Water conveyance canal lining plate anti-floating stability online intelligent diagnosis and automatic early warning device and method

Abstract

The invention discloses a water conveyance canal lining plate anti-floating stability online intelligent diagnosis and automatic early warning device and method. The device comprises a high-sensitivity water pressure sensor, an automatic water level gauge, a canal section geologic structure parameter acquisition module, a monitoring and diagnosis early warning controller and a remote monitoring terminal. The high-sensitivity water pressure sensor is arranged below the water surface of a first-stage riding track monitoring well of the water conveyance canal, the automatic water level gauge is arranged in inner side canal water, the monitoring and diagnosis early warning controller is in communication connection with the high-sensitivity water pressure sensor and the automatic water level gauge, and the remote monitoring terminal is in communication connection with the monitoring and diagnosis early warning controller. According to the method, the underground water level of the first-level riding track, the water level of the channel and the geological structure parameters of the channel section are collected in real time, an analytic formula method based on Dupuff assumption is innovatively provided for calculating the characteristic water depth of the underground water infiltration line of the channel slope, and the preset critical pressure difference judgment standard is combined; on-line monitoring, intelligent diagnosis and automatic early warning of the anti-floating stable state of the lining plate of the water delivery canal and the replacement fill stratum can be achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of water conservancy project safety monitoring, and in particular to an online intelligent diagnosis and automatic early warning device and method for anti-floating stability of a water conveyance channel lining plate based on dynamic seepage analysis. Background Art

[0002] Long-distance water transfer channels, as an essential 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 transfer channels often face complex geological and hydrological conditions. This is particularly true in areas with high groundwater levels, where the anti-floating stability of channel linings is a particularly prominent issue. The continuous action of the groundwater level causes the lining to be subjected to significant seepage pressure. Over time, this pressure can lead to localized instability, leakage, or even collapse, posing a serious threat to the safe operation of water transfer channels and regional flood control. Therefore, effective monitoring and early warning of the anti-floating stability of water transfer channel linings has become a key research topic in the field of water conservancy engineering.

[0003] Traditional monitoring and early warning methods mainly rely on manual inspections and numerical simulation technology, but these methods have many limitations in practical applications. First, the manual inspection method is inefficient, and the monitoring results often rely on the experience and subjective judgment of the inspectors, lacking systematicity and comprehensiveness. Especially in long-distance water transfer channels, manual inspections are difficult to achieve real-time, full-coverage monitoring of the anti-floating stability of the lining plates along the entire line, and potential risk points are easily missed. Secondly, although numerical simulation methods can provide relatively detailed seepage field analysis results, their application requires a large amount of geological parameters and hydrological data support, and the calculation process is complex and requires high computing resources, making it difficult to quickly promote and apply them in actual projects. In addition, existing numerical simulation methods are often based on idealized assumptions, which makes it difficult to accurately reflect the actual seepage field changes under complex geological conditions and variable hydrological environments, resulting in a certain deviation between the simulation results and the actual situation.

[0004] More seriously, existing technologies suffer from a significant lag in early warning. Traditional monitoring methods are unable to dynamically capture real-time changes in the seepage field, making it difficult to issue graded warning signals promptly when significant changes in the lining's anti-buoyancy stability occur. This prevents project managers from taking timely countermeasures, potentially leading to major engineering accidents. For example, in some water diversion channel operations involving high groundwater levels, the failure to detect early signs of lining instability ultimately led to serious leakage accidents, resulting in significant economic losses and environmental damage. Furthermore, existing technologies also suffer from numerous deficiencies in data collection and processing. Manual inspections rely on regular checks by on-site personnel, making it difficult to continuously monitor key parameters. Furthermore, the frequency and accuracy of data collection are limited, making it difficult to meet the requirements of real-time monitoring. While numerical simulation methods offer high accuracy, their dependence on data and computational complexity limit their widespread application in practical engineering. Particularly in complex geological conditions, the reliability of numerical simulation results is often difficult to guarantee due to the high uncertainty of geological parameters.

[0005] In summary, traditional monitoring and early warning methods are unable to meet the practical requirements for the safe operation of long-distance water transfer channels in terms of real-time performance, comprehensiveness, and warning accuracy. Therefore, a new monitoring method and device is urgently needed that can monitor the anti-floating stability of water transfer channel linings in real time, rapidly capture changes in the seepage field, and promptly issue graded early warning signals. This will improve the safety and reliability of water conservancy projects and provide a strong guarantee for the stable operation of long-distance water transfer channels. Summary of the Invention

[0006] The present invention provides an online intelligent diagnosis and automatic early warning device and method for the anti-floating stability of the lining plate of a water conveyance channel. By real-time collection of seepage pressure, water level and geological parameters, combined with a dynamic seepage analytical formula and a graded early warning mechanism, the problems of low manual inspection efficiency, complex numerical simulation methods and obvious early warning lag in the existing technology are solved. The device can realize real-time monitoring of the anti-floating stability of the lining plate of the water conveyance channel under high groundwater level conditions during the flood season, dynamically capture the change process of the seepage field, and calculate the characteristic water depth of the groundwater infiltration line of the channel slope based on the groundwater level of the first-level horse road of the channel, the channel water level and the geological structure parameters of the channel section, so as to realize accurate diagnosis and timely early warning of the instability risk of the lining plate, thereby ensuring the safe operation of the water conveyance channel and regional flood control safety.

[0007] An online intelligent diagnosis and automatic early warning device for anti-floating stability of a water channel lining plate, comprising:

[0008] The high-sensitivity water pressure sensor is installed below the water surface of the first-level horse track monitoring well on the channel slope, and is used to monitor the groundwater level h1 of the first-level horse track in real time;

[0009] Automatic water level gauge, installed in the water inside the water channel, used to monitor the channel water level H in real time;

[0010] The channel section geological structure parameter acquisition module is used to obtain the channel section geological structure parameters, including 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 from the first-level horse road to the water diversion channel;

[0011] The monitoring and diagnosis and early warning controller is respectively communicated with the high-sensitivity water pressure sensor, the automatic water level gauge and the channel section geological structure parameter acquisition module, and is used to receive the first-level horseway groundwater level h1 and the channel water level H, and calculate the characteristic water depth h0 and the pressure difference ΔP of the channel slope groundwater infiltration line in combination with the channel section geological structure parameters, to form a relationship curve between the first-level horseway groundwater level and the channel water level and a relationship curve between the channel water level and the pressure difference. The channel water level signal, the seepage pressure signal of the first-level horseway monitoring well and the relationship curve thereof are collected by the monitoring and diagnosis and early warning controller during the flood season each year and are sent to the remote monitoring terminal via wireless transmission. The monitoring and diagnosis and early warning controller triggers a graded early warning signal 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] The remote monitoring terminal is in communication with the monitoring and diagnosis warning controller and is used to receive and display the graded warning signals issued by the monitoring and diagnosis warning controller.

[0013] Furthermore, the first-level horse trail high-sensitive water pressure sensor adopts a high-precision pressure sensor with a measurement accuracy of ≤1mm, and is connected to the monitoring and diagnosis and early warning controller through a first cable; the channel automatic water level meter has a measurement accuracy of ≤1cm and is connected to the monitoring and diagnosis and early warning controller through a second cable; the channel section geological structure parameter acquisition module obtains the channel section geological structure parameters in the preset geological database through wireless transmission, and is connected to the monitoring and diagnosis and early warning controller through a third cable; the monitoring and diagnosis and early warning controller is connected to the remote monitoring terminal through 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 diagnosis and early warning controller; the channel automatic water level meter is powered by a second cable connected to the monitoring and diagnosis and early warning controller; and the channel section geological structure parameter acquisition module is powered by a third cable connected to the monitoring and diagnosis and 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] Among them, 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 first-level horseway to the water diversion channel; h1 is the groundwater level of the first-level horseway; L is the minimum distance from the seepage pressure monitoring point of the first-level horseway to the channel bottom; 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.

[0019] Furthermore, the monitoring and early warning controller triggers a graded early warning signal according to 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, meeting the critical value of the channel lining and replacement layer;

[0021] 0.15m≤ΔP<1.7m: triggering lining plate instability warning;

[0022] ΔP ≥ 1.7m: triggers the instability warning of the lining plate and replacement soil layer.

[0023] Furthermore, the monitoring and diagnosis early warning controller has a built-in data storage module, which stores channel water level signals, seepage pressure signals of first-level horse track monitoring wells and geological structure parameters of channel sections on an annual basis, and generates a historical trend analysis report.

[0024] Furthermore, the monitoring and diagnosis early warning controller has a built-in data storage module, which stores channel water level signals, seepage pressure signals of first-level horse track monitoring wells and geological structure parameters of channel sections on an annual basis, and generates a historical trend analysis report.

[0025] An online intelligent diagnosis and automatic early warning method for anti-floating stability of a water channel lining plate comprises the following steps:

[0026] Step 1: Real-time collection of the groundwater level h1 of the first-level horse track, the channel water level H, and the geological structural parameters of the channel section, including 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 from the first-level horse track to the water diversion 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: Trigger a graded warning signal based on the comparison result of ΔP with the preset critical value;

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

[0031] Furthermore, the calculation formula for the characteristic water depth h0 of the groundwater infiltration line and the pressure difference ΔP between the groundwater infiltration line and the channel water level is:

[0032]

[0033] Wherein, 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 first-level horseway to the water diversion channel; h1 is the groundwater level of the first-level horseway; L is the minimum distance from the seepage pressure monitoring point of the first-level horseway to the channel bottom; 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 graded warning standards in step 4 are:

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

[0036] 0.15m≤ΔP<1.7m: triggering lining plate instability warning;

[0037] ΔP ≥ 1.7m: triggers the instability warning of the lining plate and replacement soil layer.

[0038] The device is compact and easy to install. Once the first-level monitoring wells in the water channel are constructed, they are deployed within the monitoring wells and channels. 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 anti-floating stability of the channel lining, ensuring safe operation and regional flood control. This device addresses the existing issues of low manual inspection efficiency, complex numerical simulation methods, and significant early warning lags, filling a gap in the existing art for online, real-time monitoring and accurate early warning of the anti-floating stability of channel linings. It has significant engineering application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a structural diagram of the on-line intelligent diagnosis and automatic early warning device for the anti-floating stability of the lining plate of the water conveyance channel of the present invention;

[0040] Figure 2 yes Figure 1 Enlarged view of part A.

[0041] The markings in the figure are described as follows: 1-high-sensitivity water pressure sensor; 2-automatic water level gauge; 3-channel geological structure parameter acquisition module; 4-monitoring and diagnosis early warning controller; 5-first cable; 6-second cable; 7-third cable; 8-remote terminal; 9-channel water level inside the water diversion channel; 10-first-level horse trail monitoring well on the channel slope; 11-permeable layer above the channel bottom; 12-permeable layer below the channel bottom; 13-first-level horse trail to the inner slope of the water diversion channel; 14-thickness of the aquifer below the channel bottom. DETAILED DESCRIPTION

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

[0043] Please refer to Figure 1 The present invention provides an online intelligent diagnosis and automatic early warning device for the anti-floating stability of a water conveyance channel lining plate, comprising 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 arranged below the water surface of the first-level horseway monitoring well 10 on the channel slope to obtain the first-level horseway groundwater level h1; the automatic water level meter 2 is arranged in the channel water inside the water transfer 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) in the preset geological database in real time through wireless transmission, and is connected to the monitoring and diagnosis early warning controller 4 through a third cable 7.

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

[0046] The high-sensitivity water pressure sensor 1 senses water pressure with an accuracy of 1 mm. It is powered by a first cable 5 connected to a monitoring and diagnosis warning controller 4 and sends the first-level horseway groundwater level h1 signal to the controller 4 at a set data acquisition frequency of 1 time / 30 minutes (adjustable according to working conditions).

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

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

[0049] The monitoring and diagnosis warning controller 4 summarizes the received water levels 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 respectively using the following formula:

[0050]

[0051] Wherein, 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 first-level bridleway to the water diversion channel; h1 is the groundwater level of the first-level bridleway (m); L is the minimum distance from the seepage pressure monitoring point of the first-level bridleway to the channel bottom (m); k is the permeability coefficient of the aquitard above the channel bottom (m / d); k0 is the permeability coefficient of the aquitard below the channel bottom (m / d); T is the thickness of the aquifer below the channel bottom (m); 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 water level, water pressure, and geological parameter signals collected by the monitoring and diagnosis and early warning controller 4, along with the calculated characteristic water depth h0 and pressure difference ΔP of the groundwater infiltration line, form a curve relating the groundwater level in the first-level bridleway to the channel water level (h1-H) and a curve relating the channel water level to the pressure difference (H-ΔP). These data are stored annually for comparative analysis, with the relationship at the time of the first-level bridleway's highest groundwater level serving as the standard curve for comparison. By comparing and analyzing the h1-H and H-ΔP data annually, real-time online monitoring of the anti-floating stability of the lining and replacement layer is established.

[0053] The monitoring and diagnosis warning controller 4 forms an intelligent diagnosis of the anti-floating stability state and instability degree of the water conveyance channel lining plate through the real-time calculated pressure difference ΔP, triggers corresponding graded warnings according to different instability degrees, and transmits the monitoring and graded warning signals to the remote monitoring terminal 8 in real time.

[0054] The monitoring and diagnosis warning controller 4 triggers a graded warning signal based on the calculated pressure difference ΔP. The specific classification standards and response logic are as follows:

[0055] (1) Level 1 warning (no risk)

[0056] ΔP range: ΔP<0.15m;

[0057] System display: Remote monitoring terminal 8 displays a green mark, and the H-ΔP relationship curve is stable;

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

[0059] (2) Second level warning (lining plate instability):

[0060] ΔP range: 0.15m≤ΔP<1.7m;

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

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

[0063] (3) Level 3 warning (combined instability of lining plate and replacement layer):

[0064] ΔP range: ΔP ≥ 1.7m;

[0065] System display: Remote monitoring terminal 8 displays a red mark, and the H-ΔP curve continues to increase sharply;

[0066] Response measures: Trigger the emergency broadcast system and start the emergency reinforcement procedure instructions.

[0067] In one embodiment, the accuracy of the high-sensitivity water pressure sensor 1 is 1 mm, the accuracy of the automatic water level meter 2 is 1 cm, and the channel section geological structure parameter acquisition module 3 updates the parameters (k, T, m) in the geological database on an annual basis. The signal acquisition frequency of the first two is uniformly set to 1 time / 30 minutes; when rainfall causes the regional groundwater level to rise, the h1 value of the first-level horseway groundwater in the channel begins to rise rapidly, and the monitoring and diagnosis warning controller 4 begins to send a warning signal to the remote monitoring terminal 8.

[0068] Example 1: This calculation uses a water diversion channel 1 as an actual example. Using the groundwater level h1 of the primary bridleway, the channel water level H, and geological structural parameters (k, T, m) as variable factors, the analytical formula proposed in this paper provides an early warning of the channel lining's anti-floating stability. 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 Water level warning input parameters for a water channel section 1

[0070]

[0071] Table 2 Water level warning fitting process value table of a water channel section-1

[0072]

[0073] Working condition 1: When the monitoring water level h1 of the first-level bridleway is lower than 147.11m, the head difference ΔP between the characteristic water level of the groundwater infiltration line and the channel water level is less than 0.15m, and the water pressure difference between the channel lining and the replacement soil layer meets the requirements. The monitoring and diagnosis and warning controller 4 determines it as a first-level warning (no risk), the platform displays a green mark, and generates a daily monitoring report.

[0074] Working condition 2: When the monitored water level h1 of the first-level horseway is between 147.16m and 148.27m, 0.15m≤ΔP<1.7m, the water pressure difference of the replacement soil layer meets the requirements, but the water pressure difference of the lining plate does not meet the requirements. The monitoring and diagnosis warning controller 4 determines it as a second-level warning (lining plate instability). The platform displays a yellow mark and automatically sends a text message to the management personnel, prompting "Risk of lining plate instability, inspection recommended", and starts the drainage command to reduce the local water pressure.

[0075] Working condition 3: When the monitored water level h1 of the first-level bridleway exceeds 149.11 m, the head difference ΔP between the characteristic water level of the groundwater infiltration line and the channel water level is greater than 1.7 m, and the water pressure difference between the channel lining and the replacement soil layer cannot meet the requirements, the monitoring and diagnosis warning controller 4 determines it as a level 3 warning (combined instability of the lining and replacement layer). The platform displays a red mark, sends a message to the emergency broadcast system, and initiates the emergency reinforcement procedure.

[0076] Example 2: This calculation uses a water diversion channel 2 as an actual example. Using the groundwater level h1 of the primary bridleway, the channel water level H, and geological structural parameters (k, T, m) as variable factors, the analytical formula proposed in this paper provides an early warning of the channel lining's anti-floating stability. 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 Water level warning input parameters for a water channel section 2

[0078]

[0079] Table 4 Water level warning fitting process value table of a water channel section-2

[0080]

[0081] Working condition 4: When the monitoring water level h1 of the first-level horseway is lower than 78.34m, the head difference ΔP between the characteristic water level of the groundwater infiltration line and the channel water level is less than 0.15m, and the water pressure difference between the channel lining and the replacement soil layer meets the requirements, the monitoring and diagnosis and warning controller 4 determines it as a first-level warning (no risk), the platform displays a green mark, and generates a daily monitoring report.

[0082] Working condition 5: When the monitoring water level h1 of the first-level horseway is between 78.45m and 78.95m, 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 plate cannot meet the requirements. The monitoring and diagnosis warning controller 4 determines it as a second-level warning (lining plate instability). The platform displays a yellow mark and automatically sends a text message to the management personnel, prompting "Risk of lining plate instability, inspection recommended", and starts the drainage command to reduce the local water pressure.

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

[0084] The working principle of the present invention is as follows: Figure 1 As shown, rainfall in the water transfer channel and surrounding areas during the annual flood season causes a significant rise in the regional groundwater level. Under the influence of seepage, the groundwater level in the first-level bridleway of the channel begins to rise. High-sensitivity water pressure sensor 1 begins collecting groundwater pressure signals. Monitoring, diagnosis, and early warning controller 4, at a set data acquisition frequency, collects groundwater pressure values ​​from high-sensitivity water pressure sensor 1, channel water levels from automatic water level gauge 2, and geological parameters collected by channel section geological structure parameter acquisition module 3. Simultaneously, monitoring, diagnosis, and early warning controller 4 transmits this information to remote monitoring terminal 8, enabling real-time online monitoring of the anti-floating stability of the water transfer channel lining. Simultaneously, monitoring, diagnosis, and early warning controller 4 uses the collected water level, water pressure, and geological parameter signals to calculate the characteristic water depth h0 and pressure difference ΔP of the groundwater infiltration line 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, these steps are repeated, with data collection, analysis, and diagnosis performed each flood season, thus achieving long-term online monitoring, diagnosis, and early warning of the anti-floating stability of the water transfer channel lining.

[0085] The present invention also provides an online intelligent diagnosis and automatic early warning method for the anti-floating stability state of a water conveyance channel lining plate, which is performed using the above device, and the method comprises:

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

[0087] The monitoring, diagnosis and 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 channel section geological structure parameter acquisition module 3 at a set data acquisition frequency. The built-in calculation unit calculates the characteristic water depth h0 and the pressure difference ΔP of the groundwater infiltration line, and forms a relationship curve between the groundwater level of the first-level horseway and the channel water level (h1-H) and a relationship curve between the channel water level and the pressure difference (H-ΔP). During each flood season, the monitoring, diagnosis and 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 via wireless transmission.

[0088] During the annual flood season (generally May to October), the monitoring and diagnostic warning controller 4 uses the real-time collected water level, water pressure, and geological parameter signals to generate a curve showing the relationship between the first-level bridleway groundwater level and the channel water level (h1-H), and a curve showing 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 time of the first-level bridleway groundwater level reaching its highest level serving as the standard curve for comparison. By comparing and analyzing the h1-H and H-ΔP data annually, real-time online monitoring of the anti-floating stability of the lining and replacement layer is established.

[0089] The monitoring and diagnosis warning controller 4 forms an intelligent diagnosis of the anti-floating stability state and instability degree of the water conveyance channel lining plate through the real-time calculated pressure difference ΔP, triggers corresponding graded warnings according to different instability degrees, and transmits the monitoring and graded warning signals to the remote monitoring terminal 8 in real time.

[0090] The specific implementation is carried out in accordance with the above-mentioned specific classification standards and response logic of the anti-floating stability state. According to the calculated characteristic water depth and pressure difference of the groundwater infiltration line, corresponding three-level warning indicators and response measures are provided, including:

[0091] (1) Level 1 warning (no risk)

[0092] ΔP range: ΔP<0.15m;

[0093] System display: Remote monitoring terminal 8 displays a green mark, and the H-ΔP relationship curve is stable;

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

[0095] (2) Second level warning (lining plate instability):

[0096] ΔP range: 0.15m≤ΔP<1.7m;

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

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

[0099] (3) Level 3 warning (combined instability of lining plate and replacement layer):

[0100] ΔP range: ΔP ≥ 1.7m;

[0101] System display: Remote monitoring terminal 8 displays a red mark, and the H-ΔP curve continues to increase sharply;

[0102] Response measures: Trigger the emergency broadcast system and start the emergency reinforcement procedure instructions.

[0103] This invention leverages the principles of seepage control and automated data analysis to provide an online monitoring, diagnosis, and early warning system for the anti-floating stability of water channel linings, accurate to 1cm for channel water levels and 1mm for water pressure in first-level channel monitoring wells. By setting different data collection frequencies to adapt to the rate of groundwater level rise during flood seasons, it facilitates assessment of the lining's operating status and supports emergency response. During non-flood seasons, when the lining is not affected by seepage, data collection can be paused or sporadically activated to conserve power and facilitate maintenance.

[0104] Compared with the existing technology, the present invention has obvious advantages. Due to the small size of the device and its easy installation, it innovatively proposes for the first time a diagnostic formula for the anti-floating stability state based on the characteristic water depth of the groundwater infiltration line and the pressure difference between it and the channel water level. By real-time monitoring of groundwater seepage pressure, channel water level and channel section geological structure parameters, combined with the dynamic seepage analytical formula based on the Qiu Buyi assumption, the dynamic equilibrium relationship between the seepage buoyancy borne by the lining plate and its anti-floating bearing capacity can be directly reflected. Moreover, through actual engineering calculation examples, it was verified that when the anti-floating safety factor of a certain water transfer channel reached the critical value, the calculation results of the dynamic seepage analytical formula were basically consistent with the refined numerical simulation results, and the ΔP calculation error was less than 3%. In addition, by adding a graded early warning mechanism, the problems of low manual inspection efficiency, complex numerical simulation methods and obvious early warning lag in the existing technology were effectively solved, so that the operating status of the in-service lining plate, especially the anti-floating stability, can be quantitatively analyzed and diagnosed, ensuring the normal operation of the water transfer channel during the flood season and protecting regional flood control safety. The present invention makes it possible to perform real-time online analysis, diagnosis and early warning of the anti-floating stability state of a lining plate during operation, and greatly improves the efficiency and accuracy of flood season inspections. The monitoring, diagnosis and early warning device is powered by a low-voltage DC power supply and can be powered by a battery connected to a solar panel, which is energy-saving, environmentally friendly and unaffected by power outages. No human intervention is required in the entire process from information collection, analysis and calculation to early warning, and the invention belongs to an online intelligent diagnosis and automatic early warning method for the anti-floating stability state of an in-service lining plate.

[0105] The present invention can solve similar problems in diagnosing the anti-floating stability of lining plates in water transfer channels, monitor the operating status and functional changes of lining plates throughout the entire period, and realize real-time online diagnosis and timely early warning. It also conforms to the general 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 changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. An online intelligent diagnosis and automatic early warning device for the anti-floating stability of water channel lining plates, characterized in that: include: A high-sensitivity water pressure sensor (1) is provided below the water surface of a first-level horse track monitoring well on the channel slope, and is used to monitor the groundwater level h1 of the first-level horse track in real time; An automatic water level meter (2) is installed in the water inside the water delivery channel and is used to monitor the water level H of the channel in real time; The channel section geological structure parameter acquisition module (3) is used to obtain the channel section geological structure parameters, including 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 from the first-level horse road to the water diversion channel; The monitoring and diagnosis early warning controller (4) is respectively connected to the high-sensitivity water pressure sensor (1), the automatic water level meter (2) and the channel section geological structure parameter acquisition module (3), and is used to receive the first-level horse road groundwater level h1 and the channel water level H, and calculate the characteristic water depth h0 and the pressure difference ΔP of the channel slope groundwater infiltration line in combination with the channel section geological structure parameters, to form a first-level horse road groundwater level and channel water level relationship curve and a channel water level and pressure difference relationship curve. The channel water level signal, the first-level horse road monitoring well seepage pressure signal and the relationship curve collected by the monitoring and diagnosis early warning controller (4) during the flood season are sent to the remote monitoring terminal (8) through wireless transmission. The monitoring and diagnosis early warning controller (4) triggers a 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 in communication with the monitoring and diagnosis warning controller (4) and is used to receive and display the graded warning signals sent by the monitoring and diagnosis warning controller (4).

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

3. The device for online intelligent diagnosis and automatic early warning of anti-floating stability of water channel lining plates according to claim 2, characterized in that: The high-sensitivity water pressure sensor (1) is powered by a first cable (5) connected to a monitoring and diagnosis early warning controller (4); the channel automatic water level meter (2) is powered by a second cable (6) connected to the monitoring and diagnosis 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 diagnosis early warning controller (4).

4. The device for online intelligent diagnosis and automatic early warning of anti-floating stability of water channel lining plates according to claim 1, characterized in that: The monitoring and early warning controller (4) has a built-in calculation unit for calculating the characteristic water depth h0 of the groundwater infiltration line and the pressure difference ΔP between h0 and H based on the following formula: Among them, 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 first-level horseway to the water diversion channel; h1 is the groundwater level of the first-level horseway (m); L is the minimum distance from the seepage pressure monitoring point of the first-level horseway 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).

5. The device for online intelligent diagnosis and automatic early warning of anti-floating stability of water channel lining plates according to claim 1 is characterized in that: The monitoring and early warning controller (4) triggers a graded early warning signal according to the pressure difference ΔP between the calculated characteristic water depth h0 of the groundwater infiltration line and the channel water level H, specifically including: ΔP<0.15m: No risk, meeting the critical value of the channel lining and replacement layer; 0.15m≤ΔP<1.7m: triggering lining plate instability warning; ΔP ≥ 1.7m: triggers the instability warning of the lining plate and replacement soil layer.

6. The method for online intelligent diagnosis and automatic early warning of anti-floating stability of water channel lining plates according to claim 1, characterized in that: The monitoring and diagnosis early warning controller (4) has a built-in data storage module, which stores channel water level signals, seepage pressure signals of first-level horse track monitoring wells and channel section geological structure parameters on an annual basis, and generates a historical trend analysis report.

7. The method for online intelligent diagnosis and automatic early warning of anti-floating stability of water channel lining plates according to claim 1, characterized in that: The remote monitoring terminal (8) supports multi-level user authority management, and can view graded warning signals and relationship curves in real time through a Web terminal or a mobile terminal.

8. An online intelligent diagnosis and automatic early warning method for the anti-floating stability of water channel lining plates, characterized in that: The following steps are involved: Step 1: Real-time collection of the groundwater level h1 of the first-level horse track, the channel water level H, and the geological structural parameters of the channel section, including 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 from the first-level horse track to the water diversion 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: Trigger a graded warning signal based on the comparison result of ΔP with the preset critical value; Step 5: Send the graded warning signal to the remote monitoring terminal (8) via wireless transmission.

9. The method for online intelligent diagnosis and automatic early warning of anti-floating stability of water channel lining plates according to claim 8, characterized in that: The calculation formula for the characteristic water depth h0 of the groundwater infiltration line and the pressure difference ΔP between it and the channel water level is: Wherein, 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 first-level bridleway to the water diversion channel; h1 is the groundwater level of the first-level bridleway (m); L is the minimum distance from the seepage pressure monitoring point of the first-level bridleway to the channel bottom (m); k is the permeability coefficient of the aquitard above the channel bottom (m / d); k0 is the permeability coefficient of the aquitard below the channel bottom (m / d); T is the thickness of the aquifer below the channel bottom (m); 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 anti-floating stability of water channel lining plates according to claim 8, characterized in that: The graded warning standards in step 4 are: ΔP<0.15m: No risk, meeting the critical value of the channel lining and replacement layer; 0.15m≤ΔP<1.7m: triggering lining plate instability warning; ΔP ≥ 1.7m: triggers the instability warning of the lining plate and replacement soil layer.

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