An integrated system for monitoring the temperature of a glacial tillage dam and its monitoring method

Abstract

This invention provides an integrated system and method for monitoring the temperature of a glacial till dam, comprising: multi-point temperature probes, deployed at designated locations on the dam body to collect temperature information at different depths within those locations; a remote monitoring and analysis platform, communicatively connected to the multi-point temperature probes, constructing a three-dimensional temperature field model of the dam body based on the temperature information collected by the probes, and performing risk identification and early warning based on temperature gradient changes; a data acquisition module for receiving and storing the temperature information collected by the multi-point temperature probes; and a data transmission module for transmitting the pre-processed temperature information to the remote monitoring and analysis platform. The three-dimensional temperature field model is constructed through the remote platform, enabling visualized display and standardized management of temperature data. Quantitative judgment rules are established based on temperature gradient, temperature change rate, anomaly threshold, and anomaly ratio to achieve a three-level risk classification and early warning system, improving the early identification capability of disasters.

Description

Technical Field

[0001] This invention relates to the field of high-altitude glacier disaster monitoring and geotechnical engineering safety, and in particular to an integrated system for monitoring the temperature of glacial moraine dams and its monitoring method. Background Technology

[0002] Glacial moraine dams are natural, loosely deposited dams formed by glacial transport and deposition, widely distributed in high-altitude glaciers and periglacial environments. Their material origins are complex, typically composed of a mixture of multi-graded particles such as boulders, gravel, sand, and silt, with a wide range of particle sizes. The overall structure is loose and poorly cemented, exhibiting significant heterogeneity and multi-scale pore structure characteristics. The ventral structures formed between coarse particles, together with the fine-grained interstitial bodies, constitute a highly developed pore-fracture network with significantly varying connectivity, resulting in complex and spatially unevenly distributed seepage channels within the dam body.

[0003] The unique material composition and structural characteristics of glacial till dams make them highly sensitive to external temperature changes, exhibiting significant thermo-hydraulic-mechanical coupling within them. From a mechanistic perspective, temperature changes within the dam body first control the spatiotemporal distribution of freezing and thawing processes, influencing the migration and evolution of the ice-water phase transition interface. During freeze-thaw cycles, changes in pore water volume and the generation of ice expansion pressure alter the internal stress state and structural integrity of the dam body. Simultaneously, temperature gradients drive water migration and seepage field reconstruction, leading to time-varying evolution of pore water pressure. These thermo-hydraulic processes further affect the effective stress level and interparticle contact relationships, causing dam strength decay, deformation accumulation, and the gradual development of potential slip surfaces. Therefore, temperature is not only a crucial parameter characterizing environmental changes in glacial till dams but also a key driving factor controlling the evolution of dam stability, playing a significant role in the incubation and triggering of glacial lake outburst floods.

[0004] However, existing temperature monitoring technologies for glacial till dams mostly employ single-point, shallow sensor deployment, resulting in insufficient accuracy and spatial coverage of the monitoring data, making it difficult to reflect the complex three-dimensional temperature field structure within the dam body. Furthermore, they fail to meet the needs for dynamic monitoring and comprehensive analysis of the thermo-hydraulic-mechanical coupling processes within glacial till dams.

[0005] Given the high heterogeneity of glacial till dam materials and the chain-like control effect of temperature on dam stability, it is necessary to construct a temperature monitoring system for glacial till dams suitable for cold and complex environmental conditions. Summary of the Invention

[0006] This invention provides an integrated system and method for monitoring the temperature of glacial till dam bodies, which solves the problem that existing technologies cannot meet the needs of dynamic monitoring and comprehensive analysis of glacial till dam bodies.

[0007] This invention provides an integrated system for monitoring the temperature of a glacial till dam, comprising: Multiple temperature probes are placed at designated locations on the dam body to collect temperature information at different depths within those designated locations. The remote monitoring and analysis platform is connected to the multi-point temperature probes and constructs a three-dimensional temperature field model of the dam body based on the temperature information collected by the multi-point temperature probes. It also identifies and warns of risks based on changes in temperature gradient. The power supply module is used to supply power to the multi-point temperature probe. The data acquisition module is communicatively connected to the multi-point temperature probe and is used to receive and store the temperature information acquired by the multi-point temperature probe and to perform preliminary processing on the temperature information. The data transmission module is communicatively connected to both the data acquisition module and the remote monitoring and analysis platform, and is used to transmit the temperature information that has undergone preliminary processing to the remote monitoring and analysis platform.

[0008] Furthermore, the multi-point temperature probe includes a probe housing and a temperature sensor group disposed within the probe housing. The temperature sensor group includes multiple temperature sensors arranged at intervals along the axial direction of the probe. Each temperature sensor is communicatively connected to the data acquisition module to acquire temperature data at different depths of the dam body.

[0009] Furthermore, the inner wall of the probe housing is connected to a waterproof sealing layer and a thermal insulation filling layer.

[0010] Furthermore, the temperature sensor group includes a surface temperature sensor, a middle temperature sensor, and a deep temperature sensor arranged sequentially along the depth direction.

[0011] Furthermore, the communication method between the data transmission module and the remote monitoring and analysis platform includes one or more combinations of LoRa, cellular mobile communication, or BeiDou satellite communication.

[0012] Furthermore, the remote monitoring and analysis platform includes: Data storage unit, used for storing and managing temperature monitoring data; The three-dimensional visualization unit is used to construct and display a three-dimensional temperature field model of the dam body based on the temperature information received from different multi-point temperature probes. The early warning analysis unit provides graded early warnings based on the rate of change of temperature gradient or temperature anomaly threshold.

[0013] Furthermore, the power supply module includes a solar power supply unit and a battery energy storage unit; the solar power supply unit is electrically connected to the battery energy storage unit, and the battery energy storage unit is electrically connected to the multi-point temperature probe.

[0014] This invention also discloses a method for monitoring the temperature of a glacial till dam, applied to the integrated system for monitoring the temperature of a glacial till dam as described in any one of claims 1-7, comprising the following steps: S1: Temperature data at different depths at each monitoring point is collected using multi-point temperature probes, and the data acquisition module stores and performs preliminary processing. S2: The temperature data, which has been stored and preliminarily processed, is uploaded to the remote monitoring and analysis platform via the data transmission module; S3: Construct a three-dimensional temperature field model of the dam body based on temperature data on a remote monitoring and analysis platform; S4: Analyze and identify the rate of change of temperature gradient, the rate of temperature change at a single depth point, and the abnormal temperature threshold, and classify the risk based on the analysis and identification results and issue early warning information.

[0015] Furthermore, the analysis and identification of temperature gradient change rate, temperature change rate at a single depth point, and abnormal temperature threshold includes: The rate of change of the temperature gradient The calculation method is as follows: ; , Indicates the same probe rod The temperature detected by the i-th temperature sensor at time i. Indicates the same probe rod The depth corresponding to the i-th temperature sensor at time i; The method for calculating the temperature change rate at a single depth point is as follows:

[0016] This indicates that the depth is Temperature at any moment; The abnormal temperature threshold includes an upper limit threshold. Lower threshold Historical average and standard deviation ; The step of classifying risks and issuing early warning information based on the analysis and identification results includes: A temperature anomaly is determined when the actual temperature T monitored at any point meets any of the following conditions: T > T< or , where k is the standard coefficient; Within the area, let there be a shared... Of the valid measuring points, the number of measuring points identified as abnormal at a certain moment or within a time window is: The abnormal ratio is then defined as: ; When all of the following conditions are met , , and P < B1, it is determined as the first-level stable state; When any of the conditions of 1℃ / m , 0.5℃ / d , , B1 < P < B2 is met, it is determined as the second-level abnormal state; When any of the conditions of , , , P> ]>< B2 is met, it is determined as the third-level abnormal state and a warning is triggered; Among them, A1 is the first gradient threshold, B1 is the first abnormal ratio threshold, A2 is the second gradient threshold, and B2 is the second abnormal ratio threshold.

[0017] Furthermore, is <00xxxxxx>, is , B1 is 10% - 20%, and B2 is 30% 50%. <00xxxxxx><00xxxxxx>The beneficial effects of the present invention are as follows: 1. By adopting a multi-point stratified temperature probe, the temperatures at different depths of the surface layer, middle layer, and deep layer of the dam body can be synchronously collected, breaking through the limitations of traditional single-point shallow monitoring, and completely reflecting the spatio-temporal distribution of the three-dimensional temperature field of the dam body. The sensor layout is flexible and the accuracy is high, which can accurately capture the migration of the freeze-thaw interface and the change of the temperature gradient, providing reliable data for the research of the thermal-hydraulic-mechanical coupling process.

[0019] 2. By constructing a three-dimensional temperature field model through a remote platform, the visualization display and standardized management of temperature data are realized. Based on the temperature gradient, temperature change rate, abnormal threshold, and abnormal ratio, a quantitative determination rule is established to achieve a three-level risk classification warning, improving the ability of early disaster identification. The integration of automatic data collection, preliminary processing, remote transmission, analysis, and warning is realized, reducing manual intervention. <000xxxxxx>3. By applying the temperature monitoring method of the moraine dam in the monitoring integration system, the internal freeze-thaw evolution process of the moraine dam is dynamically tracked, providing a key basis for the risk assessment of glacial lake outburst. It can be integrated with multi-source data such as seepage, displacement, and meteorology, improving the scientificity of the analysis of the stability mechanism and safety assessment of the moraine dam. It is applicable to alpine glacier disaster monitoring projects, significantly improving the safety prevention and control and emergency response levels of the moraine dam. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a schematic diagram of the deployment of the integrated temperature monitoring system for the glacial till dam body according to the present invention within the glacial till dam body; Figure 2 This is a partial structural schematic diagram of the integrated system for monitoring the temperature of glacial till dams according to the present invention; Figure 3 This is a schematic diagram of the internal structure of the multi-point temperature probe of the present invention; Figure 4 This is a schematic diagram of the functional architecture of the cloud platform for data transmission and remote monitoring of the present invention.

[0022] Figure 5 This is a flowchart illustrating the method for monitoring the temperature of a glacial moraine dam according to the present invention.

[0023] Figure label: 1. Glacial till dam body; 2. Multi-point temperature probe; 21. Probe housing; 22. Waterproof sealing layer; 23. Thermal insulation filling layer; 24. Surface temperature sensor; 25. Middle layer temperature sensor; 26. Deep layer temperature sensor; 3. Data acquisition module; 4. Data transmission module; 5. Solar power supply unit; 6. Battery energy storage unit; 7. Monitoring workstation; 8. Mobile client; 9. Early warning device. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0025] The terms "first" and "second" in the specification and claims of this invention may explicitly or implicitly include one or more of those features. In the description of this invention, unless otherwise stated, "a plurality of" means two or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0026] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0027] The following is combined Figures 1-5 This invention describes an integrated temperature monitoring system for a glacial moraine dam, comprising a multi-point temperature probe 2, a remote monitoring and analysis platform, a power supply module, a data acquisition module 3, and a data transmission module 4. The multi-point temperature probe 2 is installed in vertical monitoring holes in key stress areas of the glacial moraine dam body 1, such as the top, middle, and bottom, to collect temperature information at different depths within the dam body. The remote monitoring and analysis platform communicates with the multi-point temperature probe 2 via the data transmission module 4, constructing a three-dimensional temperature field model of the dam body based on the temperature data, and using temperature gradient changes to complete risk identification and early warning. The power supply module continuously supplies power to the multi-point temperature probe 2, the data acquisition module 3, and the data transmission module 4. The data acquisition module 3 receives the temperature data collected by the multi-point temperature probe 2 and performs preliminary processing such as storage, filtering, and outlier removal. The data transmission module 4 wirelessly transmits the pre-processed temperature data to the remote monitoring and analysis platform.

[0028] Specifically, such as Figure 1 , Figure 2 As shown, multi-point temperature probes 2 collect real-time temperatures at different depths within the dam body, transmitting the data to the data acquisition module 3 for storage and preliminary processing. The processed data is then uploaded to the remote monitoring and analysis platform via the data transmission module 4. Based on the received temperature data, the platform constructs a three-dimensional temperature field model, analyzes temperature gradient changes, identifies dam safety risks, and issues early warnings. The power supply module provides stable power to all components throughout the process. This achieves integrated data collection, processing, transmission, analysis, and early warning for glacial till dam temperature data, enabling three-dimensional monitoring of the dam body temperature and providing fundamental data support for glacial till dam safety assessments.

[0029] Furthermore, the multi-point temperature probe 2 includes a probe housing 21 and a temperature sensor group disposed inside the probe housing 21. The temperature sensor group includes multiple temperature sensors arranged at intervals along the axial direction of the probe. Each temperature sensor is communicatively connected to the data acquisition module 3 to acquire temperature data at different depths of the dam body.

[0030] Furthermore, the temperature sensor group includes a surface temperature sensor 24, a middle temperature sensor 25, and a deep temperature sensor 26 arranged sequentially along the depth direction.

[0031] Specifically, the multi-point temperature probe 2 includes a probe housing 21 and a temperature sensor group, which consists of multiple temperature sensors arranged at equal intervals along the probe axis.

[0032] In one specific embodiment, such as Figure 3 As shown, the temperature sensor group is divided into surface temperature sensor 24, middle temperature sensor 25, and deep temperature sensor 26 according to depth. The spacing between each layer of sensors is 0.5 to 2 meters. The spacing can be adjusted according to the dam structure to accurately collect temperature data at different depths, such as the surface, middle, and deep layers of the dam. Of course, more than three temperature sensors can also be set in the same multi-point temperature probe 2 to collect multi-gradient temperature data.

[0033] In some specific embodiments, the temperature sensor can be a resistance temperature detector (RTD) or a digital temperature sensing chip. The temperature sensor has a measurement range of -40℃ to 50℃ and an accuracy of ±0.1℃ to 0.5℃, thus meeting the requirements for identifying temperature gradients inside the glacial moraine dam. The temperature sensor group is deployed in layers along the depth direction of the probe, synchronously collecting temperature signals at corresponding depths. The temperature data is transmitted to the data acquisition module 3 via an independent communication link, realizing synchronous acquisition of temperatures at different depths. This covers the temperature monitoring range at different depths of the dam body, solving the problem of insufficient coverage of traditional single-point monitoring.

[0034] In one specific embodiment, a data acquisition and storage device is set up, integrating the data acquisition module 3 and the data transmission module 4 within it. The data acquisition and storage device samples each temperature sensor at preset time intervals (10 minutes to 1 hour), and performs filtering and outlier removal on the collected data to improve data accuracy and stability. The temperature sensors are connected to the data acquisition module 3 within the data acquisition and storage device via signal wires, and the data acquisition module 3 is electrically connected to the data transmission module 4.

[0035] Furthermore, the probe housing 21 is internally connected to a waterproof sealing layer 22 and a thermal insulation filling layer 23.

[0036] Specifically, such as Figure 3As shown, waterproof sealing layers 22 are fixedly connected to both ends of the probe housing 21, and a thermal insulation filling layer 23 is filled inside the housing. The waterproof sealing layer 22 is made of waterproof rubber, and the thermal insulation filling layer 23 is made of vacuum insulation material, effectively preventing external moisture infiltration and interference from ambient temperature fluctuations. The probe housing 21 is made of low-temperature resistant and corrosion-resistant stainless steel or polymer composite material, with an outer diameter of 30-60mm, possessing good pressure resistance, corrosion resistance, and freeze-thaw resistance. The waterproof sealing layer 22 prevents groundwater and meltwater from entering the probe, and the thermal insulation filling layer 23 reduces the impact of extreme external temperatures on the sensor's measurement accuracy, ensuring stable operation of the sensor in cold and freeze-thaw cycles. This improves the probe's waterproof, thermal insulation, and freeze-thaw resistance performance, thereby extending the service life of the monitoring equipment.

[0037] Furthermore, the communication method between the data transmission module 4 and the remote monitoring and analysis platform includes one or more combinations of LoRa, cellular mobile communication, or BeiDou satellite communication.

[0038] Specifically, the appropriate remote transmission method can be selected based on the on-site signal environment, and one or more of the following combinations of communication methods can be used: LoRa, 4G / 5G cellular mobile communication, and BeiDou satellite communication.

[0039] Furthermore, the remote monitoring and analysis platform includes: a data storage unit for storing and managing temperature monitoring data; a three-dimensional visualization unit for constructing and displaying a three-dimensional temperature field model of the dam body based on the temperature information received from different multi-point temperature probes 2; and an early warning analysis unit for providing graded early warnings based on the rate of change of temperature gradient or temperature anomaly threshold.

[0040] Specifically, such as Figure 4 As shown, the remote monitoring and analysis platform integrates a data storage unit, a 3D visualization unit, and an early warning analysis unit. The data storage unit can utilize a cloud database to store historical and real-time temperature data. The 3D visualization unit, based on a spatial interpolation algorithm, integrates temperature monitoring data to construct and display a 3D temperature field model of the dam body. The early warning analysis unit incorporates logic for determining the rate of change of temperature gradient and temperature anomaly thresholds. It performs logical judgments on the temperature information from different multi-point temperature probes 2, achieving standardized data management, visualized temperature field display, and intelligent early warning, thereby improving the readability of monitoring results and the efficiency of risk identification.

[0041] Furthermore, the power supply module includes a solar power supply unit 5 and a battery energy storage unit 6; the solar power supply unit 5 and the battery energy storage unit 6 are electrically connected, and the battery energy storage unit 6 is electrically connected to the multi-point temperature probe 2.

[0042] Specifically, such as Figure 1 , Figure 2As shown, the solar power supply unit 5 consists of solar panels and a power conversion circuit, installed on the dam top or an independent support. The battery energy storage unit 6 uses a low-temperature lithium battery. The solar power supply unit 5 converts solar energy into electrical energy to charge the battery, which continuously supplies power to the multi-point temperature probe 2, data acquisition module 3, and data transmission module 4. During the day, the solar panels generate electricity and store it through the battery energy storage unit 6. Power consumption is controlled by the power management unit. At night or in cloudy / snowy weather, the battery discharges to supply power. The power management circuit stabilizes the output and optimizes energy consumption to ensure continuous system operation. This adapts to high-altitude, unattended scenarios, achieving self-sufficiency in clean energy, ensuring long-term stable power supply, and reducing operation and maintenance costs.

[0043] This invention also discloses a method for monitoring the temperature of a glacial till dam, applied to an integrated system for monitoring the temperature of a glacial till dam, comprising the following steps: S1: Temperature data at different depths at each monitoring point are collected by the multi-point temperature probe 2, and the data acquisition module 3 stores and performs preliminary processing. Specifically, such as Figure 1 , Figure 5 As shown, in a high-altitude glacial lake moraine dam area, multiple monitoring points were selected in the key stress areas of the upper, middle, and lower parts of the moraine dam, based on the dam's size and topographical conditions. Vertical monitoring holes were drilled at each monitoring point. The depth of the monitoring holes was determined according to the dam's height and internal structural characteristics, generally ranging from 5 to 20 meters, to cover the potential freeze-thaw interface and key internal structural layers. A multi-point temperature probe 2 was installed in each monitoring hole. After installation, the monitoring holes were backfilled with undisturbed soil or moraine to restore the dam structure to its original stable state, thereby reducing disturbance to the overall dam structure. The system was powered by a power supply module. Temperature sensors at different depths within the multi-point temperature probe 2 collected temperature data from different depths, which was stored by the data acquisition module 3 and preliminarily processed, including filtering and outlier removal.

[0044] S2: The temperature data that has been stored and preliminarily processed is uploaded to the remote monitoring and analysis platform through the data transmission module 4; Specifically, the collected temperature data is uploaded to the remote monitoring and analysis platform via data transmission module 4. Data transmission module 4 can use LoRa, 4G / 5G, or BeiDou satellite communication for transmission. The remote monitoring and analysis platform can be set up as a fixed monitoring workstation 7 or a mobile client 8.

[0045] S3: Construct a three-dimensional temperature field model of the dam body based on temperature data on a remote monitoring and analysis platform; Specifically, a spatial coordinate model of the dam body is pre-established on the remote monitoring and analysis platform. The depth and temperature data of the received multi-point temperature probe 2 are mapped to spatial nodes, and an interpolation algorithm is used to reconstruct the temperature field, thereby constructing a three-dimensional temperature field model of the dam body.

[0046] S4: Analyze and identify the rate of change of temperature gradient, the rate of temperature change at a single depth point, and the abnormal temperature threshold, and classify the risk based on the analysis and identification results and issue early warning information.

[0047] Specifically, an abnormal temperature threshold is preset on the remote monitoring and analysis platform. Based on the received temperature data, the rate of change of spatial temperature gradient and the rate of temperature change at a single depth point are calculated. Risk is classified according to the judgment rules, and early warning information is issued. The early warning information is sent to management personnel via SMS notification, platform pop-up window, or by issuing an audible and visual alarm through the early warning device 9, realizing multi-terminal linkage response.

[0048] Further, in step S4, the rate of change of the temperature gradient The calculation method is as follows: ; The vertical temperature gradient The unit is ℃ / m; Indicates the same probe rod The temperature detected by the i-th temperature sensor at time i. Indicates the same probe rod The depth corresponding to the i-th temperature sensor at time i. This represents the change over time.

[0049] Temperature change rate at a single depth point The calculation method (with units of ℃ / h or ℃ / d) is as follows:

[0050] in, Let t be the temperature information collected by the temperature sensor at this depth. This represents the change over time.

[0051] Abnormal temperature thresholds include upper limit thresholds. Lower threshold Historical average and standard deviation .

[0052] A temperature anomaly is determined when the actual temperature T monitored at any point meets any of the following conditions: T > T< or , Take 25℃, Take -3℃, Take 16℃, The value is 9.73℃, and k is the standard coefficient, with a value of 2. 3; Within the area, let there be a total of valid measurement points, and the number of measurement points determined to be abnormal at a certain moment or within a time window is , then the abnormal ratio is defined as: ; When all of , , and P < B1 are satisfied, it is determined to be in the first-level stable state; When 1℃ / m , 0.5℃ / d , , B1 < P < B2 is satisfied, it is determined to be in the second-level abnormal state; When , , , P> , B2 is satisfied, it is determined to be in the third-level abnormal state and a warning is triggered; Among them, A1 is the first gradient threshold, B1 is the first abnormal ratio threshold, A2 is the second gradient threshold, and B2 is the second abnormal ratio threshold.

[0053] In some specific embodiments, has a value range of , has a value range of , B1 has a value range of 10% - 20%, and B2 has a value range of 30% 50%.

[0054] Without conflict, the above embodiments and the features in the embodiments in this article can be combined with each other.

[0055] The above is only the preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. An integrated system for monitoring the temperature of a glacial moraine dam body, characterized in that, include: Multiple temperature probes are placed at designated locations on the dam body to collect temperature information at different depths within those designated locations. The remote monitoring and analysis platform is connected to the multi-point temperature probes and constructs a three-dimensional temperature field model of the dam body based on the temperature information collected by the multi-point temperature probes. It also identifies and warns of risks based on changes in temperature gradient. The power supply module is used to supply power to the multi-point temperature probe. The data acquisition module is communicatively connected to the multi-point temperature probe and is used to receive and store the temperature information acquired by the multi-point temperature probe and to perform preliminary processing on the temperature information. The data transmission module is communicatively connected to both the data acquisition module and the remote monitoring and analysis platform, and is used to transmit the temperature information that has undergone preliminary processing to the remote monitoring and analysis platform.

2. The integrated system for monitoring the temperature of glacial moraine dam body according to claim 1, characterized in that: The multi-point temperature probe includes a probe housing and a temperature sensor group disposed inside the probe housing. The temperature sensor group includes multiple temperature sensors arranged at intervals along the axial direction of the probe. Each temperature sensor is communicatively connected to the data acquisition module to acquire temperature data at different depths of the dam body.

3. The integrated system for monitoring the temperature of glacial moraine dam body according to claim 2, characterized in that: The inner wall of the probe housing is connected to a waterproof sealing layer and a thermal insulation filling layer.

4. The integrated system for monitoring the temperature of glacial moraine dam body according to claim 2, characterized in that: The temperature sensor group includes a surface temperature sensor, a middle temperature sensor, and a deep temperature sensor arranged sequentially along the depth direction.

5. The integrated system for monitoring the temperature of glacial till dam bodies according to claim 1, characterized in that: The communication method between the data transmission module and the remote monitoring and analysis platform includes one or more combinations of LoRa, cellular mobile communication, or BeiDou satellite communication.

6. The integrated system for monitoring the temperature of glacial till dam bodies according to claim 1, characterized in that, The remote monitoring and analysis platform includes: Data storage unit, used for storing and managing temperature monitoring data; The three-dimensional visualization unit is used to construct and display a three-dimensional temperature field model of the dam body based on the temperature information received from different multi-point temperature probes. The early warning analysis unit provides graded early warnings based on the rate of change of temperature gradient or temperature anomaly threshold.

7. The integrated system for monitoring the temperature of glacial moraine dam body according to claim 1, characterized in that: The power supply module includes a solar power supply unit and a battery energy storage unit; the solar power supply unit is electrically connected to the battery energy storage unit, and the battery energy storage unit is electrically connected to the multi-point temperature probe.

8. A method for monitoring the temperature of a glacial tillage dam, characterized in that, The integrated system for monitoring the temperature of glacial moraine dams as described in any one of claims 1-7 includes the following steps: S1: Temperature data at different depths at each monitoring point is collected using multi-point temperature probes, and the data acquisition module stores and performs preliminary processing. S2: The temperature data, which has been stored and preliminarily processed, is uploaded to the remote monitoring and analysis platform via the data transmission module; S3: Construct a three-dimensional temperature field model of the dam body based on temperature data on a remote monitoring and analysis platform; S4: Analyze and identify the rate of change of temperature gradient, the rate of temperature change at a single depth point, and the abnormal temperature threshold, and classify the risk based on the analysis and identification results and issue early warning information.

9. The method for monitoring the temperature of a glacial moraine dam body according to claim 8, characterized in that: The analysis identifies the rate of change of temperature gradient, the rate of temperature change at a single depth point, and the abnormal temperature threshold, including: The rate of change of the temperature gradient The calculation method is as follows: ； , Indicates the same probe rod The temperature detected by the i-th temperature sensor at time i. Indicates the same probe rod The depth corresponding to the i-th temperature sensor at time i; The method for calculating the temperature change rate at a single depth point is as follows: This indicates that the depth is Temperature at any moment; The abnormal temperature threshold includes an upper limit threshold. Lower threshold Historical average and standard deviation ; The step of classifying risks and issuing early warning information based on the analysis and identification results includes: A temperature anomaly is determined when the actual temperature T monitored at any point meets any of the following conditions: T > T< or , where k is the standard coefficient; Within the area, let there be a shared... Of the valid measuring points, the number of measuring points identified as abnormal at a certain moment or within a time window is: The abnormal ratio is then defined as: ; When all of the following conditions are met , , and P < B1, it is determined as the first-level stable state; When the conditions of 1℃ / m , 0.5℃ / d , , B1 <P <any one of B2 is met, it is determined as a secondary abnormal state; When satisfied , , , P> If any of the conditions in B2 are met, the situation will be classified as a Level 3 abnormal state and an early warning will be triggered. Where A1 is the first gradient threshold, B1 is the first anomaly ratio threshold, A2 is the second gradient threshold, and B2 is the second anomaly ratio threshold.

10. The method for monitoring the temperature of a glacial moraine dam body according to claim 9, characterized in that: for , for B1 accounts for 10%~20%, and B2 accounts for 30%. 50%.

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