A pulse coded optical fiber acoustic sensor system for tracking and locating a gas pipeline pig

Abstract

The application provides a pulse coding optical fiber acoustic wave sensing system for tracking and positioning of a gas pipeline pig, and belongs to the field of distributed optical fiber sensing; based on a phase-sensitive optical time domain reflection principle and a coherent detection structure, an optimized short binary phase coding sequence is generated through a pulse coding optimization module, and only a single emission is needed to realize continuous positioning of the pig with high signal-to-noise ratio, high spatial resolution and high update rate through matched filtering decoding. A signal modulation unit is integrated on the pig to emit wideband acoustic waves, optical fiber node monitoring arrays are arranged at pipeline branch junctions, and passive acoustic wave resonant cavities with unique resonant frequencies are installed at the entrances of each branch; when the pig enters a certain branch, the corresponding resonant cavity is excited to produce resonance, the resonant frequency is identified through spectrum analysis, and the accurate discrimination of the path at the branch junction is realized; the problems that the prior art cannot simultaneously consider high resolution and high update rate and is difficult to discriminate the direction of the branch junction can be solved, and the reliability of the pig tracking is significantly improved.

Description

Technical Field

[0001] This application relates to the field of distributed optical fiber sensing technology, and in particular to a pulse-code optical fiber acoustic wave sensing system for tracking and locating gas pipeline pigs. Background Technology

[0002] Pipeline cleaning is a core component of the entire lifecycle maintenance of gas pipelines. Real-time tracking and positioning of the pipeline cleaning device is crucial for ensuring the safety of the operation, preventing pipeline blockage, and improving gas transmission efficiency. Especially in long-distance, high-pressure gas pipelines, complex urban pipe networks, and sections in special terrains such as mountainous and desert areas, abnormal situations such as pipeline cleaning device blockage or displacement can easily lead to safety accidents. Currently, the tracking and positioning of gas pipeline cleaning devices mainly relies on magnetic signal point detection, traditional fiber optic acoustic sensing, and pressure wave calculation, which makes it difficult to achieve continuous, high-precision, and low-latency positioning of the cleaning device throughout the entire process.

[0003] With the rapid development of distributed fiber optic sensing technology, fiber optic acoustic sensing technology, centered on phase-sensitive optical time-domain reflectometry (Φ-OTDR), has become the mainstream technology due to its advantages such as continuous monitoring and resistance to electromagnetic interference. However, Φ-OTDR systems based on traditional single-pulse modulation have spatial resolution limited by pulse width, making it difficult to balance high resolution and large dynamic range. While conventional pulse coding schemes such as Golay and Barker codes can improve the signal-to-noise ratio, they require multiple measurements, increasing time overhead and failing to meet the real-time positioning requirements of rapid pipeline pig movement. More importantly, existing technologies generally assume pipelines are single, continuous lines, ignoring the numerous T-junctions, cross-junctions, and other branching nodes present in urban gas pipeline networks. When a pipeline pig reaches a branch, traditional systems cannot determine whether it has entered the intended main route or mistakenly entered a side branch, leading to "losing track" or misjudgment. If the pig gets stuck in an unknown branch, it will pose significant safety hazards and make emergency repairs extremely difficult. Summary of the Invention

[0004] To address the aforementioned technical issues, this application proposes a pulse-coded fiber optic acoustic wave sensing system for tracking and locating gas pipeline pigs.

[0005] The technical solution adopted in this application is as follows: a pulse-coded fiber optic acoustic wave sensing system for tracking and locating a gas pipeline pig, comprising a pig installed in the gas pipeline, a main pipeline monitoring probe, branch monitoring probes installed on the branch lines of the pipeline, a branch fiber optic node monitoring array deployed at key locations at gas pipeline branch intersections, and a single-mode sensing fiber laid along the gas pipeline. The pig is equipped with a signal modulation unit; a coherent detection structure is connected to the single-mode sensing fiber; the branch fiber optic node monitoring array is formed by the single-mode sensing fiber connected to a 1×N optical splitter. The branching system includes monitoring branches extending along the main road and monitoring branches extending along the entrances of each pipeline branch. Each monitoring branch is equipped with a monitoring probe, and each pipeline branch entrance is equipped with an acoustic resonant cavity device. Each pipeline branch acoustic resonant cavity device has a unique and different resonant frequency. When the pig enters a certain pipeline branch, it continuously emits broadband sound waves into the gas pipeline through the signal modulation unit to excite the corresponding acoustic resonant cavity device to resonate. The resonant frequency is identified through spectrum analysis to achieve accurate identification of the branching path. Based on the principle of phase-sensitive optical time-domain reflectometry (Φ-OTDR), this system employs optimized short binary phase coding (OSBPC) and a coherent detection structure, using a single single-mode sensing fiber as a distributed sensing medium to achieve high-precision positioning of the acoustic signals generated by the movement of the pig.

[0006] Furthermore, the coherent detection structure includes a narrow-linewidth laser, a first coupler, a phase modulator, an acousto-optic modulator, an optical amplifier, a circulator, a 90° optical mixer, a second coupler, a balanced detector, a data acquisition card, a signal processing and decoding unit, a positioning calculation server, a host computer monitoring platform, an optical pulse code generator, a pulse code optimization module, a junction discrimination unit, and a path discrimination server. The narrow-linewidth laser outputs continuous laser light, which is split into probe light and local oscillator light by the first coupler. The probe light enters the phase modulator, and the local oscillator light enters the second coupler. Under the configuration of the pulse code optimization module, the optical pulse code generator generates optimized short binary phase code OSBPC drive pulses, which act on the phase modulator to perform binary phase coding on the probe light. Bit-coded modulation; the coded light output from the phase modulator enters the acousto-optic modulator and is cut into a coded pulse train; the coded pulse train is amplified by the optical amplifier and injected into the single-mode sensing fiber laid along the gas pipeline through the input terminal a of the circulator; the backscattered Rayleigh light enters the 90° optical mixer through the output terminal c of the circulator and is coherently mixed with the local oscillator light; the output of the 90° optical mixer is connected to the balanced detector, converted into an electrical signal, and then synchronously sampled by the data acquisition card; the acquired digital signal is sent to the signal processing and decoding unit, performs matched filtering decoding, and recovers the single pulse response with a high signal-to-noise ratio; the decoded data is sent to the positioning calculation server, and the continuous position information of the pig is extracted in real time through the phase demodulation algorithm and uploaded to the host computer monitoring platform for display.

[0007] Furthermore, the pulse coding optimization module employs an aperiodic coding optimization method based on a distributed genetic algorithm to generate optimized short binary phase codes (OSBPCs). The generation principle is implemented through the following steps: determining the duration of the single pulse signal according to the required spatial resolution and setting the energy enhancement factor to be limited by the gain saturation of the optical amplifier; defining the coding sequence length parameter to be 3 to 4 times the energy enhancement factor, thereby determining the total number of bits in the binary sequence; using a distributed genetic algorithm to search for the optimal 0 / 1 distribution with the goal of minimizing the noise scaling factor; and upsampling the obtained optimal sequence and convolving it with the single pulse signal to generate the final OSBPC driving pulse loaded onto the phase modulator.

[0008] Furthermore, the signal processing and decoding unit performs matched filtering decoding. First, it measures the effect of the transient response of the optical amplifier on the amplitude envelope of the coded pulse actually injected into the optical fiber. Based on this, it constructs a decoding function, performs division in the frequency domain, and then performs inverse transformation to obtain a distortion-free single pulse response.

[0009] Furthermore, the signal processing and decoding unit can also extract the vibration waveform of the corresponding time window based on the current position of the pig, extract multi-dimensional features and input them into the status recognition model, and output the operating status of the pig.

[0010] Furthermore, the fiber lengths from the 1×N optical splitter to each monitoring probe are different for each monitoring branch to ensure the differentiation of backscattered signals in the time domain.

[0011] Furthermore, the signals collected by each monitoring probe are returned through the same main optical fiber single-mode sensing fiber. The lengths of the optical fibers in each monitoring branch are different, and the signals are naturally separated in the time domain. The signal processing and decoding unit extracts the vibration waveforms of each monitoring probe according to the distance window.

[0012] Furthermore, the branch intersection discrimination unit includes a spectrum analysis module and a path matching module. The spectrum analysis module performs Fourier transform on the vibration waveforms of each monitoring probe and extracts significant peak frequencies in the spectrum. The path matching module compares the peak frequencies with a preset branch resonant frequency library to determine whether the pig is on the main gas pipeline or a branch pipeline.

[0013] Furthermore, the acoustic resonant cavity device is a cavity structure made of metal, which is fixedly installed on the inner or outer wall of the pipe at the inlet of the pipe branch. Its resonant frequency is determined by the geometric dimensions of the cavity, and there is sufficient interval between the resonant frequencies of each pipe branch to facilitate differentiation.

[0014] Furthermore, the signal modulation unit includes a signal generator and an acoustic transducer. The signal generator generates a broadband electrical signal, which is converted into a broadband acoustic signal by the acoustic transducer and continuously emitted into the gas pipeline.

[0015] The advantages of this application over the prior art are as follows: I. This application proposes and employs Optimized Short Binary Phase Coding (OSBPC), which is generated based on a distributed genetic algorithm. Compared with traditional Golay codes or Simplex codes, this application eliminates the need for multiple measurements and codeword switching, significantly improving the system position update rate while maintaining high spatial resolution. The length of the coding sequence can be flexibly set, unrestricted by traditional coding mathematical rules, and can achieve the highest coding efficiency under any given conditions. This meets the real-time dynamic tracking requirements of pigs moving at high speeds.

[0016] II. This application introduces an acoustic resonant cavity device and a fiber optic node monitoring array at branch intersections. Utilizing the frequency-selective response characteristics of the passive resonant cavity, the events of the pig entering different branches are converted into unique resonant frequencies. Through multi-point sensing and spectrum analysis using the fiber optic monitoring array, the pig's trajectory can be determined in real time and accurately. Attached Figure Description

[0017] The following description, in conjunction with the accompanying drawings, further illustrates this application: Figure 1 A schematic diagram of the pulse-coded fiber optic acoustic wave sensing system for tracking and locating a gas pipeline pig provided in an embodiment of this application; In the diagram: 1 is a narrow-linewidth laser, 2 is the first coupler, 3 is a phase modulator, 4 is an acousto-optic modulator, 5 is an optical amplifier, 6 is a circulator, 7 is a 90° optical mixer, 8 is the second coupler, 9 is a balanced detector, 10 is a data acquisition card, 11 is a signal processing and decoding unit, 12 is a positioning calculation server, 13 is a host computer monitoring platform, 14 is an optical pulse code generator, 15 is a pulse code optimization module, 16 is a spectrum analysis module, 17 is a path matching module, and 18 is a junction discrimination unit. 19 is the path discrimination server, 20 is the signal generator, 21 is the acoustic transducer, 22 is the signal modulation unit, 23 is the pipeline pig, 24 is the single-mode sensing fiber, 25 is the 1×N optical splitter, 26 is the first acoustic resonant cavity device, 27 is the second acoustic resonant cavity device, 28 is the main road monitoring probe, 29 is the first branch monitoring probe, 30 is the second branch monitoring probe, 31 is the intersection fiber optic node monitoring array, 32 is the first branch of the gas pipeline, 33 is the second branch of the gas pipeline, and 34 is the gas pipeline. Detailed Implementation

[0018] like Figure 1As shown, this application provides a pulse-coded fiber optic acoustic wave sensing system for tracking and locating a gas pipeline pig, including a pig 23 installed in a gas pipeline 34, a main pipeline monitoring probe 28, branch monitoring probes installed on the branch lines of the pipeline, a branch fiber optic node monitoring array 31 deployed at key locations at the branch intersections of the gas pipeline 34, and a single-mode sensing fiber optic cable 24 laid along the gas pipeline 34. A signal modulation unit 22 is installed on the pig 23. The signal modulation unit 22 includes a signal generator 20 and an acoustic transducer 21. The signal generator 20 generates a broadband electrical signal, which is converted into a broadband acoustic wave signal by the acoustic transducer 21 and continuously transmitted into the gas pipeline 34. A coherent detection structure is connected to the single-mode sensing fiber optic cable 24.

[0019] The intersection fiber optic node monitoring array 31 is formed by splitting single-mode sensing fiber 24 through a 1×N optical splitter 25. It includes a main road monitoring branch extending along the main road and a branch monitoring branch extending along the entrance of each pipeline branch. Each branch has a wound coil wound at the intersection position as a local sensitization monitoring probe, which constitutes the main road monitoring probe 28 and the branch monitoring probe, respectively. The fiber lengths from the 1×N optical splitter 25 to each monitoring probe are different to ensure that the backscattered signals are distinguishable in the time domain.

[0020] The system of this application also includes a first acoustic resonant cavity device 26 and a second acoustic resonant cavity device 27 installed at the inlet of each pipeline branch. The acoustic resonant cavity device is a passive resonant cavity. The resonant cavity of each pipeline branch has a unique and different resonant frequency, which is determined by the geometry of the cavity.

[0021] In this embodiment, the gas pipeline 34 is provided with a first branch 32 and a second branch 33. A first branch monitoring probe 29 is installed in the first branch 32 and a second branch monitoring probe 30 is installed in the second branch 33.

[0022] The coherent detection structure includes a narrow-linewidth laser 1, a first coupler 2, a phase modulator 3, an acousto-optic modulator 4, an optical amplifier 5, a circulator 6, a 90° optical mixer 7, a second coupler 8, a balanced detector 9, a data acquisition card 10, a signal processing and decoding unit 11, a positioning and calculation server 12, a host computer monitoring platform 13, an optical pulse code generator 14, a pulse code optimization module 15, a branch intersection discrimination unit 18, and a path discrimination server 19. The branch intersection discrimination unit 18 includes a spectrum analysis module 16 and a path matching module 17. The spectrum analysis module 16 performs Fourier transform on the vibration waveforms of each monitoring point to extract significant peak frequencies in the spectrum. The path matching module 17 compares the peak frequencies with a preset branch resonant frequency library to determine whether the pig 23 has entered the main road, the first branch of the gas pipeline 32, or the second branch of the gas pipeline 33.

[0023] A narrow-linewidth laser 1 outputs continuous laser light, which is split into probe light and local oscillator light by a first coupler 2. The probe light enters a phase modulator 3, and the local oscillator light enters a second coupler 8. An optical pulse code generator 14, configured by a pulse code optimization module 15, generates optimized short binary phase-coded OSBPC drive pulses, which act on the phase modulator 3 to perform binary phase-coded modulation on the probe light. The coded light output from the phase modulator 3 enters an acousto-optic modulator 4 and is cut into a coded pulse train. This coded pulse train is amplified by an optical amplifier 5 and injected into a single-mode sensing fiber 24 laid along a gas pipeline 34 through the input a of a circulator 6. Backscattered Rayleigh light enters a 90° optical mixer 7 through the output c of the circulator 6 and coherently mixes with the local oscillator light. The output of the 90° optical mixer 7 is connected to a balanced detector 9, converted into an electrical signal, and synchronously sampled by a data acquisition card 10. The acquired digital signal is sent to a signal processing and decoding unit 11, where matched filtering decoding is performed to recover a high signal-to-noise ratio single-pulse response. The decoded data is sent to the positioning and calculation server 12, where the continuous position information of the pig 23 is extracted in real time through the phase demodulation algorithm and uploaded to the host computer monitoring platform 13 for display.

[0024] Based on the principle of phase-sensitive optical time-domain reflectometry (Φ-OTDR), this application adopts an optimized short binary phase coding OSBPC and a coherent detection structure, and uses a single single-mode sensing fiber 24 as a distributed sensing medium to achieve the acquisition and high-precision positioning of the acoustic wave signal generated by the movement of the pig 23.

[0025] The pulse coding optimization module 15 generates optimized short binary phase codes (OSBPC) by adopting an aperiodic coding optimization method based on a distributed genetic algorithm, generating the optimal binary sequence that minimizes the noise scaling factor. Its generation principle is implemented through the following steps: determining the single-pulse duration based on the required spatial resolution and setting the energy enhancement factor to be limited by the optical amplifier gain saturation; defining the coding sequence length parameter, making it 3-4 times the energy enhancement factor, thereby determining the total number of bits in the binary sequence; using a distributed genetic algorithm to search for the optimal 0 / 1 distribution with the goal of minimizing the noise scaling factor; upsampling the obtained optimal sequence and convolving it with the single-pulse signal to generate the final OSBPC driving pulse loaded onto the phase modulator 3. During decoding, the signal processing and decoding unit 11 first measures the influence of the actual injected fiber's coded pulse amplitude envelope on the transient response of the optical amplifier, constructing a decoding function based on this. A division operation is performed in the frequency domain, followed by an inverse transformation to obtain a distortion-free single-pulse response, thereby effectively suppressing noise amplification and maximizing the coding gain.

[0026] To achieve branch path identification, this application integrates a signal modulation unit 22 on the pig 23. A broadband electrical signal is generated by a signal generator 20, converted into a broadband acoustic wave by an acoustic transducer 21, and continuously emitted into the pipeline. Simultaneously, a branch fiber optic node monitoring array 31 is deployed at the pipeline branch. This array uses a 1×N optical splitter 25 to divide the single-mode sensing fiber 24 into multiple branches: the main monitoring branch extends along the main road and has a wound coil wound close to the branch intersection as a main road monitoring probe 28; the first branch and second branch monitoring branches extend to the entrances of their respective branches, also with wound coils wound as first branch monitoring probes 29 and second branch monitoring probes 30. The fiber lengths of each branch are different to ensure that the backscattered signals are distinguishable in the time domain. At the entrance of each branch, a first acoustic resonant cavity device 26 and a second acoustic resonant cavity device 27 are installed respectively. These devices are passive metal cavities, and their resonant frequencies are uniquely determined by their geometric dimensions: fA for the first branch and fB for the second branch. When the pig 23 enters a branch, its emitted broadband acoustic waves excite the resonant cavity of that branch to resonate. The resonant signal propagates through the pipe wall and is sensed by the corresponding branch monitoring probe. The signals collected by each monitoring probe are returned via the main optical fiber, and the signal processing and decoding unit 11 extracts the vibration waveforms according to the distance window. The branch intersection discrimination unit 18 receives waveforms from each monitoring probe, and its spectrum analysis module 16 performs Fourier transform on each waveform to extract significant peak frequencies. The path matching module 17 compares the peak frequencies with a preset branch resonant frequency library: if no resonant peak is observed from any monitoring probe, the pig 23 is determined to have entered the main road; if the first branch monitoring probe 29 shows a resonant peak at frequency fA and no other monitoring point shows this peak, it is determined to have entered the first branch 32 of the gas pipeline; similarly, if the second branch monitoring probe 30 shows a resonant peak at frequency fB, it is determined to have entered the first branch 33 of the gas pipeline. The discrimination results are uploaded to the host computer monitoring platform 13 via the path discrimination server 19 and displayed in conjunction with the positioning information.

[0027] In some embodiments, the signal processing and decoding unit 11 can also extract the vibration waveform of the corresponding time window according to the current position of the pig 23, extract multi-dimensional features and input them into the status recognition model, and output the operating status of the pig 23, such as jamming or offset. When an abnormality is detected, the host computer monitoring platform 13 will automatically issue an early warning.

[0028] In a specific embodiment, the non-periodic encoding optimization method based on distributed genetic algorithm of this application is implemented according to the following steps: Step 1: Calculate the duration of the single-pulse signal based on the spatial resolution required for tracking and positioning by the pig 23. This single-pulse signal corresponds to the probe optical pulse in the system's traditional single-pulse operating mode. Simultaneously, determine the energy enhancement factor based on system physical constraints. This parameter represents the total increase in optical energy of the coded pulse sequence relative to the single pulse, and its upper limit is limited by factors such as nonlinear effects and gain saturation of the optical amplifier 5. The value of the energy enhancement factor must ensure that maximum signal-to-noise ratio improvement is achieved without introducing additional noise or distortion.

[0029] Step 2: Define the encoding sequence length parameter *m*, which represents the ratio of the total number of bits in the binary unipolar sequence to the energy enhancement factor. An optimal encoding gain is obtained when this ratio is between 3 and 4. The total number of bits in the binary unipolar sequence, consisting of 0 and 1 elements, is then calculated, where the number of 1s equals the energy enhancement factor.

[0030] Step 3: Define an index to measure the degree of noise amplification after decoding. The ratio of the noise variance after decoding to the noise variance before decoding is called the noise scaling factor. This index is closely related to the spectral characteristics of the encoded sequence. The optimization objective is to minimize the noise scaling factor by designing the distribution of 0s and 1s in the binary unipolar sequence, thereby maximizing the signal-to-noise ratio improvement after decoding.

[0031] Step 4: The pulse coding optimization module 15 runs a distributed genetic algorithm to search for the optimal binary sequence that minimizes the noise scaling factor, given the energy enhancement factor and the total number of bits in the sequence. The algorithm steps are as follows: 1. Population initialization: Create multiple subpopulations, each containing several randomly generated candidate binary sequences, with a specified number of 1s and 0s randomly distributed in each candidate binary sequence.

[0032] 2. Fitness Evaluation: Considering the amplitude envelope function introduced by optical amplifier 5, calculate the noise scaling factor corresponding to each candidate binary sequence. The smaller the value, the better the sequence.

[0033] 3. Selection operation: Select the parent sequence based on fitness. The smaller the noise scaling factor, the greater the probability of the candidate binary sequence being selected.

[0034] 4. Crossover operation: Randomly select two parent sequences, swap a certain segment of their binary bits, and generate two new sequences.

[0035] 5. Mutation operation: Randomly flip the values ​​of several bits in the sequence with a low probability to introduce new genetic information.

[0036] 6. Population migration: Regularly exchange superior individuals between different subpopulations to avoid the algorithm getting stuck in local optima.

[0037] 7. Termination Judgment: Stop iterating when no better sequence appears for several consecutive generations, and output the optimal sequence that minimizes the noise scaling factor.

[0038] Step 5: Upsample the optimal binary sequence to obtain the baseband sequence. For return-to-zero (RZ) format, the upsampling factor must be greater than the single pulse length to avoid inter-pulse crosstalk; for non-RZ format, the upsampling factor is equal to the single pulse length. Then, linearly convolve the baseband sequence with the single pulse signal to obtain the final coded pulse sequence. This sequence is the drive signal loaded onto phase modulator 3.

[0039] Its decoding principle is implemented according to the following steps: Step 1: The OSBPC drive pulse generated by the optical pulse encoder 14 acts on the phase modulator 3 to perform binary phase encoding modulation on the probe light. This modulated pulse is then cut into an encoded pulse train by the acousto-optic modulator 4, amplified by the optical amplifier 5, and injected into the single-mode sensing fiber 24. Due to the gain saturation effect of the optical amplifier 5, the actual encoded optical pulse sequence injected into the fiber exhibits a non-uniform amplitude envelope, which is determined by the transient response characteristics of the amplifier.

[0040] The actual injected coded optical pulse sequence is measured at the fiber input end, the energy of each optical pulse is extracted, and the amplitude envelope information of the baseband sequence is reconstructed. This measurement result serves as the basis for decoding.

[0041] The backscattered Rayleigh light is output through circulator 6 and coherently mixed with the local oscillator light in 90° optical mixer 7. The balanced detector 9 outputs orthogonal signals, which are sampled by data acquisition card 10 to obtain the coded fiber response. This response can be expressed as a linear convolution of the actual injected coded sequence and the fiber impulse response, with noise added.

[0042] The second step: The signal processing and decoding unit 11 performs a discrete Fourier transform on the encoded fiber response to obtain a frequency domain representation. Using the Fourier transform of the actually measured baseband sequence as the decoding function, frequency domain division is performed, followed by an inverse Fourier transform to obtain the decoded single-pulse response. This process recovers the distortion-free single-pulse response, while noise is shaped by the decoding function.

[0043] Because the OSBPC sequence has extremely low autocorrelation sidelobe characteristics after optimization by genetic algorithm, the decoding function is flat in the frequency domain and has no deep valleys. Therefore, the noise amplification effect is minimized, and the coding gain close to the theoretical upper limit is achieved.

[0044] Step 3: Location Information Extraction The decoded high signal-to-noise ratio single pulse response is input to the positioning and calculation server 12. Through the phase demodulation algorithm, the continuous position information of the pig 23 along the gas pipeline 34 is extracted in real time and uploaded to the host computer monitoring platform 13 for display.

[0045] In this application, by integrating a signal modulation unit 22 on the pig 23 to emit broadband acoustic waves, and utilizing the frequency-selective response characteristics of the acoustic resonant cavity, combined with the multi-point sensing capability of the fiber optic node monitoring array 31 at the junction, the pig 23 can determine the path at complex pipeline junctions. The specific principle is as follows: First, the first acoustic resonant cavity device 26 and the second acoustic resonant cavity device 27, as passive frequency encoders, are essentially acoustic resonant structures with specific inherent frequencies. According to the principle of acoustic resonance, when the incident sound wave frequency matches the inherent frequency of the cavity, the cavity resonates, generating significantly enhanced resonant sound waves; when the incident sound wave frequency deviates from the inherent frequency, the cavity response is weak. Based on this principle, this application designs resonant cavities with unique resonant frequencies for each branch: a first branch resonant frequency fA and a second branch resonant frequency fB. Sufficient intervals are left between the resonant frequencies of each branch to ensure easy differentiation during spectrum analysis.

[0046] Secondly, the signal modulation unit 22 integrated on the pig 23 continuously emits broadband sound waves into the gas pipeline 34. These broadband sound waves cover the resonant frequency range of all branch resonant cavities, and can effectively excite the resonant cavity of any branch the pig 23 enters to resonate.

[0047] Secondly, the fiber optic node monitoring array 31 at the branch intersection deploys multiple monitoring probes in different directions at the intersection. Each monitoring probe forms a localized sensitivity enhancement area through a wound coil. If the pig 23 enters the main road, it does not enter any branch, and no resonant cavity is excited. Each monitoring probe only senses the broadband acoustic background emitted by the pig 23 itself, with no significant resonance peak in the spectrum. If the pig 23 enters the first branch, the broadband acoustic wave emitted by the pig 23 excites the resonant cavity at the entrance of the first branch, generating a resonant signal with a frequency of fA. This resonant signal propagates through the pipe wall and is sensed by the wound coil of the first branch monitoring probe 29. Since the resonant cavity is located at the entrance of the first branch and the first branch monitoring probe 29 is adjacent to this location, the resonant signal intensity sensed by the first branch monitoring probe 29 is the largest, while the signals sensed by other monitoring probes are weaker or have no resonance. Similarly, if the pig 23 enters the second branch, it excites the resonant cavity of the second branch, generating a resonant signal with a frequency of fB, which is sensed by the second branch monitoring probe 30.

[0048] The signals collected by each monitoring probe are returned through the same main optical fiber single-mode sensing fiber 24. Since the lengths of the branch optical fibers are different, the signals are naturally separated in the time domain. The signal processing and decoding unit 11 can extract the vibration waveforms of each monitoring probe according to the distance window.

[0049] Finally, the branch intersection discrimination unit 18 receives the vibration waveforms of each monitoring probe output by the signal processing and decoding unit 11 and executes the following discrimination process: the spectrum analysis module 16 performs Fourier transform on the signals of each monitoring probe, converts the time-domain waveform into a spectrum, and extracts the significant peak frequencies in the spectrum; since the resonance signal intensity is much higher than the broadband background, the spectrum will show obvious single-peak characteristics; the path matching module 17 identifies the main peak frequency in the spectrum of each monitoring probe and compares it with the preset branch resonance frequency library. If none of the monitoring probes have significant resonance peaks, it is determined that the pig 23 has entered the main road; if the spectrum of the first branch monitoring probe 29 shows a resonance peak of frequency fA and this peak does not exist or has a significantly lower intensity in the spectrum of other monitoring probes, it is determined that the pig has entered the first branch; if the spectrum of the second branch monitoring probe 30 shows a resonance peak of frequency fB, it is determined that the pig 23 has entered the second branch. The discrimination results are uploaded to the host computer monitoring platform 13 via the path discrimination server 19 and displayed in fusion with the positioning information.

[0050] In some embodiments, the optimized short binary phase coding sequence is obtained by the pulse coding optimization module 15 through an intelligent optimization algorithm to achieve extremely low autocorrelation sidelobe characteristics. Only a single transmission is required to achieve high-precision positioning through matched filtering decoding, which solves the drawback of traditional coding requiring multiple measurements. While maintaining high spatial resolution, it significantly improves the system position update rate, achieving a unity of high spatial resolution, high signal-to-noise ratio and high measurement update rate, and meeting the real-time dynamic tracking requirements of the pig 23 under high-speed movement.

[0051] In some embodiments, the acoustic resonant cavity device is a cavity structure made of metal material, which is fixedly installed on the inner or outer wall of the pipe at the branch inlet. Its resonant frequency is determined by the geometry of the cavity, and there is sufficient interval between the resonant frequencies of each branch to facilitate differentiation.

[0052] In some embodiments, the signal processing and decoding unit 11 performs matched filtering decoding to obtain a distance-time complex signal matrix and demodulates the vibration phase waveform at each position; at the same time, based on the current position of the pig 23 provided by the positioning calculation server 12, it extracts the vibration waveform of the corresponding time window, extracts multi-dimensional vibration features, inputs them into a pre-trained state recognition model, and outputs the current operating state of the pig 23.

[0053] In some embodiments, the host computer monitoring platform 13 displays the location trajectory of the pig 23 in real time and uses different colors or icons to indicate its operating status and path. When an abnormal state is detected or the pig accidentally enters a branch, an early warning is automatically issued.

[0054] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A pulse-code fiber optic acoustic wave sensing system for tracking and locating gas pipeline pigs, characterized in that: The system includes a pig (23) installed in the gas pipeline (34), a main road monitoring probe (28), branch monitoring probes installed on the branch lines of the pipeline, a branch fiber optic node monitoring array (31) located at key locations at the branch intersections of the gas pipeline (34), and a single-mode sensing fiber (24) laid along the gas pipeline (34). The pig (23) is equipped with a signal modulation unit (22); a coherent detection structure is connected to the single-mode sensing fiber (24); the branch fiber optic node monitoring array (31) is constructed by connecting the single-mode sensing fiber (24) to a 1×N optical splitter (2). 5) Branch formation, including main road monitoring branches extending along the main road and branch monitoring branches extending along the entrance of each pipeline branch. Each monitoring branch is equipped with a monitoring probe, and each pipeline branch entrance is equipped with an acoustic resonant cavity device. Each pipeline branch acoustic resonant cavity device has a unique and different resonant frequency. When the pig enters a certain pipeline branch, it continuously emits broadband sound waves to the gas pipeline (34) through the signal modulation unit (22) to excite the corresponding acoustic resonant cavity device to generate resonance. The resonant frequency is identified through spectrum analysis to achieve accurate identification of the branch path. Based on the principle of phase-sensitive optical time-domain reflectometry (Φ-OTDR), the system adopts optimized short binary phase coding (OSBPC) and coherent detection structure, and uses a single single-mode sensing fiber (24) as a distributed sensing medium to achieve high-precision positioning of the acoustic wave signal generated by the movement of the pig (23).

2. The pulse-coded fiber optic acoustic wave sensing system for tracking and locating a gas pipeline pig according to claim 1, characterized in that: The coherent detection structure includes a narrow linewidth laser (1), a first coupler (2), a phase modulator (3), an acousto-optic modulator (4), an optical amplifier (5), a circulator (6), a 90° optical mixer (7), a second coupler (8), a balanced detector (9), a data acquisition card (10), a signal processing and decoding unit (11), a positioning calculation server (12), a host computer monitoring platform (13), an optical pulse code generator (14), a pulse code optimization module (15), a fork in the road discrimination unit (18), and a path discrimination server (19). The narrow linewidth laser (1) outputs continuous laser light, which is split into probe light and local oscillator light by the first coupler (2). The probe light enters the phase modulator (3), and the local oscillator light enters the second coupler (8). The optical pulse code generator (14) generates optimized short binary phase code OSBPC driving pulses under the configuration of the pulse code optimization module (15), which act on the phase modulator (3) to perform binary phase code modulation on the probe light. The coded light output from the phase modulator (3) enters the acousto-optic modulator (4) and is cut into a coded pulse train. After being amplified by the optical amplifier (5), the coded pulse train is injected into the single-mode sensing fiber (24) laid along the gas pipeline (34) through the input end a of the circulator (6). The backscattered Rayleigh light enters the 90° optical mixer (7) through the output end c of the circulator (6) and is coherently mixed with the local oscillator light. The output of the 90° optical mixer (7) is connected to the balanced detector (9), converted into an electrical signal, and then synchronously sampled by the data acquisition card (10). The acquired digital signal is sent to the signal processing and decoding unit (11) to perform matched filtering decoding and recover the single pulse response with a high signal-to-noise ratio. The decoded data is sent to the positioning calculation server (12), which extracts the continuous position information of the pig (23) in real time through the phase demodulation algorithm and uploads it to the host computer monitoring platform (13) for display.

3. The pulse-coded fiber optic acoustic wave sensing system for tracking and locating a gas pipeline pig according to claim 2, characterized in that: The pulse coding optimization module (15) uses an aperiodic coding optimization method based on distributed genetic algorithm to generate optimized short binary phase code OSBPC. The generation principle is implemented in the following steps: determine the duration of the single pulse signal according to the required spatial resolution, and set the gain saturation limit of the energy enhancement factor of the light amplifier (5); define the coding sequence length parameter to be 3 to 4 times the energy enhancement factor, thereby determining the total number of bits of the binary sequence; With the goal of minimizing the noise scaling factor, a distributed genetic algorithm is used to search for the optimal 0 / 1 distribution; the obtained optimal sequence is upsampled and convolved with a single pulse signal to generate the OSBPC driving pulse that is finally loaded onto the phase modulator (3).

4. The pulse-coded fiber optic acoustic wave sensing system for tracking and locating a gas pipeline pig according to claim 3, characterized in that: The signal processing and decoding unit (11) performs matched filtering decoding. First, it measures the influence of the transient response of the optical amplifier (5) on the amplitude envelope of the actual injected fiber. Based on this, it constructs a decoding function, performs division in the frequency domain, and then performs inverse transformation to obtain a distortion-free single pulse response.

5. The pulse-coded fiber optic acoustic wave sensing system for tracking and locating a gas pipeline pig according to claim 4, characterized in that: The signal processing and decoding unit (11) can also extract the vibration waveform of the corresponding time window according to the current position of the pig (23), extract multi-dimensional features and input them into the status recognition model, and output the running status of the pig (23).

6. The pulse-coded fiber optic acoustic wave sensing system for tracking and locating a gas pipeline pig according to claim 1, characterized in that: The fiber lengths from the 1×N optical splitter (25) to each monitoring probe are different for each monitoring branch, in order to ensure the differentiation of backscattered signals in the time domain.

7. The pulse-coded fiber optic acoustic wave sensing system for tracking and locating a gas pipeline pig according to claim 6, characterized in that: The signals collected by each monitoring probe are returned through the same main optical fiber single-mode sensing fiber (24). The lengths of the optical fibers of each monitoring branch are different, and the signals are naturally separated in the time domain. The signal processing and decoding unit (11) extracts the vibration waveforms of each monitoring probe according to the distance window.

8. The pulse-coded fiber optic acoustic wave sensing system for tracking and locating a gas pipeline pig according to claim 7, characterized in that: The intersection discrimination unit (18) includes a spectrum analysis module (16) and a path matching module (17). The spectrum analysis module (16) performs Fourier transform on the vibration waveform of each monitoring probe and extracts the significant peak frequency in the spectrum. The path matching module (17) compares the peak frequency with the preset branch resonant frequency library to determine whether the pig (23) is on the main road of the gas pipeline (34) or a certain branch of the pipeline.

9. The pulse-coded fiber optic acoustic wave sensing system for tracking and locating a gas pipeline pig according to claim 1, characterized in that: The acoustic resonant cavity device is a cavity structure made of metal, which is fixedly installed on the inner or outer wall of the pipe at the inlet of the pipe branch. Its resonant frequency is determined by the geometric dimensions of the cavity, and there is sufficient interval between the resonant frequencies of each pipe branch to facilitate differentiation.

10. The pulse-coded fiber optic acoustic wave sensing system for tracking and locating a gas pipeline pig according to claim 1, characterized in that: The signal modulation unit (22) includes a signal generator (20) and an acoustic transducer (21). The signal generator (20) generates a wideband electrical signal, which is converted into a wideband acoustic signal by the acoustic transducer (21) and continuously emitted into the gas pipeline (34).

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