An intelligent coherent fading suppression method and system for optical fiber distributed sensing

Abstract

The application provides an intelligent coherent fading suppression method and system for optical fiber distributed sensing, and relates to the field of coherent fading suppression.The method comprises double constraints of polarization fading and coherent fading in a phi-OTDR system, and the problem that signal-to-noise ratio and spatial resolution cannot be considered simultaneously in traditional equal-bandwidth spectrum extraction and mixed methods, polarization fading is suppressed by using a differential polarization vector sum algorithm, and by taking maximum signal-to-noise ratio and minimum spatial resolution as optimization objectives, and combining a constraint condition that a sidelobe bandwidth is less than a main lobe bandwidth, an optimal non-uniform bandwidth distribution scheme of a detection pulse spectrum is solved; the optimal bandwidth scheme performs non-uniform segmentation and interception on a signal spectrum, and deep suppression of coherent fading is realized.The application greatly improves signal-to-noise ratio under the premise of maintaining original spatial resolution, simultaneously suppresses double fading, and is suitable for long-distance, high-precision distributed optical fiber vibration monitoring scenes.

Description

Technical Field

[0001] This application relates to the field of coherent fading suppression, and in particular to an intelligent coherent fading suppression method and system for fiber optic distributed sensing. Background Technology

[0002] Phase-sensitive optical time-domain reflectometers (φ-OTDRs) are widely used in distributed vibration sensing scenarios such as oil and gas pipeline security, perimeter monitoring, seismic wave detection, and resource exploration due to their advantages such as resistance to electromagnetic interference, long-distance continuous monitoring, and flexible deployment. φ-OTDRs locate external disturbances and reconstruct waveforms by analyzing the phase changes of backscattered Rayleigh light from optical fibers, making them a mainstream distributed acoustic wave sensing technology.

[0003] The performance of φ-OTDR systems has long been constrained by two major effects: polarization fading and coherent fading. Polarization fading is caused by the mismatch in polarization states between the local oscillator and the Rayleigh backscattered light, resulting in drastic fluctuations in the received light intensity and directly reducing signal stability. Coherent fading is caused by the coherent cancellation of light waves from multiple scattering units within the probe pulse, forming low signal-to-noise ratio fading points in the fiber optic link, which can lead to phase demodulation distortion and monitoring failure in severe cases.

[0004] Currently, the mainstream coherent fading suppression method is the Spectrum Extraction and Hybridization (SEMS) method. This method divides the probe pulse spectrum into equal-bandwidth uniform segments and combines the Rotating Vector Sum (RVS) algorithm to fuse multiple sub-band signals to suppress coherent fading. However, traditional equal-bandwidth segmentation does not consider the differences in energy distribution between the main lobe and side lobes of the pulse spectrum: excessively wide side lobe bandwidth introduces a large amount of noise, while limited main lobe bandwidth results in the loss of effective signal energy, creating an inherent contradiction between signal-to-noise ratio and spatial resolution, making it impossible to simultaneously achieve high signal-to-noise ratio and high spatial resolution. Existing improved schemes such as polarization processing, pulse coding, dual-pulse detection, and dynamic differential fitting have not fundamentally solved the performance trade-off problem caused by frequency band segmentation, making it difficult to meet the engineering requirements of high-precision, long-distance distributed vibration sensing. Summary of the Invention

[0005] The purpose of this invention is to address the problem that existing spectrum extraction and mixing methods employ an equal-bandwidth spectrum partitioning strategy, which fails to consider the energy distribution differences between the main lobe and side lobes of the pulse spectrum, resulting in an inherent contradiction between improving the signal-to-noise ratio and maintaining spatial resolution, thus making it impossible to simultaneously achieve high signal-to-noise ratio and high spatial resolution. This invention provides an intelligent coherent fading suppression method and system for fiber-optic distributed sensing.

[0006] The above-mentioned objective of this application is achieved through the following technical solution: S1: Construct the optical path system of a phase-sensitive optical time-domain reflectometer to acquire dual-polarization raw signals; S2: Perform differential polarization vector sum processing on the original dual-polarization signal to obtain a polarization-insensitive composite signal; S3: Construct a multi-objective optimization model based on the NSGA-II non-dominated sorting genetic algorithm to obtain the optimal non-uniform bandwidth allocation scheme; S4: Based on the optimal non-uniform bandwidth allocation scheme, non-uniform spectrum division is performed on the polarization-insensitive composite signal, and multi-subband signals are fused by combining rotation vector sum algorithm to suppress coherent fading; S5: Perform phase demodulation and post-processing on the fused multi-subband signals to restore the distributed vibration phase signal.

[0007] Optionally, step S1 includes: The phase-sensitive optical time-domain reflectometer optical path system includes a narrow linewidth laser, a first fiber coupler, an acousto-optic modulator, an erbium-doped fiber amplifier, a circulator, a second fiber coupler, a polarization beam splitter, a balanced photodetector, and a data acquisition card. The narrow linewidth laser outputs continuous light, which is split into a probe light branch and a local oscillator light branch by the first fiber coupler. The optical signal of the probe optical branch is sequentially modulated into a rectangular probe pulse by the acousto-optic modulator, amplified by the erbium-doped fiber amplifier, and then injected into the sensing fiber under test through the circulator. The optical signal of the local oscillator branch is split into two paths by the second fiber coupler, and respectively forms X and Y orthogonal polarization component beat frequency signals with the Rayleigh backscattered light returning from the sensing fiber under test at the polarization beam splitter; the X and Y orthogonal polarization component beat frequency signals are respectively converted into electrical signals by the balanced photodetector, and sampled at high speed by the data acquisition card to obtain the dual polarization raw signal.

[0008] Optionally, step S2 includes: S201: Perform down-conversion processing on the original dual-polarization signals to shift the effective signal to the low-frequency range; S202: Uses an FIR low-pass filter to remove out-of-band high-frequency noise and interference from the original dual-polarization signal; S203: Perform polarization vector difference operation on the filtered dual-polarization original signal to correct static phase shift and extract dynamic phase information; S204: The two processed dual-polarization original signals are vector-summed to obtain a polarization-insensitive composite signal.

[0009] Optionally, step S3 includes: The probe pulse spectrum is divided into three continuous, non-overlapping sub-bands: the main lobe, the first side lobe, and the second side lobe; the multi-objective optimization model is: Optimization objective 1: Maximize the system signal-to-noise ratio; Optimization objective 2: Minimize system spatial resolution; Constraints: 0 <Freq_len1<Freq_len2,0<Freq_len3<Freq_len2; Where Freq_len1 is the bandwidth of the first sidelobe, Freq_len3 is the bandwidth of the second sidelobe, and Freq_len2 is the bandwidth of the main lobe. The system spatial resolution is calculated using the following formula:

[0010] in, The speed of light in a vacuum The refractive index of the fiber core. The equivalent pulse time-domain width after spectrum partitioning; The system signal-to-noise ratio is obtained as follows: the phase signal is obtained by IQ demodulation, and the signal power and noise power are calculated based on the phase noise amplitude to obtain the system signal-to-noise ratio; The NSGA-II non-dominated sorting genetic algorithm is used to iteratively optimize the multi-objective optimization model: the Pareto optimal solution set is screened by non-dominated sorting and crowding calculation. Under the preset spatial resolution index, the optimal non-uniform bandwidth allocation ratio of the main lobe to a wide bandwidth and the side lobes to a narrow bandwidth is determined, and the optimal non-uniform bandwidth allocation scheme for solving the detection pulse spectrum is obtained.

[0011] Optionally, step S4 includes: S401: According to the optimal non-uniform bandwidth allocation scheme, three sets of FIR filters are used to non-uniformly segment the spectrum of the polarization-insensitive composite signal to obtain three independent sub-band signals. S402: The three independent sub-band signals are fused using a rotation vector sum algorithm.

[0012] Optionally, step S4 includes: S401: According to the optimal non-uniform bandwidth allocation scheme, three sets of FIR filters are used to non-uniformly segment the spectrum of the polarization-insensitive composite signal to obtain three independent sub-band signals. S402: The three independent sub-band signals are fused using a rotation vector sum algorithm.

[0013] A smart coherent fading suppression system for fiber-optic distributed sensing, the system comprising: Narrow linewidth laser, acousto-optic modulator, signal driver, erbium-doped fiber amplifier, circulator, filter, polarization beam splitter, first fiber coupler, second fiber coupler, piezoelectric ceramic, fiber under test, photodetector, data acquisition card and host computer; The output end of the narrow linewidth laser is connected to the input end of the first fiber coupler; the first fiber coupler splits the optical signal into a probe light branch and a local oscillator light branch with a splitting ratio of 90:10. The probe light output terminal of the first fiber optic coupler is connected to the light input terminal of the acousto-optic modulator; the radio frequency drive terminal of the acousto-optic modulator is connected to the output terminal of the signal driver, and the signal driver outputs a control signal to drive the acousto-optic modulator to pulse modulate the probe light. The optical output terminal of the acousto-optic modulator is connected to the input terminal of the erbium-doped fiber amplifier. The output of the erbium-doped fiber amplifier is connected to the first port of the circulator; The second port of the circulator is connected to one end of the optical fiber under test; the third port of the circulator is connected to the input of the filter; and the output of the filter is connected to the optical signal input of the polarization beam splitter. The local oscillator output terminal of the first fiber coupler is connected to the input terminal of the second fiber coupler; the second fiber coupler splits the local oscillator light into two paths with a splitting ratio of 50:50, and the output terminals of the two local oscillator lights are respectively connected to the two local oscillator light input terminals of the polarization beam splitter; The X-polarization output terminal of the polarization beam splitter is connected to the first optical input terminal of the balanced photodetector; the Y-polarization output terminal of the polarization beam splitter is connected to the second optical input terminal of the balanced photodetector; the electrical signal output terminal of the balanced photodetector is connected to the first acquisition channel and the second acquisition channel of the data acquisition card, respectively. The data output terminal of the data acquisition card is connected to the data input terminal of the host computer. The host computer has a built-in digital signal processing module; A piezoelectric ceramic transducer is installed at a predetermined position on the optical fiber under test as a standard vibration excitation source, used to apply a sinusoidal vibration signal or a swept frequency vibration signal at a preset frequency.

[0014] Optionally, the narrow-linewidth laser is used to generate a continuous optical signal; The acousto-optic modulator is used to pulse modulate the continuous optical signal; the erbium-doped fiber amplifier is used to amplify the modulated optical signal, and the amplified optical signal is injected into the fiber under test through the circulator; The signal driver is used to drive the acousto-optic modulator; The photodetector is used to detect the dual-polarization raw signal returned from the optical fiber under test; the acquisition card is used to acquire the dual-polarization raw signal from the photodetector. The host computer is used to process the dual-polarization signal to achieve real-time analysis and processing of the sensor signal.

[0015] The beneficial effects of the technical solution provided in this application are: 1. By suppressing polarization fading through differential polarization vector sum algorithm and combining it with the NSGA-II optimized non-uniform bandwidth SEMS method to deeply suppress coherent fading, the fading points of the fiber optic link are basically eliminated and the signal strength fluctuation is greatly reduced.

[0016] 2. By using a genetic algorithm, the inherent contradiction between signal-to-noise ratio and spatial resolution can be alleviated, achieving noise reduction while ensuring spatial resolution, and significantly reducing phase demodulation error. Attached Figure Description

[0017] The present application will be further described below with reference to the accompanying drawings and embodiments. In the accompanying drawings: Figure 1 This is a system connection diagram in an embodiment of this application; Figure 2 This is a flowchart of the data processing in the embodiments of this application; Figure 3 This is a schematic diagram of the rotation vector algorithm in the embodiments of this application; Figure 4 This is a schematic diagram illustrating the impact of the frequency band division method on spatial resolution in an embodiment of the present invention; Figure 5 This is a schematic diagram illustrating the genetic algorithm optimization in an embodiment of the present invention. Detailed Implementation

[0018] To provide a clearer understanding of the technical features, objectives, and effects of this application, the specific embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0019] The embodiments of this application provide an intelligent coherent fading suppression method for fiber optic distributed sensing.

[0020] Please refer to Figure 1 , Figure 1 This is a system connection diagram of an intelligent coherent fading suppression method for fiber optic distributed sensing, as described in an embodiment of this application, including: S1: Construct the optical path system of a phase-sensitive optical time-domain reflectometer to acquire dual-polarization raw signals; S2: Perform differential polarization vector sum processing on the original dual-polarization signal to obtain a polarization-insensitive composite signal; S3: Construct a multi-objective optimization model based on the NSGA-II non-dominated sorting genetic algorithm to obtain the optimal non-uniform bandwidth allocation scheme; S4: Based on the optimal non-uniform bandwidth allocation scheme, non-uniform spectrum division is performed on the polarization-insensitive composite signal, and multi-subband signals are fused by combining rotation vector sum algorithm to suppress coherent fading; S5: Perform phase demodulation and post-processing on the fused multi-subband signals to restore the distributed vibration phase signal.

[0021] By adopting the above-mentioned technical solution, this application significantly improves the signal-to-noise ratio while maintaining the original spatial resolution, simultaneously suppresses polarization fading and coherent fading, and improves the phase demodulation accuracy and disturbance positioning reliability.

[0022] Step S1 includes: The phase-sensitive optical time-domain reflectometer optical path system includes a narrow linewidth laser, a first fiber coupler, an acousto-optic modulator, an erbium-doped fiber amplifier, a circulator, a second fiber coupler, a polarization beam splitter, a balanced photodetector, and a data acquisition card. The narrow linewidth laser outputs continuous light, which is split into a probe light branch and a local oscillator light branch by the first fiber coupler. The optical signal of the probe optical branch is sequentially modulated into a rectangular probe pulse by the acousto-optic modulator, amplified by the erbium-doped fiber amplifier, and then injected into the sensing fiber under test through the circulator. The optical signal of the local oscillator branch is split into two paths by the second fiber coupler, and respectively forms X and Y orthogonal polarization component beat frequency signals with the Rayleigh backscattered light returning from the sensing fiber under test at the polarization beam splitter; the X and Y orthogonal polarization component beat frequency signals are respectively converted into electrical signals by the balanced photodetector, and sampled at high speed by the data acquisition card to obtain the dual polarization raw signal.

[0023] As one example, a φ-OTDR optical path system is constructed to acquire dual-polarization raw signals; A narrow-linewidth laser is used as the light source, and the output light is split into a probe light branch and a local oscillator light branch via a 90:10 fiber coupler: The probe optical branch is modulated into a rectangular probe pulse by an acousto-optic modulator (AOM), amplified by an erbium-doped fiber amplifier (EDFA), and then injected into the sensing fiber under test through a circulator. The local oscillator branch is split into two paths by a 50:50 coupler, which, together with the Rayleigh backscattered light returned from the sensing fiber, form X and Y orthogonal polarization components beat frequency signals at the polarization beam splitter (PBS). The two polarization beat frequency signals are converted into electrical signals by a balanced photodetector (BPD) and sampled at high speed by a data acquisition card (DAQ) to obtain the raw data of the X and Y dual polarization channels.

[0024] Step S2 includes: S201: Perform down-conversion processing on the original dual-polarization signals to shift the effective signal to the low-frequency range; S202: Uses an FIR low-pass filter to remove out-of-band high-frequency noise and interference from the original dual-polarization signal; S203: Perform polarization vector difference operation on the filtered dual-polarization original signal to correct static phase shift and extract dynamic phase information; S204: The two processed dual-polarization original signals are vector-summed to obtain a polarization-insensitive composite signal.

[0025] As one example, differential polarization vector sum processing is performed on the acquired dual-polarization original signal to suppress polarization fading and obtain a polarization-insensitive composite signal.

[0026] Step S3 includes: The probe pulse spectrum is divided into three continuous, non-overlapping sub-bands: the main lobe, the first side lobe, and the second side lobe; the multi-objective optimization model is: Optimization objective 1: Maximize the system signal-to-noise ratio; Optimization objective 2: Minimize system spatial resolution; Constraints: 0 <Freq_len1<Freq_len2,0<Freq_len3<Freq_len2; Where Freq_len1 is the bandwidth of the first sidelobe, Freq_len3 is the bandwidth of the second sidelobe, and Freq_len2 is the bandwidth of the main lobe. The system spatial resolution is calculated using the following formula:

[0027] in, The speed of light in a vacuum The refractive index of the fiber core. The equivalent pulse time-domain width after spectrum partitioning; The system signal-to-noise ratio is obtained as follows: the phase signal is obtained by IQ demodulation, and the signal power and noise power are calculated based on the phase noise amplitude to obtain the system signal-to-noise ratio; The NSGA-II non-dominated sorting genetic algorithm is used to iteratively optimize the multi-objective optimization model: the Pareto optimal solution set is screened by non-dominated sorting and crowding calculation. Under the preset spatial resolution index, the optimal non-uniform bandwidth allocation ratio of the main lobe to a wide bandwidth and the side lobes to a narrow bandwidth is determined, and the optimal non-uniform bandwidth allocation scheme for solving the detection pulse spectrum is obtained.

[0028] Step S4 includes: S401: According to the optimal non-uniform bandwidth allocation scheme, three sets of FIR filters are used to non-uniformly segment the spectrum of the polarization-insensitive composite signal to obtain three independent sub-band signals. S402: The three independent sub-band signals are fused using a rotation vector sum algorithm.

[0029] As one embodiment, based on the optimal non-uniform bandwidth allocation scheme, the polarization-insensitive composite signal is non-uniformly divided into three independent sub-band signals; and the multi-sub-band signals are fused using the Rotating Vector Sum (RVS) algorithm to suppress coherent fading. Specifically, this includes: 1) According to the optimal bandwidth scheme output by NSGA-II, three sets of FIR filters are used to non-uniformly segment the spectrum of the polarization-suppressed composite signal to obtain three sub-band signals; 2) The three sub-band signals are fused using the Rotating Vector Sum (RVS) algorithm: eliminating absolute phase, avoiding new fading points, while retaining the relative phase changes caused by external disturbances, thus suppressing coherent fading.

[0030] Step S5 includes: The original phase is obtained by IQ demodulation of the fused multi-subband signal. Phase unwinding operation is performed to eliminate phase jump, and finally a smooth, low-noise phase waveform is output, thus completing the demodulation and disturbance localization of distributed vibration signal.

[0031] A smart coherent fading suppression system for fiber-optic distributed sensing, the system comprising: Narrow linewidth laser, acousto-optic modulator, signal driver, erbium-doped fiber amplifier, circulator, filter, polarization beam splitter, first fiber coupler, second fiber coupler, piezoelectric ceramic, fiber under test, photodetector, data acquisition card and host computer; The output end of the narrow linewidth laser is connected to the input end of the first fiber coupler; the first fiber coupler splits the optical signal into a probe light branch and a local oscillator light branch with a splitting ratio of 90:10. The probe light output terminal of the first fiber optic coupler is connected to the light input terminal of the acousto-optic modulator; the radio frequency drive terminal of the acousto-optic modulator is connected to the output terminal of the signal driver, and the signal driver outputs a control signal to drive the acousto-optic modulator to pulse modulate the probe light. The optical output terminal of the acousto-optic modulator is connected to the input terminal of the erbium-doped fiber amplifier. The output of the erbium-doped fiber amplifier is connected to the first port of the circulator; The second port of the circulator is connected to one end of the optical fiber under test; the third port of the circulator is connected to the input of the filter; and the output of the filter is connected to the optical signal input of the polarization beam splitter. The local oscillator output terminal of the first fiber coupler is connected to the input terminal of the second fiber coupler; the second fiber coupler splits the local oscillator light into two paths with a splitting ratio of 50:50, and the output terminals of the two local oscillator lights are respectively connected to the two local oscillator light input terminals of the polarization beam splitter; The X-polarization output terminal of the polarization beam splitter is connected to the first optical input terminal of the balanced photodetector; the Y-polarization output terminal of the polarization beam splitter is connected to the second optical input terminal of the balanced photodetector; the electrical signal output terminal of the balanced photodetector is connected to the first acquisition channel and the second acquisition channel of the data acquisition card, respectively. The data output terminal of the data acquisition card is connected to the data input terminal of the host computer. The host computer has a built-in digital signal processing module; A piezoelectric ceramic transducer is installed at a predetermined position on the optical fiber under test as a standard vibration excitation source, used to apply a sinusoidal vibration signal or a swept frequency vibration signal at a preset frequency.

[0032] The narrow linewidth laser is used to generate continuous optical signals; The acousto-optic modulator is used to pulse modulate the continuous optical signal; the erbium-doped fiber amplifier is used to amplify the modulated optical signal, and the amplified optical signal is injected into the fiber under test through the circulator; The signal driver is used to drive the acousto-optic modulator; The photodetector is used to detect the dual-polarization raw signal returned from the optical fiber under test; the acquisition card is used to acquire the dual-polarization raw signal from the photodetector. The host computer is used to process the dual-polarization signal to achieve real-time analysis and processing of the sensor signal.

[0033] This application utilizes the aforementioned hardware system combined with an intelligent fading suppression algorithm to address the coexistence of polarization fading and coherent fading in φ-OTDR systems. It employs a differential polarization vector sum algorithm to suppress polarization fading, while simultaneously optimizing the bandwidth allocation method of spectrum extraction and mixing (SEMS) based on the NSGA-II genetic algorithm. Combined with the rotation vector sum algorithm, it suppresses coherent fading, thereby improving the signal-to-noise ratio without sacrificing the system's spatial resolution and accurately reproducing the vibration and acoustic signals along the optical fiber.

[0034] As one example, such as Figure 1 As shown, the continuous optical signal generated by the laser is first transmitted to an acousto-optic modulator for pulse modulation. The modulated optical signal then enters an erbium-doped fiber amplifier for power amplification. The amplified optical signal is injected into the single-mode fiber under test through a circulator for distributed vibration sensing. The signal driver outputs a control signal in real time to drive the acousto-optic modulator to operate stably. When the fiber under test is subjected to external vibration or excitation by piezoelectric ceramics, it returns Rayleigh backscattered light carrying disturbance information. This beam is transmitted to a photodetector for photoelectric conversion. The electrical signal output by the detector is sampled at high speed by a data acquisition card and then uploaded to a digital signal processing module. The module uses built-in algorithms to perform signal noise reduction, fading suppression, phase demodulation, and disturbance localization, ultimately achieving real-time analysis and processing of the sensing signal.

[0035] The core improvement of this invention lies in its non-uniform bandwidth division of the probe pulse spectrum, which differs from the traditional equal bandwidth division mode. Traditional SEMS methods use a uniform bandwidth to cut the spectrum, failing to consider the characteristics of concentrated energy in the main lobe and enriched noise in the side lobes of the pulse spectrum, ultimately resulting in a trade-off between signal-to-noise ratio and spatial resolution. This invention, based on the pulse spectrum energy distribution characteristics, adopts a division strategy of allocating a wide bandwidth to the main lobe and a narrow bandwidth to the side lobes, amplifying the effective signal energy and suppressing side lobe noise interference.

[0036] To obtain the optimal non-uniform bandwidth allocation, this invention introduces the NSGA-II non-dominated sorting genetic algorithm for multi-objective optimization. This algorithm aims to maximize the system signal-to-noise ratio and minimize the spatial resolution, while also imposing the constraint that the bandwidth of both side lobes is less than that of the main lobe. Through iterative optimization, non-dominated sorting, and crowding calculation, the algorithm outputs a Pareto optimal solution set. Engineers can then select a bandwidth scheme from the optimal solution set that matches a preset spatial resolution based on actual engineering requirements, thus balancing the two core performance indicators.

[0037] After determining the optimal bandwidth parameters, this invention employs three independent FIR filters to segment and truncate the signal spectrum, resulting in three continuous, non-overlapping sub-band signals. Since direct superposition of multiple sub-band signals can easily cause phase cancellation and generate new fading points, this invention uses the Rotating Vector Sum (RVS) algorithm to fuse the multi-sub-band signals. This algorithm can eliminate absolute phase components in the signal, avoid new fading points, and simultaneously preserve the relative phase changes caused by external disturbances, achieving deep suppression of coherent fading.

[0038] After completing dual-fading suppression, IQ demodulation is performed on the fused signal to extract phase information at various locations along the fiber. Since the demodulated phase signal has periodic jumps, this invention corrects the phase abrupt changes through phase unwinding operation, outputting a continuous and smooth phase waveform, and completing disturbance location and vibration waveform reconstruction based on the amount of phase change.

[0039] This invention, through a complete signal processing chain, sequentially completes dual-polarization signal preprocessing, polarization fading suppression, genetic algorithm bandwidth optimization, non-uniform spectrum partitioning, rotation vector sum fusion, and phase demodulation and repair, forming a complete φ-OTDR dual-fading suppression scheme from optical path acquisition to algorithm processing, effectively solving various defects of traditional technologies. Figure 2 The data processing flowchart shown is shown.

[0040] To verify the actual effect of the technical solution of this invention, a 2.5km commercial single-mode fiber φ-OTDR experimental system was built for field testing. The system hardware parameters are as follows: the linewidth of the narrow-linewidth laser was set to 100Hz, and the output optical power was 168mW; the acousto-optic modulator output a rectangular probe pulse with a pulse width of 40ns, a repetition frequency of 10kHz, and an optical frequency shift of 200MHz; the erbium-doped fiber amplifier amplified the peak power of the probe pulse to 22.3mW; the sampling rate of the data acquisition card was set to 8GSa / s; a piezoelectric ceramic transducer was arranged at a distance of 2.1km on the fiber under test as a standard vibration excitation source, and sinusoidal vibration signals of 200Hz and 500Hz and a 0~1kHz sweep frequency vibration signal were applied respectively.

[0041] Combination Figure 3 The signal strength comparison chart shows that: Figure 3 (a) The displayed signal contains many deep fading points with large intensity fluctuations. It can be seen that the fading phenomenon causes the signal amplitude at multiple locations to be significantly lower than the noise floor. After polarization fading suppression... Figure 3 (b) The signal stability is significantly improved, with intensity fluctuations reduced to approximately 30 dB. Following the fading suppression method proposed in this paper, Figure 3 (c) The fading points are almost eliminated, the signal strength is flat and uniform, and the fluctuation is only about 20 dB, which greatly improves the reliability of demodulation. like Figure 4 As shown, the first figure illustrates the impact of equal-frequency band division on spatial resolution; the second shows 1 / 2 of the main lobe and two 1 / 4 of the side lobes; and the third shows 2 / 3 of the main lobe and two 1 / 6 of the side lobes. (Combined with...) Figure 4 As can be seen from the schematic diagram of the impact of frequency band allocation on spatial resolution, compared with the traditional equal bandwidth allocation mode, the non-uniform bandwidth allocation method adopted in this invention will not degrade the spatial resolution of the system and can optimize the signal-to-noise ratio while ensuring positioning accuracy.

[0042] Combination Figure 5 As shown in the NSGA-II multi-objective optimization diagram, the Pareto optimal front output by the algorithm fully reflects the correspondence between signal-to-noise ratio (SNR) and spatial resolution. When the system spatial resolution is maintained at 6.1m, for a 200Hz vibration signal, the non-uniform bandwidth scheme of this invention improves the SNR by 8.37dB compared to the traditional equal-bandwidth SEMS method; at this time, the optimal bandwidth ratio is 80.21% for the main lobe and 10.43% and 9.36% for the two side lobes, respectively. For a 500Hz sine wave signal and a 0~1kHz swept frequency signal, the SNR of this scheme is improved by 5.21dB and 3.57dB, respectively, achieving performance optimization.

[0043] Phase demodulation results show that the standard deviation of the recovered phase using the traditional equal-bandwidth SEMS method is 0.233 radians, while the standard deviation is reduced to 0.045 radians after processing by the method of this invention. This significantly reduces the phase demodulation error and improves the accuracy of the vibration waveform restoration. Simultaneously, the phase differential positioning curve is smooth and distortion-free, with clear disturbance peaks, effectively ensuring the system's positioning accuracy.

[0044] The above experimental results fully demonstrate that the dual fading suppression scheme based on NSGA-II optimized non-uniform bandwidth of this invention can simultaneously suppress polarization fading and coherent fading of the φ-OTDR system, completely breaking the performance constraints of traditional methods in terms of signal-to-noise ratio and spatial resolution, and is suitable for long-distance, high-precision distributed optical fiber vibration monitoring scenarios.

[0045] The above are merely exemplary embodiments of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure.

[0046] This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described in this disclosure. The specification and embodiments are to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A smart coherent fading suppression method for fiber-optic distributed sensing, characterized in that, The method includes the following steps: S1: Construct the optical path system of a phase-sensitive optical time-domain reflectometer to acquire dual-polarization raw signals; S2: Perform differential polarization vector sum processing on the original dual-polarization signal to obtain a polarization-insensitive composite signal; S3: Construct a multi-objective optimization model based on the NSGA-II non-dominated sorting genetic algorithm to obtain the optimal non-uniform bandwidth allocation scheme; S4: Based on the optimal non-uniform bandwidth allocation scheme, non-uniform spectrum division is performed on the polarization-insensitive composite signal, and multi-subband signals are fused by combining rotation vector sum algorithm to suppress coherent fading; S5: Perform phase demodulation and post-processing on the fused multi-subband signals to restore the distributed vibration phase signal.

2. The intelligent coherent fading suppression method for fiber-optic distributed sensing as described in claim 1, characterized in that, Step S1 includes: The phase-sensitive optical time-domain reflectometer optical path system includes a narrow linewidth laser, a first fiber coupler, an acousto-optic modulator, an erbium-doped fiber amplifier, a circulator, a second fiber coupler, a polarization beam splitter, a balanced photodetector, and a data acquisition card. The narrow linewidth laser outputs continuous light, which is split into a probe light branch and a local oscillator light branch by the first fiber coupler. The optical signal of the probe optical branch is sequentially modulated into a rectangular probe pulse by the acousto-optic modulator, amplified by the erbium-doped fiber amplifier, and then injected into the sensing fiber under test through the circulator. The optical signal of the local oscillator branch is split into two paths by the second fiber coupler, and respectively forms X and Y orthogonal polarization component beat frequency signals with the Rayleigh backscattered light returning from the sensing fiber under test at the polarization beam splitter; the X and Y orthogonal polarization component beat frequency signals are respectively converted into electrical signals by the balanced photodetector, and sampled at high speed by the data acquisition card to obtain the dual polarization raw signal.

3. The intelligent coherent fading suppression method for fiber-optic distributed sensing as described in claim 1, characterized in that, Step S2 includes: S201: Perform down-conversion processing on the original dual-polarization signals to shift the effective signal to the low-frequency range; S202: Uses an FIR low-pass filter to remove out-of-band high-frequency noise and interference from the original dual-polarization signal; S203: Perform polarization vector difference operation on the filtered dual-polarization original signal to correct static phase shift and extract dynamic phase information; S204: The two processed dual-polarization original signals are vector-summed to obtain a polarization-insensitive composite signal.

4. The intelligent coherent fading suppression method for fiber-optic distributed sensing as described in claim 1, characterized in that, Step S3 includes: The probe pulse spectrum is divided into three continuous, non-overlapping sub-bands: the main lobe, the first side lobe, and the second side lobe; the multi-objective optimization model is: Optimization objective 1: Maximize the system signal-to-noise ratio; Optimization objective 2: Minimize system spatial resolution; Constraints: 0 <Freq_len1<Freq_len2,0<Freq_len3<Freq_len2; Where Freq_len1 is the bandwidth of the first sidelobe, Freq_len3 is the bandwidth of the second sidelobe, and Freq_len2 is the bandwidth of the main lobe. The system spatial resolution is calculated using the following formula: in, The speed of light in a vacuum The refractive index of the optical fiber core. The equivalent pulse time-domain width after spectrum partitioning; The system signal-to-noise ratio is obtained as follows: the phase signal is obtained by IQ demodulation, and the signal power and noise power are calculated based on the phase noise amplitude to obtain the system signal-to-noise ratio; The NSGA-II non-dominated sorting genetic algorithm is used to iteratively optimize the multi-objective optimization model: the Pareto optimal solution set is screened by non-dominated sorting and crowding calculation. Under the preset spatial resolution index, the optimal non-uniform bandwidth allocation ratio of the main lobe to a wide bandwidth and the side lobes to a narrow bandwidth is determined, and the optimal non-uniform bandwidth allocation scheme for solving the detection pulse spectrum is obtained.

5. The intelligent coherent fading suppression method for fiber-optic distributed sensing as described in claim 1, characterized in that, Step S4 includes: S401: According to the optimal non-uniform bandwidth allocation scheme, three sets of FIR filters are used to non-uniformly segment the spectrum of the polarization-insensitive composite signal to obtain three independent sub-band signals. S402: The three independent sub-band signals are fused using a rotation vector sum algorithm.

6. The intelligent coherent fading suppression method for fiber-optic distributed sensing as described in claim 1, characterized in that, Step S5 includes: The original phase is obtained by IQ demodulation of the fused multi-subband signal. Phase unwinding operation is performed to eliminate phase jump, and finally a smooth, low-noise phase waveform is output, thus completing the demodulation and disturbance localization of distributed vibration signal.

7. An intelligent coherent fading suppression system for fiber-optic distributed sensing, used to implement the intelligent coherent fading suppression method for fiber-optic distributed sensing as described in any one of claims 1-6, characterized in that, The system includes: Narrow linewidth laser, acousto-optic modulator, signal driver, erbium-doped fiber amplifier, circulator, filter, polarization beam splitter, first fiber coupler, second fiber coupler, piezoelectric ceramic, fiber under test, photodetector, data acquisition card and host computer; The output end of the narrow linewidth laser is connected to the input end of the first fiber coupler; the first fiber coupler splits the optical signal into a probe light branch and a local oscillator light branch with a splitting ratio of 90:

10. The probe light output terminal of the first fiber optic coupler is connected to the light input terminal of the acousto-optic modulator; the radio frequency drive terminal of the acousto-optic modulator is connected to the output terminal of the signal driver, and the signal driver outputs a control signal to drive the acousto-optic modulator to pulse modulate the probe light. The optical output terminal of the acousto-optic modulator is connected to the input terminal of the erbium-doped fiber amplifier. The output of the erbium-doped fiber amplifier is connected to the first port of the circulator; The second port of the circulator is connected to one end of the optical fiber under test; the third port of the circulator is connected to the input of the filter; and the output of the filter is connected to the optical signal input of the polarization beam splitter. The local oscillator output terminal of the first fiber coupler is connected to the input terminal of the second fiber coupler; the second fiber coupler splits the local oscillator light into two paths with a splitting ratio of 50:50, and the output terminals of the two local oscillator lights are respectively connected to the two local oscillator light input terminals of the polarization beam splitter; The X-polarization output terminal of the polarization beam splitter is connected to the first optical input terminal of the balanced photodetector; the Y-polarization output terminal of the polarization beam splitter is connected to the second optical input terminal of the balanced photodetector; the electrical signal output terminal of the balanced photodetector is connected to the first acquisition channel and the second acquisition channel of the data acquisition card, respectively. The data output terminal of the data acquisition card is connected to the data input terminal of the host computer. The host computer has a built-in digital signal processing module; A piezoelectric ceramic transducer is installed at a predetermined position on the optical fiber under test as a standard vibration excitation source, used to apply a sinusoidal vibration signal or a swept frequency vibration signal at a preset frequency.

8. The intelligent coherent fading suppression system for fiber optic distributed sensing as described in claim 7, characterized in that, The narrow linewidth laser is used to generate continuous optical signals; The acousto-optic modulator is used to pulse modulate the continuous optical signal; The erbium-doped fiber amplifier is used to amplify the power of the modulated optical signal, and the amplified optical signal is injected into the fiber under test through the circulator. The signal driver is used to drive the acousto-optic modulator; The photodetector is used to detect the dual-polarization raw signal returned from the optical fiber under test; the acquisition card is used to acquire the dual-polarization raw signal from the photodetector. The host computer is used to process the dual-polarization signal to achieve real-time analysis and processing of the sensor signal.

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