Plateau permafrost thickness detection and monitoring method and system based on distributed fiber optic acoustic sensing

Abstract

The present invention discloses a method and system for detecting and monitoring the thickness of permafrost on the plateau based on distributed fiber optic acoustic sensing. The method includes deploying spiral and linear optical fibers in the permafrost according to predetermined observation locations, collecting vibration signals using the spiral and linear fibers, respectively; preprocessing the collected vibration signals to convert them into particle velocity signals; vector decomposing the two particle velocity signals obtained from the spiral and linear fibers to suppress the surface wave component and enhance the body wave component; self-excited and self-received recording of the measurement point locations based on the vector decomposition data; extracting the upper and lower limit travel times of the permafrost from the recorded data; and obtaining the upper and lower limit burial depth and thickness of the permafrost based on the upper and lower limit travel times of the permafrost and the velocity of the overlying strata and the permafrost layer. The present application can output the spatial distribution of permafrost in real time, monitor the buried depth, thickness, and upper and lower limit positions of the permafrost in real time, and provide a scientific basis for improving geological interpretation for railway survey and design and ensuring safe railway operation.

Description

Technical Field

[0001] The present invention relates to the technical field of non-destructive detection of railway engineering, and in particular to a method and system for detecting and monitoring the thickness of frozen soil in a plateau based on distributed optical fiber acoustic sensing. Background Art

[0002] During the survey and operation and maintenance of railways in cold and high-altitude areas, the presence and changes of permafrost will have a profound impact on the construction and operational safety of the railway. The physical properties and distribution characteristics of permafrost are directly related to the stability of the roadbed, and the phenomena of frost heave and thaw settlement of permafrost can even cause serious engineering problems, affecting the safety and efficiency of railway operations. Therefore, in-depth research on the formation mechanism, spatial distribution and dynamic changes of permafrost under different climatic conditions is of vital importance. Traditional methods generally use point sensors for data collection and processing, but this method has disadvantages such as difficulty in data synchronization, low resolution, limited coverage, and high deployment costs. It is difficult to meet the high efficiency and low cost requirements of large-scale and long-distance permafrost detection and monitoring.

[0003] Distributed Acoustic Sensing (DAS) is an advanced sensing technology developed in recent years that uses communication optical cables as dense array sensors. By detecting changes in the backscattering of laser pulses in the optical fiber, DAS enables high-density, all-round monitoring of physical fields such as sound waves or vibrations around the optical fiber. It has the advantages of long range, low cost, distributed high-density data collection, and long-term real-time monitoring.

[0004] 1. Long distance and wide range: DAS technology can monitor optical fibers up to tens of kilometers long, with a wide coverage area. It can be applied to large-scale monitoring scenarios such as railway lines, tunnels, and pipelines.

[0005] 2. Low cost: DAS technology uses existing optical fibers as sensors, eliminating the need to install a large number of additional sensors and equipment, thus saving monitoring costs.

[0006] 3. Distributed high-density acquisition: In DAS acquisition, every point on the optical cable can be used as a acquisition point, and the minimum track spacing can reach 25 cm.

[0007] 4. Real-time monitoring: DAS technology can realize real-time monitoring of optical fibers. The monitoring data can be transmitted to the monitoring center in real time, realizing real-time monitoring and data analysis of the monitoring area.

[0008] In existing fiber optic detection technology, for example, in Icelandic volcano monitoring, 100 kilometers of communication optical fiber is converted into 10,000 channels, capturing magma migration in minutes, demonstrating that fiber optic detection has broad application prospects in the field of geology. However, in the field of railway geological survey, data collection and processing still rely on point sensors, which cannot form dynamic perception of the entire section of the railway line. Therefore, the plateau permafrost thickness detection and monitoring method and system based on distributed fiber optic acoustic sensing proposed in this application aims to provide important data support and scientific basis for plateau railway construction and operation and maintenance based on distributed optical fiber detection of permafrost thickness on plateau railways, thereby reducing the risk of survey and design. Summary of the Invention

[0009] Therefore, the present invention aims to provide a method for detecting and monitoring frozen soil thickness on plateau railways based on distributed fiber-optic acoustic sensing. Furthermore, the present invention provides an integrated detection and monitoring system for implementing this method on a computer. This integrated detection and monitoring system can output the spatial distribution of frozen soil in real time, monitoring its depth, thickness, and upper and lower limits. This system improves geological interpretation for railway survey and design, and provides a scientific basis for safe railway operation.

[0010] To achieve the above objectives, the present invention provides a method for detecting and monitoring the thickness of frozen soil in plateaus based on distributed optical fiber acoustic sensing, comprising the following steps:

[0011] S1. Deploying a spiral optical fiber and a linear optical fiber in the frozen soil according to a predetermined observation position, and collecting vibration signals using the spiral optical fiber and the linear optical fiber respectively;

[0012] S2. Preprocessing the collected vibration signal to convert the vibration signal into a particle velocity signal;

[0013] S3, performing vector decomposition on the two particle velocity signals obtained from the helical optical fiber and the straight optical fiber, suppressing the surface wave component and enhancing the body wave component;

[0014] S4. Record the position of the measuring point by self-excitation and self-receiving according to the data after vector decomposition; pick up the upper and lower limit travel time of frozen soil from the recorded data;

[0015] S5. Obtain the upper burial depth and thickness of frozen soil based on the upper and lower travel times of frozen soil and the velocity of the overlying stratum and the frozen soil layer; the velocity of the overlying stratum and the frozen soil layer are calculated based on the reference well data.

[0016] Further preferably, in S1, when the spiral optical fiber and the linear optical fiber are laid out, the linear optical fiber is used as the axis, and the spiral optical fiber is spirally wound around the linear optical fiber. The linear optical fiber is used to collect surface wave vibration signals, and the spiral optical fiber is used to collect body wave vibration signals.

[0017] Further preferably, in S2, the preprocessing of the collected vibration signal includes:

[0018] The surface wave vibration signal and the body wave vibration signal are integrated in the time domain to obtain the surface wave strain rate and the body wave strain rate;

[0019] (1)

[0020] (2)

[0021] Converting the surface wave strain rate and the body wave strain rate into the surface wave particle velocity and the body wave particle velocity respectively;

[0022] (3)

[0023] (4)

[0024] Where t represents the moment of the time domain signal, k is the wave number, and w is the circular frequency; and are the original vibration signals of straight and helical optical fibers; and The strain rate signals collected for the strain signals of straight and helical optical fibers; and is the particle velocity signal of straight and spiral optical fiber.

[0025] Further preferably, in S3, the vector decomposition of the two particle velocity signals obtained from the spiral optical fiber and the straight optical fiber includes extracting the body wave component using the following formula:

[0026] (5)

[0027] Among them, sign is the sign function, is the vertical particle velocity signal after vector decomposition, and is the particle velocity signal of straight and spiral optical fiber.

[0028] Further preferably, the upper and lower limit travel times of frozen soil are obtained by connecting the waveforms when the body wave event axis is extracted after removing the surface wave data from the self-excited and self-received records formed by the vector decomposition data.

[0029] Further preferably, when obtaining the upper and lower limit travel times of frozen soil and the velocity of the overlying stratum and the frozen soil layer, the upper limit burial depth and thickness of frozen soil are obtained, the following formula (6) is used to calculate the upper limit burial depth of frozen soil, and formula (7) is used to calculate the thickness of frozen soil;

[0030] Upper limit of permafrost burial depth: (6)

[0031] Thickness of frozen soil:

[0032] (7)

[0033] in, and are the upper burial depth of permafrost and the thickness of permafrost, respectively.

[0034] Further preferably, the overlying formation velocity and the frozen soil layer velocity are calculated based on reference well data, and further include:

[0035] When there are two reference wells,

[0036] (8)

[0037] (9)

[0038] in, 、 、 、 They are the upper limit burial depth of frozen soil, the thickness of frozen soil, the upper limit travel time of frozen soil and the lower limit travel time of frozen soil at the location of reference well 1. 、 、 、 They are the upper limit burial depth of frozen soil, the thickness of frozen soil, the upper limit travel time of frozen soil and the lower limit travel time of frozen soil at the location of reference well 2.

[0039] Further preferably, the overlying formation velocity and the frozen soil layer velocity are calculated based on reference well data, and further include:

[0040] When there is a reference well,

[0041] (10)

[0042] (11)

[0043] in, 、 、 、 They are the upper limit burial depth of frozen soil, the thickness of frozen soil, the upper limit travel time of frozen soil and the lower limit travel time of frozen soil at the reference well location.

[0044] The present invention also provides a plateau permafrost thickness detection and monitoring system based on distributed optical fiber acoustic sensing, which is used to implement the steps of the plateau permafrost thickness detection and monitoring method based on distributed optical fiber acoustic sensing; the system comprises:

[0045] DAS data acquisition module: uses spiral optical fiber and straight optical fiber to collect vibration signals respectively

[0046] The data processing module pre-processes the collected vibration signals and converts them into particle velocity signals; it performs vector decomposition on the two particle velocity signals obtained from spiral optical fibers and linear optical fibers, suppresses the surface wave component and enhances the body wave component.

[0047] Self-excitation and self-receiving record calculation module: self-excitation and self-receiving record of measuring point position according to vector decomposition data; record data and pick up upper and lower limit travel time of frozen soil;

[0048] The permafrost thickness calculation and monitoring module obtains the upper and lower limit burial depth and thickness of permafrost based on the upper and lower limit travel times of permafrost and the velocity of overlying strata and permafrost layer.

[0049] The present application discloses a plateau permafrost thickness detection and monitoring method and system based on distributed fiber optic acoustic sensing, which is mainly used for large-scale, long-distance, real-time dynamic monitoring of the buried depth and thickness of permafrost on plateau railways. Its advantages lie in collecting random perturbation signals by combining spiral optical fibers and linear optical fibers, and suppressing the horizontal surface wave component based on the properties of vector operations, highlighting the vertical body wave (longitudinal wave) component. It has a scientific theoretical basis and good vector decomposition effect. Its advantages lie in calculating the wave velocity values ​​of the overlying bottom layer and permafrost layer of permafrost with the help of reference well data, and obtaining the upper buried depth and thickness of permafrost in combination with self-excited and self-collected records, thereby realizing real-time detection and monitoring of permafrost thickness. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 The figure is a flow chart of the method for detecting and monitoring the thickness of frozen soil on the plateau based on distributed optical fiber acoustic sensing according to the present invention.

[0051] Figure 2 Schematic diagram of the combined layout of spiral optical fiber and straight optical fiber.

[0052] Figure 3 Schematic diagram of vector decomposition of vibration signal.

[0053] Figure 4 Time domain multi-channel self-excited and self-acquired recording of spiral optical fiber data.

[0054] Figure 5 It is the time domain multi-channel self-excited and self-received record of the data after vector decomposition.

[0055] Figure 6 It is a deep domain multi-channel self-excited and self-received record.

[0056] Figure 7 The present invention provides a plateau railway frozen soil thickness monitoring system based on distributed optical fiber acoustic sensing. DETAILED DESCRIPTION

[0057] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0058] like Figure 1 As shown, an embodiment of the present invention provides a method for detecting and monitoring the thickness of frozen soil on a plateau based on distributed optical fiber acoustic sensing, comprising the following steps:

[0059] S1. Laying a spiral optical fiber and a straight optical fiber in the frozen soil according to a predetermined observation position, and using the spiral optical fiber and the straight optical fiber to collect vibration signals respectively; In S1, when the spiral optical fiber and the straight optical fiber are laid out, the straight optical fiber is used as the axis, and the spiral optical fiber is spirally wound around the straight optical fiber. The straight optical fiber is used to collect surface wave vibration signals, and the spiral optical fiber is used to collect body wave vibration signals. Figure 2 shown.

[0060] S2. Preprocess the collected vibration signal to convert it into a particle velocity signal; mainly using the relationship between the particle strain rate and the particle vibration velocity to convert the signal into a particle velocity signal that can be used for physical detection. Further, the preprocessing of the collected vibration signal includes:

[0061] The surface wave vibration signal and the body wave vibration signal are integrated in the time domain to obtain the surface wave strain rate and the body wave strain rate;

[0062] (1)

[0063] (2)

[0064] Converting the surface wave strain rate and the body wave strain rate into the surface wave particle velocity and the body wave particle velocity respectively;

[0065] (3)

[0066] (4)

[0067] Where t represents the moment of the time domain signal, k is the wave number, and w is the circular frequency; and are the original vibration signals of straight and helical optical fibers; and The strain rate signals collected for the strain signals of straight and helical optical fibers; and is the particle velocity signal of straight and spiral optical fiber.

[0068] S3. Vector decomposition of the two particle velocity signals obtained by the spiral fiber and the straight fiber is performed to suppress the surface wave component and enhance the body wave component. The optical fiber as a sensor collects the vibration signal in the radial direction of the fiber. Therefore, the signal collected by the straight fiber is mainly the surface wave component in the horizontal direction, and the signal collected by the spiral fiber is tilted. Therefore, in order to highlight the vertical longitudinal wave component, such as Figure 3 As shown, it is necessary to perform vector decomposition on the particle velocity signals collected by the helical fiber and the straight fiber based on the properties of vector operations. After decomposition, only the vertical component is extracted to achieve the purpose of suppressing facial enhancement body waves. In S3, the two particle velocity signals obtained by the helical fiber and the straight fiber are vector decomposed; including extracting the body wave component using the following formula:

[0069] (5)

[0070] Among them, sign is the sign function, is the vertical particle velocity signal after vector decomposition, and is the particle velocity signal of straight and spiral optical fiber.

[0071] Further preferably, the upper and lower limit travel times of frozen soil are obtained by connecting the waveforms when the body wave event axis is extracted after removing the surface wave data from the self-excited and self-received records formed by the vector decomposition data.

[0072] S4. Record the position of the measuring point by self-excitation and self-receiving according to the data after vector decomposition; pick up the upper and lower limit travel time of frozen soil from the recorded data;

[0073] Based on the interference theory, the self-excitation and self-receiving records of the measuring point are calculated. Figure 4 and Figure 5 The self-excited and self-received records are obtained from the spiral fiber signal and the signal after vector decomposition. It can be clearly seen that the surface wave energy is dominant in the record obtained from the spiral fiber data, while there are obvious body wave phase axes in the record after vector decomposition to remove the surface wave. The two groups of phase axes ( Figure 5 The solid and dashed lines in the figure represent the upper and lower travel time positions of frozen soil, respectively.

[0074] S5. Obtain the upper burial depth and thickness of frozen soil based on the upper and lower travel times of frozen soil and the velocity of the overlying stratum and the frozen soil layer; the velocity of the overlying stratum and the frozen soil layer are calculated based on the reference well data.

[0075] according to Figure 5 Continuity of the mid-phase axis, picking up the travel time of the upper and lower limits of frozen soil and , and obtain the overlying formation velocity based on the reference well and permafrost velocity , thus calculating the upper limit burial depth of frozen soil. According to the upper and lower limit travel times of frozen soil and the velocity of overlying strata and frozen soil layer, the upper limit burial depth and thickness of frozen soil are obtained. The following formula (6) is used to calculate the upper limit burial depth of frozen soil, and formula (7) is used to calculate the thickness of frozen soil;

[0076] Upper limit of permafrost burial depth: (6)

[0077] Thickness of frozen soil:

[0078] (7)

[0079] in, and are the upper burial depth of permafrost and the thickness of permafrost, respectively.

[0080] like Figure 6 As shown in the figure, it is a multi-channel self-excited and self-collected record in the depth domain. It can be clearly seen that the upper and lower limit burial depths of frozen soil and the thickness of frozen soil are further optimized. The overlying stratum velocity and frozen soil layer velocity are calculated based on the reference well data, and also include:

[0081] When there are two reference wells,

[0082] (8)

[0083] (9)

[0084] in, 、 、 、 They are the upper limit burial depth of frozen soil, the thickness of frozen soil, the upper limit travel time of frozen soil and the lower limit travel time of frozen soil at the location of reference well 1. 、 、 、 They are the upper limit burial depth of frozen soil, thickness of frozen soil, upper limit travel time of frozen soil and lower limit travel time of frozen soil at the location of reference well 2.

[0085] Further preferably, the overlying formation velocity and the frozen soil layer velocity are calculated based on reference well data, further comprising:

[0086] When there is a reference well,

[0087] (10)

[0088] (11)

[0089] in, 、 、 、 They are the upper limit burial depth of frozen soil, the thickness of frozen soil, the upper limit travel time of frozen soil and the lower limit travel time of frozen soil at the reference well location.

[0090] When there is no reference well, the overburden velocity and permafrost velocity Obtained based on geological survey results and empirical estimates.

[0091] like Figure 7 As shown, the present invention also provides a plateau frozen soil thickness detection and monitoring system based on distributed optical fiber acoustic sensing, which is used to implement the steps of the plateau frozen soil thickness detection and monitoring method based on distributed optical fiber acoustic sensing; comprising:

[0092] DAS data acquisition module: uses spiral optical fiber and straight optical fiber to collect vibration signals respectively

[0093] The data processing module pre-processes the collected vibration signals and converts them into particle velocity signals; it performs vector decomposition on the two particle velocity signals obtained from spiral optical fibers and linear optical fibers, suppresses the surface wave component and enhances the body wave component.

[0094] Self-excitation and self-receiving record calculation module: self-excitation and self-receiving record of measuring point position according to vector decomposition data; record data and pick up upper and lower limit travel time of frozen soil;

[0095] The permafrost thickness calculation and monitoring module obtains the upper and lower limit burial depth and thickness of permafrost based on the upper and lower limit travel times of permafrost and the velocity of overlying strata and permafrost layer.

[0096] Obviously, the above embodiments are merely examples for clarity of explanation and are not intended to limit the implementation methods. Those skilled in the art will readily appreciate that other variations or modifications based on the above descriptions are possible. It is not necessary and impossible to enumerate all implementation methods here. Obvious variations or modifications arising therefrom remain within the scope of protection of the present invention.

Claims

1. A method for detecting and monitoring the thickness of frozen soil in plateaus based on distributed optical fiber acoustic sensing, characterized in that: The following steps are involved: S1. Deploying a spiral optical fiber and a linear optical fiber in the frozen soil according to a predetermined observation position, and collecting vibration signals using the spiral optical fiber and the linear optical fiber respectively; S2. Preprocessing the collected vibration signal to convert the vibration signal into a particle velocity signal; S3, performing vector decomposition on the two particle velocity signals obtained from the helical optical fiber and the straight optical fiber, suppressing the surface wave component and enhancing the body wave component; S4. Record the position of the measuring point by self-excitation and self-receiving according to the data after vector decomposition; pick up the upper and lower limit travel time of frozen soil from the recorded data; S5. Obtain the upper burial depth and thickness of frozen soil based on the upper and lower travel times of frozen soil and the velocity of the overlying stratum and the frozen soil layer; the velocity of the overlying stratum and the frozen soil layer are calculated based on the reference well data.

2. The plateau frozen soil thickness detection and monitoring method based on distributed optical fiber acoustic sensing according to claim 1 is characterized in that: In S1, when the spiral optical fiber and the linear optical fiber are laid out, the linear optical fiber is used as the axis and the spiral optical fiber is spirally wound around the linear optical fiber. The linear optical fiber is used to collect surface wave vibration signals, and the spiral optical fiber is used to collect body wave vibration signals.

3. The plateau frozen soil thickness detection and monitoring method based on distributed optical fiber acoustic sensing according to claim 1 is characterized in that: In S2, the collected vibration signal is preprocessed, including: The surface wave vibration signal and the body wave vibration signal are integrated in the time domain to obtain the surface wave strain rate and the body wave strain rate; (1) (2) Converting the surface wave strain rate and the body wave strain rate into the surface wave particle velocity and the body wave particle velocity respectively; (3) (4) Where t represents the moment of the time domain signal, k is the wave number, and w is the circular frequency; and are the original vibration signals of straight and helical optical fibers; and The strain rate signals collected for the strain signals of straight and helical optical fibers; and is the particle velocity signal of straight and spiral optical fiber.

4. The method for detecting and monitoring the thickness of frozen soil in plateaus based on distributed optical fiber acoustic sensing according to claim 1 is characterized in that: In S3, the two particle velocity signals obtained from the spiral optical fiber and the straight optical fiber are vector-decomposed, including extracting the body wave component using the following formula: (5) Among them, sign is the sign function, is the vertical particle velocity signal after vector decomposition, and is the particle velocity signal of straight and spiral optical fiber.

5. The method for detecting and monitoring the thickness of frozen soil in plateaus based on distributed optical fiber acoustic sensing according to claim 1 is characterized in that: From the self-excited and self-received records formed by the vector decomposition data, the upper and lower limit travel times of frozen soil are obtained by connecting the waveforms when the body wave phase axis is extracted after removing the surface wave data.

6. The method for detecting and monitoring the thickness of frozen soil in plateaus based on distributed optical fiber acoustic sensing according to claim 1 is characterized in that: According to the upper and lower limit travel times of frozen soil and the velocity of the overlying stratum and frozen soil layer, the upper limit burial depth and thickness of frozen soil are obtained. The following formula (6) is used to calculate the upper limit burial depth of frozen soil, and formula (7) is used to calculate the thickness of frozen soil; Upper limit of permafrost burial depth: (6) Thickness of frozen soil: （7） in, and are the upper burial depth of permafrost and the thickness of permafrost, respectively.

7. The method for detecting and monitoring plateau frozen soil thickness based on distributed optical fiber acoustic sensing according to claim 1 is characterized in that: The overlying stratum velocity and permafrost velocity are calculated based on reference well data, and also include: When there are two reference wells, （8） （9） in, 、 、 、 They are the upper limit burial depth of frozen soil, the thickness of frozen soil, the upper limit travel time of frozen soil and the lower limit travel time of frozen soil at the location of reference well 1. 、 、 、 They are the upper limit burial depth of frozen soil, thickness of frozen soil, upper limit travel time of frozen soil and lower limit travel time of frozen soil at the location of reference well 2.

8. The method for detecting and monitoring plateau frozen soil thickness based on distributed optical fiber acoustic sensing according to claim 1 is characterized in that: The overlying stratum velocity and permafrost velocity are calculated based on reference well data, and also include: When there is a reference well, （10） （11） in, 、 、 、 They are the upper limit burial depth of frozen soil, the thickness of frozen soil, the upper limit travel time of frozen soil and the lower limit travel time of frozen soil at the reference well location.

9. A plateau permafrost thickness detection and monitoring system based on distributed fiber optic acoustic sensing, configured to implement the steps of the plateau permafrost thickness detection and monitoring method based on distributed fiber optic acoustic sensing as described in any one of claims 1 to 8; comprising: DAS data acquisition module: uses spiral optical fiber and straight optical fiber to collect vibration signals respectively The data processing module pre-processes the collected vibration signals and converts them into particle velocity signals; it performs vector decomposition on the two particle velocity signals obtained from spiral optical fibers and linear optical fibers, suppresses the surface wave component and enhances the body wave component. Self-excitation and self-receiving record calculation module: self-excitation and self-receiving record of measuring point position according to vector decomposition data; record data and pick up upper and lower limit travel time of frozen soil; The permafrost thickness calculation and monitoring module obtains the upper and lower limit burial depth and thickness of permafrost based on the upper and lower limit travel times of permafrost and the velocity of overlying strata and permafrost layer.

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