Pipeline anti-excavation method and system based on optical fiber sensing

Abstract

The application discloses a pipeline anti-excavation method and system based on optical fiber sensing, and belongs to the technical field of pipeline anti-excavation. R ( k ) and the setting of the energy ratio and the barycenter frequency threshold value, accurately distinguishing and identifying whether the pipeline has the excavation behavior from two dimensions of the energy ratio and the barycenter frequency, the accuracy of the pipeline anti-excavation signal determination is high, and the false alarm rate is low; the sensor arranged on the underground pipeline collects the pipeline anti-excavation signal, the pipeline anti-excavation signal collected by the sensor is summarized and wired transmitted through the composite cable, the signal is not easily affected by the burial of the sensor, the loss of signal transmission and the burial interference are small, and the anti-interference capability is strong; the 4G / 5G module and the transmission module of the host module buried in the ground inspection well construct a wireless data transmission channel between the cloud server, without carrying out scattered point excavation or full-line excavation in some positions, installation, networking and monitoring are more convenient.

Description

Technical Field

[0001] This invention relates to the field of pipeline anti-excavation technology, and in particular to a pipeline anti-excavation method and system based on fiber optic sensing. Background Technology

[0002] With the continuous progress and development of modern society, energy such as oil, natural gas and domestic water are mainly transported through pipelines of various materials. The safe and stable operation of pipelines has become an important factor in social development. However, in actual pipeline operation, the greatest safety risk comes from pipeline damage caused by third-party construction, which leads to gas and liquid leaks. The consequences and disasters caused by this have brought huge losses to people's lives and property.

[0003] In current technologies, most operators rely on manual patrols or surveillance cameras for pipeline excavation prevention. A very small number have begun to experiment with sensor monitoring, but these all utilize noise recorders. Furthermore, acoustic sensors often experience high background noise due to the liquid inside the pipeline or external vibrations, resulting in significant overlap with the pipeline excavation prevention signal. Traditional algorithms struggle to distinguish between this signal and the background noise, leading to a high false alarm rate and low accuracy. Simultaneously, the low accuracy of acoustic sensors in acquiring pipeline excavation prevention signals further hinders accurate signal identification and precise location of excavation points.

[0004] Furthermore, while sensor arrays based on 4G / 5G modules for self-organizing network technology overcome the construction and maintenance problems of traditional distributed optical fiber requiring full-line pipeline excavation during installation, the integrated coupling design of the 4G / 5G module and sensor necessitates the formation of a self-organizing network sensor array among the sensors via the 4G / 5G module before vibration signals are collected and centrally uploaded. However, 4G / 5G self-organizing network sensor arrays installed on underground pipelines experience frequent offlineing due to signal shielding caused by burial. The integrated coupling of the 4G / 5G module and the sensor's anti-interference capability is also relatively poor. Additionally, during the maintenance and repair of traditional distributed optical fiber sensors, battery replacement requires scattered excavation of all sensors along the pipeline or partial full-line excavation, resulting in high maintenance costs for sensor battery replacement and repair.

[0005] Therefore, the purpose of this invention is to provide a pipeline anti-excavation method and system based on fiber optic sensing, which improves the energy ratio of the pipeline anti-excavation algorithm. R ( kBy setting the energy ratio and center-of-gravity frequency threshold, the presence of excavation activity in the pipeline can be accurately distinguished and identified from two dimensions: energy ratio and center-of-gravity frequency. The accuracy of pipeline anti-excavation signal determination is high, and the false alarm rate is low. Pipeline anti-excavation signals are collected by sensors installed on underground pipelines and transmitted via a composite cable. The signals are less affected by the burial of the sensors, resulting in minimal signal transmission loss and ground interference, and strong anti-interference capabilities, overcoming the technical problem of frequent sensor offline occurrences. Furthermore, a wireless data transmission channel is established between the main unit module (4G / 5G module and transmission module) buried in the ground inspection well and the cloud server, eliminating the need for scattered excavation or partial full-line excavation, making installation, networking, and monitoring more convenient. Summary of the Invention

[0006] To address the aforementioned problems, a method and system for preventing pipeline excavation based on fiber optic sensing is provided. This method utilizes the energy ratio of the pipeline excavation prevention algorithm. R ( k The system accurately distinguishes and identifies whether there is excavation activity in the pipeline by using the center of gravity frequency. The accuracy of pipeline excavation prevention signal judgment is high and the false alarm rate is low. The pipeline excavation prevention signal is collected by sensors installed on the underground pipeline. The pipeline excavation prevention signal collected by the sensors is collected and transmitted via a composite cable. The signal transmission loss and buried interference are small and the anti-interference capability is strong. The 4G / 5G module and transmission module of the host module buried in the ground inspection well form a wireless data transmission channel between the host module and the cloud server. There is no need to carry out scattered excavation or partial full-line excavation. The installation, networking and monitoring are more convenient.

[0007] To achieve the above objectives, the technical solution adopted by the present invention is: a pipeline anti-excavation algorithm, comprising the following steps.

[0008] Step 1: The anti-dig signal for the pipeline picked up by the sensor. x ( i Select a sliding long-time window, and set a short-time window within the long-time window. The endpoints of the long-time window and the short-time window coincide. Calculate the energy of the long-time window separately. E L and short window energy E S : in, S The length of the short time window; L The length of the long window; i Sampling time; x ( i ) indicates the first i The sampled value of the pipeline anti-excavation signal at the sampling time;k For the first sample k One point; Step 2: Calculate the energy ratio of the short window to the long window. R ( k )= E S / E L ; Step 3: Send the pipeline anti-excavation signal x ( i Perform a Fourier transform to obtain the Fourier transform coefficients. X ( f i ); Step 4: Calculate the centroid frequency of the pipeline anti-excavation signal f c in, i Sampling time; f i Indicates the first i A discrete frequency point; X ( f i () represents the Fourier transform coefficients; N This represents the number of sampling points; Step 5: The energy ratio of the short-time window to the long-time window of the pipeline anti-excavation signal R ( k If the value is greater than the set threshold and the center of gravity frequency is less than 200, it is determined that there is excavation activity in the pipeline, and an alarm is triggered and sent; otherwise, it is determined that there is no excavation activity in the pipeline, and no alarm is triggered.

[0009] Preferably, the formula for the Fourier transform in step 3 is as follows: in, N This represents the number of sampling points; j The imaginary unit; i Sampling time; x ( i ) indicates the first i The sampled value of the pipeline anti-excavation signal at the sampling time; f i Indicates the first i A discrete frequency point.

[0010] Preferably, when the threshold value in step 5 is set to 2.5, the corresponding short window length is... S The duration is 40ms, which is the length of the long window. L It takes 120ms.

[0011] A pipeline anti-excavation system based on fiber optic sensing includes sensors for picking up pipeline anti-excavation signals, a host module, a composite cable for information transmission between the sensors and the host module, and a cloud server. The host module includes a 4G / 5G module for sending and receiving signals, a transmission module, and a GPS module for uploading the sensor's own location information. The sensors are interferometric fiber optic sensors. The sensors are sequentially deployed on the pipeline to be tested buried underground, and the sensors are connected to the host module in a surface inspection well via the composite cable.

[0012] Preferably, the pipeline anti-excavation signal collected by the sensor is output to the host module via a composite cable. The host module receives and demodulates the signal, and then outputs it to the cloud server via a 4G / 5G module. The cloud server determines whether excavation behavior exists based on the pipeline anti-excavation algorithm. If excavation behavior exists, an alarm is triggered and an alarm message is sent; if no excavation behavior exists, no alarm is triggered.

[0013] Preferably, the host module further includes a battery and a power cable for powering each sensor.

[0014] Preferably, the battery is a rechargeable, replaceable lithium battery.

[0015] A method for applying the aforementioned pipeline anti-excavation system, characterized by comprising the following steps: Step S1: Determine the area of ​​the pipeline to be tested, including the length and direction of the pipeline, the number and distribution of manholes, and the spacing between manholes; Step S2: Based on the characteristics of the pipeline, the sensor is installed on the pipeline to be tested, and the main unit module is installed in the inspection well above the area of ​​the pipeline to be tested. The distance between two adjacent sensors is ≤200m. Step S3: The sensors on the pipeline under test are activated and upload their own location information to the host module via the GPS module and composite cable. The transmission module in the host module receives and summarizes the information and then uploads it to the cloud server via the 4G / 5G module. Step S4: The cloud server sends a data acquisition command to the host module deployed in the inspection well via the 4G / 5G module. The 4G / 5G module of the host module receives the data acquisition command and outputs it to each sensor on the pipeline under test via the transmission module and composite cable in sequence. Step S5: The sensor picks up the pipeline anti-excavation signal according to the acquisition command in step S4. The pipeline anti-excavation signal is output to the host module via a composite cable. After being received and demodulated by the transmission module in the host module, it is uploaded to the cloud server via the 4G / 5G module. Step S6: The cloud server calculates and identifies the uploaded pipeline anti-excavation signal based on the pipeline anti-excavation algorithm to determine whether there is any excavation activity in the pipeline area to be tested; Step S7: If it is determined that there is excavation activity, an alarm is triggered and an alarm message is sent; if it is determined that there is no excavation activity, return to step S5 and do not trigger an alarm.

[0016] Preferably, the acquisition command in step S4 includes real-time continuous signal acquisition or signal acquisition for a set specific time period.

[0017] By adopting the above technical solution, the present invention has the following beneficial effects.

[0018] (1) The energy ratio of the pipeline anti-excavation algorithm of this invention R ( k By setting the energy ratio and center of gravity frequency threshold, the existence of excavation behavior in the pipeline can be accurately distinguished and identified from two dimensions: energy ratio and center of gravity frequency. Compared with traditional noise recorders, the background noise of this invention is low, does not cover the pipeline excavation prevention signal, and has high accuracy in determining the pipeline excavation prevention signal with a low false alarm rate.

[0019] (2) This invention collects anti-excavation signals from underground pipelines using sensors installed on the pipelines. These signals are then aggregated and transmitted via a composite cable. The signals are less affected by the burial of the sensors, resulting in minimal signal transmission loss and interference. This provides strong anti-interference capabilities and overcomes the technical problem of frequent sensor offline occurrences. Furthermore, a wireless data transmission channel is established between the main unit module (4G / 5G module and transmission module) and the cloud server, which is embedded in the ground inspection well. This eliminates the need for scattered excavation or partial full-line excavation, making installation, networking, and monitoring more convenient.

[0020] (3) By employing an interferometric fiber optic sensing optical sensor, this invention achieves higher accuracy and sensitivity in the acquisition, identification, and positioning of pipeline anti-excavation signals, thereby improving monitoring accuracy. The battery in this invention is a rechargeable and removable lithium battery, which is installed in the inspection well in the pipeline area to be monitored, making the maintenance of the sensor battery more convenient. Attached Figure Description

[0021] The following provides a detailed discussion of the manufacture and application of preferred embodiments of the present invention. However, it should be understood that the present invention provides many applicable inventive concepts that can be embodied in various specific environments. The specific embodiments discussed are merely illustrative of specific ways of manufacturing and using the present invention and do not limit the scope of the invention. For those skilled in the art, other drawings can be obtained from these drawings without any creative effort.

[0022] Figure 1This is a flowchart of the algorithm of the present invention.

[0023] Figure 2 This is a schematic diagram of the structure of the present invention.

[0024] Figure 3 This is a schematic diagram of the fiber optic sensor used in this invention.

[0025] Among them, 1-sensor; 2-host module; 3-battery; 4-transmission module; 5-4G / 5G module; 6-GPS module; 7-composite cable; 8-power supply cable; 9-pipeline; 10-inspection well; 11-top cover; 12-base; 13-mass block; 14-modulation fiber optic; 15-metal film; 16-reference fiber optic; 17-neodymium magnet. Detailed Implementation

[0026] The following provides a detailed discussion of the manufacture and application of preferred embodiments of the present invention. However, it should be understood that the present invention provides many applicable inventive concepts that can be embodied in various specific environments. The specific embodiments discussed are merely illustrative of specific ways of manufacturing and using the invention and do not limit the scope of the invention.

[0027] This invention utilizes the energy ratio of pipeline anti-excavation algorithms. R ( k By setting the energy ratio and center of gravity frequency threshold, the existence of excavation behavior in the pipeline can be accurately distinguished and identified from two dimensions: energy ratio and center of gravity frequency. This invention features low background noise, which does not obscure the pipeline excavation prevention signal, resulting in high accuracy and a low false alarm rate in the determination of the pipeline excavation prevention signal.

[0028] The following is in conjunction with the appendix Figure 1-3 Provide a detailed description. Example 1

[0029] like Figure 1 The flowchart of the pipeline anti-excavation algorithm shown includes the following steps: Step 1: Calculate the energy of the long time window E L and short window energy E S .

[0030] Step 2: Calculate the energy ratio of the short window to the long window. R ( k ).

[0031] Step 3: Calculate the Fourier transform coefficients using Fourier transform. X ( f i ).

[0032] Step 4: Calculate the centroid frequency of the pipeline anti-excavation signal f c .

[0033] Step 5: Determine if excavation has occurred.

[0034] Step 6: When it is determined that there is excavation activity in pipeline 9, an alarm is triggered and an alarm message is sent; otherwise, it is determined that there is no excavation activity in pipeline 9 and no alarm is triggered.

[0035] The process of the pipeline anti-excavation algorithm of the present invention is described in detail below. A pipeline anti-excavation algorithm includes the following steps.

[0036] Step 1: The anti-dig signal of the pipeline picked up by sensor 1 x ( i Select a sliding long-time window, and set a short-time window within the long-time window. The endpoints of the long-time window and the short-time window coincide. Calculate the energy of the long-time window separately. E L and short window energy E S : in, S The length of the short time window; L The length of the long window; i Sampling time; x ( i ) indicates the first i The sampled value of the pipeline anti-excavation signal at the sampling time; k For the first sample k Several points. Among them, the length of the short time window. S Set to 40ms, the length of the long window. L It takes 120ms.

[0037] Step 2: Calculate the energy ratio of the short window to the long window. R ( k )= E S / E L .

[0038] Step 3: Send the pipeline anti-excavation signal x ( i Perform a Fourier transform to obtain the Fourier transform coefficients. X ( f i The formula for the Fourier transform is as follows: in, N This represents the number of sampling points; j The imaginary unit; iSampling time; x ( i ) indicates the first i The sampled value of the pipeline anti-excavation signal at the sampling time; f i Indicates the first i A discrete frequency point.

[0039] Step 4: Calculate the centroid frequency of the pipeline anti-excavation signal f c : in, i Sampling time; f i Indicates the first i A discrete frequency point; X ( f i () represents the Fourier transform coefficients; N This represents the number of sampling points.

[0040] Step 5: The energy ratio of the short-time window to the long-time window of the pipeline anti-excavation signal R ( k If the value is greater than 2.5 and the center of gravity frequency is less than 200, it is determined that there is excavation activity in pipeline 9, and an alarm is triggered and an alarm message is sent; otherwise, it is determined that there is no excavation activity in pipeline 9, and no alarm is triggered. Example 2

[0041] This invention employs an interferometric fiber optic sensing type optical sensor 1, which improves the accuracy and sensitivity of pipeline anti-excavation signal acquisition, identification, and anti-excavation location positioning, thereby enhancing monitoring precision. The battery 3 of this invention uses a rechargeable and removable lithium battery and is installed within the inspection well 10 in the area of ​​the pipeline to be monitored 9, making the maintenance of the sensor 1 and battery 3 more convenient.

[0042] The structural schematic diagram of the present invention is shown below. Figure 2 As shown, a pipeline anti-excavation system based on fiber optic sensing includes a sensor 1 for picking up pipeline anti-excavation signals, a host module 2, a composite cable 7 for information transmission between the sensor 1 and the host module 2, and a cloud server. The host module 2 includes a 4G / 5G module 5 for sending and receiving signals, a transmission module 4, and a GPS module 6 for uploading the sensor 1's own location information. The sensor 1 is an interferometric fiber optic sensor. The sensor 1 is sequentially deployed on the pipeline 9 to be tested buried underground, and the sensor 1 is connected to the host module 2 in a surface inspection well 10 via the composite cable 7.

[0043] The anti-excavation signal collected by sensor 1 is output to host module 2 via composite cable 7. It is received and demodulated by transmission module 4 within host module 2, and then output to cloud server via 4G / 5G module 5. Cloud server uses an anti-excavation algorithm to determine if excavation activity exists. If excavation activity is detected, an alarm is triggered and an alarm message is sent; otherwise, no alarm is triggered. Host module 2 also includes a battery 3 and a power cable 8 for powering each sensor 1. The battery 3 is a rechargeable and replaceable lithium battery.

[0044] Specifically, a pipeline anti-excavation system based on fiber optic sensing includes a sensor 1 for picking up pipeline anti-excavation signals, a host module 2, a composite cable 7 for information transmission between the sensor 1 and the host module 2, and a cloud server. The host module 2 includes a 4G / 5G module 5 for sending and receiving signals, a transmission module 4, a GPS module 6 for uploading the sensor 1's own location information, a power supply cable 8, and a battery 3. The battery 3 is a detachable, rechargeable battery assembly, and can also be a mains power or solar power module; for ease of explanation, a lithium battery is used in this patent. Furthermore, the battery 3 is positioned at the wellhead during on-site installation for easy replacement.

[0045] The power supply cable is used to power the host module and sensor 1 from battery 3, and generally has basic properties such as waterproof and dustproof, low loss, and tensile strength. The transmission module 4 is used to demodulate the signal picked up by sensor 1 and transmit the data to the cloud server through 4G / 5G module 5, while also receiving acquisition instructions from the cloud server. The GPS module 6 is used to mark the geographical location of the monitoring point when sensor 1 is installed, and to report and display it on the cloud server. The composite cable 7 is used for power supply and data transmission between host module 2 and sensor 1, and generally has basic properties such as waterproof and dustproof, low loss, anti-interference, and tensile strength. The fiber optic sensor 1 is used to monitor and pick up vibration data of the measured pipe 9, and transmits the data to host module 2 through composite cable 7; the transmitted signal type is digital signal.

[0046] The sensor 1 uses, as shown in... Figure 3 The interferometric fiber optic sensor 1 shown includes a neodymium magnet 17, a base 12, a metal film 15, a mass block 13, a reference fiber 16, a top cover 11, and a modulation fiber 14. The neodymium magnet 17 is used for portable adsorption of the sensor 1 onto the outer wall of the pipe 9. The mass block 13 is made of copper and is shaped like an "I". The reference fiber 16 is evenly wound around the outer walls of the grooves on both sides of the "I". The metal film 15 is also made of copper and is generally on the order of millimeters in thickness. It is installed below the mass block 13 and fixed to the base. The modulation fiber 14 is evenly wound around the surface of the lower center position of the metal film 15.

[0047] The upper cover 11 and the base 12 constitute the housing of the fiber optic sensor. The upper end of the housing has a hole for the transmission of the composite cable, and the lower end of the housing has a circular thread or snap-fit ​​structure that fits into the upper end of the base 12. The lower end of the base 12 has a cylindrical groove in the middle that fits into the neodymium magnet 17. The edge of the base 12 is a flat circle that adapts to the neodymium magnet 17. The cross-section of the entire base 12 is concave, and the cross-section of the neodymium magnet 17 is convex, which fits into the lower end of the base 12.

[0048] The process and principle of the fiber optic sensor 1 in picking up pipeline anti-excavation signals are as follows: The fiber optic sensor 1 is adsorbed onto the outer wall of the pipeline 9 buried underground by a neodymium magnet 17. When excavation occurs around the pipeline 9, a vibration signal is generated. This vibration signal is transmitted to the surface of the pipeline 9 through media such as soil and sand. The vibration signal is transmitted to the base 12 of the sensor 1 through the neodymium magnet 17, which in turn causes the metal membrane 15 to generate synchronous, constant-amplitude vibration stimulation and produce micro-deformation. The surface of the metal membrane 15 is wound with a modulation fiber 14. At this time, the length of the modulation fiber 14 wound on the surface of the metal membrane 15 will change due to the micro-synchronization of the metal membrane 15. However, the length of the reference fiber 16 wound on the mass block 13 does not change because the mass block 13 is fixed on the surface of the sensor 1 and the mass block 13 is insensitive to vibration. At this time, the two signals formed between the reference fiber 16 and the modulation fiber 14 will generate a phase difference affected by the external vibration signal. The interference signal formed by the phase difference between the two signals can realize high-precision acquisition of the external vibration signal.

[0049] The vibration signal collected by sensor 1 is the pipeline anti-excavation signal. This signal is output to host module 2 via a composite cable, received and demodulated by transmission module 4 within host module 2, and then uploaded to the cloud server via 4G / 5G module 5. At this time, the cloud server calculates and identifies the uploaded pipeline anti-excavation signal according to the pipeline anti-excavation algorithm in Embodiment 1, determining whether excavation activity exists within the area of ​​the pipeline to be tested 9. If excavation activity is detected, an alarm is triggered and an alarm message is sent; if no excavation activity is detected, the process returns to step S5 without triggering an alarm.

[0050] The following describes how to use a pipeline anti-digging system, including the following steps.

[0051] Step S1: Determine the area of ​​the pipe to be tested 9, including the length and direction of the pipe to be tested 9, the number and distribution of the manholes 10, and the spacing between the manholes 10.

[0052] Step S2: Based on the characteristics of the pipeline, the sensor 1 is installed on the pipeline to be tested 9, and the host module 2 is installed in the inspection well 10 above the area of ​​the pipeline to be tested 9. The distance between two adjacent sensors 1 is ≤200m.

[0053] Step S3: The sensor 1 on the pipeline to be tested 9 is activated and uploads its own location information to the host module 2 via the GPS module 6 and composite cable 7. The transmission module 4 in the host module 2 receives and summarizes the information and uploads it to the cloud server via the 4G / 5G module 5.

[0054] Step S4: The cloud server sends a data acquisition command to the host module 2 installed in the inspection well 10 through the 4G / 5G module 5. The 4G / 5G module 5 of the host module 2 receives the data acquisition command and outputs it to each sensor 1 on the pipeline to be tested 9 through the transmission module 4 and the composite cable 7 in sequence. The data acquisition command includes real-time continuous signal acquisition or signal acquisition for a specific time period.

[0055] Step S5: The sensor 1 picks up the pipeline anti-excavation signal according to the acquisition command in step S4. The pipeline anti-excavation signal is output to the host module 2 via a composite cable. The transmission module 4 in the host module 2 receives and demodulates the signal, and then uploads it to the cloud server via the 4G / 5G module 5.

[0056] Step S6: The cloud server calculates and identifies the uploaded pipeline anti-excavation signal based on the pipeline anti-excavation algorithm to determine whether there is any excavation activity in the area of ​​the pipeline to be tested 9.

[0057] Step S7: If it is determined that there is excavation activity, an alarm is triggered and an alarm message is sent; if it is determined that there is no excavation activity, return to step S5 and do not trigger an alarm.

[0058] This invention uses a composite cable 7 to aggregate and transmit the pipeline anti-excavation signals collected by sensor 1. Sensor 1, installed on the underground pipeline 9, provides excellent electromagnetic interference protection against these signals. The signal is less affected by the burial of the sensor, resulting in minimal signal transmission loss and interference from the burial site, thus overcoming the technical problem of sensor 1 frequently going offline. Furthermore, a wireless data transmission channel is established between the main unit module 2 (4G / 5G module 5 and transmission module 4) and the cloud server, buried within the surface inspection well 10. This eliminates the need for scattered excavation or partial full-line excavation, making installation, networking, and monitoring more convenient.

[0059] Although the specification has provided a detailed description, it should be understood that various changes, substitutions, and modifications can be made without departing from the spirit and scope of the invention as defined by the appended claims. Furthermore, the specific embodiments described are not intended to limit the scope of the invention, and those skilled in the art will readily understand based on this invention that existing or future-developed processes, machines, manufactures, compositions of matter, means, methods, or steps can perform substantially the same functions or achieve substantially the same results as the embodiments of the invention. Therefore, the appended claims are intended to include such processes, machines, manufactures, compositions of matter, means, methods, or steps within their scope.

Claims

1. A pipeline anti-excavation algorithm, characterized in that: Includes the following steps: Step 1: The anti-dig signal for the pipeline picked up by the sensor. x ( i Select a sliding long time window, and set a short time window within the long time window. The endpoints of the long time window and the short time window coincide. The length of the short time window is... S The length of the long time window is 40ms. L Calculate the energy of the long time window for 120ms. E L and short window energy E S : in, S The length of the short time window; L The length of the long window; i Sampling time; x ( i ) indicates the first i The sampled value of the pipeline anti-excavation signal at the sampling time; k For the first sample k One point; Step 2: Calculate the energy ratio of the short window to the long window. R ( k )= E S / E L ; Step 3: Send the pipeline anti-excavation signal x ( i Perform a Fourier transform to obtain the Fourier transform coefficients. X ( f i ); Step 4: Calculate the centroid frequency of the pipeline anti-excavation signal f c in, i Sampling time; f i Indicates the first i A discrete frequency point; X ( f i () represents the Fourier transform coefficients; N This represents the number of sampling points; Step 5: The energy ratio of the short-time window to the long-time window of the pipeline anti-excavation signal R ( k If the value is greater than 2.5 and the center of gravity frequency is less than 200, it is determined that there is excavation activity in the pipeline, and an alarm is triggered and an alarm message is sent; otherwise, it is determined that there is no excavation activity in the pipeline, and no alarm is triggered.

2. The pipeline anti-excavation algorithm as described in claim 1, characterized in that: The formula for the Fourier transform in step 3 is as follows: in, N This represents the number of sampling points; j The imaginary unit; i Sampling time; x ( i ) indicates the first i The sampled value of the pipeline anti-excavation signal at the sampling time; f i Indicates the first i Discrete frequency points.

3. A pipeline anti-excavation system based on fiber optic sensing, employing the pipeline anti-excavation algorithm as described in any one of claims 1-2, characterized in that: The system includes a sensor for picking up pipeline anti-excavation signals, a host module, a composite cable for transmitting information between the sensor and the host module, and a cloud server. The host module includes a 4G / 5G module for sending and receiving signals, a transmission module, and a GPS module for uploading the sensor's own location information. The sensor is an interferometric fiber optic sensor. The sensors are sequentially deployed on the pipeline to be tested buried underground, and the sensors are connected to the host module in a surface inspection well via the composite cable. The anti-excavation signal of the pipeline collected by the sensor is output to the host module via a composite cable. The host module receives and demodulates the signal, and then outputs it to the cloud server via a 4G / 5G module. The cloud server determines whether excavation behavior exists based on the pipeline anti-excavation algorithm. If excavation behavior exists, an alarm is triggered and an alarm message is sent; if no excavation behavior exists, no alarm is triggered.

4. The pipeline anti-excavation system based on fiber optic sensing as described in claim 3, characterized in that: The host module also includes batteries and power cables for powering the sensors.

5. The pipeline anti-excavation system based on fiber optic sensing as described in claim 4, characterized in that: The battery is a rechargeable, replaceable lithium battery.

6. A method for applying the pipeline anti-excavation system as described in any one of claims 3-5, characterized in that: Includes the following steps: Step S1: Determine the area of ​​the pipeline to be tested, including the length and direction of the pipeline, the number and distribution of manholes, and the spacing between manholes; Step S2: Based on the characteristics of the pipeline, the sensor is installed on the pipeline to be tested, and the main unit module is installed in the inspection well above the area of ​​the pipeline to be tested. The distance between two adjacent sensors is ≤200m. Step S3: The sensors on the pipeline under test are activated and upload their own location information to the host module via the GPS module and composite cable. The transmission module in the host module receives and summarizes the information and then uploads it to the cloud server via the 4G / 5G module. Step S4: The cloud server sends a data acquisition command to the host module deployed in the inspection well via the 4G / 5G module. The 4G / 5G module of the host module receives the data acquisition command and outputs it to each sensor on the pipeline under test via the transmission module and composite cable in sequence. Step S5: The sensor picks up the pipeline anti-excavation signal according to the acquisition command in step S4. The pipeline anti-excavation signal is output to the host module via a composite cable. After being received and demodulated by the transmission module in the host module, it is uploaded to the cloud server via the 4G / 5G module. Step S6: The cloud server calculates and identifies the uploaded pipeline anti-excavation signal based on the pipeline anti-excavation algorithm to determine whether there is any excavation activity in the pipeline area to be tested; Step S7: If it is determined that there is excavation activity, an alarm is triggered and an alarm message is sent; if it is determined that there is no excavation activity, return to step S5 and do not trigger an alarm.

7. The method as described in claim 6, characterized in that: The acquisition instructions in step S4 include real-time continuous signal acquisition or signal acquisition for a specific time period.

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