signals into electrical signals.

3. The aircraft composite material structure health monitoring system according to claim 2, characterized in that, One arm of the unbalanced Mach-Zehnder interferometer includes an acousto-optic modulator, and the other arm includes a first optical circulator, an integrated optical phase modulator, a Faraday rotator, and an optical fiber delay loop; one end of the acousto-optic modulator and one end of the first optical circulator are connected to a semiconductor optical amplifier through a first single-mode fiber coupler; the other end of the acousto-optic modulator and the other end of the first optical circulator are connected to a second optical circulator through a second single-mode fiber coupler. The second optical circulator is used to connect the DAS integrated optical module, the single-mode fiber optic sensor network, and the digital signal processing module. An acousto-optic modulator is used to frequency-shift pulsed light to generate the heterodyne frequency required for heterodyne detection, thereby performing frequency-shifting of the pulsed light; An integrated optical phase modulator is used to introduce high-frequency phase modulation, continuously applying phase modulation processing to pulsed light.

4. The aircraft composite material structure health monitoring system according to claim 3, characterized in that, Electrical signals are represented as: ； in, for The electrical signal at a given moment; The amplitude of the AC signal detected by the detector; It is a sine function; The heterodyne frequency generated by the acousto-optic modulator; The phase change caused by the acoustic emission signal; The modulated signal generated by the integrated optical phase modulator; This is the initial phase.

5. The aircraft composite material structure health monitoring system according to claim 1, characterized in that, In processing the electrical signal using a heterodyne phase modulation method based on instantaneous frequency tracking, the digital signal processing module is configured to: The electrical signal is low-pass filtered to obtain the filtered signal; The filtered signal is demodulated using IQ to obtain the acoustic phase signal; Calculate the instantaneous frequency of the sound wave signal; Based on the instantaneous frequency, determine the rotation direction of the demodulated output and the correction factor band where the average instantaneous carrier frequency is located; Based on the rotation direction and correction factor frequency band, a correction factor is determined and applied to correct the acoustic wave phase signal obtained by IQ demodulation in order to eliminate phase winding. Based on the corrected phase information, determine whether there is structural damage in the aircraft composite material structure; Based on the deployment location information of the distributed optical fiber sensor network and the time difference of optical pulse transmission, combined with the spatial distribution characteristics of Rayleigh scattering light, the damage location of the aircraft composite material structure is calculated.

6. The aircraft composite material structure health monitoring system according to claim 5, characterized in that, In determining whether structural damage exists in an aircraft composite material structure based on the corrected phase information, the digital signal processing module is used for: The corrected phase information is subjected to spectral analysis and feature extraction to calculate the power spectral density and signal-to-noise ratio of the signal. When the signal amplitude exceeds the dynamic threshold and the signal-to-noise ratio is better than the set signal-to-noise ratio value, it is determined that there is structural damage in the aircraft composite material structure.

7. The aircraft composite material structure health monitoring system according to claim 1, characterized in that, The single-mode fiber optic sensing network is fixed to the surface of the aircraft composite material structure by a combination of spiral winding and linear bonding. The spacing between the network members in stress concentration areas does not exceed 5 cm, and the spacing between them in non-stress concentration areas does not exceed 15 cm.

8. A method for monitoring the health of aircraft composite structures based on the aircraft composite structure health monitoring system of claim 1, characterized in that, The aircraft composite material structure health monitoring method includes: The DAS integrated optical module generates and transmits heterodyne phase-modulated optical pulses to a single-mode fiber optic sensing network; using the coherent Rayleigh scattering effect, the acoustic emission signal containing the physical changes of the aircraft composite material structure is converted into an optical phase change signal; and the backscattered Rayleigh light carrying the optical phase change signal is converted into an electrical signal. The electrical signal is processed using a heterodyne phase modulation method based on instantaneous frequency tracking to identify and locate damage to the aircraft composite material structure. When structural damage is detected, the location of the damage, the level of damage, and the alarm signal of the aircraft composite material structure are output in real time.

9. The method for monitoring the health of aircraft composite material structures according to claim 8, characterized in that, The electrical signal is processed using a heterodyne phase modulation method based on instantaneous frequency tracking to identify and locate damage in aircraft composite material structures, specifically including: The electrical signal is low-pass filtered to obtain the filtered signal; The filtered signal is demodulated using IQ to obtain the acoustic phase signal; Calculate the instantaneous frequency of the sound wave signal; Based on the instantaneous frequency, determine the rotation direction of the demodulated output and the correction factor band where the average instantaneous carrier frequency is located; Based on the rotation direction and correction factor frequency band, a correction factor is determined and applied to correct the acoustic wave phase signal obtained by IQ demodulation in order to eliminate phase winding. Based on the corrected phase information, determine whether there is structural damage in the aircraft composite material structure; Based on the deployment location information of the distributed optical fiber sensor network and the time difference of optical pulse transmission, combined with the spatial distribution characteristics of Rayleigh scattering light, the damage location of the aircraft composite material structure is calculated.

10. The method for monitoring the health of aircraft composite material structures according to claim 9, characterized in that, Based on the corrected phase information, the determination of whether structural damage exists in the aircraft composite material structure includes: The corrected phase information is subjected to spectral analysis and feature extraction to calculate the power spectral density and signal-to-noise ratio of the signal. When the signal amplitude exceeds the dynamic threshold and the signal-to-noise ratio is better than the set signal-to-noise ratio value, it is determined that there is structural damage in the aircraft composite material structure.

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