Pipeline pig positioning method, system and medium based on distributed optical fiber

Abstract

A method, system and medium for locating a pipe cleaner based on distributed optical fiber, the method comprising the following steps: obtaining an estimated position of the pipe cleaner and a vibration signal of the pipeline at the current moment; based on the estimated position, calculating a first probability that the pipe cleaner is located at each position of the pipeline; based on the vibration signal, calculating at least one second probability that the pipe cleaner is located at each position of the pipeline; according to the first probability and at least one second probability, obtaining a total probability that the pipe cleaner is located at each position of the pipeline, determining the position with the largest total probability as the positioning position of the pipe cleaner at the current moment, and using the positioning position at the current moment as the estimated position of the pipe cleaner at the next moment. The present invention can locate the pipe cleaner based only on the data at the current moment, shortening the data collection cycle, and without the need for image processing, greatly reducing the amount of calculation, being able to quickly determine the location of the pipe cleaner, and significantly improving the efficiency of searching for the blocked position of the pipe cleaner.

Description

Technical Field

[0001] The present invention relates to the technical field of pipe cleaning device positioning, and in particular to a pipe cleaning device positioning method, system and medium based on distributed optical fiber. Background Art

[0002] Pipe cleaning plays a vital role in the commissioning and operation of oil and gas pipelines. This process not only improves fluid flow rate and production efficiency, but also helps reduce corrosion in the pipeline, ensures production safety, reduces maintenance costs, implements online monitoring, and extends the service life of the pipeline. However, when the pig is stuck somewhere in the pipeline and it is difficult to locate it quickly, it will not only hinder the normal flow of oil and gas, but also threaten the safety of the pipeline. Therefore, it is particularly important to effectively track and locate the pig during the pig cleaning process.

[0003] At present, the main methods for monitoring the cleaning process of oil and gas pipelines include radioactive labeling, mechanical detection, ultrasonic positioning, differential pressure detection, electromagnetic pulse tracking, and distributed optical fiber positioning. Among them, the working principle of using distributed optical fiber vibration sensing technology to track and locate pipe cleaners is based on the principle of coherent Rayleigh scattering. The optical fiber in the optical cable laid in the same trench of the pipeline is used to collect the vibration signals generated by the friction with the oil and gas pipeline wall and the impact on the weld during the movement of the pipe cleaner, and then locate the position of the pipe cleaner. Since the amplitude difference between the vibration signal of the pipe cleaner and the background noise is small, and there is uncertainty in the external environment, the amplitude of the vibration signal generated at the location of the pipe cleaner at a certain moment is not necessarily the maximum amplitude of the vibration signal of the entire pipeline.

[0004] Therefore, the prior art mainly calculates the position of the pipe cleaner based on the vibration signal within a period of time. For example, patent CN110375840A discloses a method for tracking and positioning a pipe cleaner based on distributed optical fiber sensing, which splices the vibration signals obtained at each moment to obtain a full-segment vibration signal matrix, performs binarization, Hough transform and other processing on the full-segment vibration signal matrix to draw an optical fiber vibration data image, and then processes the optical fiber vibration data image to obtain the position of the pipe cleaner within a period of time. However, since this type of method needs to obtain a vibration signal within a period of time, such as 20 seconds, to produce an optical fiber vibration data image, it is impossible to obtain the position of the pipe cleaner in real time based on each moment, and the data acquisition cycle is relatively long; in addition, after obtaining the optical fiber vibration data image, a series of image processing is required, which has a large amount of calculation and is also not conducive to obtaining the position of the pipe cleaner in real time. Summary of the invention

[0005] One object of the present invention is to provide a pipe cleaner positioning method based on distributed optical fiber. The method calculates the probability of the pipe cleaner being at various positions on the pipeline at the current moment based on the estimated position information of the pipe cleaner and the vibration signals at various moments, and determines the position of the pipe cleaner at the current moment based on a voting mechanism. There is no need to perform analysis based on vibration signals over a period of time, which greatly reduces the amount of data calculation and realizes real-time and efficient monitoring of the position of the pipe cleaner at various moments.

[0006] The present invention is achieved through the following technical solutions:

[0007] The method for positioning a pipe cleaner based on distributed optical fiber comprises the following steps:

[0008] Obtain the estimated position of the pig and the vibration signal of the pipeline at the current moment;

[0009] Based on the estimated position, calculating a first probability that the pig is located at each position of the pipeline;

[0010] Calculating at least one second probability that the pig is located at each position of the pipeline based on the vibration signal;

[0011] According to the first probability and at least one second probability, the total probability of the pipe cleaner being located at each position of the pipeline is obtained, the position with the largest total probability is determined as the positioning position of the pipe cleaner at the current moment, and the positioning position at the current moment is used as the estimated position of the pipe cleaner at the next moment.

[0012] In the present technical solution, it is first necessary to obtain the estimated position of the pipe cleaner and the vibration signal at the current moment. The estimated position can be estimated based on the starting position of the pipe cleaner, or it can be the positioning position of the pipe cleaner calculated at the previous moment. In one or more embodiments, the estimated position of the pipe cleaner can be roughly estimated based on the starting position and moving speed of the pipe cleaner. In one or more embodiments, the estimated position of the pipe cleaner can also be set to 0, or other possible values, and the probability of the pipe cleaner moving to each position within a certain distance range from the estimated position is calculated. The vibration signal of the pipeline is collected by the sensing optical fiber laid in the same trench as the pipeline, and the vibration signal used is the vibration signal of all monitoring units contained in the sensing optical fiber on the pipeline at the current moment.

[0013] In this technical solution, the first probability of the pipe cleaner appearing at various positions in the pipeline at the current moment can be calculated based on the estimated position. For example, the probability of the pipe cleaner appearing between the estimated position and a certain point in the direction of the pipe cleaner's advance can be calculated using the Beta distribution. At the same time, based on the vibration signal, the vibration signal can be transformed in a variety of ways to calculate the probability of the pipe cleaner appearing at various positions in its forward direction based on the mutation of the vibration signal. In some embodiments, the signal mutation position of the vibration signal can be calculated based on methods such as wavelet transform and Fourier transform.

[0014] In this technical solution, after obtaining the first probability calculated based on the estimated position and one or more second probabilities calculated based on the vibration signal, a voting mechanism is used to determine the total probability that a pipe cleaner exists at each position point in the forward direction of the estimated position. The total probability obtained is determined as the location of the pipe cleaner at the current moment, and the location can also be used as the estimated position of the pipe cleaner at the next moment.

[0015] In the technical scheme, the probability of the pipe cleaner at each position on its route is calculated based on the two types of data obtained, namely the position information and the vibration signal. Then, the various probabilities are combined and a voting mechanism is used to determine the total probability of the pipe cleaner. The pipe cleaner can be located based only on the data at the current moment, thus shortening the data collection cycle. In addition, the method does not require image processing, greatly reducing the amount of calculation, and can quickly determine the position of the pipe cleaner, significantly improving the efficiency of searching for the blocked position of the pipe cleaner.

[0016] Furthermore, the first probability is calculated using Beta distribution:

[0017]

[0018] P Beta =P′ Beta / max(P′ Beta )

[0019] Among them, n e is the estimated position, n is any position of the pig within a distance F along its moving direction starting from the estimated position, α and β are Beta distribution parameters, and u is the integral variable.

[0020] In this technical solution, the estimated position n e It can be determined by combining the starting position and speed of the pipe cleaner, or it can be set to 0 or other possible values, or the location of the pipe cleaner at the last moment can be used. Use Beta distribution to search for the position of the pipe cleaner and calculate the estimated position n of the pipe cleaner e To any position within the range of the pig's advance distance F. In some embodiments, the distance F can be set to 1000-3000 meters. Then, the probability distribution of the pig at the current moment is normalized, that is, the first probability P is obtained. Beta .

[0021] As a preferred implementation of the present invention, at least one of discrete wavelet transform, short-time Fourier transform and Wigner quasi-probability distribution is used to calculate the second probability that the pig is located at each position of the pipeline.

[0022] In the present technical solution, any one of discrete wavelet transform, short-time Fourier transform and Wigner quasi-probability distribution is used to process the vibration signal to obtain the second probability of the pipe cleaner appearing at various positions in the pipeline. Among them, the discrete wavelet transform has a dynamically adjustable resolution and can effectively analyze the local characteristics of the vibration signal; the short-time Fourier transform has a stronger analysis ability for non-stationary vibration signals and can better handle signals with large amplitude changes; and the Wigner quasi-probability distribution has a better processing ability for random vibration signals. In some preferred embodiments, the discrete wavelet transform, short-time Fourier transform and Wigner quasi-probability distribution are respectively used to calculate the signal mutation position of the vibration signal to further obtain three different second probabilities, which can not only maintain a low amount of calculation, but also better process the vibration signal to obtain a second probability with higher reliability.

[0023] Furthermore, the formula for calculating the second probability using discrete wavelet transform is:

[0024]

[0025] P wavelet =P′ wavelet / max(P′ wavelet )

[0026] Among them, a is the scale parameter, b is the displacement parameter, ψ is the complex conjugate of the wavelet function, N is the length of the signal, x is the vibration signal, and n is the index is the discrete position index of the pipeline, N a The number of scales chosen for the wavelet transform.

[0027] In this technical solution, discrete wavelet transform is used to calculate the signal mutation position of the vibration signal. After discrete wavelet transform, the wavelet transform results W(a j ,b) Take the square modulus and sum it to get P′ wavelet , and then P′ wavelet A normalization process is performed to obtain a second probability that the pipe cleaner is located at each position in the forward direction.

[0028] Furthermore, the formula for calculating the second probability using short-time Fourier transform is:

[0029]

[0030] P stft =P′ stft / max(P′ stft )

[0031] Among them, n index is the discrete position index of the pipeline, w is the window function, N stftis the window length, L is the step length between frames, x is the vibration signal, m is the integral variable, and the discrete frequency k is the frequency index, i is an imaginary number, N k is the number of frequency indices.

[0032] In this technical solution, short-time Fourier transform is used to calculate the signal mutation position of the vibration signal. index ,ω k ) is the position n index and frequency ω k Similarly, after the short-time Fourier transform, the derivative of the result is taken and the square modulus is summed, and then the result of each position is normalized to obtain a second probability that the pipe cleaner is located at each position in the forward direction.

[0033] Furthermore, the formula for calculating the second probability using Wigner quasi-probability distribution is:

[0034]

[0035] P wv =P′ wv / max(P′ wv )

[0036] Among them, n index is the discrete position index of the pipeline, x is the vibration signal, k′ is the discrete frequency index, N wv is the total number of samples.

[0037] In this technical solution, the Wigner quasi-probability distribution is used to calculate the signal mutation position of the vibration signal. Similarly, after the Wigner quasi-probability distribution transformation, the calculation result is derived and the square modulus is summed, and then the results of each position are normalized to obtain a second probability that the pipe cleaner is located at each position in the forward direction.

[0038] In this technical solution, the second probability uses the discrete position index n of the entire pipeline at the current moment. index When the pipe cleaner moves to a distance outside F, for example, to a position F+100 meters away from the estimated position, one or more second probabilities based on the pipeline discrete position index, after combining with the first probability, can make the total probability form a peak outside the distance F, which is conducive to more accurate positioning of the position of the pipe cleaner, and is also conducive to quickly correcting the estimated position or distance F, further improving the accuracy of positioning. In some embodiments, in order to save calculation amount, the pipeline discrete position index n in the second probability index It can also be replaced by the pig position n for calculation.

[0039] Further, the geometric mean of the first probability and at least one second probability is calculated to obtain the total probability that the pig is located at each position of the pipeline. After obtaining the first probability and at least one second probability, the geometric mean is calculated based on the first probability and the second probability to obtain the total spatial probability distribution along the length direction of the pipeline at the current moment, and the position with the largest total probability is selected as the positioning position of the pig at the current moment.

[0040] The present invention also provides a pig positioning system based on distributed optical fiber, the system comprising:

[0041] Distributed optical fiber, used to collect vibration signals from pipelines;

[0042] An input unit, used to input an estimated position of the pig and a vibration signal of the pipeline at the current moment;

[0043] an analysis unit, calculating a first probability that the pipe pig is located at each position of the pipeline based on the estimated position, calculating at least one second probability that the pipe pig is located at each position of the pipeline based on the vibration signal, calculating a total probability that the pipe pig exists at each position of the pipeline according to a geometric mean of the first probability and at least one second probability, determining a position with the largest total probability as the positioning position of the pipe pig at a current moment, and using the positioning position at the current moment as the estimated position of the pipe pig at a next moment;

[0044] The output unit outputs the positioning position of the pipe cleaning device at the current moment.

[0045] Furthermore, at least one method selected from discrete wavelet transform, short-time Fourier transform and Wigner quasi-probability distribution is used to calculate the second probability that the pig is located at each position of the pipeline.

[0046] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of any of the aforementioned distributed optical fiber-based pipe cleaner positioning methods are implemented.

[0047] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0048] 1. The present invention calculates the probability of each position of the pipe cleaner on its forward route based on the acquired position information and vibration signal data, and then combines various probabilities to determine the total probability of the pipe cleaner by a voting mechanism. The pipe cleaner can be located only based on the data at the current moment, shortening the data collection cycle. In addition, the method does not require image processing, greatly reducing the amount of calculation, and can quickly determine the location of the pipe cleaner, significantly improving the efficiency of searching for the blocked position of the pipe cleaner;

[0049] 2. The present invention calculates the signal mutation position of the vibration signal based on discrete wavelet transform, short-time Fourier transform and Wigner quasi-probability distribution to further obtain three different second probabilities, which can not only maintain a low amount of calculation, but also better process the vibration signal to obtain a second probability with higher reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of this application, and do not constitute a limitation of the embodiments of the present invention. In the drawings:

[0051] Figure 1 is a flowchart of a positioning method in a specific embodiment of the present invention;

[0052] Figure 2 The positioning result of the pipeline cleaning device in Example 4 of the present invention at a certain moment is shown, wherein (a) is the vibration signal of the entire pipeline at the current moment, (b) is the distribution of the first probability calculated by Beta distribution, (c) is the distribution of the second probability calculated by discrete wavelet transform, (d) is the distribution of the second probability calculated by short-time Fourier transform, (e) is the distribution of the second probability calculated by Wigner quasi-probability distribution, and (f) is the total probability distribution along the entire pipeline at the current moment;

[0053] Figure 3 The positioning result of the pipeline cleaning device in Example 5 of the present invention at a certain moment is shown, wherein (a) is the vibration signal of the entire pipeline at the current moment, (b) is the distribution of the first probability calculated by Beta distribution, (c) is the distribution of the second probability calculated by discrete wavelet transform, (d) is the distribution of the second probability calculated by short-time Fourier transform, (e) is the distribution of the second probability calculated by Wigner quasi-probability distribution, and (f) is the total probability distribution along the entire pipeline at the current moment;

[0054] Figure 4 The moving track of the pipe cleaning device in Example 5 of the present invention within a certain period of time is shown. DETAILED DESCRIPTION

[0055] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with embodiments and drawings. The exemplary embodiments of the present invention and their description are only used to explain the present invention and are not intended to limit the present invention.

[0056] In the description of the present invention, it should be understood that the terms "front", "rear", "left", "right", "up", "down", "vertical", "horizontal", "high", "low", "inside", "outside", etc., indicating directions or positional relationships are based on the directions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore should not be understood as limiting the scope of protection of the present invention.

[0057] Embodiment 1:

[0058] like Figure 1 The pig positioning method based on distributed optical fiber shown includes the following steps:

[0059] Obtain the estimated position of the pig and the vibration signal of the pipeline at the current moment;

[0060] Based on the estimated position, calculating a first probability that the pig is located at each position of the pipeline;

[0061] Calculating at least one second probability that the pig is located at each position of the pipeline based on the vibration signal;

[0062] According to the first probability and at least one second probability, the total probability of the pipe cleaner being located at each position of the pipeline is obtained, the position with the largest total probability is determined as the positioning position of the pipe cleaner at the current moment, and the positioning position at the current moment is used as the estimated position of the pipe cleaner at the next moment.

[0063] In some embodiments, after obtaining the position of the pipe cleaner at each moment, the positioning result of the pipe cleaner within a certain time range can be constructed based on the time and the position of the pipe cleaner. In one or more embodiments, if the position of the pipe cleaner is not continuous in two or more adjacent calculations, it indicates that the pipe cleaner may be stuck.

[0064] In some preferred embodiments, Beta distribution is used to calculate the first probability:

[0065]

[0066] P Beta =P′ Beta / max(P′ Beta )

[0067] Among them, n e is the estimated position, n is any position of the pig within a distance F along its moving direction starting from the estimated position, α and β are Beta distribution parameters, and u is the integral variable.

[0068] In some embodiments, at least one of discrete wavelet transform, short-time Fourier transform, and Wigner quasi-probability distribution is used to calculate the second probability that the pig is located at each position of the pipeline.

[0069] In some preferred embodiments, discrete wavelet transform, short-time Fourier transform and Wigner quasi-probability distribution are used to calculate the signal mutation position of the vibration signal.

[0070] The formula for calculating the second probability using discrete wavelet transform is:

[0071]

[0072] P wavelet =P′ wavelet / max(P′ wavelet )

[0073] Among them, a is the scale parameter, b is the displacement parameter, ψ is the complex conjugate of the wavelet function, N is the length of the signal, x is the vibration signal, and n is the index is the discrete position index of the pipeline, N a The number of scales chosen for the wavelet transform.

[0074] The formula for calculating the second probability using short-time Fourier transform is:

[0075]

[0076] P stft =P′ stft / max(P′ stft )

[0077] Among them, n index is the discrete position index of the pipeline, w is the window function, N stft is the window length, L is the step length between frames, x is the vibration signal, m is the integral variable, and the discrete frequency k is the frequency index, i is an imaginary number, N k is the number of frequency indices.

[0078] The formula for calculating the second probability using Wigner quasi-probability distribution is:

[0079]

[0080] P wv =P′ wv / max(P′ wv )

[0081] Among them, n index is the discrete position index of the pipeline, x is the vibration signal, k′ is the discrete frequency index, N wv is the total number of samples.

[0082] In some preferred embodiments, a geometric mean of the first probability and at least one second probability is calculated to obtain a total probability that the pig is located at each position of the pipeline.

[0083] Taking the calculation of the first probability and the second probability using Beta distribution, discrete wavelet transform, short-time Fourier transform and Wigner quasi-probability distribution as an example, the total probability P is the geometric mean of the four probabilities:

[0084]

[0085] Embodiment 2:

[0086] The pig positioning system based on distributed optical fiber includes:

[0087] Distributed optical fiber, used to collect vibration signals from pipelines;

[0088] An input unit, used to input an estimated position of the pig and a vibration signal of the pipeline at the current moment;

[0089] an analysis unit, calculating a first probability that the pipe pig is located at each position of the pipeline based on the estimated position, calculating at least one second probability that the pipe pig is located at each position of the pipeline based on the vibration signal, calculating a total probability that the pipe pig exists at each position of the pipeline according to a geometric mean of the first probability and at least one second probability, determining a position with the largest total probability as the positioning position of the pipe pig at a current moment, and using the positioning position at the current moment as the estimated position of the pipe pig at a next moment;

[0090] The output unit outputs the positioning position of the pipe cleaning device at the current moment.

[0091] Furthermore, at least one method selected from discrete wavelet transform, short-time Fourier transform and Wigner quasi-probability distribution is used to calculate the second probability that the pig is located at each position of the pipeline.

[0092] Embodiment 3:

[0093] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the pig positioning method based on distributed optical fiber in any of the above embodiments are implemented.

[0094] In this embodiment, when implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the present invention implements all or part of the process in the above-mentioned embodiment method, and can also be stored in a computer-readable storage medium through a computer program. When the computer program is executed by the processor, the steps of each of the above-mentioned method embodiments can be implemented. Among them, the computer program includes computer program code, object code form, executable file or some intermediate form, etc. The computer-readable medium may include any entity or device that can carry the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory, random access memory, point carrier signal, telecommunication signal and software distribution medium, etc.

[0095] Embodiment 4:

[0096] This embodiment locates the position of the pipe cleaning device at a certain moment based on the aforementioned positioning method.

[0097] Specifically, Figure 2 (a) shows the vibration curve of the entire pipeline at a certain moment during the cleaning process. As shown in the figure, due to the uncertainty of the external environment of the pipeline, the amplitude of the vibration signal at the location of the cleaning device (in the red box) is not the maximum amplitude of the vibration signal of the entire pipeline.

[0098] like Figure 2 As shown in (b), the estimated position is set to 4680 meters. The first probability distribution is obtained by Beta distribution calculation. The closer to the estimated position, the higher the probability of the pipe cleaner appearing. Subsequently, the second probability is calculated by discrete wavelet transform, short-time Fourier transform and Wigner quasi-probability distribution, as shown in Figure 2 As shown in (c) to (e), there are certain differences in the three calculation methods based on vibration signals, and the obtained extreme points are different. Finally, by solving the geometric mean of the first probability and the three second probabilities, the spatial probability distribution diagram of the pig along the length of the pipeline at the current moment is obtained. At this moment, the probability that the pig is located at 4799 meters is the largest. Therefore, 4799 meters is determined as the pig positioning position at the current moment.

[0099] Embodiment 5:

[0100] This embodiment locates the position of the pipe cleaning device at a certain moment based on the aforementioned positioning method.

[0101] Specifically, Figure 3 (a) shows the vibration curve of the entire pipeline at a certain moment during the cleaning process. As shown in the figure, due to the uncertainty of the external environment of the pipeline, the amplitude of the vibration signal at the location of the cleaning device (in the red box) is also not the location where the maximum amplitude of the vibration signal of the entire pipeline is located.

[0102] like Figure 3 As shown in (b), the estimated position is set to 9790 meters, and the first probability distribution is obtained by Beta distribution calculation. The closer to the estimated position, the higher the probability of the pipe cleaner appearing. Subsequently, the second probability is calculated using discrete wavelet transform, short-time Fourier transform and Wigner quasi-probability distribution, as shown in Figure 3 As shown in (c) to (e), there are certain differences in the three calculation methods based on vibration signals, and the obtained extreme points are different. Finally, by solving the geometric mean of the first probability and the three second probabilities, the spatial probability distribution diagram of the pig along the length of the pipeline at the current moment is obtained. At this moment, the probability that the pig is located at 9857 meters is the largest. Therefore, 9857 meters is determined as the pig positioning position at the current moment.

[0103] Finally, if Figure 4 As shown, as time goes by, after calculating the positioning position of the pipe cleaning device at each moment, the movement trajectory of the pipe cleaning device during the pipe cleaning process is obtained.

[0104] The terms "first", "second", etc. (e.g., first probability, second probability, etc.) used in the present invention are only used to distinguish the corresponding components for the sake of clarity of description, and are not intended to limit any order or emphasize importance, etc. In addition, the term "connected" used in the present invention may be directly connected or indirectly connected via other components unless otherwise specified.

[0105] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A pipe cleaner positioning method based on distributed optical fiber, characterized in that: The following steps are involved: Obtain the estimated position of the pig and the vibration signal of the pipeline at the current moment; Based on the estimated position, calculating a first probability that the pig is located at each position of the pipeline; Calculating at least one second probability that the pig is located at each position of the pipeline based on the vibration signal; According to the first probability and at least one second probability, a total probability that the pig is located at each position of the pipeline is obtained, a position with the largest total probability is determined as the positioning position of the pig at the current moment, and the positioning position at the current moment is used as the estimated position of the pig at the next moment; The first probability is calculated using Beta distribution: P Beta =P′ Beta / max(P′ Beta ) Among them, n e is the estimated position, n is any position of the pig within a distance F along its moving direction starting from the estimated position, α and β are Beta distribution parameters, and u is the integral variable.

2. The method for locating a pipe cleaner based on distributed optical fiber according to claim 1, characterized in that: At least one of discrete wavelet transform, short-time Fourier transform and Wigner quasi-probability distribution is used to calculate the second probability that the pig is located at each position of the pipeline.

3. The method for locating a pipe cleaner based on distributed optical fiber according to claim 2, characterized in that: The formula for calculating the second probability using discrete wavelet transform is: P wavelet =P′ wavelet / max(P′ wavelet ) Among them, a is the scale parameter, b is the displacement parameter, ψ is the complex conjugate of the wavelet function, N is the length of the signal, x is the vibration signal, and n is the index is the discrete position index of the pipeline, N a The number of scales chosen for the wavelet transform.

4. The method for locating a pipe cleaner based on distributed optical fiber according to claim 2, characterized in that: The formula for calculating the second probability using short-time Fourier transform is: P stft =P′ stft / max(P′ stft ) Among them, n index is the discrete position index of the pipeline, w is the window function, N stft is the window length, L is the step length between frames, x is the vibration signal, m is the integral variable, and the discrete frequency k is the frequency index, i is an imaginary number, N k is the number of frequency indices.

5. The method for locating a pipe cleaner based on distributed optical fiber according to claim 2, characterized in that: The formula for calculating the second probability using Wigner quasi-probability distribution is: P wv =P′ wv / max(P′ wv ) Among them, n index is the discrete position index of the pipeline, x is the vibration signal, k′ is the discrete frequency index, N wv is the total number of samples.

6. The method for locating a pipe cleaner based on distributed optical fiber according to any one of claims 1 to 5, characterized in that: The geometric mean of the first probability and at least one second probability is calculated to obtain a total probability that the pig is located at each position of the pipeline.

7. A pig positioning system based on distributed optical fiber, characterized in that: The method for locating a pipe cleaner based on distributed optical fiber according to any one of claims 1 to 6 is adopted, and the system comprises: Distributed optical fiber, used to collect vibration signals from pipelines; An input unit, used to input an estimated position of the pig and a vibration signal of the pipeline at the current moment; an analysis unit, calculating a first probability that the pipe pig is located at each position of the pipeline based on the estimated position, calculating at least one second probability that the pipe pig is located at each position of the pipeline based on the vibration signal, calculating a total probability that the pipe pig exists at each position of the pipeline according to a geometric mean of the first probability and at least one second probability, determining a position with the largest total probability as the positioning position of the pipe pig at a current moment, and using the positioning position at the current moment as the estimated position of the pipe pig at a next moment; The output unit outputs the positioning position of the pipe cleaning device at the current moment.

8. The distributed optical fiber based pig positioning system according to claim 7, characterized in that: At least one of discrete wavelet transform, short-time Fourier transform and Wigner quasi-probability distribution is used to calculate the second probability that the pig is located at each position of the pipeline.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the pig positioning method based on distributed optical fiber are implemented as described in any one of claims 1 to 6.

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