Distributed fiber optic vibration sensing system and deep integration applications with cesium

Abstract

This invention relates to the field of fiber optic sensing technology and data visualization. Specifically, it describes a deep integration of a distributed fiber optic vibration sensing system with Cesium, including the integration system and method. The system comprises a coherent detection φ-OTDR, a down-conversion signal processing module, a high-speed AD module, a ZYNQ-7020 chip, a 4G module, a web backend server, MySQL database software, a realistic 3D model, and a Cesium frontend GIS framework. This invention provides a visualization tool for on-site engineering or management personnel, displaying the location and amplitude of vibration at appropriate locations, and promotes the engineering application of distributed fiber optic vibration sensing systems.

Description

Technical Field

[0001] This invention relates to the field of fiber optic sensing technology and data visualization, specifically to a system and method for the deep integration of a distributed fiber optic vibration sensing system and Cesium. Background Technology

[0002] Distributed fiber optic vibration sensing systems are an important member of the distributed fiber optic sensing family. They utilize the backscattered Rayleigh light from the fiber to sense vibrations occurring along its path. Coherent detection type. Cesium is applied in various fields, such as national defense, safety monitoring of oil pipelines, power transmission line monitoring, and safety and health monitoring of large-scale infrastructure projects such as highways and bridges. However, there has been a lack of a visually appealing front-end GIS framework that integrates seamlessly with it. When vibration is detected, distributed fiber optic vibration sensing systems cannot intuitively display the specific geographical location of the vibration or the specific 3D structure of the vibration point to on-site engineering or management personnel. Therefore, the further promotion of distributed fiber optic vibration sensing systems urgently requires a data visualization tool. Cesium is a web-based GIS framework, an open-source JavaScript library for displaying 3D globes and maps. It can be used to display massive amounts of 3D model data, image data, terrain elevation data, and vector data, and can be integrated into web-based user management systems for immediate use. Cesium supports loading various 3D model formats, including 3D Tiles. 3D Tiles is an open 3D spatial data standard designed primarily to improve the loading and rendering speed of models in large 3D scenes. Cesium uses streaming, tiled loading to render 3D Tiles models, achieving on-demand model loading and thus providing a smooth 3D model browsing experience.

[0003] The deep integration of the distributed fiber optic vibration sensing system with the Cesium front-end Gis framework can vividly display the vibration location and vibration level in real time, realizing the fusion of virtual and reality. Summary of the Invention

[0004] This invention addresses the shortcomings of existing technologies by proposing a deep integration system of a distributed fiber optic vibration sensing system and Cesium. It utilizes a MySQL database to store the specific latitude and longitude information of the sensing fiber, and renders the fiber's routing distribution on a real-world 3D model loaded in Cesium. Data from the distributed fiber optic vibration sensing system is processed by a down-conversion signal processing module and then fed into an AD module for digital-to-analog conversion. The data is demodulated in real time, and the demodulation results are transmitted to the cloud via a 4G module. Cesium acquires the real-time vibration source data, enabling on-site personnel to monitor the fiber optic line in real time, and stores the vibration information in the MySQL database for administrator review.

[0005] A distributed fiber optic vibration sensing system deeply integrated with Cesium includes a down-conversion signal processing module, a ZYNQ-7020 chip, a web server backend, a 3D tile format real-scene 3D model, and a Cesium frontend framework. The down-conversion signal processing module reduces the sensing signal from high frequency to low frequency, and then the analog signal is converted into a digital signal by an analog-to-digital converter and sent to the ZYNQ-7020 chip for processing. The ZYNQ-7020 chip demodulates the vibration signal and communicates with the web server backend via a 4G module. The web server backend stores the vibration signal data and the 3D tile format real-scene 3D model data. The Cesium frontend framework visualizes the 3D tile format real-scene 3D model data and the vibration signal data.

[0006] In the above technical solution, the down-conversion signal processing module includes a high-performance IQ mixer module, a DDS signal generator, a dual-ended to single-ended differential operational amplifier, and a low-pass filter. The high-performance IQ mixer module receives the signal output from the coherent detection φ-OTDR at the RF port and the high-frequency sinusoidal signal generated by the DDS signal generator at the LO port. After receiving the two input signals, it splits them into two paths. The first path signal at the LO port remains unchanged, while the second path signal at the LO port is phase-shifted by 90 degrees. The first path signal at the RF port remains unchanged, while the second path signal at the RF port is inverted. Then, the two paths are multiplied together to output I. + I - Q + Q - Four signals; the DDS signal generator outputs a high-frequency sine wave with fixed frequency, amplitude, and phase upon power-up after its ROM is programmed; the high-performance IQ mixer module is input to the low-pass filter I... + I - Q + Q - Because signal multiplication results in sum and difference frequency terms, with the sum frequency in the high-frequency range (MHz) and the difference frequency in the low-frequency range (kHz), a low-pass filter removes the high-frequency components, outputting the low-frequency components to a dual-ended to single-ended differential operational amplifier module. The input of the dual-ended to single-ended differential operational amplifier module is I... + I - Or Q + Q - Differential filtering is performed within the module to eliminate common-mode noise and improve signal quality.

[0007] In the above technical solution, the ZYNQ-7020 chip demodulates the I and Q signals acquired by the dual-channel AD converter to determine the location and amplitude of the vibration source, and communicates with the 4G module via a serial port.

[0008] A further improvement of this invention is that the web server backend receives HTTP requests sent from the 4G module, extracts the received information by line, obtains the request line and request header fields, thereby extracting the vibration point location and amplitude data, and writes the data into a MySQL database via JDBC. Simultaneously, it receives requests from the browser and returns the vibration point location and amplitude data to the browser. The real-scene 3D model is generated by using a drone to perform oblique photography along the fiber optic line, and importing the oblique photography data into ContextCapture software to generate a 3D tile format 3D model. The Cesium frontend framework loads the 3D tile format 3D model along the fiber optic line, and after initiating an HTTP request through the browser to return the vibration point location and amplitude data, renders the vibration point location as points on the real-scene 3D model, indicating the amplitude. Simultaneously, the wiring of the sensing fiber optic cable is rendered on a map as 3D pipelines.

[0009] A further improvement to this invention is that the web server backend runs on a Linux system and uses the Spring Boot framework to handle HTTP requests.

[0010] A further improvement to this invention utilizes the Cesium front-end Gis framework to load a 3D tile format real-world 3D model to visualize the fiber optic layout and cabling, and to provide alarms for the location and amplitude of vibration points.

[0011] A further improvement of the present invention is that the ZYNQ-7020 chip performs cross-differentiation on the collected Rayleigh scattering curve data and demodulates the vibration point position and amplitude in real time.

[0012] The specific steps for integrating this system are as follows:

[0013] Step 1: In the early stages of construction, the location of the sensing fiber is recorded every 10 meters using a handheld GPS locator, and then a CSV file is generated to record the latitude and longitude.

[0014] Step 2: The server backend reads the CSV file, obtains a series of latitude and longitude values, and writes them into the database in sequence after connecting to the MySQL database via JDBC. The id column is set to auto-increment, thus storing the latitude and longitude data of the starting and ending points of multiple sensing fiber optic segments.

[0015] Step 3: Use a drone to take oblique photographs of the area around the fiber optic cabling location at multiple different angles and heights. Import the oblique photograph data into ContextCapture software for 3D reconstruction and set the 3D format to 3DTiles. The generated 3D Tiles format 3D data is placed on the server backend.

[0016] Step 4: When vibration occurs along the optical fiber, the signal output by the distributed optical fiber vibration sensing system is: A s sin(ω s t+φ(t)), A s ω is the product of the amplitudes of the signal light (backscattered Rayleigh light) and the local oscillator light. s Let ωt be the difference between the angular frequency of the signal light and the angular frequency of the local oscillator light, respectively, with a difference of 200MHz. Let φ(t) be the phase of the external vibration signal. Figure 2 As shown, the signal output from the distributed fiber optic vibration sensing system enters the down-conversion module for processing. The high-performance IQ mixer module mixes the LO port signal A0sin(ω0t+φ0) with the RF port signal A... s sin(ω s t+φ(t)) are both divided into two paths, where Ao is the amplitude of the 200M sine wave output by the DDS, ω0 is the angular frequency corresponding to the 200M sine wave, and φ0 is the initial phase of the 200M sine wave output by the DDS. The first path signal at the LO port remains unchanged, while the second path signal at the LO port is phase-shifted by 90 degrees. The first path signal at the RF port remains unchanged, while the second path signal at the RF port is inverted. Then, they are multiplied pairwise, where the first path signal at the LO port A0sin(ω0t+φ0) and the first path signal at the RF port A s sin(ω s The output I+ is obtained by multiplying t+φ(t) and the first signal A0sin(ω0t+φ0) at the LO port with the inverted signal -A from the second signal at the RF port. s sin(ω s The product of t+φ(t) is I-. The second signal at the LO port, after a 90-degree phase shift, becomes A0cos(ω0t+φ0) and is multiplied by the first signal at the RF port. s sin(ω s The product of t+φ(t) and Q+ is output. The second signal at the LO port is phase-shifted by 90 degrees to become Q+.

[0017] A0cos(ω0t+φ0) and the inverted signal from the second RF terminal -A s sin(ω s The output Q- is generated by multiplying t+φ(t)). After the signal is multiplied, a sum frequency and a difference frequency term appear. The sum frequency term is as high as 400MHz, which generates a high-frequency component and a low-frequency signal component with a frequency of 400MHz. The four outputs of the high-performance IQ mixer enter the low-pass filter to filter out the high-frequency component and leave only the low-frequency component. After I+ and I- are filtered by the low-pass filter, they enter the differential operational amplifier from dual-ended to single-ended to eliminate common-mode noise and amplify. Similarly, the outputs of Q+ and Q- also go through the same process.

[0018] Step 5: The IQ dual-channel signal output from the down-conversion signal processing module is sampled by a high-speed AD converter, quantized, and encoded before being input to the PL side of the ZYNQ-7020 chip. Figure 3 As shown: For the input IQ dual-channel data, it is processed by Xilinx's multiplier IP core, i.e., I-channel multiplied by I-channel and Q-channel multiplied by Q-channel, finally yielding I... 2 With Q 2 At this point, I and Q are added together by the adder IP core to obtain I. 2 +Q 2 Finally, we obtain the square root of the cordic IP core. This means obtaining the data from the first backscattering Rayleigh scattering curve and storing the data in a single-port RAM. Here, the single-port RAM is set to read. In the first mode, before new data is stored, the previous backscattering Rayleigh scattering curve data is read from RAM and sent to the differential module for processing. When the second backscattering Rayleigh scattering curve is acquired, the quantized value of the corresponding position point of the first backscattering Rayleigh scattering curve data in the single-port RAM is retrieved and differentially analyzed with the second Rayleigh scattering data. The result is stored in another dual-port RAM. When the third backscattering Rayleigh scattering curve data arrives, differential analysis is performed with the second backscattering Rayleigh scattering curve. The differential result is stored in the dual-port RAM according to the corresponding position for accumulation. This process is repeated to build a pipeline operation. When 100 backscattering Rayleigh scattering curves are counted, the dual-port RAM read enable is pulled high, the accumulated result is read from the dual-port RAM, the result is stored in FIFO, and a full signal is generated to notify the PS side of the ZYNQ-7020 chip to read. This achieves real-time data processing. After obtaining the position and amplitude of the vibration point, the PS side of the ZYNQ-7020 chip communicates with the 4G module through the serial port to transmit the data to the 4G module.

[0019] Step Six: The 4G module initiates an HTTP request, which includes the location and amplitude information of the vibration source.

[0020] Step 7: After receiving the request, the server backend writes the data to the MySQL database via JDBC and adds a time parameter to each vibration point data.

[0021] Step 8: When the browser initiates a request to view the location and amplitude information of the vibration source, the server backend reads the data from the database via JDBC and calculates the specific latitude and longitude of the vibration source. For example, if the vibration occurs at 108 meters, the server finds the latitude and longitude of the 10th and 11th fiber segments from the latitude and longitude table of the sensor fiber layout and wiring stored in the database. The longitude of the vibration point is the longitude of the 10th fiber segment minus the longitude of the 11th fiber segment, divided by 8, and then added back to the longitude of the 10th fiber segment. The latitude of the vibration point is calculated in the same way.

[0022] Step Nine: When a user views the location of the vibration source, Cesium loads a realistic 3D model of the vibration source location from the server backend on demand, reducing screen rendering, increasing screen smoothness, and improving user experience. The server backend returns the latitude and longitude of the vibration point, the amplitude level, the time of vibration, and all latitude and longitude data along the fiber optic cable to the browser. The frontend framework Cesium then renders a virtual fiber optic cable at the corresponding location in the realistic 3D model. After obtaining the vibration source's latitude and longitude and amplitude data, Cesium categorizes the amplitude levels and renders them as text labels directly above the corresponding vibration point.

[0023] The beneficial effects of this invention are as follows: The coherent detection type φ-OTDR of this invention responds to vibration events. The amplitude and location information of the vibration source are demodulated at the FPGA end and sent to the 4G module via serial communication. Then, the 4G module initiates an HTTP request. After receiving the request, the backend stores the data in a MySQL database. Cesium initiates an HTTP request to the server backend through the axios network communication framework. After receiving the request, the backend reads the information from the MySQL database and returns it to Cesium. Cesium loads a real-world 3D model on the Web end and displays the location and amplitude of the vibration at the corresponding position, providing a visualization tool for on-site engineering or management personnel, thus promoting the engineering application of distributed fiber optic vibration sensing systems. Attached Figure Description

[0024] Figure 1 This is a system overall framework diagram of the present invention.

[0025] Figure 2 This diagram illustrates how the signal output from the distributed fiber optic vibration sensing system in this invention is processed by the down-conversion module.

[0026] Figure 3 This is a schematic diagram showing the IQ dual-channel signal output by the downconversion signal processing module in this invention being quantized and encoded by high-speed AD sampling. Detailed Implementation

[0027] To enhance understanding of the present invention, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. These embodiments are only used to explain the invention and do not limit the scope of protection of the invention.

[0028] like Figure 1As shown, a distributed fiber optic vibration sensing system deeply integrated with Cesium includes a down-conversion signal processing module, a ZYNQ-7020 chip, a web server backend, a 3dtiles format real-scene 3D model, and a Cesium frontend framework. The down-conversion signal processing module reduces the sensing signal from high frequency to low frequency, and then the analog signal is converted into a digital signal by an analog-to-digital converter and sent to the ZYNQ-7020 chip for processing. The ZYNQ-7020 chip demodulates the vibration signal and communicates with the web server backend through a 4G module. The web server backend stores the vibration signal data and the 3dtiles format real-scene 3D model data. The Cesium frontend framework visualizes the 3dtiles format real-scene 3D model data and the vibration signal data.

[0029] The specific steps for integrating this system are as follows:

[0030] Step 1: In the early stages of construction, the location of the sensing fiber is recorded every 10 meters using a handheld GPS locator, and then a CSV file is generated to record the latitude and longitude.

[0031] Step 2: The server backend reads the CSV file, obtains a series of latitude and longitude values, and writes them into the database in sequence after connecting to the MySQL database via JDBC. The id column is set to auto-increment, thus storing the latitude and longitude data of the starting and ending points of multiple sensing fiber optic segments.

[0032] Step 3: Use a drone to take oblique photographs of the area around the fiber optic cabling location at multiple different angles and heights. Import the oblique photograph data into ContextCapture software for 3D reconstruction and set the 3D format to 3DTiles. The generated 3D Tiles format 3D data is placed on the server backend.

[0033] Step 4: When vibration occurs along the optical fiber, the signal output by the distributed optical fiber vibration sensing system is: A s sin(ω s t+φ(t)), A s ω is the product of the amplitudes of the signal light (backscattered Rayleigh light) and the local oscillator light. s Let ωt be the difference between the angular frequency of the signal light and the angular frequency of the local oscillator light, respectively, with a difference of 200MHz. Let φ(t) be the phase of the external vibration signal. Figure 2 As shown, the signal output from the distributed fiber optic vibration sensing system enters the down-conversion module for processing. The high-performance IQ mixer module mixes the LO port signal A0sin(ω0t+φ0) with the RF port signal A... s sin(ω st+φ(t)) are both divided into two paths, where Ao is the amplitude of the 200M sine wave output by the DDS, ω0 is the angular frequency corresponding to the 200M sine wave, and φ0 is the initial phase of the 200M sine wave output by the DDS. The first path signal at the LO port remains unchanged, while the second path signal at the LO port is phase-shifted by 90 degrees. The first path signal at the RF port remains unchanged, while the second path signal at the RF port is inverted. Then, they are multiplied pairwise, where the first path signal at the LO port A0sin(ω0t+φ0) and the first path signal at the RF port A s sin(ω s The output I+ is obtained by multiplying t+φ(t) and the first signal A0sin(ω0t+φ0) at the LO port with the inverted signal -A from the second signal at the RF port. s sin(ω s The product of t+φ(t) is I-. The second signal at the LO port, after a 90-degree phase shift, becomes A0cos(ω0t+φ0) and is multiplied by the first signal at the RF port. s sin(ω s The product of t+φ(t) and Q+ is output. The second signal at the LO port is phase-shifted by 90 degrees to become Q+.

[0034] A0cos(ω0t+φ0) and the inverted signal from the second RF terminal -A s sin(ω s The output Q- is generated by multiplying t+φ(t)). After the signal is multiplied, a sum frequency and a difference frequency term appear. The sum frequency term is as high as 400MHz, which generates a high-frequency component and a low-frequency signal component with a frequency of 400MHz. The four outputs of the high-performance IQ mixer enter the low-pass filter to filter out the high-frequency component and leave only the low-frequency component. After I+ and I- are filtered by the low-pass filter, they enter the differential operational amplifier from dual-ended to single-ended to eliminate common-mode noise and amplify. Similarly, the outputs of Q+ and Q- also go through the same process.

[0035] Step 5: The IQ dual-channel signal output from the down-conversion signal processing module is sampled by a high-speed AD converter, quantized, and encoded before being input to the PL side of the ZYNQ-7020 chip. Figure 3 As shown: For the input IQ dual-channel data, it is processed by Xilinx's multiplier IP core, i.e., I-channel multiplied by I-channel and Q-channel multiplied by Q-channel, finally yielding I... 2 With Q 2 At this point, I and Q are added together by the adder IP core to obtain I. 2 +Q 2 Finally, we obtain the square root of the cordic IP core. This means obtaining the data from the first backscattering Rayleigh scattering curve and storing the data in a single-port RAM. Here, the single-port RAM is set to read. In the first mode, before new data is stored, the previous backscattering Rayleigh scattering curve data is read from RAM and sent to the differential module for processing. When the second backscattering Rayleigh scattering curve is acquired, the quantized value of the corresponding position point of the first backscattering Rayleigh scattering curve data in the single-port RAM is retrieved and differentially analyzed with the second Rayleigh scattering data. The result is stored in another dual-port RAM. When the third backscattering Rayleigh scattering curve data arrives, differential analysis is performed with the second backscattering Rayleigh scattering curve. The differential result is stored in the dual-port RAM according to the corresponding position for accumulation. This process is repeated to build a pipeline operation. When 100 backscattering Rayleigh scattering curves are counted, the dual-port RAM read enable is pulled high, the accumulated result is read from the dual-port RAM, the result is stored in FIFO, and a full signal is generated to notify the PS side of the ZYNQ-7020 chip to read. This achieves real-time data processing. After obtaining the position and amplitude of the vibration point, the PS side of the ZYNQ-7020 chip communicates with the 4G module through the serial port to transmit the data to the 4G module.

[0036] Step Six: The 4G module initiates an HTTP request, which includes the location and amplitude information of the vibration source.

[0037] Step 7: After receiving the request, the server backend writes the data to the MySQL database via JDBC and adds a time parameter to each vibration point data.

[0038] Step 8: When the browser initiates a request to view the location and amplitude information of the vibration source, the server backend reads the data from the database via JDBC and calculates the specific latitude and longitude of the vibration source. For example, if the vibration occurs at 108 meters, the server finds the latitude and longitude of the 10th and 11th fiber segments from the latitude and longitude table of the sensor fiber layout and wiring stored in the database. The longitude of the vibration point is the longitude of the 10th fiber segment minus the longitude of the 11th fiber segment, divided by 8, and then added back to the longitude of the 10th fiber segment. The latitude of the vibration point is calculated in the same way.

[0039] Step Nine: When a user views the location of the vibration source, Cesium loads a realistic 3D model of the vibration source location from the server backend on demand, reducing screen rendering, increasing screen smoothness, and improving user experience. The server backend returns the latitude and longitude of the vibration point, the amplitude level, the time of vibration, and all latitude and longitude data along the fiber optic cable to the browser. The frontend framework Cesium then renders a virtual fiber optic cable at the corresponding location in the realistic 3D model. After obtaining the vibration source's latitude and longitude and amplitude data, Cesium categorizes the amplitude levels and renders them as text labels directly above the corresponding vibration point.

[0040] The above description is an exemplary embodiment of the present invention and does not limit the scope of patent protection of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A system for deep integration of a distributed fiber optic vibration sensing system with Cesium, comprising: The system includes a down-conversion signal processing module, a ZYNQ-7020 chip, a web server backend, a 3D Tiles format real-world 3D model, and a Cesium frontend framework. The down-conversion signal processing module reduces the frequency of the sensor signal from high to low, and then the analog signal is converted to digital by an analog-to-digital converter before being fed into the ZYNQ-7020 chip for processing. The ZYNQ-7020 chip demodulates the vibration signal and communicates with the web server backend via a 4G module. The web server backend stores the vibration signal data and the 3D Tiles format real-world 3D model data. The Cesium frontend framework processes the 3D Tiles format real-world 3D model data... The vibration signal data is visualized; the down-conversion signal processing module includes a high-performance IQ mixer module, a DDS signal generator, a dual-end to single-end differential operational amplifier, and a low-pass filter; the high-performance IQ mixer module receives the signal output from the coherent detection type φ-OTDR at the RF port and the high-frequency sinusoidal signal generated by the DDS signal generator at the LO port, and splits each of the two input signals into two paths. The first signal at the LO port remains unchanged, while the second signal at the LO port is phase-shifted by 90 degrees. The first signal at the RF port remains unchanged, while the second signal at the RF port is inverted. Then, the two signals are multiplied together to output I. + I - Q + Q - Four signals; the DDS signal generator outputs a high-frequency sine wave with fixed frequency, amplitude, and phase upon power-up after its ROM is programmed; the high-performance IQ mixer module is input to the low-pass filter I... + I - Q + Q - Because signal multiplication results in sum and difference frequency terms, with the sum frequency in the high-frequency range and the difference frequency in the low-frequency range, a low-pass filter removes the high-frequency components, outputting the low-frequency components to a dual-ended to single-ended differential operational amplifier module. The input of this module is I... + I - Or Q + Q - Differential filtering is performed within the module to eliminate common-mode noise and improve signal quality.

2. The distributed fiber optic vibration sensing system and deep integration system with Cesium according to claim 1, characterized in that, The ZYNQ-7020 chip differentiates the Rayleigh scattering curve data collected from each other, and demodulates the vibration point position and amplitude in real time.

3. The distributed fiber optic vibration sensing system and deep integration system with Cesium of claim 2, wherein, The ZYNQ-7020 chip demodulates the I and Q signals collected by the two-way AD to obtain the position and amplitude of the vibration source, and communicates with the 4G module through the serial port.

4. The distributed fiber optic vibration sensing system and deep integration system with Cesium of claim 1, wherein, The Web server backend receives the Http request sent by the 4G module, extracts the received information, obtains the request line and request header field, extracts the vibration point position and amplitude data, and writes the data into the Mysql database through JDBC, and also receives the request sent by the browser and returns the vibration point position and amplitude data to the browser.

5. The distributed fiber optic vibration sensing system and deep integration system with Cesium of claim 4, wherein, The Web server backend runs on the linux system and uses the Springboot framework to process Http requests.

6. The distributed fiber optic vibration sensing system and deep integration system with Cesium of claim 1, wherein, The real scene three-dimensional model is generated by tilting the camera on the optical fiber along the line by the unmanned aerial vehicle, and the tilting camera data is imported into the ContextCapture software to generate a three-dimensional model in the 3dtiles format.

7. The distributed fiber optic vibration sensing system and deep integration system with Cesium of claim 1, wherein, The Cesium front-end framework loads the 3dtiles format three-dimensional model of the optical fiber along the line, and renders the vibration point position on the real scene three-dimensional model in the form of a point and marks the amplitude after the browser initiates an Http request to return the vibration point position and amplitude data, and renders the sensing optical fiber wiring in the form of a three-dimensional pipeline on the map.

8. A method for deep integration of a distributed fiber optic vibration sensing system with Cesium, comprising: The method comprises the following steps: Step one, in the initial stage of construction, the sensing optical fiber is positioned by a handheld GPS positioning instrument every 10 meters to record the sensing optical fiber position, and then a CSV file is generated to record the longitude and latitude; Step two, the server backend reads the CSV file to obtain a series of longitude and latitude values, links to the Mysql database through JDBC, and writes the values into the database in order and sets the id column to auto-increment; Step three: use a UAV to take multiple oblique photographs of the optical fiber wiring position from different angles and heights, import the oblique photograph data into the ContextCapture software for three-dimensional reconstruction, set the three-dimensional format to 3D Tiles format, and place the generated 3D Tiles format three-dimensional data on the server backend; Step four: when the fiber along the line vibration occurs, the signal output by the distributed optical fiber vibration sensing system is: A s sin(ω s t+φ(t)),A s is the product of the signal light and the local oscillator light field amplitude, ω s is the difference between the angular frequency of the signal light and the angular frequency of the local oscillator light, which is 200 MHZ, φ(t) is the phase of the external vibration signal, the high-performance IQ mixing module divides the LO port signal and the RF end signal into two paths, where A0 is the amplitude of the 200M sinusoidal signal output by the DDS, ω0 is the angular frequency corresponding to the 200M sinusoidal signal, φ0 is the initial phase of the 200M sinusoidal signal output by the DDS, the first LO port signal is not changed, the second LO port signal is phase-shifted by 90 degrees, the first RF end signal is not changed, and the second RF end signal is inverted, and then two by two are multiplied, where the first LO port signal and the first RF end signal are multiplied to output I+, the first LO port signal and the inverted signal of the second RF end signal are multiplied to output I - , the second LO port signal after phase shift by 90 degrees becomes and the first RF end signal A s sin(ω s t+φ(t)) are multiplied to output Q+, the second LO port signal after phase shift by 90 degrees becomes A0cos(ω0t+φ0) and the inverted signal of the second RF end signal-A s sin(ω s t+φ(t)) are multiplied to output Q-, after signal multiplication, sum frequency and difference frequency terms appear, where the sum frequency term is as high as 400 MHZ, that is, a high frequency component with a frequency of 400 MHz and a low frequency signal component are generated, the four outputs of the high-performance IQ mixing module enter the low-pass filter, and the high-frequency component is filtered out only to leave the low-frequency component, I+ and I- after filtering by the low-pass filter enter the differential amplifier to eliminate common-mode noise and amplify, and similarly, the outputs of Q+ and Q- also go through the same process; Step five: IQ double channel signal output by the down-conversion signal processing module is quantitatively coded by high-speed AD sampling and enters the PL side of the ZYNQ-7020 chip. For the input IQ double channel data, the I channel is multiplied by the I channel and the Q channel is multiplied by the Q channel through the multiplier IP core of xilinx, and finally the I 2 and Q 2 At this time, the I and Q channels enter the adder IP core to be added, and the I 2 +Q 2 , and finally enter the cordic IP core to be square rooted, that is, the I The data of the first backscattering curve is obtained, and the data is stored in the single-port RAM. The single-port RAM is set to the read first mode. Before new data is stored, the last backscattering curve data in the RAM is read out and sent to the difference module for operation. When the second backscattering curve is collected, the quantized value of the first backscattering curve data corresponding to the position point in the single-port RAM is taken out and is different from the second backscattering data, and the result is stored in another dual-port RAM. When the third backscattering curve data arrives, the difference is continued with the second backscattering curve. The difference result is put into the dual-port RAM according to the corresponding position to be accumulated. The counting is repeated, and the pipeline operation is built. When the number of backscattering curves reaches 100, the read enable of the dual-port RAM is pulled high, the accumulated result is read out from the dual-port RAM, the result is stored in the FIFO, and the full signal is generated to notify the PS side of the ZYNQ-7020 chip to read. A real-time data processing is achieved, the position and amplitude of the vibration point are obtained, the PS side of the ZYNQ-7020 chip communicates with the 4G module through the serial port, and the data is transmitted to the 4G module. Step six: the 4G module initiates an Http request, and the request contains the position and amplitude information of the vibration source; Step seven: the server backend receives the request, writes the data into the Mysql database through JDBC, and adds a time parameter to each vibration point data; Step eight: when the browser initiates a request to view the vibration source position and amplitude information, the server backend reads the data from the database through JDBC and calculates the specific longitude and latitude of the vibration source. Step nine: When the user checks the location of the vibration source, Cesium loads the real three-dimensional model of the vibration source location on demand from the server backend, and the service backend returns the longitude and latitude of the vibration point and the amplitude level to the browser, and the front-end framework Cesium renders a virtual optical fiber at the corresponding position in the real three-dimensional model after getting the optical fiber longitude and latitude data. Cesium gets the longitude and latitude of the vibration source and the amplitude data, classifies the amplitude size, and renders it in the form of a text label directly above the corresponding vibration point.

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