An online intelligent diagnosis and automatic early warning device and method for anti-floating stability of a water delivery channel lining plate

Abstract

The application discloses a kind of water delivery channel lining board anti-floating stable online intelligent diagnosis and automatic early warning device and method, the device includes high-sensitive water pressure sensor, automatic water level gauge, channel section geological structure parameter acquisition module, monitoring and diagnosis early warning controller and remote monitoring terminal.High-sensitive water pressure sensor is arranged in the water surface below the first horse path monitoring well of water delivery channel, automatic water level gauge is arranged in inside channel water, monitoring and diagnosis early warning controller is connected with high-sensitive water pressure sensor and automatic water level gauge communication respectively, remote monitoring terminal is connected with the monitoring and diagnosis early warning controller communication.The application is by real-time acquisition first horse path underground water level, channel water level and channel section geological structure parameter, and innovatively proposes a kind of analytical formula method based on Qiu Buibi assumption calculation channel slope groundwater infiltration line characteristic water depth, and can realize water delivery channel lining board and replacement soil layer anti-floating stable state online monitoring, intelligent diagnosis and automatic early warning in combination with preset critical pressure difference judgment standard.

Description

Technical Field

[0001] This invention relates to the field of water conservancy project safety monitoring technology, specifically to an online intelligent diagnosis and automatic early warning device and method for the anti-buoyancy stability of water conveyance channel lining plates based on dynamic seepage analysis. Background Technology

[0002] Long-distance water conveyance channels, as an important component of modern water conservancy projects, play an irreplaceable role in water resource allocation, agricultural irrigation, and flood control and disaster reduction. However, in actual operation, long-distance water conveyance channels often face complex geological and hydrological conditions, especially in areas with high groundwater levels, where the anti-buoyancy stability of the channel lining is a particularly prominent issue. The continuous influence of the groundwater level causes the lining to bear significant seepage pressure. Over time, this pressure may lead to local instability, leakage, or even collapse of the lining, seriously threatening the safe operation of the water conveyance channel and regional flood control safety. Therefore, how to effectively monitor and provide early warning of the anti-buoyancy stability of water conveyance channel linings has become a key research direction in the field of water conservancy engineering.

[0003] Traditional monitoring and early warning methods mainly rely on manual inspections and numerical simulation techniques, but these methods have many limitations in practical applications. First, manual inspections are inefficient, and monitoring results often depend on the experience and subjective judgment of the inspectors, lacking systematicity and comprehensiveness. Especially in long-distance water conveyance channels, manual inspections struggle to achieve real-time, full-coverage monitoring of the lining stability along the entire length, easily overlooking potential risks. Second, while numerical simulation methods can provide relatively detailed seepage field analysis results, their application requires substantial geological parameters and hydrological data, and the computational process is complex, demanding significant computational resources, making rapid promotion and application in practical engineering difficult. Furthermore, existing numerical simulation methods are often based on idealized assumptions, failing to accurately reflect actual seepage field changes under complex geological conditions and variable hydrological environments, leading to discrepancies between simulation results and actual conditions.

[0004] More seriously, existing technologies exhibit significant lag in early warning capabilities. Traditional monitoring methods cannot dynamically capture real-time changes in the seepage field, making it difficult to issue timely, tiered early warning signals when significant changes occur in the lining's anti-buoyancy stability. This prevents engineering managers from taking timely countermeasures, potentially leading to major engineering accidents. For example, in some high groundwater level water conveyance channel operation cases, the failure to detect early signs of lining instability in a timely manner ultimately resulted in serious leakage accidents, causing huge economic losses and environmental damage. Furthermore, existing technologies also have many shortcomings in data acquisition and processing. Manual inspections rely on periodic checks by on-site personnel, making it difficult to achieve continuous monitoring of key parameters. Moreover, the frequency and accuracy of data acquisition are limited, failing to meet the needs of real-time monitoring. While numerical simulation methods can provide high accuracy, their dependence on data and computational complexity limit their widespread application in practical engineering. Especially under complex geological conditions, due to the significant uncertainty of geological parameters, the reliability of numerical simulation results is often difficult to guarantee.

[0005] In summary, traditional monitoring and early warning methods fall short of meeting the practical requirements for the safe operation of long-distance water conveyance channels in terms of real-time performance, comprehensiveness, and accuracy. Therefore, there is an urgent need for a new monitoring method and device capable of real-time monitoring of the buoyancy stability of the lining slabs of water conveyance channels, rapid detection of changes in the seepage field, and timely issuance of tiered early warning signals. This would enhance the safety and reliability of water conservancy projects and provide strong support for the stable operation of long-distance water conveyance channels. Summary of the Invention

[0006] This invention provides an online intelligent diagnosis and automatic early warning device and method for the anti-buoyancy stability of water conveyance channel lining slabs. By collecting seepage pressure, water level, and geological parameters in real time, combined with dynamic seepage analysis formulas and a graded early warning mechanism, it solves the problems of low efficiency of manual inspection, complex numerical simulation methods, and significant early warning lag in existing technologies. It can monitor the anti-buoyancy stability of water conveyance channel lining slabs in real time under high groundwater levels during the flood season, dynamically capture the seepage field change process, and calculate the characteristic water depth of the groundwater infiltration line on the channel slope based on the groundwater level of the first-level walkway, the channel water level, and the geological structure parameters of the channel section. This enables accurate diagnosis and timely early warning of the instability risk of the lining slabs, thereby ensuring the safe operation of the water conveyance channel and regional flood control safety.

[0007] An online intelligent diagnostic and automatic early warning device for the buoyancy stability of water conveyance channel lining slabs includes:

[0008] A high-sensitivity water pressure sensor is installed below the water surface of the monitoring well on the first-level walkway of the channel slope to monitor the groundwater level h1 of the first-level walkway in real time.

[0009] An automatic water level gauge is installed in the water inside the water conveyance channel to monitor the channel water level H in real time.

[0010] The canal section geological structure parameter acquisition module is used to acquire the geological structure parameters of the canal section, including the permeability coefficient k of the permeable layer above the canal bottom, the permeability coefficient k0 of the permeable layer below the canal bottom, the thickness T of the aquifer below the canal bottom, and the inner slope coefficient m from the first-level horse path to the water conveyance channel.

[0011] The monitoring and diagnostic early warning controller is communicatively connected to the high-sensitivity water pressure sensor, the automatic water level gauge, and the canal section geological structure parameter acquisition module. It is used to receive the groundwater level h1 of the primary canal and the channel water level H, and calculate the characteristic water depth h0 of the groundwater infiltration line and the pressure difference ΔP of the canal slope groundwater infiltration line in combination with the canal section geological structure parameters. This forms the relationship curve between the groundwater level of the primary canal and the channel water level and the relationship curve between the channel water level and the pressure difference. During the annual flood season, the channel water level signal, the seepage pressure signal of the primary canal monitoring well, and their relationship curves collected by the monitoring and diagnostic early warning controller are transmitted wirelessly to the remote monitoring terminal. The monitoring and diagnostic early warning controller triggers graded early warning signals based on the calculated characteristic water depth h0 of the groundwater infiltration line and the pressure difference ΔP of the channel water level H.

[0012] A remote monitoring terminal is communicatively connected to the monitoring and diagnostic early warning controller, and is used to receive and display the graded early warning signals issued by the monitoring and diagnostic early warning controller.

[0013] Furthermore, the primary high-sensitivity water pressure sensor for the canal adopts a high-precision pressure sensor with a measurement accuracy of ≤1mm, and is connected to the monitoring and diagnostic early warning controller via a first cable; the automatic water level gauge for the canal has a measurement accuracy of ≤1cm, and is connected to the monitoring and diagnostic early warning controller via a second cable; the canal section geological structure parameter acquisition module acquires the canal section geological structure parameters from a preset geological database via wireless transmission, and is connected to the monitoring and diagnostic early warning controller via a third cable; the monitoring and diagnostic early warning controller is connected to the remote monitoring terminal via 4G / 5G or LoRa wireless communication.

[0014] Furthermore, the high-sensitivity water pressure sensor is powered by a first cable connected to the monitoring and diagnostic early warning controller; the automatic channel water level gauge is powered by a second cable connected to the monitoring and diagnostic early warning controller; and the channel geological structure parameter acquisition module is powered by a third cable connected to the monitoring and diagnostic early warning controller.

[0015] Furthermore, the monitoring and early warning controller has a built-in calculation unit that calculates the characteristic water depth h0 of the groundwater infiltration line and the pressure difference ΔP between h0 and H based on the following formula:

[0016]

[0017]

[0018] Where h0 is the characteristic water depth of the groundwater infiltration line; H is the channel water level; m is the inner slope coefficient from the primary walkway to the water conveyance channel; h1 is the groundwater level of the primary walkway; L is the minimum distance from the primary walkway seepage pressure monitoring point to the channel bottom plate; k is the permeability coefficient of the permeable layer above the channel bottom; k0 is the permeability coefficient of the permeable layer below the channel bottom; and T is the thickness of the aquifer below the channel bottom.

[0019] Furthermore, the monitoring and early warning controller triggers a graded early warning signal based on the calculated pressure difference ΔP between the characteristic water depth h0 of the groundwater infiltration line and the channel water level H, specifically including:

[0020] ΔP<0.15m: No risk, meets the allowable critical value for channel lining and replacement layer;

[0021] 0.15m≤ΔP<1.7m: Triggering lining slab instability warning;

[0022] ΔP≥1.7m: Triggers an early warning for instability of the lining slab and replacement soil layer.

[0023] Furthermore, the monitoring and diagnostic early warning controller has a built-in data storage module that stores channel water level signals, first-level roadway monitoring well seepage pressure signals, and geological structure parameters of the channel section on an annual basis, and generates historical trend analysis reports.

[0024] Furthermore, the monitoring and diagnostic early warning controller has a built-in data storage module that stores channel water level signals, first-level roadway monitoring well seepage pressure signals, and geological structure parameters of the channel section on an annual basis, and generates historical trend analysis reports.

[0025] A method for online intelligent diagnosis and automatic early warning of buoyancy stability of water conveyance channel lining slabs includes the following steps:

[0026] Step 1: Real-time collection of groundwater level h1 of the primary paved road, water level H of the channel, and geological structural parameters of the channel section. The geological structural parameters of the channel section include the permeability coefficient k of the permeable layer above the channel bottom, the permeability coefficient k0 of the permeable layer below the channel bottom, the thickness T of the aquifer below the channel bottom, and the inner slope coefficient m of the primary paved road to the water conveyance channel.

[0027] Step 2: Calculate the characteristic water depth h0 of the groundwater infiltration line based on the analytical formula;

[0028] Step 3: Calculate the pressure difference ΔP between h0 and H;

[0029] Step 4: Based on the comparison result of ΔP and the preset critical value, trigger a graded early warning signal;

[0030] Step 5: Send the graded early warning signal to the remote monitoring terminal via wireless transmission.

[0031] Furthermore, the formulas for calculating the characteristic water depth h0 of the groundwater infiltration line and the pressure difference ΔP between it and the channel water level are as follows:

[0032]

[0033] Where h0 is the characteristic water depth of the groundwater infiltration line; H is the channel water level; m is the inner slope coefficient from the primary walkway to the water conveyance channel; h1 is the groundwater level of the primary walkway; L is the minimum distance from the seepage pressure monitoring point of the primary walkway to the bottom of the channel; k is the permeability coefficient of the permeable layer above the channel bottom; k0 is the permeability coefficient of the permeable layer below the channel bottom; T is the thickness of the aquifer below the channel bottom; and ΔP is the pressure difference between the characteristic water depth h0 of the groundwater infiltration line and the channel water level H.

[0034] Furthermore, the tiered early warning criteria in step 4 are as follows:

[0035] ΔP<0.15m: No risk, meets the allowable critical value for channel lining and replacement layer;

[0036] 0.15m≤ΔP<1.7m: Triggering lining slab instability warning;

[0037] ΔP≥1.7m: Triggers an early warning for instability of the lining slab and replacement soil layer.

[0038] This invention features a small and easy-to-install device. After the construction of the primary walkway monitoring well in the water conveyance channel, it is deployed within the monitoring well and the channel itself. By monitoring groundwater pressure, channel water level, and geological parameters in real time, it dynamically captures changes in the seepage field, enabling accurate diagnosis and timely early warning of the buoyancy stability of the water conveyance channel lining. This ensures the safe operation of the water conveyance channel and guarantees regional flood control safety. This invention solves the problems of low efficiency of manual inspections, complex numerical simulation methods, and significant early warning lag in existing technologies. It fills the gap in existing technologies for online real-time monitoring and accurate early warning of the buoyancy stability of water conveyance channel linings, and has significant engineering application value. Attached Figure Description

[0039] Figure 1 This is a schematic diagram of the structure of the online intelligent diagnosis and automatic early warning device for the anti-buoyancy stability of water conveyance channel lining plates of the present invention;

[0040] Figure 2 yes Figure 1 Enlarged view of section A in the middle.

[0041] The markings in the diagram are as follows: 1-High-sensitivity water pressure sensor; 2-Automatic water level gauge; 3-Ditch section geological structure parameter acquisition module; 4-Monitoring and diagnostic early warning controller; 5-First cable; 6-Second cable; 7-Third cable; 8-Remote terminal; 9-Water level on the inner side of the water conveyance channel; 10-Channel slope monitoring well; 11-Permeable layer above the channel bottom; 12-Permeable layer below the channel bottom; 13-Inner slope from the primary walkway to the water conveyance channel; 14-Thickness of the aquifer below the channel bottom. Detailed Implementation

[0042] The technical solutions of the present invention will now be clearly and completely described with reference to the accompanying drawings.

[0043] Please refer to Figure 1 This invention provides an online intelligent diagnosis and automatic early warning device for the anti-buoyancy stability of water conveyance channel lining plates, including a high-sensitivity water pressure sensor 1, an automatic water level gauge 2, a channel section geological structure parameter acquisition module 3, a monitoring and diagnosis early warning controller 4, and a remote monitoring terminal 8.

[0044] The high-sensitivity water pressure sensor 1 is installed below the water surface of the first-level walkway monitoring well 10 on the channel slope to obtain the groundwater level h1 of the first-level walkway; the automatic water level gauge 2 is installed in the water inside the water conveyance channel 9 to monitor the channel water level H in real time; the channel section geological structure parameter acquisition module 3 collects the channel section geological structure parameters (k, T, m) from the preset geological database in real time through wireless transmission, and is connected to the monitoring and diagnostic early warning controller 4 through the third cable 7.

[0045] The high-sensitivity water pressure sensor 1 and the automatic water level gauge 2 are connected to the monitoring and diagnostic early warning controller 4 via the first cable 5 and the second cable 6, respectively. The monitoring and diagnostic early warning controller 4 and the remote monitoring terminal 8 are connected via 4G / 5G or LoRa wireless communication to form a system. The slope structure of the water conveyance channel 9 includes a permeable layer 11 above the channel bottom and a permeable layer 12 below the channel bottom. Groundwater seeps into the primary walkway monitoring well 10 through the permeable layer 11, forming a seepage pressure monitoring signal.

[0046] The high-sensitivity water pressure sensor 1 has a water pressure sensing accuracy of 1mm. It is powered by the first cable 5 connected to the monitoring and diagnostic early warning controller 4 and sends the first-level groundwater level h1 signal to the controller 4 at a set data acquisition frequency of 1 time / 30 minutes (which can be adjusted according to the working conditions).

[0047] The automatic water level gauge 2 has a measurement accuracy of 1 cm. It is powered by the second cable 6 and transmits the channel water level H signal to the monitoring and diagnostic early warning controller 4 at a set data acquisition frequency of once every 30 minutes.

[0048] The geological structure parameter acquisition module 3 of the canal section updates the parameters (k, T, m) in the geological database annually and is connected to the controller 4 via the third cable 7 to ensure real-time parameter synchronization.

[0049] The monitoring and diagnostic early warning controller 4 summarizes the received water level h1, H, and geological parameters, and its built-in calculation unit calculates the characteristic water depth h0 of the groundwater infiltration line and the pressure difference ΔP using the following formulas:

[0050]

[0051] Where h0 is the characteristic water depth of the groundwater infiltration line (m); H is the channel water level (m); m is the inner slope coefficient from the primary walkway to the water conveyance channel; h1 is the groundwater level of the primary walkway (m); L is the minimum distance from the primary walkway seepage pressure monitoring point to the channel bottom (m); k is the permeability coefficient of the permeable layer above the channel bottom (m / d); k0 is the permeability coefficient of the permeable layer below the channel bottom (m / d); T is the thickness of the aquifer below the channel bottom (m); and ΔP is the pressure difference between the characteristic water depth h0 of the groundwater infiltration line and the channel water level H (m).

[0052] The data collected from the monitoring and diagnostic early warning controller 4, including water level, water pressure, geological parameters, and the calculated characteristic water depth h0 and pressure difference ΔP of the groundwater infiltration line, form the relationship curves between the groundwater level of the primary channel and the channel water level (h1-H) and between the channel water level and the pressure difference (H-ΔP). These curves are stored annually for comparative analysis, with the relationship at the first time when the groundwater level of the primary channel is at its highest serving as the standard curve. Through annual comparative analysis of h1-H and H-ΔP data, real-time online monitoring of the buoyancy stability of the lining slab and replacement layer is achieved.

[0053] The monitoring and diagnostic early warning controller 4 uses the pressure difference ΔP calculated in real time to form an intelligent diagnosis of the anti-buoyancy stability and instability of the lining plate of the water conveyance channel. It triggers corresponding graded early warnings according to different degrees of instability and transmits the monitoring and graded early warning signals to the remote monitoring terminal 8 in real time.

[0054] The monitoring and diagnostic early warning controller 4 triggers graded early warning signals based on the calculated pressure difference ΔP. The specific grading criteria and response logic are as follows:

[0055] (1) Level 1 Warning (No Risk)

[0056] ΔP range: ΔP < 0.15m;

[0057] The system displays: Remote monitoring terminal 8 shows a green indicator, and the H-ΔP relationship curve is stable;

[0058] Response measures: Generate daily monitoring reports without manual intervention.

[0059] (2) Level II warning (lining plate instability):

[0060] ΔP range: 0.15m ≤ ΔP < 1.7m;

[0061] System display: Remote monitoring terminal 8 shows a yellow indicator, and the H-ΔP curve suddenly rises;

[0062] Response measures: Automatically send a text message to management personnel, prompting "Risk of lining plate instability, inspection recommended", and initiate drainage instructions to reduce local water pressure.

[0063] (3) Level III warning (combined instability of lining and backfill layer):

[0064] ΔP range: ΔP ≥ 1.7m;

[0065] The system displays: Remote monitoring terminal 8 shows a red indicator, and the H-ΔP curve continues to increase sharply;

[0066] Response measures: Trigger the emergency broadcast system and initiate emergency reinforcement procedures.

[0067] In one embodiment, the high-sensitivity water pressure sensor 1 has an accuracy of 1 mm, the automatic water level gauge 2 has an accuracy of 1 cm, and the geological structure parameter acquisition module 3 of the canal section updates the parameters (k, T, m) in the geological database annually. The signal acquisition frequency of the first two is uniformly set to 1 time / 30 minutes. When rainfall causes the groundwater level in the area to rise, the groundwater h1 value of the first-level canal walkway begins to rise rapidly, and the monitoring and diagnostic early warning controller 4 begins to send an early warning signal to the remote monitoring terminal 8.

[0068] Example 1: This calculation example uses a water conveyance channel-1 as the actual example. The groundwater level h1 of the primary access road, the channel water level H, and geological structural parameters (k, T, m) are used as variable factors. The analytical formula proposed in this invention is used to provide an early warning of the anti-buoyancy stability of the channel lining slab, and the results are compared and verified with actual numerical simulation values. The main calculation parameters are shown in Table 1, and the calculation results are shown in Table 2.

[0069] Table 1 Input Parameters for Water Level Early Warning of a Certain Section of a Water Conveyor Canal

[0070]

[0071] Table 2. Fitting process values ​​for water level early warning of a certain section of a water conveyance canal.

[0072]

[0073] Condition 1: When the water level h1 of the first-level walkway is lower than 147.11m, the head difference ΔP between the characteristic water level of the groundwater infiltration line and the water level of the channel is less than 0.15m, and the water pressure difference between the channel lining plate and the replacement soil layer can meet the requirements. The monitoring and diagnostic early warning controller 4 determines it to be a first-level early warning (no risk), the platform displays a green mark, and a daily monitoring report is generated.

[0074] Condition 2: When the water level h1 of the primary walkway is between 147.16m and 148.27m, 0.15m≤ΔP<1.7m, the water pressure difference of the replacement soil layer can meet the requirements, but the water pressure difference of the lining slab cannot meet the requirements. The monitoring and diagnostic early warning controller 4 determines it as a level two early warning (lining slab instability). The platform displays a yellow mark, automatically pushes a text message to the management personnel, prompting "Risk of lining slab instability, inspection recommended", and initiates a drainage command to reduce local water pressure.

[0075] Condition 3: When the water level h1 monitored by the first-level walkway exceeds 149.11m, the head difference ΔP between the characteristic water level of the groundwater saturation line and the water level of the channel is greater than 1.7m. The water pressure difference between the channel lining slab and the replacement soil layer cannot meet the requirements. The monitoring and diagnostic early warning controller 4 determines that it is a level three early warning (joint instability of the lining slab and the replacement layer). The platform displays a red mark, sends an emergency broadcast system, and initiates an emergency reinforcement procedure.

[0076] Example 2: This calculation example uses a water conveyance channel-2 as the actual example. The groundwater level h1 of the primary access road, the channel water level H, and geological structural parameters (k, T, m) are used as variable factors. The analytical formula proposed in this invention is used to provide an early warning of the anti-buoyancy stability of the channel lining slab, and the results are compared and verified with actual numerical simulation values. The main calculation parameters are shown in Table 3, and the calculation results are shown in Table 4.

[0077] Table 3 Input Parameters for Water Level Early Warning of a Certain Section of a Water Conveyor Canal (Table 2)

[0078]

[0079] Table 4. Fitting process values ​​for the -2 water level early warning of a certain water conveyance canal section.

[0080]

[0081] Condition 4: When the water level h1 of the first-level walkway is below 78.34m, the head difference ΔP between the characteristic water level of the groundwater infiltration line and the water level of the channel is less than 0.15m, and the water pressure difference between the channel lining plate and the replacement soil layer can meet the requirements, the monitoring and diagnostic early warning controller 4 determines it as a first-level early warning (no risk), the platform displays a green mark, and a daily monitoring report is generated.

[0082] Condition 5: When the water level h1 of the primary walkway is between 78.45m and 78.95m, 0.15m≤ΔP<1.7m, the water pressure difference of the backfill soil layer can meet the requirements, but the water pressure difference of the lining slab cannot meet the requirements. The monitoring and diagnostic early warning controller 4 determines it as a level two early warning (lining slab instability). The platform displays a yellow mark, automatically pushes a text message to the management personnel, prompting "Risk of lining slab instability, inspection recommended", and initiates a drainage command to reduce local water pressure.

[0083] The monitoring and diagnostic early warning controller 4 collects water level, water pressure and geological parameter signals in real time every flood season (May to October) and generates a relationship curve. Based on the calculated pressure difference ΔP, it triggers a graded early warning signal of the corresponding level and sends it to the remote monitoring terminal 8.

[0084] The working principle of this invention is as follows: Figure 1 As shown, rainfall in and around the water conveyance channel during the annual flood season significantly raises the groundwater level. Due to seepage, the groundwater level at the first-level access road of the channel begins to rise. High-sensitivity water pressure sensor 1 begins collecting groundwater pressure signals. The monitoring and diagnostic early warning controller 4 then collects the groundwater pressure value detected by the high-sensitivity water pressure sensor 1, the channel water level value detected by the automatic water level gauge 2, and the geological parameter values ​​collected by the channel section geological structure parameter acquisition module 3, according to a set data acquisition frequency. Simultaneously, the monitoring and diagnostic early warning controller 4 sends this information to the remote monitoring terminal 8, achieving real-time online monitoring of the anti-buoyancy status of the water conveyance channel lining. At the same time, the monitoring and diagnostic early warning controller 4 uses the collected water level, water pressure, and geological parameter signals to calculate the characteristic water depth h0 of the groundwater infiltration line and the pressure difference ΔP according to formulas. Based on the calculated pressure difference ΔP, it triggers a graded early warning signal of the corresponding level and transmits it wirelessly to the remote monitoring terminal. Over time, the above steps are repeated, with data collection, analysis, and diagnosis performed annually during the flood season, thus achieving long-term online monitoring and diagnostic early warning of the anti-buoyancy stability of the water conveyance channel lining.

[0085] This invention also provides an online intelligent diagnosis and automatic early warning method for the anti-buoyancy stability of water conveyance channel lining plates, which uses the above-mentioned device and includes the following steps:

[0086] During the flood season, as the groundwater level in the water conveyance channel rises, the high-sensitivity water pressure sensor 1 monitors the water pressure of the groundwater level in the first-level access road in real time and transmits the monitored water pressure signal to the monitoring and diagnostic early warning controller 4; the automatic water level gauge 2 monitors the channel water level value in real time and transmits the monitored water level signal to the monitoring and diagnostic early warning controller 4; the channel geological structure parameter acquisition module 3 collects the geological structure parameters of the channel section in real time, including permeability coefficient, aquifer thickness, etc., and transmits the collected data to the monitoring and diagnostic early warning controller 4;

[0087] The monitoring and diagnostic early warning controller 4 collects the water pressure signal from the high-sensitivity water pressure sensor 1, the water level signal from the automatic water level gauge 2, and the geological parameter data from the canal section geological structure parameter acquisition module 3 according to the set data acquisition frequency. It calculates the characteristic water depth h0 of the groundwater infiltration line and the pressure difference ΔP through the built-in calculation unit, and forms the relationship curve between the groundwater level of the first-level roadway and the channel water level (h1-H) and the relationship curve between the channel water level and the pressure difference (H-ΔP) respectively. During the flood season each year, the monitoring and diagnostic early warning controller 4 transmits the collected water level, water pressure and geological parameter signals and their relationship curves to the remote monitoring terminal 8 through wireless transmission.

[0088] During the annual flood season (generally May to October), the monitoring and diagnostic early warning controller 4 collects real-time signals of water level, water pressure, and geological parameters, generating curves showing the relationship between the groundwater level of the primary channel and the channel water level (h1-H) and the relationship between the channel water level and the pressure difference (H-ΔP). These curves are stored annually for comparative analysis, with the relationship at the first time when the groundwater level of the primary channel is at its highest serving as the standard curve. Through annual comparative analysis of h1-H and H-ΔP data, real-time online monitoring of the buoyancy stability of the lining slab and replacement layer is achieved.

[0089] The monitoring and diagnostic early warning controller 4 uses the pressure difference ΔP calculated in real time to form an intelligent diagnosis of the anti-buoyancy stability and instability of the lining plate of the water conveyance channel. It triggers corresponding graded early warnings according to different degrees of instability and transmits the monitoring and graded early warning signals to the remote monitoring terminal 8 in real time.

[0090] In practice, the implementation follows the aforementioned grading standards and response logic for anti-buoyancy stability. Based on the calculated characteristic water depth and pressure difference of the groundwater infiltration line, corresponding three-level early warning indicators and response measures are implemented, specifically including:

[0091] (1) Level 1 Warning (No Risk)

[0092] ΔP range: ΔP < 0.15m;

[0093] The system displays: Remote monitoring terminal 8 shows a green indicator, and the H-ΔP relationship curve is stable;

[0094] Response measures: Generate daily monitoring reports without manual intervention.

[0095] (2) Level II warning (lining plate instability):

[0096] ΔP range: 0.15m ≤ ΔP < 1.7m;

[0097] System display: Remote monitoring terminal 8 shows a yellow indicator, and the H-ΔP curve suddenly rises;

[0098] Response measures: Automatically send a text message to management personnel, prompting "Risk of lining plate instability, inspection recommended", and initiate drainage instructions to reduce local water pressure.

[0099] (3) Level III warning (combined instability of lining and backfill layer):

[0100] ΔP range: ΔP ≥ 1.7m;

[0101] The system displays: Remote monitoring terminal 8 shows a red indicator, and the H-ΔP curve continues to increase sharply;

[0102] Response measures: Trigger the emergency broadcast system and initiate emergency reinforcement procedures.

[0103] This invention fully utilizes seepage control principles and automatic data analysis capabilities to provide an online monitoring, diagnostic, and early warning device for the anti-buoyancy stability of water conveyance channel lining slabs, with channel water levels accurate to 1 cm and water pressure values ​​in the primary channel walkway monitoring wells accurate to 1 mm. By setting different data acquisition frequencies to adapt to the rate of groundwater level rise during the flood season, it facilitates the assessment of the lining slab's operational status and provides support for emergency rescue. During non-flood seasons when the lining slab is not affected by seepage, data acquisition can be paused or set to occur intermittently to save power and facilitate maintenance.

[0104] Compared with existing technologies, this invention has significant advantages. Due to its small size and simple installation, it innovatively proposes a diagnostic formula for anti-buoyancy stability based on the characteristic water depth of the groundwater infiltration line and its pressure difference with the channel water level. By real-time monitoring of groundwater seepage pressure, channel water level, and geological structure parameters of the channel section, combined with a dynamic seepage analysis formula based on the Dubuis assumption, the dynamic balance between the seepage buoyancy borne by the lining slab and its anti-buoyancy bearing capacity can be directly reflected. Furthermore, through actual engineering examples, it has been verified that when the anti-buoyancy safety factor of a certain water conveyance channel reaches the critical value, the calculation results of the dynamic seepage analysis formula are basically consistent with the results of refined numerical simulation, with a ΔP calculation error of less than 3%. In addition, by incorporating a graded early warning mechanism, it effectively solves the problems of low efficiency of manual inspection, complex numerical simulation methods, and significant early warning lag in existing technologies. This allows for quantitative analysis and diagnosis of the operating status of in-service lining slabs, especially their anti-buoyancy stability, ensuring the normal operation of water conveyance channels during the flood season and safeguarding regional flood control safety. This invention enables real-time online analysis, diagnosis, and early warning of the buoyancy stability of lining slabs during operation, greatly improving the efficiency and accuracy of inspections during the flood season. The monitoring and early warning device uses DC low-voltage power supply and can be powered by a battery connected to a solar panel, making it energy-saving, environmentally friendly, and unaffected by power outages. The entire process from information collection, analysis, and calculation to early warning requires no human intervention, making it a method for online intelligent diagnosis and automatic early warning of the buoyancy stability of in-service lining slabs.

[0105] This invention can solve the problem of diagnosing the buoyancy stability of lining plates in similar water conveyance channels, monitor the operating status and functional changes of lining plates around the clock, and realize real-time online diagnosis and timely early warning. It also fits the major trend of water conservancy informatization and digital twins, and has broad application prospects.

[0106] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. An online intelligent diagnosis and automatic early warning device for the anti-buoyancy stability of water conveyance channel lining plates, characterized in that, include: A high-sensitivity water pressure sensor (1) is installed below the water surface of the monitoring well of the first-level walkway on the side slope of the channel, and is used to monitor the groundwater level h1 of the first-level walkway in real time. Automatic water level gauge (2) is installed in the water inside the water conveyance channel to monitor the channel water level H in real time; The geological structure parameter acquisition module (3) is used to acquire geological structure parameters of the canal section, including the permeability coefficient k of the permeable layer above the canal bottom, the permeability coefficient k0 of the permeable layer below the canal bottom, the thickness T of the aquifer below the canal bottom, and the inner slope coefficient m from the first-level horse path to the water conveyance channel. The monitoring and diagnostic early warning controller (4) is connected to the high-sensitivity water pressure sensor (1), the automatic water level gauge (2) and the channel geological structure parameter acquisition module (3) respectively. It is used to receive the groundwater level h1 of the first-level roadway and the channel water level H, and calculate the characteristic water depth h0 of the groundwater infiltration line and the pressure difference ΔP of the channel slope groundwater infiltration line in combination with the geological structure parameters of the channel section. It forms the relationship curve between the groundwater level of the first-level roadway and the channel water level and the relationship curve between the channel water level and the pressure difference. Every year during the flood season, the channel water level signal, the seepage pressure signal of the monitoring well of the first-level roadway and their relationship curve are collected by the monitoring and diagnostic early warning controller (4) and sent to the remote monitoring terminal (8) through wireless transmission. The monitoring and diagnostic early warning controller (4) triggers the graded early warning signal according to the calculated characteristic water depth h0 of the groundwater infiltration line and the pressure difference ΔP of the channel water level H. The remote monitoring terminal (8) is connected in communication with the monitoring and diagnostic early warning controller (4) and is used to receive and display the graded early warning signals issued by the monitoring and diagnostic early warning controller (4).

2. The online intelligent diagnosis and automatic early warning device for the anti-buoyancy stability of water conveyance channel lining plates as described in claim 1, characterized in that: The high-sensitivity water pressure sensor (1) is a high-precision pressure sensor with a measurement accuracy of ≤1mm. It is connected to the monitoring and diagnostic early warning controller (4) via the first cable (5). The automatic water level gauge (2) has a measurement accuracy of ≤1cm. It is connected to the monitoring and diagnostic early warning controller (4) via the second cable (6). The channel geological structure parameter acquisition module (3) acquires the channel geological structure parameters in the preset geological database through wireless transmission. It is connected to the monitoring and diagnostic early warning controller (4) via the third cable (7). The monitoring and diagnostic early warning controller (4) is connected to the remote monitoring terminal (8) via 4G / 5G or LoRa wireless communication.

3. The online intelligent diagnosis and automatic early warning device for the anti-buoyancy stability of water conveyance channel lining plates as described in claim 2, characterized in that: The high-sensitivity water pressure sensor (1) is powered by a first cable (5) connected to the monitoring and diagnostic early warning controller (4); the automatic water level gauge (2) is powered by a second cable (6) connected to the monitoring and diagnostic early warning controller (4); and the channel section geological structure parameter acquisition module (3) is powered by a third cable (7) connected to the monitoring and diagnostic early warning controller (4).

4. The online intelligent diagnosis and automatic early warning device for the anti-buoyancy stability of water conveyance channel lining plates as described in claim 1, characterized in that: The monitoring and diagnostic early warning controller (4) has a built-in calculation unit that calculates the characteristic water depth h0 of the groundwater infiltration line and the pressure difference ΔP between h0 and H based on the following formula: ； ； Where h0 is the characteristic water depth of the groundwater infiltration line (m); H is the channel water level (m); m is the inner slope coefficient from the primary walkway to the water conveyance channel; h1 is the groundwater level of the primary walkway (m); L is the minimum distance from the primary walkway seepage pressure monitoring point to the channel bottom (m); k is the permeability coefficient of the permeable layer above the channel bottom (m / d); k0 is the permeability coefficient of the permeable layer below the channel bottom (m / d); and T is the thickness of the aquifer below the channel bottom (m).

5. The online intelligent diagnosis and automatic early warning device for the anti-buoyancy stability of water conveyance channel lining plates as described in claim 1, characterized in that: The monitoring and diagnostic early warning controller (4) triggers a graded early warning signal based on the calculated pressure difference ΔP between the characteristic water depth h0 of the groundwater infiltration line and the channel water level H, specifically including: ΔP < 0.15m: No risk, meets the allowable critical value for channel lining and replacement layer; 0.15m ≤ ΔP < 1.7m: Triggering lining slab instability warning; ΔP ≥ 1.7m: Triggers an early warning for instability of the lining slab and replacement soil layer.

6. The online intelligent diagnosis and automatic early warning device for the anti-buoyancy stability of water conveyance channel lining plates as described in claim 1, characterized in that: The monitoring and diagnostic early warning controller (4) has a built-in data storage module that stores channel water level signals, first-level roadway monitoring well seepage pressure signals and channel geological structure parameters annually, and generates historical trend analysis reports.

7. The online intelligent diagnosis and automatic early warning device for the anti-buoyancy stability of water conveyance channel lining plates as described in claim 1, characterized in that: The remote monitoring terminal (8) supports multi-level user permission management and allows users to view graded early warning signals and relationship curves in real time via the Web or mobile terminal.

8. A method for online intelligent diagnosis and automatic early warning of the buoyancy stability of lining plates in water conveyance channels, characterized in that, Includes the following steps: Step 1: Real-time collection of groundwater level h1 of the primary paved road, water level H of the channel, and geological structural parameters of the channel section. The geological structural parameters of the channel section include the permeability coefficient k of the permeable layer above the channel bottom, the permeability coefficient k0 of the permeable layer below the channel bottom, the thickness T of the aquifer below the channel bottom, and the inner slope coefficient m of the primary paved road to the water conveyance channel. Step 2: Calculate the characteristic water depth h0 of the groundwater infiltration line based on the analytical formula; Step 3: Calculate the pressure difference ΔP between h0 and H; Step 4: Based on the comparison result of ΔP and the preset critical value, trigger a graded early warning signal; Step 5: Send the graded early warning signal to the remote monitoring terminal (8) via wireless transmission.

9. The method for online intelligent diagnosis and automatic early warning of buoyancy stability of water conveyance channel lining plates as described in claim 8, characterized in that: The formulas for calculating the characteristic water depth h0 of the groundwater infiltration line and the pressure difference ΔP between it and the channel water level are as follows: ； ； Where h0 is the characteristic water depth of the groundwater infiltration line (m); H is the channel water level (m); m is the inner slope coefficient from the primary walkway to the water conveyance channel; h1 is the groundwater level of the primary walkway (m); L is the minimum distance from the primary walkway seepage pressure monitoring point to the channel bottom (m); k is the permeability coefficient of the permeable layer above the channel bottom (m / d); k0 is the permeability coefficient of the permeable layer below the channel bottom (m / d); T is the thickness of the aquifer below the channel bottom (m); and ΔP is the pressure difference between the characteristic water depth h0 of the groundwater infiltration line and the channel water level H (m).

10. The method for online intelligent diagnosis and automatic early warning of buoyancy stability of water conveyance channel lining plates as described in claim 8, characterized in that: The graded early warning standard in step 4 is as follows: ΔP < 0.15m: No risk, meets the allowable critical value for channel lining and replacement layer; 0.15m ≤ ΔP < 1.7m: Triggering lining slab instability warning; ΔP ≥ 1.7m: Triggers an early warning for instability of the lining slab and replacement soil layer.

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