Ground surface matrix multi-parameter optical fiber monitoring system and method

Abstract

The invention relates to the technical field of surface matrix parameter monitoring, in particular to a surface matrix multi-parameter optical fiber monitoring system and method. The method comprises the following steps: an optical fiber moisture content temperature optical cable used for monitoring the temperature and moisture content corresponding to a surface matrix; the optical fiber water level sensor is used for monitoring the underground water level corresponding to the surface matrix; the optical fiber matrix suction sensor is used for monitoring matrix suction corresponding to the surface matrix; the optical fiber interrogator, the optical fiber moisture content temperature optical cable, the optical fiber water level sensor and the optical fiber matrix suction sensor are respectively connected with the optical fiber interrogator through communication optical cables, and the optical fiber interrogator generates monitoring parameters corresponding to temperature, moisture content, underground water level and matrix suction; the optical fiber demodulator transmits the monitoring data to the remote multi-parameter monitoring module, and the remote multi-parameter monitoring module is used for calculating, managing and analyzing the temperature, the moisture content, the underground water level and the matrix suction corresponding to the surface matrix according to the monitoring data.

Description

Technical Field

[0001] This application relates to the technical field of surface substrate parameter monitoring, and particularly to a multi-parameter optical fiber monitoring system and method for surface substrates. Background Art

[0002] As the basic material for nurturing and supporting various natural resources such as soil, forests, grasslands, water, and wetlands on the earth's surface, the dynamic changes in the physical properties (such as temperature, water content, groundwater level, matrix suction, etc.) of the surface substrate directly affect the utilization efficiency of natural resources and the effectiveness of ecological protection. For example, the fluctuations in the temperature of the surface substrate layer not only determine the growth cycles of vegetation and crops, but also indirectly affect soil fertility, vegetation root development, and ecosystem stability by influencing changes in matrix water content and suction. In extreme cases, it may trigger disasters such as soil drought and salinization; abnormal fluctuations in the groundwater level may lead to ecological problems such as soil salinization, vegetation death, and wetland expansion. Therefore, long-term, real-time, and in-situ monitoring of multiple physical parameters such as surface substrate temperature, water content, groundwater level, and matrix suction is a key technical requirement for mastering the evolution law of surface substrate state, warning ecological risks, and supporting the scientific protection and rational development of natural resources.

[0003] Currently, the monitoring methods for the above parameters generally have significant deficiencies: traditional temperature monitoring (such as resistance thermometers, thermocouples, infrared thermometry), water content monitoring (remote sensing method, time domain reflectometry, neutron method), groundwater level monitoring (pressure type water level gauge, capacitance type water level gauge), and matrix suction monitoring (tensiometer method, thermocouple humidity method) all use independent devices for decentralized measurement, which not only leads to great integration difficulty and high installation cost of the monitoring system, but also is limited by problems such as insufficient equipment durability and weak anti-interference ability, making it difficult to achieve long-term in-situ monitoring; at the same time, the data of each parameter lacks coordination, and a systematic matrix physical state evaluation system cannot be formed, making it difficult to meet the needs of multi-parameter coupling analysis in complex ecological environments.

[0004] Optical fiber monitoring technology has shown application potential in the fields of geotechnical engineering, structural health monitoring, etc. due to its advantages such as small volume, anti-electromagnetic interference, strong durability, and distributed measurement. However, for the special requirements of multi-parameter monitoring of surface substrates, there are still key bottlenecks in existing optical fiber technologies: on the one hand, the traditional optical fiber temperature and water content monitoring functions are independent of each other, lacking an integrated design, especially in water content measurement, it is difficult to balance energy consumption control and measurement accuracy; on the other hand, existing optical fiber sensors mostly rely on single-parameter perception, and a collaborative monitoring mechanism for temperature, water content, groundwater level, and matrix suction has not been formed, making it impossible to meet the actual needs of multi-physical field coupling analysis of surface substrates.

[0005] Based on this, there is an urgent need for a system solution that can integrate the advantages of optical fiber monitoring technology and achieve multi-parameter integration and long-term stable monitoring. Summary of the Invention

[0006] The present application provides a multi-parameter optical fiber monitoring system and method for surface matrix, aiming to solve the key bottlenecks still existing in the existing optical fiber technology for the special requirements of multi-parameter monitoring of surface matrix: on the one hand, the traditional optical fiber temperature and water content monitoring functions are independent of each other, lacking an integrated design. Especially in the measurement of water content, it is difficult to balance energy consumption control and measurement accuracy; on the other hand, the existing optical fiber sensors mostly rely on single-parameter perception, and do not form a collaborative monitoring mechanism for temperature, water content, groundwater level, and matrix suction, and cannot meet the actual needs of coupled analysis of multi-physical fields of surface matrix and other problems.

[0007] In a first aspect, an embodiment of the present application provides a multi-parameter optical fiber monitoring system for surface matrix, including: an optical fiber water content and temperature optical cable for monitoring the temperature and water content corresponding to the surface matrix. The optical fiber water content and temperature optical cable fixes the array water content and temperature measurement gratings on the surface of a customized hollow copper rod by full pasting and encapsulates them into an optical cable. A resistance wire equal in length to the copper rod is inserted into the customized hollow copper rod; the optical fiber water content and temperature optical cable is arranged in a borehole corresponding to the surface matrix, and the borehole is backfilled with undisturbed soil consistent with the formation soil properties; an optical fiber water level sensor for monitoring the groundwater level corresponding to the surface matrix; an optical fiber matrix suction sensor for monitoring the matrix suction corresponding to the surface matrix; an optical fiber demodulator. The optical fiber water content and temperature optical cable, the optical fiber water level sensor, and the optical fiber matrix suction sensor are respectively connected to the optical fiber demodulator through communication optical cables, and the optical fiber demodulator generates monitoring parameters corresponding to the temperature, water content, groundwater level, and matrix suction; a heating control module. The optical fiber water content and temperature optical cable is connected to the heating control module through a wire, and the heating control module remotely controls the voltage, time, and channels of the heating task; a remote multi-parameter monitoring module. The optical fiber demodulator transmits the monitoring data to the remote multi-parameter monitoring module, and the remote multi-parameter monitoring module is used to calculate, manage, and analyze the temperature, water content, groundwater level, and matrix suction corresponding to the surface matrix according to the monitoring data.

[0008] In a second aspect, the present application provides a multi-parameter optical fiber monitoring method for surface matrix, which is applied to the remote multi-parameter monitoring module of the multi-parameter optical fiber monitoring system for surface matrix provided in any embodiment of the present application. The method includes: obtaining the monitoring data transmitted by the optical fiber demodulator through the data transmission module; the monitoring data includes temperature, water content, groundwater level, and matrix suction; remotely controlling the voltage, time, and channels of the heating task through the heating control module; Calculate, manage, and analyze the temperature, water content, groundwater level, and matrix suction corresponding to the surface matrix based on the monitoring data.

[0009] Through hardware integration design and multi-parameter collaborative monitoring mechanism, the multi-parameter optical fiber monitoring system for surface matrix realizes the integrated and precise monitoring of the temperature, water content, groundwater level, and matrix suction of the surface matrix. The corresponding structure design of the system includes using an array of water content and temperature measurement gratings fully pasted and fixed on the surface of a customized hollow copper rod, and encapsulating it into an optical cable. Equal-length resistance wires are inserted into the copper rod to form a "heating-sensing" integrated structure. The installation method is to place the sensing optical cable in the borehole of the surface matrix, and backfill the borehole with undisturbed soil consistent with the formation soil properties to ensure the physical property matching between the sensor and the surrounding matrix, reducing environmental interference. The grating array synchronously senses the temperature and water content. The resistance wire can actively heat the matrix under the drive of the heating control module, optimize the water content measurement accuracy through the thermal response characteristics, and at the same time control the energy consumption (such as heating on demand to avoid continuous high power consumption).

[0010] By configuring an optical fiber water level sensor and an optical fiber matrix suction sensor, independent monitoring of the groundwater level and matrix suction is carried out respectively, forming a collaborative monitoring network of four parameters (temperature, water content, water level, matrix suction) with the optical fiber water content and temperature optical cable. Each sensor is uniformly connected to the optical fiber demodulator through a communication optical cable to realize the synchronous acquisition and digital conversion of multi-source signals, and generate standardized monitoring parameters.

[0011] The heating control module is used to remotely adjust the voltage, time, and channel of the resistance wire heating, realize the directional heating of the matrix in a specific area, and combine with the temperature-water content coupling model to balance the measurement accuracy and energy consumption through a dynamic heating strategy (such as short-time heating to obtain transient thermal signals and avoid excessive energy consumption caused by long-term heating).

[0012] The remote multi-parameter monitoring module is used to receive the data of the demodulator, integrate data calculation (such as inverting the water content based on the heat conduction model), storage management, and multi-physical field coupling analysis functions, support real-time visualization, historical data traceability, and anomaly warning, and provide comprehensive data support for the stability assessment of the surface matrix.

[0013] In traditional technologies, the temperature and water content monitoring functions are separated, and sensors need to be independently deployed. This system integrates the grating array and the heating structure to synchronously realize the dual-parameter measurement in a single optical cable, reducing the number of sensors and the installation complexity, and lowering the monitoring cost. The design of backfilling the borehole with undisturbed soil ensures the physical compatibility between the sensor and the matrix, avoids measurement errors caused by material differences, and improves the data reliability.

[0014] The heating control module dynamically adjusts the heating parameters (voltage, time) of the resistance wire, enabling short-term heating to be initiated when needed (such as in periodic calibration or high-precision measurement scenarios). By leveraging the rapid temperature response, the water content can be inversely calculated, avoiding the high energy consumption issues associated with traditional continuous monitoring. Additionally, the measurement sensitivity of the water content is enhanced through the thermal signal amplification effect (especially suitable for low water content scenarios).

[0015] Integrating four key parameters: temperature, water content, groundwater level, and matrix suction, a multi-field coupling monitoring system for the "water-thermal-mechanical" state of the surface matrix is formed, meeting the analytical requirements for the interaction of multiple matrix parameters in fields such as slope stability, land degradation, and eco-hydrology (e.g., evaluating changes in soil shear strength through the correlation model between matrix suction and water content).

[0016] The remote control and data processing module automates the entire process from signal acquisition, heating strategy to data analysis, reducing manual intervention and supporting long-term unattended monitoring. Meanwhile, through multi-parameter correlation analysis, it provides a data basis for predicting the evolution trend of the surface matrix, facilitating disaster warning and environmental governance decision-making.

[0017] Optical fiber sensing technology itself has advantages such as electromagnetic interference resistance, corrosion resistance, and long-distance transmission. Combined with customized packaging (protected by a hollow copper rod and backfilled with undisturbed soil), the durability and environmental adaptability of the sensor in geotechnical media are enhanced, making it suitable for long-term monitoring under complex field geological conditions.

[0018] In summary, through three core technologies: hardware function integration, multi-parameter collaborative sensing, and intelligent heating control, this system overcomes the problems of single-parameter independent measurement and the contradiction between energy consumption and accuracy in traditional optical fiber monitoring, constructing a multi-physical field coupling monitoring system for the surface matrix, and providing a high-precision, low-energy consumption, and intelligent comprehensive solution for fields such as geological disaster prevention, ecological environment monitoring, and engineering construction.

[0019] It should be understood that the above general description and the following detailed description are merely exemplary and explanatory, and do not limit this application. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] To more clearly illustrate the technical solutions of the embodiments of this application, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are some embodiments of this application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0021] Figure 1 Schematic diagram of the multi-parameter monitoring system for the surface matrix of the present invention; Figure 2 is Figure 1 Schematic diagram of the internal structure of the optical fiber water content and temperature optical cable in Figure 3 is Figure 1 a schematic cross-sectional structure diagram of an optical fiber water level sensor in Figure 4 is Figure 1 a schematic cross-sectional structure diagram of an optical fiber matrix suction sensor in Figure 5 a schematic flow chart of the steps of a method for monitoring multi-parameters of surface matrix by optical fiber provided by an embodiment of the present application; Figure 6 a schematic block diagram of the structure of a device for monitoring multi-parameters of surface matrix by optical fiber provided by an embodiment of the present application; Figure 7 a schematic block diagram of the structure of a remote multi-parameter monitoring module provided by an embodiment of the present application; The corresponding reference numerals in the present application are: 1. Optical fiber moisture content and temperature optical cable; 11. Moisture content and temperature measurement grating; 12. Customized hollow copper rod; 13. Resistance wire; 14. Conducting wire; 2. Optical fiber water level sensor; 21. Water inlet base; 22. Bottom film mounting seat; 23. Outer cylinder; 24. Pressure film; 25. Strain measurement grating; 3. Optical fiber matrix suction sensor; 31. Encapsulation main body; 32. Filter element; 33. Connecting socket; 34. Suction measurement grating; 35. Temperature measurement grating; 4. Liquid level tube; 5. Optical fiber demodulator; 51. Data transmission module; 6. Remote multi-parameter monitoring module; 7. Heating control module; 71. Heating power supply; 72. Control module; 8. Solar power supply system; 81. Solar panel; 82. Bracket; 83. Storage battery; 84. Controller; 9. System integration cabinet.

[0022] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. Specific embodiments

[0023] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0024] The flow chart shown in the accompanying drawings is only an example, and does not necessarily include all the contents and operations / steps, nor does it necessarily need to be executed in the described order. For example, some operations / steps can also be decomposed, combined or partially merged, so the actual execution order may change according to the actual situation.

[0025] It should be understood that, for the convenience of clearly describing the technical solutions of the embodiments of the present invention, in the embodiments of the present invention, terms such as "first" and "second" are used to distinguish identical or similar items with basically the same functions and effects. Those skilled in the art can understand that terms such as "first" and "second" do not limit the quantity and execution order, and "first", "second", etc. do not necessarily mean different.

[0026] It should be understood that the terms used in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application. As used in the specification of this application and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include the plural forms.

[0027] It should also be understood that the term "and / or" used in the specification of this application and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0028] The following will describe in detail some embodiments of this application with reference to the accompanying drawings. Without conflict, the following embodiments and the features in the embodiments can be combined with each other.

[0029] As the basic material for nurturing and supporting various natural resources such as soil, forests, grasslands, water, and wetlands on the earth's surface, the physical properties (such as temperature, moisture content, groundwater level, matrix suction, etc.) of the surface substrate directly affect the utilization efficiency of natural resources and the effectiveness of ecological protection. For example, the fluctuation of the temperature of the surface substrate layer not only determines the growth cycle of vegetation and crops, but also indirectly affects soil fertility, vegetation root development, and ecosystem stability by affecting the changes in matrix moisture content and suction. In extreme cases, it may cause disasters such as soil drought and salinization; the abnormal rise and fall of the groundwater level may lead to ecological problems such as soil salinization, vegetation death, and wetland expansion. Therefore, long-term, real-time, and in-situ monitoring of multiple physical parameters such as the temperature, moisture content, groundwater level, and matrix suction of the surface substrate is a key technical requirement for mastering the evolution law of the surface substrate state, warning ecological risks, and supporting the scientific protection and reasonable development of natural resources.

[0030] At present, the monitoring methods for the above parameters generally have significant defects: traditional temperature monitoring (such as resistance thermometers, thermocouples, infrared thermometry), moisture content monitoring (remote sensing method, time domain reflectometry, neutron method), groundwater level monitoring (pressure type water level gauge, capacitive water level gauge), and matric suction monitoring (tensiometer method, thermocouple humidity method) all use independent devices for decentralized measurement, which not only leads to great difficulty in integrating the monitoring system and high installation costs, but also is limited by problems such as insufficient durability of the devices and weak anti-interference ability, making it difficult to achieve long-term in-situ monitoring; at the same time, the data of each parameter lacks coordination, and a systematic evaluation system of the physical state of the substrate cannot be formed, making it difficult to meet the needs of multi-parameter coupling analysis in complex ecological environments.

[0031] Optical fiber monitoring technology has shown application potential in the fields of geotechnical engineering, structural health monitoring, etc. due to its advantages such as small size, electromagnetic interference resistance, strong durability, and distributed measurement. However, for the special requirements of multi-parameter monitoring of surface substrates, there are still key bottlenecks in existing optical fiber technologies: on the one hand, the traditional optical fiber temperature and moisture content monitoring functions are independent of each other and lack an integrated design. Especially in moisture content measurement, it is difficult to balance energy consumption control and measurement accuracy; on the other hand, existing optical fiber sensors mostly rely on single-parameter perception, and a coordinated monitoring mechanism for temperature, moisture content, groundwater level, and matric suction has not been formed, making it impossible to meet the actual needs of multi-physical field coupling analysis of surface substrates.

[0032] Based on this, there is an urgent need for a system solution that can integrate the advantages of optical fiber monitoring technology and achieve multi-parameter integration and long-term stable monitoring.

[0033] Such as Figures 1-4As shown in the figure, the present application provides a multi-parameter optical fiber monitoring system for surface matrix, including: an optical fiber moisture content and temperature cable 1, which is used to monitor the temperature and moisture content corresponding to the surface matrix. The optical fiber moisture content and temperature cable 1 fixes the array moisture content and temperature measurement gratings 35 on the surface of the customized hollow copper rod 12 by full pasting and encapsulates them into a cable. A resistance wire 13 equal in length to the copper rod is inserted into the customized hollow copper rod 12; the optical fiber moisture content and temperature cable 1 is arranged in a borehole corresponding to the surface matrix, and the borehole is backfilled with undisturbed soil consistent with the formation soil properties; an optical fiber water level sensor 2, which is used to monitor the groundwater level corresponding to the surface matrix; an optical fiber matrix suction sensor 3, which is used to monitor the matrix suction corresponding to the surface matrix; an optical fiber demodulator 5, the optical fiber moisture content and temperature cable 1, the optical fiber water level sensor 2, and the optical fiber matrix suction sensor 3 are respectively connected to the optical fiber demodulator 5 through communication cables, and the optical fiber demodulator 5 generates monitoring parameters corresponding to the temperature, moisture content, groundwater level, and matrix suction; a heating control module 7, the optical fiber moisture content and temperature cable 1 is connected to the heating control module 7 through a wire 14, and the heating control module 7 remotely controls the voltage, time, and channel of the heating task; a remote multi-parameter monitoring module 6, the optical fiber demodulator 5 transmits the monitoring data to the remote multi-parameter monitoring module 6, and the remote multi-parameter monitoring module 6 is used to calculate, manage, and analyze the temperature, moisture content, groundwater level, and matrix suction corresponding to the surface matrix according to the monitoring data.

[0034] Specifically, based on optical fiber sensing technology, the present system constructs a technical solution for integrated monitoring of multi-parameters such as temperature, moisture content, groundwater level, and matrix suction. The optical fiber moisture content and temperature cable 1 uses fiber Bragg gratings (FBGs) distributed in an array as sensitive units, and is fixed on the surface of the customized hollow copper rod 12 through a full pasting process to form a high-density temperature-moisture content composite sensing unit. A resistance wire 13 equal in length to the rod body is built into the hollow copper rod as an active heating element for periodic heating during moisture content measurement. Utilizing the characteristic that the wavelength of the FBG changes with temperature, the matrix temperature is directly sensed; Moisture content monitoring: The copper rod is heated by the resistance wire 13. Based on the heat conduction theory, the matrix moisture content is inversely calculated using the temperature response curve (the moisture content affects the matrix thermal conductivity, and the temperature decay rate after heating is negatively correlated with the moisture content). Encapsulation process: The hollow copper rod and the grating are encapsulated into a cable, which has both heat conduction and mechanical protection functions and can adapt to complex field environments.

[0035] The optical fiber water level sensor 2 is based on the pressure-sensitive characteristic of the FBG. Through an elastic diaphragm or bellows structure, the water pressure caused by the water level change is converted into grating strain to achieve high-precision measurement of the groundwater level.

[0036] The fiber optic matrix suction sensor 3 uses a porous ceramic filter element 32 as the matrix suction conduction medium. Combining with the FBG strain sensing principle, it converts the change of matrix suction into the grating wavelength drift to achieve long-term monitoring of unsaturated matrix suction.

[0037] The fiber optic demodulator 5 integrates a multi-channel wavelength demodulation module to collect the wavelength signals of each sensor in real time and convert them into physical parameters such as temperature, water content, groundwater level, and matrix suction through a calibration algorithm.

[0038] The heating control module 7 is used to remotely control the heating voltage, time, and channels of the heating wire 13 to achieve on-demand heating (such as periodic short-term heating), balance energy consumption and measurement accuracy, and avoid moisture loss in the matrix caused by continuous heating. Based on cloud computing and Internet of Things technologies, it receives the data from the demodulator and conducts multi-parameter coupling analysis to construct a matrix physical state model to support real-time warning, trend prediction, and ecological risk assessment.

[0039] Through the innovative structural design of the hollow copper rod and the heating wire 13, the temperature and water content monitoring functions are integrated into the same optical cable, solving the problems of independent functions and scattered measurements of traditional fiber optic sensors. Using the periodic heating of the heating wire 13 and combining with the high-precision temperature measurement of FBG, the water content is inversely calculated through a heat conduction model, taking into account both energy consumption control (only consuming energy during heating) and measurement accuracy (avoiding energy loss in steady-state heating). Through unified demodulation and data synchronization, spatio-temporal collaborative acquisition of temperature, water content, groundwater level, and matrix suction is realized, supporting multi-physical field coupling analysis (such as the impact of temperature-water content linkage on root development).

[0040] During the actual construction process, the drilling depth and position can be determined according to the monitoring requirements. The drilling diameter is slightly larger than the outer diameter of the sensing optical cable to ensure the smooth lowering of the optical cable. After drilling, backfill the original soil consistent with the formation soil properties (sieving to remove impurities), compact it in layers, and restore the original structure of the matrix to avoid measurement errors caused by disturbance.

[0041] The fiber optic water content and temperature optical cable 1 is laid along the axial direction of the drilling hole, and the hollow copper rod is in close contact with the matrix to ensure the heat conduction efficiency; the heating wire 13 is led out through the wire 14 and connected to the heating control module 7. The fiber optic water level sensor 2 is deployed at the bottom of the drilling hole or in the groundwater monitoring well, and the sensor probe is in direct contact with the water body to prevent signal attenuation through waterproof encapsulation. The fiber optic matrix suction sensor 3 is buried in the unsaturated matrix layer, and the porous ceramic filter element 32 is in full contact with the matrix to ensure no lag in suction conduction.

[0042] Each sensor is connected to the fiber optic demodulator 5 through a low-loss communication optical cable. The demodulator is deployed in a field monitoring base station or a protective box, and supports solar power supply or mains power access. The heating control module 7 communicates with the demodulator through RS485 or Ethernet, receives remote instructions and controls the heating parameters of the heating wire 13 (such as heating voltage 24V, single heating time 30s, heating once every 1 hour).

[0043] The heating control module 7 starts the heating of the heating wire 13 according to a preset cycle. The hollow copper rod quickly heats up and transfers heat to the substrate; the FBG real-time collects the temperature change curve during the heating process, and calculates the moisture content through a preset heat conduction model (considering the relationship between the thermal conductivity, specific heat capacity and moisture content of the substrate). The fiber optic demodulator 5 synchronously collects temperature, water level and suction signals at a frequency of 1Hz~10Hz to avoid data deviation caused by asynchronous acquisition; after the data is denoised and filtered, it is transmitted to the remote monitoring platform through communication modules such as 4G / Beidou.

[0044] The monitoring module establishes a baseline of the physical state of the substrate based on historical data, identifies abnormal states through threshold judgment (such as a sudden rise in the groundwater level exceeding 50cm / h) or machine learning models, and automatically triggers ecological risk warnings (such as soil salinization risks); it supports multi-parameter correlation analysis, for example, drawing spatio-temporal distribution maps of temperature-moisture content, and coupling curves of groundwater level and substrate suction, providing a decision-making basis for natural resource protection.

[0045] Traditional monitoring requires the deployment of multiple sets of independent devices (such as thermometers, TDRs, water level gauges). This system integrates fiber optic sensors, reducing the number of devices by more than 70%, and reducing the installation cost and maintenance difficulty. Fiber optic sensors are resistant to electromagnetic interference and corrosion, and the encapsulation of the hollow copper rod improves mechanical durability, solving the problems of traditional electronic sensors (such as resistance thermometers, neutron meters) being vulnerable to environmental interference and short lifespan, and supporting in-situ monitoring for more than 5 years. Breaking through the limitation of isolated traditional monitoring data, realizing the spatio-temporal synchronous acquisition of temperature, moisture content, water level and suction, and providing data support for revealing the coupling mechanism of the substrate physical field (such as the chain reaction of the decrease in substrate suction caused by the increase in temperature).

[0046] By adopting the "intermittent heating-transient heat response" measurement method, only consumes electric energy during the heating period (about 1 / 20 of the energy consumption of the traditional continuous heating method), and at the same time uses the high thermal conductivity of the copper rod to improve the temperature measurement resolution (up to 0.1°C), and the moisture content measurement accuracy reaches ±3% (volume moisture content).

[0047] The fiber optic sensing optical cable can achieve array layout with a meter-level spacing, constructing a distributed monitoring network of surface substrate physical parameters. Compared with traditional single-point measurement, it greatly improves the spatial resolution and captures micro-scale environmental changes (such as local moisture content anomalies in the root zone).

[0048] Through multi-parameter coupling analysis, the impact of matrix status on vegetation and soil (such as the synergistic effect of groundwater level drop and matrix suction increase leading to water shortage in vegetation roots) is evaluated in real time, providing accurate data for wetland protection, farmland irrigation optimization, and salinization prevention and control, and facilitating scientific management of natural resources and early warning of ecological risks.

[0049] In summary, this system is suitable for typical ecological zones such as forests, grasslands, farmlands, and wetlands. It can support major needs such as evaluation of the effectiveness of ecological restoration in national land space, efficient use of water resources, and research on the impact of climate change on surface matrices. It can promote the upgrading of monitoring technology from "single-point discreteness" to "full-domain coordination", and has significant environmental benefits and engineering application value.

[0050] In some embodiments, after lowering the optical fiber moisture content temperature cable and the optical fiber matrix suction sensor to the specified position in the borehole, backfilling with original soil consistent with the soil properties of the formation; lowering the liquid level pipe 4 into the liquid level hole, and lowering the optical fiber water level sensor to a position below the water level in the liquid level pipe; connecting the optical fiber moisture content temperature cable to the heating control module through a wire, and connecting the optical fiber moisture content temperature cable, the optical fiber matrix suction sensor, and the optical fiber water level sensor to the optical fiber demodulator through leads, respectively, to obtain monitoring wavelength data; transmitting the monitoring wavelength data to the remote multi-parameter monitoring system through a data transmission module, and configuring the corresponding algorithm in the system to calculate the temperature, moisture content, water level, and matrix suction.

[0051] Among them, through the formula Calculate the temperature of the soil using the formula Calculate the moisture content of soil: Where, T is the soil temperature, KT is the temperature coefficient of the moisture content temperature measurement grating, ΔλT is the wavelength change of the moisture content temperature measurement grating, T0 is the initial temperature, θ is the soil moisture content, Tt is the temperature characteristic value, which can be obtained according to the temperature rise value measured by the moisture content temperature measurement grating after heating for 15 minutes in the moisture content test, A, B, and C are the moisture content temperature correlation coefficients, which can be obtained according to the indoor soil sample calibration experiment.

[0052] By formula Calculate the change in groundwater level, where D is the change in groundwater level, KD is the liquid level coefficient of the strain measurement grating 25, and ΔλD is the wavelength change of the strain measurement grating By formula and Calculate matrix suction; where, , are the temperature sensitivity coefficients of the suction measurement grating and the temperature measurement grating, is the humidity sensitivity coefficient of the suction measurement grating, Δ λ 1 and Δ λ2 is the wavelength change of the suction measurement grating and the temperature measurement grating, and are the initial temperature and relative humidity, is matrix suction; R is the universal gas constant, which is 8.31432 J / (molK); T is the soil temperature; is the volume of water or the reciprocal of water, i.e. 1 / , is the density of water, when t =20℃, =998kg / m 3 ; ω v is the gram molecular weight of water vapor, which is 18.016 kg / k mol, RH It is the soil pore gas humidity.

[0053] In some embodiments, in the optical fiber moisture content temperature cable 1, the array moisture content temperature measurement grating 35 is fixed to the surface of the customized hollow copper rod 12 by a full-adhesion method, so as to reduce the single-grating fusion point and operation difficulty by a full-adhesion method; the customized hollow copper rod 12 is made of metal, and the length of the resistance wire 13 inserted inside is equal to the length of the customized hollow copper rod 12, so as to realize point heat source heating and reduce energy consumption; the array moisture content temperature measurement grating 35 measures the temperature by measuring the stretching amount caused by the thermal expansion of the customized hollow copper rod 12, and the resistance wire 13 is used to realize point heat source heating to measure the moisture content, thereby realizing integrated monitoring of temperature and moisture content.

[0054] In the design of the optical fiber moisture content temperature cable 1, the array-distributed moisture content temperature measurement grating 35 (such as fiber Bragg grating, FBG) is first fixed on the surface of the customized hollow copper rod 12 through a full-pasting process. The full-pasting method uses a high-strength thermal conductive adhesive (such as epoxy resin-based thermal conductive adhesive) to tightly fit the grating along the axial direction of the copper rod, eliminating the fusion point of the single grating independent package and simplifying the assembly process. The customized hollow copper rod 12 is made of a high-thermal conductivity metal material (such as copper) with a wall thickness of 0.5~1mm. A resistance wire 13 (such as a nickel-chromium alloy wire) of the same length as the copper rod is inserted inside. The two ends of the resistance wire 13 are led out through a high-temperature resistant wire 14 and connected to the external heating control module 7. The grating measures the axial tensile strain (ΔL / L) generated by the thermal expansion of the copper rod, combined with the metal thermal expansion coefficient (copper's α=17×10 -6 / ℃), converting the wavelength drift (Δλ) into a temperature value (ΔT=Δλ / (K_T*λ0), K_T is the temperature sensitivity coefficient). After the resistance wire 13 is energized, it acts as a point heat source, and uses the uniform thermal conductivity of the copper rod to form radial heat diffusion in the surrounding matrix. By monitoring the temperature response curve before and after heating (such as the cooling rate), the moisture content is inverted in combination with the heat conduction model.

[0055] Reduce the operation difficulty of single-grid independent installation by full-pasting method, avoid the splicing error of multi-grids, and improve the consistency of sensors; after eliminating the fusion points, reduce the risk of grating detachment and extend the service life. The metal material of the hollow copper rod ensures rapid and uniform heat transfer. The equal-length resistance wires 13 achieve an approximation of "linear heat source", reducing energy loss compared with point heat sources and increasing the heating efficiency by more than 30%; intermittent heating on demand (non-continuous operation) reduces the energy consumption by 80% compared with the traditional continuous heating scheme. Integrating the temperature and moisture content monitoring functions on the same copper rod avoids the spatial asynchronous error of traditional independent sensors, realizes synchronous measurement of dual parameters at the same position, and provides accurate data for thermo-hydraulic coupling analysis (such as the correction of moisture content measurement by temperature).

[0056] In some embodiments, the fiber optic water level sensor 2 includes: a water inlet base 21, a bottom film mounting seat 22, an outer cylinder 23 and a pressure film 24. The water inlet base 21 and the outer cylinder 23 enclose a cavity. The bottom film mounting seat 22 is located in the cavity and is provided with a deformable pressure film 24. A strain fiber optic grating is arranged on the surface of the pressure film 24. The deformation of the pressure film 24 caused by the liquid height difference acts on the strain fiber optic grating to realize the monitoring of tiny changes in the groundwater level.

[0057] The structure of the fiber optic water level sensor 2 includes a water inlet base 21, a bottom film mounting seat 22, an outer cylinder 23 and a pressure film 24. The water inlet base 21 is a porous metal plate (such as stainless steel), which is welded to the outer cylinder 23 (a cylindrical metal pipe) to form a cavity with a sealed bottom. The height of the cavity is 5 - 10 cm. The bottom film mounting seat 22 is an annular metal part, which is fixed in the middle of the outer cylinder 23, and a deformable pressure film 24 (such as a silicone rubber film with a thickness of 0.3 mm) is pasted on it. The center position of the lower surface of the pressure film 24 is pasted with a strain fiber optic grating by glue, and both ends of the grating are fixed on the inner wall of the outer cylinder 23 to form a cantilever beam structure. When the groundwater level changes, the water pressure is transmitted to the pressure film 24 through the pores of the water inlet base 21, causing it to produce a flexural deformation (Δd), driving the grating to produce an axial strain (ε = Δd / L, where L is the grating gauge length), calculating the water pressure through the wavelength drift amount (ΔP = K_P * Δλ, where K_P is the pressure sensitivity coefficient), and then converting it into the water level height h according to the hydrostatic pressure formula (P = ρgh).

[0058] The flexible design of the pressure membrane 24 amplifies minute water pressure changes (e.g., a 0.1 cm water level change corresponds to a 0.01 mm membrane deformation). Combining with the high-precision measurement of FBG (strain resolution of 1 με), it realizes millimeter-level accuracy monitoring of the groundwater level (error ±1 mm). The porous design of the water inlet base 21 allows water to freely enter and exit, while filtering sediment (pore size 0.1 mm) to avoid blockage. The sealing structure between the pressure membrane 24 and the outer cylinder 23 prevents corrosive liquids from invading, making it suitable for complex water environments such as salt water and sewage. Based on the linear relationship between strain and pressure, the sensor does not require on-site calibration after factory calibration, reducing maintenance costs. Without electronic components contacting the water body, it avoids electrochemical corrosion, and its lifespan is extended by more than 2 times compared to traditional pressure water level gauges.

[0059] In some embodiments, the fiber optic matrix suction sensor 3 includes: a packaging body 31, a filter element 32, a connecting socket 33, a suction measurement grating 34, and a temperature measurement grating 35. One end of the packaging body 31 is provided with a filter element 32 sintered at high temperature, and the other end fixes the filter element 32 through the connecting socket 33. The suction measurement grating 34 is coated with a humidity-sensitive material, polyimide, to respond to humidity and suction changes, and the temperature measurement grating 35 is coated with acrylate to separately respond to temperature changes and is used for temperature compensation calculation.

[0060] The packaging body 31 of the fiber optic matrix suction sensor 3 is a cylindrical PVC pipe. One end is embedded with a porous ceramic filter element 32 sintered at high temperature (pore size 1 - 5 μm, permeable to water but not air), and the other end fixes the filter element 32 through a threaded connecting socket 33. The inside of the filter element 32 is filled with a saturated salt solution (such as KCl solution), which balances with the external matrix moisture through capillary action. The surface of the suction measurement grating 34 is coated with a polyimide film (thickness 5 μm), and this material is sensitive to humidity. After absorbing moisture, it expands and generates axial strain to respond to matrix suction changes. The temperature measurement grating 35 is coated with an acrylate protective layer (thickness 20 μm), which is only sensitive to the thermal expansion caused by temperature and is used to compensate for the temperature interference in suction measurement. The two gratings are connected in series on the same optical fiber, and the temperature (Δλ_T) and suction (Δλ_h) signals are separated through wavelength demodulation. Finally, the matrix suction h_m is calculated by the formula h_m = f(Δλ_h - K_T*Δλ_T), where f is the humidity-strain calibration function and K_T is the temperature correction coefficient.

[0061] The humidity response characteristics of polyimide (moisture absorption strain coefficient 100 με / %RH) are directly correlated with the matrix suction (through the soil-water characteristic curve), avoiding the problem of bubble blockage in traditional tensiometers; the independent temperature grating corrects the influence of temperature on suction measurement in real time (for example, when the temperature changes by 1 °C, the suction measurement error is reduced by 0.5%). The porous ceramic filter element 32 allows the free migration of moisture while blocking the rapid entry of air, and is applicable to the matrix in the unsaturated zone (water content 10% - 80%). Compared with the effective range of traditional tensiometers (<80 kPa), it is increased to 200 kPa, covering a wider suction range. The chemical inert materials (PVC, ceramic) of the encapsulation body 31 are resistant to acid and alkali corrosion, and the physical stability of the coating layer and the filter element 32 ensures no attenuation during long-term (>5 years) moisture absorption-desorption cycles, solving the problem of material aging of traditional humidity sensors.

[0062] In some embodiments, the optical fiber demodulator 5 is used to separate the optical fiber reflected light wave in the wavelength domain and convert it into an electrical signal, and integrates a 4G / 5G data transmission module 51 for realizing remote real-time transmission of monitoring data.

[0063] The optical fiber demodulator 5 internally integrates a wavelength demodulation module, which uses a tunable optical fiber filter (such as an optical fiber Fabry-Perot filter) or a spectrometer to separate the incident broadband optical signal in the wavelength domain (resolution 0.1 pm), converts it into an electrical signal through a photodetector, and then extracts the central wavelength of each grating through analog-to-digital conversion (ADC, 24-bit precision) and digital signal processing (DSP). The demodulator is equipped with a 4G / 5G data transmission module 51 (such as Huawei ME909s), accesses the cellular network through a SIM card, supports the TCP / IP protocol, packs the processed temperature, water content and other data (JSON format), and remotely transmits them to the cloud server at intervals of 1 Hz - 1 min. The module has a built-in GPS positioning function, adds geographical coordinate tags to each monitoring point, and is convenient for spatial data matching.

[0064] The wavelength resolution reaches 0.1 pm, corresponding to a temperature measurement accuracy of 0.01 °C and a strain accuracy of 1 με, meeting the monitoring requirements for micro-changes in the surface matrix; the real-time digital filtering algorithm (such as Kalman filtering) eliminates environmental noise (such as light source fluctuations, optical fiber vibrations), and the data reliability is increased by more than 95%. The 4G / 5G module supports network coverage in remote areas, eliminates the need to lay dedicated communication cables, and reduces the field construction cost; the remote real-time transmission realizes minute-level updates of monitoring data. Compared with traditional manual collection (cycle 24 h), the early warning response speed is increased by 24 times. The demodulator supports parallel acquisition of 8 - 64 channels, and a single device can access hundreds of sensors, adapting to large-area distributed monitoring networks, and the system integration degree is increased by 50% compared with traditional independent demodulation devices.

[0065] In some embodiments, it further includes: a solar power supply system 8, which includes a solar panel 81, a bracket 82, a storage battery 83 and a controller 84. The solar panel 81 is fixed by the bracket 82 and faces the sunlight direction. The solar panel 81 and the storage battery 83 are respectively connected to the controller 84 to achieve charge management. The output end of the controller 84 supplies power to the optical fiber demodulator 5 and the heating control module 7, supporting the long-term outdoor operation of the system.

[0066] The solar power supply system 8 includes a solar panel 81 (with a power of 50 - 100 W, made of monocrystalline silicon, and a conversion efficiency of 20%), an adjustable inclination bracket 82 (made of aluminum alloy, supporting an angle adjustment of 0° - 60°), a storage battery 83 (lead-acid battery or lithium battery, with a capacity of 100 - 200 Ah), and a controller 84 (MPPT charging controller 84, with an input voltage of 12 - 24 V). The solar panel 81 is fixed in the open area of the monitoring point through the bracket 82, faces due south (in the Northern Hemisphere), and the inclination angle is set to the local latitude ±10° to optimize sunlight reception. The output end of the solar panel 81 is connected to the controller 84. The controller 84 tracks the maximum power point in real time through the MPPT algorithm and stores the electric energy in the storage battery 83; the output end of the storage battery 83 supplies power to the optical fiber demodulator 5 (12 V) and the heating control module 7 (24 V) after DC-DC conversion. The controller 84 is built-in with overcharge / overdischarge protection circuits. When the power of the storage battery 83 is lower than 20%, it automatically cuts off non-essential loads (such as the heating module) to ensure the lowest power consumption operation of the system.

[0067] The daily power generation of the solar panel 81 (calculated according to 5 hours of effective sunlight) can support the system to work continuously for 7 days (including 10 heating tasks per day). With the backup power supply of the storage battery 83, it realizes the long-term outdoor operation of "zero external power supply", solving the power supply problem in remote areas. The MPPT controller 84 improves the solar energy utilization rate by more than 15%. Compared with traditional non-tracking power supply systems, the power generation in winter increases by 25%; the overcharge / overdischarge protection extends the life of the storage battery 83 by 30% and reduces the maintenance and replacement frequency. The anti-ultraviolet coating (with a thickness of 50 μm) on the surface of the solar panel 81 can withstand outdoor aging, and the anti-corrosion treatment (anodic oxidation) of the bracket 82 can adapt to harsh environments such as high humidity and salt spray, ensuring stable power supply within the temperature range of -40°C to 60°C.

[0068] Exemplarily, the heating control module 7 includes: a heating power supply 71 and a control module 72. The heating power supply 71 is connected to the solar power supply system 8 to obtain electric energy. The control module 72 is used to remotely set the voltage parameters, heating time and corresponding channels of the heating task, realizing precise control of the heating process of the heating wire 13.

[0069] The heating control module 7 consists of a heating power supply 71 (a 24V DC power supply with an output power of 50 - 100W) and a control module 72 (an embedded MCU, such as STM32). The input end of the heating power supply 71 is connected to the storage battery 83 of the solar power supply system 8, and the output end is connected to the resistance wires 13 of each sensing optical cable (each path supports a current of 10A) through a multi-channel relay (the power of a single resistance wire ≤ 10W). The control module 72 receives remote instructions through a 4G module, analyzes the heating task parameters (such as voltage 12V / 24V, heating time 10 - 60s, target channel number), and precisely controls the on / off of the relay through PWM (pulse width modulation) technology to achieve stepped heating of the resistance wires 13 (for example, quickly heating up to a certain temperature with 24V for 10s first, and then maintaining at a certain temperature with 12V for 20s). The module is built-in with a temperature sensor to continuously monitor the surface temperature of the resistance wires 13 and prevent abnormal evaporation of the matrix moisture caused by overheating (threshold 60°C).

[0070] Heating parameters can be set remotely, avoiding on-site manual intervention and adapting to different matrix types (such as the difference in the optimal heating time between sandy soil / clay). The PWM technology controls the heating power fluctuation within ±5%, ensuring that the repeatability error of the thermal response curve < 2%. The temperature feedback mechanism prevents local drying of the matrix caused by overheating of the resistance wires 13 and maintains the effectiveness of the physical model during the heating process (such as assuming that the initial moisture content of the matrix is uniform). The stepped heating combined with short-time high-power startup improves the signal-to-noise ratio of the thermal signal, and the inversion accuracy of the moisture content is increased by 10%. It supports parallel heating of up to 32 channels, adapts to a distributed sensing network, and the control efficiency is 3 times higher than that of single-channel control, meeting the synchronous measurement requirements of large-area monitoring scenarios.

[0071] Exemplarily, it further includes: a system integration cabinet 9, which is a waterproof and shock-resistant cabinet made of outdoor metal. The optical fiber demodulator 5, the heating control module 7, and the controller 84 of the solar power supply system 8 are integrated inside to achieve centralized installation and protection of each module.

[0072] The system integration cabinet 9 adopts an outdoor metal cabinet (material Q235B, surface galvanized + sprayed, protection level IP67), with dimensions of 600mm × 400mm × 300mm. Inside, it is divided into a power supply area, a demodulator area, and a control module 72 area by partitions. The solar controller 84 and the storage battery 83 (with an insulating bracket 82) are installed in the power supply area; the optical fiber demodulator 5 is fixed in the demodulator area, and an optical fiber splicing tray (accommodating a 12-core communication optical cable) is configured; the heating control module 7, a 4G router, etc. are installed in the control module 72 area. Waterproof cable entry holes (with rubber sealing rings) are opened at the bottom of the cabinet, and cables are connected to external sensors through armored cables; a sunshade eaves (extending 10cm) is provided at the top, and louvers (with insect-proof nets) are opened on the side, and a temperature-controlled fan (starting temperature 35°C) is installed inside to maintain the temperature inside the cabinet at 25°C ± 5°C.

[0073] The partition layout facilitates module replacement (such as separately disassembling the demodulator for maintenance), and the standardized design of the splicing tray reduces the optical fiber connection loss (<0.1 dB); the cabinet is reserved with expansion interfaces (such as spare power supply interfaces, Ethernet ports) to support the later system upgrade (such as adding CO2 sensors). The thickness of the metal cabinet is 1.5 mm, which can withstand an impact force of 50 J (such as human impact); it is equipped with a three-point anti-theft lock to prevent the equipment from being stolen or maliciously damaged, and improve the security of the field monitoring system.

[0074] In some embodiments, the optical fiber moisture content and temperature optical cable 1 is encapsulated with a ribbon optical cable, so as to improve the installation convenience and long-term monitoring stability of the sensor by combining the characteristics of high structural strength and small volume of the ribbon optical cable and the array grating distribution design.

[0075] The optical fiber moisture content and temperature optical cable 1 adopts a ribbon optical cable encapsulation structure, with 12-core single-mode optical fibers (including array gratings) integrated inside, and an aramid fiber reinforcement layer (thickness 0.5 mm) and a polyvinyl chloride outer sheath (thickness 1 mm) wrapped outside. The overall outer diameter is 4 - 6 mm. The flat design of the ribbon optical cable (width 8 mm) facilitates laying along the axial direction of the borehole and is fixed to the positioning bracket 82 (spacing 50 cm) preset on the inner wall of the borehole through cable ties, avoiding the grating strain interference caused by the bending of the optical cable. The array gratings are distributed at intervals of 50 cm (2 grating points per meter), and each grating point corresponds to a hollow copper rod (length 10 cm). The adjacent copper rods are connected by a flexible section of the optical cable to adapt to the small displacements caused by matrix settlement (allowing a deformation of ±5 mm). The aramid fiber reinforcement layer enables the optical cable to have a tensile strength of 500 N and a bending resistance radius of ≤20 mm. Compared with traditional circular optical cables, the installation efficiency is increased by 40% (no special laying tools are required); the flat structure reduces the requirement for the borehole diameter (saving 20% of the borehole diameter compared to circular optical cables), reducing the construction cost. The flexible section design absorbs the matrix deformation stress, avoiding false wavelength drift of the grating caused by mechanical strain (strain interference <5 με); the weather-resistant material (PVC) of the outer sheath resists soil microbial erosion, and the service life is extended by more than 2 years compared with ordinary optical cables. Continuous profile monitoring of the physical parameters of the surface matrix is achieved through a 50 cm grating point spacing. Compared with traditional single-point sensors (spacing 1 - 5 m), the spatial resolution is increased by more than 10 times, and local microenvironment changes (such as temperature - moisture heterogeneity in the root zone) can be captured.

[0076] The embodiment of the present application provides a method for monitoring multiple parameters of surface matrix optical fibers, which is applied to the remote multi-parameter monitoring module of the surface matrix multi-parameter optical fiber monitoring system provided in any embodiment of the present application. Specifically, as Figure 5 shown, the provided method for monitoring multiple parameters of surface matrix optical fibers includes steps S101 to S103. Details are as follows: Step S101. Obtain the monitoring data transmitted by the fiber optic demodulator through the data transmission module; the monitoring data includes temperature, moisture content, groundwater level, and matrix suction.

[0077] Specifically, the wavelength signals of the distributed fiber optic sensors are collected in real time by the fiber optic demodulator. After wavelength-physical quantity conversion, multi-parameter data such as temperature, moisture content, groundwater level, and matrix suction are remotely transmitted to the cloud or local server through the 4G / 5G data transmission module. The monitoring data includes the spatial coordinates of the sensor array, the timestamp, and the original wavelength signals and converted engineering physical quantities of each parameter.

[0078] The fiber optic demodulator is built-in with a tunable filter (such as a Fabry-Perot filter), which scans the reflection spectra of each sensor grating at a sampling rate of 100 Hz, and extracts the central wavelength λB through a peak detection algorithm (accuracy ±0.1 pm).

[0079] For the temperature measurement grating (coated with acrylate), the temperature change is calculated using the formula ΔT = Δλ / λB*(α + ξ), where α is the thermal expansion coefficient of the optical fiber (5.5×10 -7 / ℃), and ξ is the thermo-optic coefficient (1.2×10 -5 / ℃).

[0080] The moisture content is retrieved by inverting the cooling curve after heating a custom-made hollow copper rod, based on the heat conduction model , and the moisture content is fitted by combining the heating power of the resistance wire and the temperature recovery rate (αw is the matrix thermal diffusivity, which is positively correlated with the moisture content).

[0081] The groundwater level is calculated by the wavelength drift of the pressure film strain grating to obtain the water pressure, and then converted into the water level height (h = ρgP, where ρ is the water density and g is the acceleration due to gravity). The matrix suction is obtained by referring to the soil-water characteristic curve (SWCC) after deducting the temperature correction term from the wavelength drift of the humidity-sensitive grating (polyimide coating).

[0082] The demodulator encodes the data of each parameter into a JSON format data packet, which includes the device ID (16-bit unique code), channel number (1~64), geographical coordinates (latitude and longitude, accuracy 0.0001°), timestamp (UTC millisecond level), and data value (temperature accuracy 0.01℃, moisture content accuracy 0.5%, water level accuracy 1 mm, suction accuracy 1 kPa).

[0083] The 4G / 5G module communicates with the server through a TCP long connection, supports resume from breakpoint, and the data encryption adopts the AES-128 protocol to ensure the reliability and security of the transmission.

[0084] Support 64-channel parallel acquisition through a single demodulator, realize synchronous monitoring of temperature, water content, water level, and suction at the same point, with a time synchronization error < 10 ms, avoiding the analysis deviation of coupling effects caused by asynchronous measurement. The wavelength demodulation resolution reaches 0.1 pm, corresponding to a temperature measurement error of ±0.02 °C and a strain error of ±2 με. Combining digital filtering algorithms (such as wavelet denoising), effectively suppress interference such as environmental vibration and light source noise, and the data efficiency > 99%. The 4G / 5G network has a wide coverage, supports real-time data transmission in remote areas, and cooperates with the solar power supply system to achieve 7×24-hour continuous monitoring, solving the problems of long traditional manual inspection cycles (usually ≥24 h) and data lag.

[0085] Step S102. Remotely control the voltage, time, and channels of the heating task through the heating control module.

[0086] Specifically, send instructions to the heating control module through the cloud platform or local terminal, accurately configure the voltage parameters (12V / 24V), heating time (10~60 s), and target channels (corresponding to the sensing optical cable numbers) for the resistance wire heating, realizing remote automatic control of the point heat source heating process and providing a thermal excitation signal for water content inversion.

[0087] The user inputs heating parameters through the Web or mobile interface. After the instructions are parsed by the server, they are sent to the embedded MCU (such as STM32) of the heating control module through the MQTT protocol (Message Queuing Telemetry Transport), and the instruction response time < 5 s. The control module has a built-in safety verification mechanism to verify the legality of the voltage (≤24V), time (≤60 s), and channel number (1~32), and rejects abnormal instructions to protect the device. Pulse Width Modulation (PWM) technology is used to adjust the on / off of the relay. For example, at 24V voltage, heat for 20 s with a 50% duty cycle, and the equivalent power control accuracy is ±3%, avoiding overheating of the resistance wire (the surface temperature threshold is 60 °C, and power is automatically cut off when overheated). Support multi-channel polling heating (such as an interval of 5 minutes for each channel), avoiding mutual interference between multiple heat sources. The energy consumption of a single heating task ≤ 0.1 Wh (heating a 24V / 10W resistance wire for 10 s), and the efficiency is 5 times higher than that of manual control. The heating module real-time transmits the resistance wire temperature (through the built-in NTC sensor, accuracy ±1 °C), voltage / current values to the server, forming a heating process log (including start time, duration, actual power consumption), for later energy consumption analysis and model optimization.

[0088] Adapt to different substrate types through remote parameter configuration (for example, sandy soil requires high-power heating for a short time, and clay requires low-power heating for a long time). The repeatability error of the thermal response curve is <2%, and the inversion accuracy of water content is improved by 15%. The on-demand heating mode saves more than 40% energy compared with fixed-parameter heating. Eliminate the risks of on-site manual operations (such as electric shock and equipment damage), automatically protect against abnormal working conditions (power off when overheating, fuse when overcurrent), and reduce the equipment failure rate by 60%. The heating task can be automatically executed through preset strategies (such as triggering at a fixed time or when the water content is abnormal), reducing manual intervention. Support single-channel fine heating (for single-point substrate characteristic analysis) and multi-channel synchronous heating (for regional heat conduction model verification), meeting the requirements of different scenarios such as laboratory calibration and long-term field monitoring.

[0089] Step S103. Calculate, manage, and analyze the temperature, water content, groundwater level, and matrix suction corresponding to the surface substrate according to the monitoring data.

[0090] Specifically, perform physical quantity calculation, spatio-temporal data management, and professional analysis on the collected multi-parameter data, including temperature compensation and correction, water content model inversion, water level trend prediction, matrix suction coupling analysis, etc., providing decision-making support for the multi-field coupling research of surface substrate water-heat-mechanics.

[0091] Temperature compensation is carried out by linearly correcting the humidity-sensitive grating data of the matrix suction sensor using the synchronous data of the temperature measurement grating (Δλ correction = Δλ humidity - K T * Δλ temperature, K_T is the temperature cross-sensitivity coefficient), eliminating the interference of temperature on suction measurement (the error after correction is <1%).

[0092] Water content inversion is based on the temperature rise rate (dT / dt 加热 ) during the heating stage and the temperature drop rate (dT / dt 冷却 ) during the cooling stage. Fit the water content through the porous medium heat conduction model (such as Luikov theory), and the formula is θ = a * (dT / dt heating dT / dt cooling) + b, where a and b are calibration coefficients (obtained through indoor experiments).

[0093] Water level-suction coupling calculation combines the groundwater level h and the matrix suction h_m, and calculates the matrix water content profile through the saturated-unsaturated seepage theory (such as Richards equation) to verify the consistency of sensor data.

[0094] Build a spatio-temporal database (such as PostgreSQL + PostGIS), store data according to a three-dimensional index of "device - channel - time", and support high-frequency query of second-level data (response time < 200ms); set a data backup strategy (local hard disk + cloud storage) to ensure data integrity (loss rate < 0.01%). The device management module records sensor calibration parameters (such as the initial wavelength of the grating, the thermal expansion coefficient of the copper rod), installation location (X / Y / Z coordinates, accuracy ±5cm), and maintenance logs (such as calibration time, optical cable replacement records) for convenient later traceability and fault troubleshooting.

[0095] Dynamically display data of each monitoring point through the WebGIS platform, support the drawing of three-dimensional profiles (such as temperature - water content distribution along the borehole depth), generation of contour maps (such as groundwater level contour lines), and the update frequency is 1 time / minute. Set abnormal thresholds (such as a sudden water level rise > 5cm / h, a sudden drop in matrix suction > 10kPa), trigger SMS / email warnings, and the warning response time < 30s; predict the short-term water level change trend based on machine learning algorithms (such as LSTM) (prediction error within the next 24h < 3cm). Identify key influencing factors through correlation matrices (such as when the negative correlation coefficient between temperature and water content > 0.8, trigger a heat conduction anomaly alarm) and principal component analysis (PCA) to provide data support for the research on the evolution mechanism of the surface matrix.

[0096] The temperature compensation algorithm eliminates the cross-sensitivity error of the sensor, enabling the measurement accuracy of matrix suction to reach 1kPa, and the inversion error of water content < 2% (volumetric water content), meeting the professional analysis requirements in fields such as geotechnical engineering and eco-hydrology. The spatio-temporal database supports long-term data mining (such as analyzing the law of matrix water and heat changes on a ten-year scale), and the warning mechanism improves the ability to identify precursors of disasters (such as landslides, piping), with an efficiency improvement of more than 10 times compared to manual analysis; the coupling analysis function provides measured verification data for surface matrix physical models (such as HYDRUS), promoting the optimization of theoretical models. The data interface is compatible with RESTful API and can be seamlessly connected to third-party platforms such as smart agriculture and geological disaster monitoring to achieve cross-system data sharing, build an integrated closed-loop of "monitoring - analysis - decision-making", and improve the scientific level of surface matrix management.

[0097] It should be noted that those skilled in the art can clearly understand that for the convenience and simplicity of description, the above-described multi-parameter fiber optic monitoring method of the surface matrix and the specific working processes of each step can refer to the corresponding processes in the embodiments of the multi-parameter fiber optic monitoring system of the surface matrix described in the above embodiments, and will not be elaborated here.

[0098] Please refer to Figure 6 shown Figure 6It is a schematic structural diagram of a surface matrix multi-parameter optical fiber monitoring device 200 provided by an embodiment of the present application. The surface matrix multi-parameter optical fiber monitoring device 200 is used to execute the steps of the surface matrix multi-parameter optical fiber monitoring method shown in the above embodiments. The surface matrix multi-parameter optical fiber monitoring device 200 can be a single server or a server cluster, or the surface matrix multi-parameter optical fiber monitoring device 200 can be a terminal, and the terminal can be a handheld terminal, a laptop computer, a wearable device, or a robot, etc.

[0099] As Figure 6 shown, the surface matrix multi-parameter optical fiber monitoring device 200 includes: A data acquisition unit 201, configured to acquire the monitoring data transmitted by the optical fiber demodulator through the data transmission module; the monitoring data includes temperature, moisture content, groundwater level, and matrix suction; A heating control unit 202, configured to remotely control the voltage, time, and channel of the heating task through the heating control module; A management and analysis unit 203, configured to calculate, manage, and analyze the temperature, moisture content, groundwater level, and matrix suction corresponding to the surface matrix according to the monitoring data.

[0100] It should be noted that those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the above-described surface matrix multi-parameter optical fiber monitoring device and each module can refer to the corresponding processes in the surface matrix multi-parameter optical fiber monitoring method embodiments described in the above embodiments, and will not be elaborated here.

[0101] The above-described surface matrix multi-parameter optical fiber monitoring method can be implemented in the form of a computer program, and the computer program can run on a device such as Figure 6 shown.

[0102] Please refer to Figure 7 , Figure 7 It is a schematic block diagram of the structure of a remote multi-parameter monitoring module provided by an embodiment of the present application. The remote multi-parameter monitoring module includes a processor, a memory, and a network interface connected through a device bus. Among them, the memory can include a storage medium and an internal memory.

[0103] The storage medium can store an operating device and a computer program. The computer program includes program instructions, and when the program instructions are executed, the processor can be made to execute any surface matrix multi-parameter optical fiber monitoring method.

[0104] The processor is used to provide computing and control capabilities to support the operation of the entire remote multi-parameter monitoring module.

[0105] The internal memory provides an environment for the operation of a computer program in a non-volatile storage medium. When the computer program is executed by a processor, the processor can be made to execute any one of the multi-parameter optical fiber monitoring methods for surface matrixes.

[0106] This network interface is used for network communication, such as sending assigned tasks, etc. Those skilled in the art can understand that Figure 7 the structure shown in is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the terminal to which the solution of this application is applied. Specifically, the remote multi-parameter monitoring module may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0107] It should be understood that the processor may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0108] Among them, in one embodiment, the processor is used to run a computer program stored in the memory to implement the following steps: Obtain the monitoring data transmitted by the optical fiber demodulator through the data transmission module; the monitoring data includes temperature, moisture content, groundwater level, and matrix suction; Remotely control the voltage, time, and channels of the heating task through the heating control module; Calculate, manage, and analyze the temperature, moisture content, groundwater level, and matrix suction corresponding to the surface matrix according to the monitoring data.

[0109] This application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the processor is made to implement the steps of the multi-parameter optical fiber monitoring method for surface matrixes provided in any embodiment of this application.

[0110] Among them, the computer-readable storage medium may be an internal storage unit of the remote multi-parameter monitoring module described in the foregoing embodiments, such as the hard disk or memory of the remote multi-parameter monitoring module. The computer-readable storage medium may also be an external storage device of the remote multi-parameter monitoring module, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. equipped on the remote multi-parameter monitoring module.

[0111] As described above, the foregoing is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of various equivalent modifications or substitutions, and these modifications or substitutions should all be covered within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A multi-parameter optical fiber monitoring system for surface matrix, characterized in that, Including: An optical fiber moisture content and temperature cable for monitoring the temperature and moisture content of the surface substrate. The optical fiber moisture content and temperature cable fixes an array of moisture content and temperature measurement gratings on the surface of a customized hollow copper rod by full adhesion and encapsulates it into a cable. A resistance wire equal in length to the copper rod is inserted into the customized hollow copper rod; the optical fiber moisture content and temperature cable is arranged in a borehole corresponding to the surface substrate, and the borehole is backfilled with undisturbed soil consistent with the formation soil properties; An optical fiber water level sensor for monitoring the groundwater level corresponding to the surface substrate; An optical fiber matrix suction sensor for monitoring the matrix suction corresponding to the surface substrate; An optical fiber demodulator. The optical fiber moisture content and temperature cable, the optical fiber water level sensor, and the optical fiber matrix suction sensor are respectively connected to the optical fiber demodulator through communication cables. The optical fiber demodulator generates monitoring parameters corresponding to the temperature, moisture content, groundwater level, and matrix suction; A heating control module. The optical fiber moisture content and temperature cable is connected to the heating control module through a wire. The heating control module remotely controls the voltage, time, and channels of the heating task; A remote multi-parameter monitoring module. The optical fiber demodulator transmits the monitoring data to the remote multi-parameter monitoring module. The remote multi-parameter monitoring module is used to calculate, manage, and analyze the temperature, moisture content, groundwater level, and matrix suction corresponding to the surface substrate according to the monitoring data.

2. The multi-parameter optical fiber monitoring system for surface matrix according to claim 1, characterized in that, In the optical fiber moisture content and temperature cable, the array of moisture content and temperature measurement gratings is fixed on the surface of the customized hollow copper rod by full adhesion to reduce the single grating fusion points and operation difficulty by full adhesion; The customized hollow copper rod is made of metal material, and the length of the resistance wire inserted inside is equal to the length of the customized hollow copper rod to achieve point heat source heating and reduce energy consumption; The array of moisture content and temperature measurement gratings measures the temperature by measuring the tensile amount generated by the thermal expansion of the customized hollow copper rod. The resistance wire is used to achieve point heat source heating to measure the moisture content, realizing the integrated monitoring of temperature and moisture content.

3. The multi-parameter optical fiber monitoring system for surface matrix according to claim 1, characterized in that, The optical fiber water level sensor includes: An inlet base, a bottom film mounting seat, an outer cylinder, and a pressure film. The inlet base and the outer cylinder enclose a cavity. The bottom film mounting seat is located inside the cavity and is provided with a deformable pressure film. A strain optical fiber grating is arranged on the surface of the pressure film. The deformation of the pressure film caused by the liquid height difference acts on the strain optical fiber grating to realize the monitoring of minute changes in the groundwater level.

4. The multi-parameter optical fiber monitoring system for surface matrix according to claim 1, characterized in that, The optical fiber matrix suction sensor includes: An encapsulation body, a filter element, a connecting socket, a suction measurement grating, and a temperature measurement grating. A high-temperature sintered filter element is arranged at one end of the encapsulation body, and the filter element is fixed at the other end through the connecting socket; The suction measurement grating is coated with a humidity-sensitive material, polyimide, to respond to humidity and suction changes. The temperature measurement grating is coated with acrylate to separately respond to temperature changes and is used for temperature compensation calculation.

5. The multi-parameter optical fiber monitoring system for surface matrix according to claim 1, characterized in that, The optical fiber demodulator is used to separate the optical fiber reflected light wave in the wavelength domain and convert it into an electrical signal, and integrates a 4G / 5G data transmission module to realize the remote real-time transmission of monitoring data.

6. The multi-parameter optical fiber monitoring system for surface matrix according to claim 1, characterized in that, Also including: The solar power supply system includes a solar panel, a bracket, a storage battery, and a controller. The solar panel is fixed by the bracket and faces the sunlight direction. The solar panel and the storage battery are respectively connected to the controller to achieve charge management. The output end of the controller supplies power to the fiber optic demodulator and the heating control module, supporting the long-term outdoor operation of the system.

7. The multi-parameter optical fiber monitoring system for surface matrix according to claim 6, characterized in that, The heating control module includes: A heating power supply and control system. The heating power supply is connected to the solar power supply system to obtain electrical energy. The control system is used to remotely set the voltage parameters, heating time, and corresponding channels of the heating task, realizing precise control of the resistance wire heating process.

8. The multi-parameter optical fiber monitoring system for surface matrix according to claim 6, characterized in that, It further includes: A system integration cabinet, which is a waterproof and impact-resistant cabinet made of outdoor metal. The fiber optic demodulator, the heating control module, and the controller of the solar power supply system are integrated inside, realizing the centralized installation and protection of each module.

9. The multi-parameter optical fiber monitoring system for surface matrix according to claim 1, characterized in that, The fiber optic moisture content and temperature optical cable is encapsulated with a ribbon optical cable. Based on the characteristics of the ribbon optical cable, such as high self-structural strength and small volume, combined with the array grating distribution design, the installation convenience of the sensor and the long-term monitoring stability are improved.

10. A multi-parameter optical fiber monitoring method for surface matrix, characterized in that, A remote multi-parameter monitoring module applied to the surface matrix multi-parameter fiber optic monitoring system according to any one of claims 1-9. The method includes: Obtaining the monitoring data transmitted by the fiber optic demodulator through the data transmission module; the monitoring data includes temperature, moisture content, groundwater level, and matrix suction; Remotely controlling the voltage, time, and channels of the heating task through the heating control module; Calculating, managing, and analyzing the temperature, moisture content, groundwater level, and matrix suction corresponding to the surface matrix according to the monitoring data.

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