Water conservancy and hydropower dam leakage detection method and system based on intelligent sensor

Abstract

The invention discloses a water conservancy and hydropower dam leakage detection method and system based on an intelligent sensor, and belongs to the field of dam leakage detection. Leakage risk assessment is carried out on the basis of the leakage analysis result of the corresponding position and the water flow threat abnormity analysis result of the corresponding position, and leakage risk early warning is carried out through the leakage risk assessment result. The dam leakage process is accurately analyzed based on the humidity change condition of each position of the dam under the water flow impact, the accuracy and safety of dam leakage danger early warning are improved, and the problem that the dam leakage process cannot be analyzed based on the humidity change condition of each position of the dam under the water flow impact is solved. And therefore, the accuracy of dam leakage danger early warning is relatively low.

Description

Technical Field

[0001] This application belongs to the field of dam leakage detection, and specifically relates to a method and system for detecting leakage of water conservancy and hydropower dams based on intelligent sensors. Background Art

[0002] After a dam is built, it is necessary to frequently detect the leakage of the dam. The traditional dam leakage detection methods mainly have the following disadvantages. After years of operation, the sensors used in the traditional methods may have damage to the measuring points, resulting in a decrease in accuracy. In addition, the traditional manual observation method is affected by human factors and it is difficult to ensure the accuracy and stability of the observation. The data obtained by the traditional methods need to be processed and analyzed tediously to obtain useful information, which not only increases the workload but also increases the risk of human errors. There are deficiencies in the perception ability of the safety monitoring of the dam, and the monitoring scope and elements have not been comprehensively covered. The communication protocols and data standards of the acquisition equipment are not unified, resulting in difficulties in realizing large-scale and standardized monitoring management, thus affecting the early warning ability. The monitoring equipment of reservoir dams is relatively backward technically and cannot meet the requirements of modern safety monitoring. This technical deficiency makes it difficult to detect and handle potential safety hazards in a timely manner, posing a potential threat to the safety of the dam. Therefore, with the progress of technology, more and more reservoir dams are beginning to adopt intelligent monitoring technologies based on sensor networks to improve monitoring accuracy, expand the monitoring scope, simplify the data processing process, enhance the early warning ability, and update the monitoring equipment technology;

[0003] However, the existing technologies ignore the influence of water flow impact on the structural characteristics of the dam when detecting dam leakage, and are unable to conduct a risk assessment on the dam leakage process based on the structural characteristics of the dam and the regular characteristics of dam leakage, resulting in the inability to analyze the dam leakage process based on the humidity change conditions at various positions of the dam under water flow impact, thus leading to a relatively low accuracy of the dam leakage danger early warning. Most of the existing technologies have the above problems;

[0004] To solve the problems raised in this background art, this application designs a method and system for detecting leakage of water conservancy and hydropower dams based on intelligent sensors. Summary of the Invention

[0005] To address the deficiencies in the prior art mentioned in the background art, the present application proposes a method and system for detecting seepage in water conservancy and hydropower dams based on intelligent sensors. The present application performs an abnormal analysis of water flow threats at corresponding positions based on the water flow data of the corresponding position areas of the dam, conducts a seepage risk assessment based on the seepage analysis results of the corresponding positions and the abnormal analysis results of the water flow threats at the corresponding positions, and issues a seepage risk warning through the seepage risk assessment results. The present application conducts a risk assessment of the dam seepage process based on the structural characteristics of the dam and the regular characteristics of the dam seepage, and accurately analyzes the dam seepage process based on the humidity changes at various positions of the dam under the impact of water flow, improving the accuracy and safety of the dam seepage risk warning.

[0006] To achieve the above object, the present application provides the following technical solutions: In the first aspect, the present application provides a method for detecting seepage in a water conservancy and hydropower dam based on intelligent sensors, which includes the following specific steps:

[0007] Step 1: Install sensors at the monitoring positions of the dam to collect the humidity data and construction specifications of the corresponding positions of the dam, and at the same time obtain the water flow data of the corresponding position areas of the dam;

[0008] Step 2: Conduct a seepage analysis of the corresponding positions based on the humidity data and construction specifications of the corresponding positions of the dam;

[0009] Step 3: Conduct an abnormal analysis of the water flow threats at the corresponding positions based on the water flow data of the corresponding position areas of the dam;

[0010] Step 4: Conduct a seepage risk assessment based on the seepage analysis results of the corresponding positions and the abnormal analysis results of the water flow threats at the corresponding positions;

[0011] Step 5: Issue a seepage risk warning through the seepage risk assessment results.

[0012] In one implementation manner of the present invention, the specific content of installing sensors at the monitoring positions of the dam to collect the humidity data and construction specifications of the corresponding positions of the dam, and at the same time obtaining the water flow data of the corresponding position areas of the dam is as follows:

[0013] Step 11: Set humidity sensors at the positions on the dam that need to be detected to collect the humidity of the monitoring positions, map it into the three-dimensional model of the dam, and construct a humidity model for each position of the dam;

[0014] Step 12: At the same time, obtain the construction specification data of the corresponding positions of the dam, where the construction specification data includes the strength, thickness data, and anti-seepage grade data of the components of each monitoring point area;

[0015] Step 13: Obtain the water flow impact data at the corresponding position of the dam. The water flow impact data includes the water flow impact speed and the impact force data, and store the obtained data in the storage module.

[0016] In an implementation manner of the present invention, the leakage analysis of the corresponding position based on the humidity data at the corresponding position of the dam and the construction specifications of the corresponding position includes the following specific steps:

[0017] Step 21: Obtain the humidity data at the corresponding position of the dam, obtain a three-dimensional image composed of the corresponding positions where the obtained humidity is greater than or equal to the set safety humidity, set it as the abnormal position three-dimensional image, and obtain the construction specification data of each area corresponding to the abnormal position three-dimensional image;

[0018] Step 22: Obtain the abnormal position three-dimensional image of the current monitoring and the abnormal position three-dimensional image of the previous monitoring moment. At the same time, obtain the construction specification data of each area corresponding to the abnormal position three-dimensional image, and import the obtained abnormal position three-dimensional image and the construction specification data of each area corresponding to the abnormal position three-dimensional image into the seepage anomaly coefficient calculation formula to calculate the seepage anomaly coefficient. Among them, the seepage anomaly coefficient calculation formula is: Among them, n is the number of regions across which the abnormal position three-dimensional image spans, p i is the anti-seepage grade of the i-th region, pm is the average anti-seepage grade of the region, a is the volume anomaly proportion coefficient, Vi is the volume of the three-dimensional image in the i-th region, Vim is the volume of the i-th region of the dam, h i is the maximum depth of the three-dimensional image in the i-th region, and h im is the average thickness of the i-th region of the dam; in this formula, the difficulty of water seeping into the region is weighted and analyzed through the anti-seepage grades of different regions, and then the dangerous situation of water in the i-th region is comprehensively analyzed through the maximum depth of water in the i-th region and the volume of water in the i-th region, so as to comprehensively analyze the seepage anomaly of the dam;

[0019] Step 23: Obtain the seepage anomaly coefficient of the current monitoring calculated and the seepage anomaly coefficient of the previous monitoring moment.

[0020] In an implementation manner of the present invention, the water flow threat anomaly analysis of the corresponding position based on the water flow data in the corresponding position area of the dam includes the following specific steps:

[0021] Step 31: Obtain the water flow impact speed and impact force data at the corresponding position of the dam during the time interval from the current monitoring to the previous monitoring moment;

[0022] Step 32: Import the water flow impact speed and impact force data at the corresponding position during the interval time into the water flow threat anomaly value calculation formula to calculate the water flow threat anomaly value. Among them, the water flow threat anomaly value calculation formula is: Wherein, Tr is the duration of the interval time, vt is the impact water velocity at the corresponding position at time t, vm is the maximum value within the safe range of the impact water velocity, ft is the water flow impact force at the corresponding position at time t, fm is the maximum value within the safe range of the water flow impact force, λ is the weight of the water velocity ratio, and dt is the time integral.

[0023] In one implementation manner of the present invention, the leakage risk assessment based on the leakage analysis result at the corresponding position and the abnormal analysis result of the water flow threat at the corresponding position includes the following specific contents:

[0024] Step 41: Obtain the calculated seepage anomaly coefficient of the current monitoring and the seepage anomaly coefficient of the previous monitoring moment, and at the same time obtain the abnormal value of the water flow threat within the interval time;

[0025] Step 42: Substitute the calculated seepage anomaly coefficient of the current monitoring, the seepage anomaly coefficient of the previous monitoring moment, and the abnormal value of the water flow threat within the interval time into the leakage risk assessment value calculation formula to calculate the leakage risk assessment value. Among them, the leakage risk assessment value calculation formula is: Wherein, Hstz is the seepage anomaly coefficient of the current monitoring, and Hstc is the seepage anomaly coefficient of the previous monitoring moment.

[0026] In one implementation manner of the present invention, the leakage risk warning based on the leakage risk assessment result includes the following specific contents: Compare the calculated leakage risk assessment value with the set leakage risk assessment threshold, and compare the seepage anomaly coefficient of the current monitoring with the set seepage anomaly threshold. If the leakage risk assessment value is greater than or equal to the set leakage risk assessment threshold and / or the seepage anomaly coefficient of the current monitoring is greater than or equal to the set seepage anomaly threshold, then conduct a leakage risk warning to remind the management personnel to maintain the leakage part; if the leakage risk assessment value is less than the set leakage risk assessment threshold and the seepage anomaly coefficient of the current monitoring is less than the set seepage anomaly threshold, then no leakage risk warning is conducted.

[0027] In a second aspect, the present application provides a water conservancy and hydropower dam leakage detection system based on intelligent sensors, which is implemented based on the above-mentioned water conservancy and hydropower dam leakage detection method based on intelligent sensors, and specifically includes a data acquisition module, a leakage analysis module, a water flow threat abnormal analysis module, a leakage risk assessment module, and a risk warning module;

[0028] Among them, the data acquisition module is used to install sensors at the monitoring positions of the dam to collect the humidity data and the construction specifications at the corresponding positions of the dam, and at the same time obtain the water flow data in the area corresponding to the positions of the dam;

[0029] The leakage analysis module is used to perform leakage analysis on the corresponding positions based on the humidity data and the construction specifications at the corresponding positions of the dam;

[0030] The water flow threat anomaly analysis module is used to perform water flow threat anomaly analysis on the corresponding position based on the water flow data of the corresponding position area of the dam;

[0031] The leakage risk assessment module is used to perform leakage risk assessment based on the leakage analysis result of the corresponding position and the water flow threat anomaly analysis result of the corresponding position;

[0032] The risk warning module is used to perform leakage risk warning through the leakage risk assessment result.

[0033] In a third aspect, the present application provides an electronic device, including: a processor and a memory, wherein a computer program callable by the processor is stored in the memory;

[0034] The processor executes the above-mentioned method for detecting leakage of a water conservancy and hydropower dam based on intelligent sensors by calling the computer program stored in the memory.

[0035] In a fourth aspect, the present application provides a computer-readable storage medium storing instructions, which when run on a computer, cause the computer to execute the above-mentioned method for detecting leakage of a water conservancy and hydropower dam based on intelligent sensors.

[0036] Compared with the prior art, the present application has the following beneficial effects: The present application performs leakage analysis on the corresponding position based on the humidity data of the corresponding position of the dam and the construction specifications of the corresponding position, performs water flow threat anomaly analysis on the corresponding position based on the water flow data of the corresponding position area of the dam, performs leakage risk assessment based on the leakage analysis result of the corresponding position and the water flow threat anomaly analysis result of the corresponding position, and performs leakage risk warning through the leakage risk assessment result. The present application performs risk assessment on the dam leakage process based on the structural characteristics of the dam and the regular characteristics of the dam leakage, and accurately analyzes the dam leakage process based on the humidity change conditions of each position of the dam under the impact of water flow, improving the accuracy and safety of the dam leakage risk warning. Description of the Drawings

[0037] By reading the detailed description of the non-limiting embodiments with reference to the following drawings, other features, objects, and advantages of the present invention will become more apparent;

[0038] Figure 1 It represents a schematic diagram of the overall process of a method for detecting leakage of a water conservancy and hydropower dam based on intelligent sensors according to the present application;

[0039] Figure 2 It represents a schematic diagram of step 1 of a method for detecting leakage of a water conservancy and hydropower dam based on intelligent sensors according to the present application;

[0040] Figure 3 It shows the schematic diagram of step 2 of a water conservancy and hydropower dam leakage detection method based on intelligent sensors in this application;

[0041] Figure 4 It shows the schematic diagram of step 5 of a water conservancy and hydropower dam leakage detection method based on intelligent sensors in this application;

[0042] Figure 5 It shows the schematic diagram of the overall framework of a water conservancy and hydropower dam leakage detection system based on intelligent sensors in this application. Specific implementation manners

[0043] The technical solutions of the present invention will be described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solutions of the present invention, rather than limitations on the technical solutions of the present invention. Without conflict, the technical features in the embodiments of the present invention and the embodiments can be combined with each other.

[0044] Embodiment 1

[0045] To solve the technical problems proposed in the background art, this application provides a preferred embodiment: As Figures 1-4 shown, a water conservancy and hydropower dam leakage detection method based on intelligent sensors includes the following specific steps:

[0046] Step 1: Install sensors at the monitoring positions of the dam to collect the humidity data of the corresponding positions of the dam and the construction specifications of the corresponding positions, and at the same time obtain the water flow data of the corresponding position area of the dam;

[0047] In this embodiment, the specific content of step 1 is:

[0048] Step 11: Set humidity sensors at the positions on the dam that need to be detected to collect the humidity of the monitoring positions, map it into the three-dimensional model of the dam, and construct the humidity model of each position of the dam;

[0049] Step 12: At the same time, obtain the construction specification data of the corresponding positions of the dam, where the construction specification data includes the strength, thickness data and anti-seepage grade data of the components in each monitoring point area;

[0050] Step 13: Obtain the water flow impact data of the corresponding positions of the dam. The water flow impact data includes the water flow impact speed and impact force data. Among them, the water flow impact speed is obtained through a water flow impact speed sensor, and the impact force is obtained through an impact force sensor, and the obtained data is stored in the storage module;

[0051] Step 2: Conduct leakage analysis on the corresponding positions based on the humidity data of the corresponding positions of the dam and the construction specifications of the corresponding positions;

[0052] Meanwhile, in this embodiment, the specific content of step 2 is as follows: Step 21, obtain the humidity data at the corresponding position of the dam, obtain the three-dimensional image formed by the corresponding positions where the corresponding humidity is greater than or equal to the set safety humidity, which is set as the abnormal position three-dimensional image, and obtain the construction specification data of each area corresponding to the abnormal position three-dimensional image. For example, the dam can be divided into: Dam foundation layer: This is the bottom layer of the dam, usually located on the riverbed or riverbank. The main function of the dam foundation layer is to bear the overall weight of the dam and the pressure of the water flow. It is usually composed of concrete, rock or other suitable materials to ensure the stability and durability of the dam; Impermeable layer: The impermeable layer is located above the dam foundation layer and is mainly used to prevent water from seeping through the dam foundation. The impermeable layer is usually composed of concrete, asphalt concrete or other waterproof materials to ensure the waterproof performance of the dam; Main structure layer: The main structure layer is the main load-bearing part of the dam and is usually composed of materials such as concrete or stone. This layer can be divided into multiple sub-layers according to design requirements, such as the upstream and downstream surface layers, the middle isolation layer, etc. The main function of the main structure layer is to bear the weight of the dam, the pressure of the water flow and temperature changes, etc.; Observation layer: The observation layer is usually located inside or on the surface of the dam and is used to monitor the operation status and safety performance of the dam;

[0053] Step 22, obtain the abnormal position three-dimensional image of this monitoring and the abnormal position three-dimensional image of the previous monitoring moment. At the same time, obtain the construction specification data of each area corresponding to the abnormal position three-dimensional image, and import the obtained abnormal position three-dimensional image and the construction specification data of each area corresponding to the abnormal position three-dimensional image into the calculation formula of the seepage anomaly coefficient. Among them, the calculation formula of the seepage anomaly coefficient is: Among them, n is the number of regions across which the abnormal position three-dimensional image spans, p i is the anti-seepage grade of the i-th region, pm is the average anti-seepage grade of the region, a is the volume anomaly ratio coefficient, Vi is the volume of the three-dimensional image within the i-th region, Vim is the volume of the i-th region of the dam, h i is the maximum depth of the three-dimensional image within the i-th region, and h im is the average thickness of the i-th region of the dam; It should be specifically explained in this embodiment that in this formula, the difficulty of water seeping into the region is weighted and analyzed through the anti-seepage grades of different regions, and then the danger situation of water within the i-th region is comprehensively analyzed through the maximum depth of water within the i-th region and the volume within the i-th region, so as to comprehensively analyze the seepage anomaly of the dam;

[0054] Step 23, obtain the seepage anomaly coefficient of this monitoring obtained by calculation and the seepage anomaly coefficient of the previous monitoring moment;

[0055] Step 3, perform an abnormal analysis of the water flow threat at the corresponding position based on the water flow data of the corresponding position area of the dam;

[0056] Meanwhile, in this embodiment, the specific content of step 3 is as follows: Step 31, obtain the water flow impact speed and impact force data at the corresponding position during the time interval from the current dam monitoring to the previous monitoring moment;

[0057] Step 32, import the water flow impact speed and impact force data at the corresponding position during the time interval into the water flow threat outlier calculation formula to calculate the water flow threat outlier value. The water flow threat outlier calculation formula is as follows: where Tr is the duration of the time interval, vt is the impact water speed at the corresponding position at time t, vm is the maximum value of the impact water speed safety range, ft is the water flow impact force at the corresponding position at time t, fm is the maximum value of the water flow impact force safety range, λ is the water speed ratio weight, and dt is the time integral. In this embodiment, it should be specifically noted that the impact water speed safety range and the water flow impact force safety range are the inherent properties of the dam during construction. There will be corresponding standards when the dam is built. At the same time, in this formula, the continuous impact of the water flow on the dam caused by the water speed and water impact force is analyzed for comprehensive evaluation;

[0058] Step 4, conduct a leakage risk assessment based on the leakage analysis results at the corresponding position and the water flow threat outlier analysis results at the corresponding position;

[0059] Meanwhile, in this embodiment, the specific content of step 4 is as follows: Step 41, obtain the calculated seepage anomaly coefficient of the current monitoring and the seepage anomaly coefficient of the previous monitoring moment, and at the same time obtain the water flow threat outlier value during the time interval;

[0060] Step 42, substitute the calculated seepage anomaly coefficient of the current monitoring, the seepage anomaly coefficient of the previous monitoring moment, and the water flow threat outlier value during the time interval into the leakage risk assessment value calculation formula to calculate the leakage risk assessment value. The leakage risk assessment value calculation formula is as follows: where Hstz is the seepage anomaly coefficient of the current monitoring, and Hstc is the seepage anomaly coefficient of the previous monitoring moment;

[0061] Step 5, conduct a leakage risk warning based on the leakage risk assessment result;

[0062] Meanwhile, as Figure 4As shown, in this embodiment, the specific content of step 5 is as follows: Compare the calculated leakage risk assessment value with the set leakage risk assessment threshold, and compare the infiltration anomaly coefficient of this monitoring with the set infiltration anomaly threshold. If the leakage risk assessment value is greater than or equal to the set leakage risk assessment threshold and / or the infiltration anomaly coefficient of this monitoring is greater than or equal to the set infiltration anomaly threshold, issue a leakage risk warning to remind the management personnel to maintain the leakage location; if the leakage risk assessment value is less than the set leakage risk assessment threshold and the infiltration anomaly coefficient of this monitoring is less than the set infiltration anomaly threshold, do not issue a leakage risk warning.

[0063] It should be specifically noted that the value-taking method of the set parameters in this embodiment is obtained by those skilled in the art through experiments. Specifically, for example, the value-taking method of the set parameters (such as the volume anomaly ratio coefficient, water velocity ratio weight, leakage risk assessment threshold, and infiltration anomaly threshold) in this embodiment is as follows: Obtain at least 100 groups of humidity data at the corresponding positions of the dam, the construction specifications at the corresponding positions, and the water flow data in the area corresponding to the dam as the experimental group. Substitute the experimental group into the leakage risk assessment value calculation formula to calculate the leakage risk assessment value, and at the same time import it into the infiltration anomaly coefficient calculation formula to calculate the infiltration anomaly coefficient. Obtain the expert's judgment results on whether there is an infiltration risk at the corresponding positions of these dams. Import the calculated infiltration anomaly coefficient, leakage risk assessment value, and infiltration risk judgment results into the fitting software, and output the value-taking of the set parameters (such as the volume anomaly ratio coefficient, water velocity ratio weight, leakage risk assessment threshold, and infiltration anomaly threshold) that meets the maximum judgment accuracy rate.

[0064] The advantages of this embodiment over the prior art are as follows: Conduct leakage analysis at the corresponding positions based on the humidity data and construction specifications at the corresponding positions of the dam, conduct abnormal analysis of water flow threats at the corresponding positions based on the water flow data in the area corresponding to the dam, conduct leakage risk assessment based on the leakage analysis results and water flow threat abnormal analysis results at the corresponding positions, and issue a leakage risk warning through the leakage risk assessment results. This application conducts risk assessment on the dam leakage process based on the structural characteristics of the dam and the regular characteristics of dam leakage, and accurately analyzes the dam leakage process based on the humidity changes at each position of the dam under the impact of water flow, improving the accuracy and safety of dam leakage risk warning.

[0065] Embodiment 2

[0066] As Figure 5 shown, a water conservancy and hydropower dam leakage detection system based on intelligent sensors is implemented based on the above-mentioned water conservancy and hydropower dam leakage detection method based on intelligent sensors, and specifically includes a data acquisition module, a leakage analysis module, a water flow threat abnormal analysis module, a leakage risk assessment module, and a risk warning module;

[0067] Among them, the data acquisition module is used to install sensors at the monitoring positions of the dam to collect the humidity data and construction specifications of the corresponding positions of the dam, and at the same time obtain the water flow data of the corresponding position area of the dam; the leakage analysis module is used to perform leakage analysis of the corresponding position based on the humidity data and construction specifications of the corresponding position of the dam; the water flow threat anomaly analysis module is used to perform water flow threat anomaly analysis of the corresponding position based on the water flow data of the corresponding position area of the dam; the leakage risk assessment module is used to perform leakage risk assessment based on the leakage analysis results of the corresponding position and the water flow threat anomaly analysis results of the corresponding position; the risk warning module is used to perform leakage risk warning through the leakage risk assessment results. It may also include a control component, and the role of the control component is to control the operation of the data acquisition module, the leakage analysis module, the water flow threat anomaly analysis module, the leakage risk assessment module, and the risk warning module;

[0068] In addition, the data transmission process in this embodiment is as Figure 5 shown by the arrow direction in, and at the same time, the specific steps of each module in this embodiment have been described in detail in the above method embodiment, and will not be elaborated here.

[0069] Embodiment 3

[0070] This embodiment provides an electronic device, including: a processor and a memory, where a computer program callable by the processor is stored in the memory;

[0071] The processor executes the above-mentioned method for detecting leakage of a water conservancy and hydropower dam based on intelligent sensors by calling the computer program stored in the memory.

[0072] This electronic device may have relatively large differences due to different configurations or performances, and can include one or more processors and one or more memories. Among them, at least one computer program is stored in the memory, and this computer program is loaded and executed by the processor to implement the method for detecting leakage of a water conservancy and hydropower dam based on intelligent sensors provided by the above method embodiment. This electronic device can also include other components for realizing the functions of the device. For example, this electronic device can also have components such as wired or wireless network interfaces and input / output interfaces for data input and output. This embodiment will not be elaborated here.

[0073] Embodiment 4

[0074] This embodiment proposes a computer-readable storage medium, on which a rewritable computer program is stored;

[0075] When the computer program runs on a computer device, it enables the computer device to execute the above-mentioned method for detecting leakage of a water conservancy and hydropower dam based on intelligent sensors.

[0076] For example, a computer-readable storage medium can be a read-only memory, a random access memory, a compact disc read-only memory, magnetic tape, a floppy disk, an optical data storage device, etc.

[0077] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions according to the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired network or / and a wireless network. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that includes one or more collections of available media. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, magnetic tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0078] The term "comprising", "including", or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, article, or device that includes a series of elements includes not only those elements but also other elements not expressly listed, or elements that are inherent to such process, method, article, or device.

[0079] The above description is only a preferred embodiment of the present application and an explanation of the applied technical principles. Those skilled in the art should understand that the scope of the application involved in the present application is not limited to the technical solutions formed by the specific combination of the above technical features, and should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the foregoing application concept. For example, the technical solutions formed by mutually replacing the above features with the technical features (but not limited to) having similar functions applied in the present application.

Claims

1. A water conservancy and hydropower dam leakage detection method based on intelligent sensors, characterized in that: It includes the following specific steps: Install sensors at the monitoring location of the dam to collect humidity data and construction specifications at the corresponding location of the dam, and obtain water flow data in the area corresponding to the location of the dam; Conduct leakage analysis at corresponding locations based on humidity data at corresponding locations of the dam and construction specifications at corresponding locations; Based on the water flow data of the corresponding location of the dam, analyze the water flow threat anomaly at the corresponding location; Conduct leakage risk assessment based on leakage analysis results at corresponding locations and water flow threat anomaly analysis results at corresponding locations; Leakage risk warning is issued based on the leakage risk assessment results.

2. A water conservancy and hydropower dam leakage detection method based on intelligent sensor as claimed in claim 1, characterized in that: The leakage analysis of the corresponding position based on the humidity data of the corresponding position of the dam and the construction specifications of the corresponding position includes the following specific steps: Obtain humidity data of corresponding positions of the dam, obtain a three-dimensional image of corresponding positions whose humidity is greater than or equal to the set safety humidity, set it as the abnormal position three-dimensional image, and obtain construction specification data of each area corresponding to the abnormal position three-dimensional image; The three-dimensional image of the abnormal position of this monitoring and the three-dimensional image of the abnormal position at the previous monitoring time are obtained, and the construction specification data of each area corresponding to the three-dimensional image of the abnormal position are obtained at the same time. The obtained three-dimensional image of the abnormal position and the construction specification data of each area corresponding to the three-dimensional image of the abnormal position are imported into the calculation formula of the permeability anomaly coefficient to calculate the permeability anomaly coefficient, wherein the calculation formula of the permeability anomaly coefficient is: Where n is the number of regions across which the three-dimensional image of the abnormal position crosses, pi is the anti-seepage grade of the ith region, pm is the average anti-seepage grade of the region, a is the volume anomaly ratio, Vi is the volume of the three-dimensional image in the ith region, Vim is the volume of the ith region of the dam, hi is the maximum depth of the three-dimensional image in the ith region, and him is the average thickness of the ith region of the dam; Obtain the calculated permeability anomaly coefficient of this monitoring and the permeability anomaly coefficient of the previous monitoring moment.

3. A water conservancy and hydropower dam leakage detection method based on intelligent sensor as claimed in claim 1, characterized in that: The water flow threat anomaly analysis of the corresponding location based on the water flow data of the corresponding location area of ​​the dam includes the following specific steps: Obtain the water flow impact velocity and impact force data at the corresponding position during the interval between the current monitoring and the previous monitoring time of the dam; The water flow impact velocity and impact force data at the corresponding position within the interval time are imported into the water flow threat abnormal value calculation formula to calculate the water flow threat abnormal value, where the water flow threat abnormal value calculation formula is: Among them, Tr is the interval time, vt is the impact water velocity at the corresponding position at time t, vm is the maximum value of the impact water velocity safety range, ft is the water flow impact force at the corresponding position at time t, fm is the maximum value of the water flow impact force safety range, λ is the water velocity weight, and dt is the time integral.

4. A water conservancy and hydropower dam leakage detection method based on intelligent sensor as claimed in claim 3, characterized in that: The leakage risk assessment based on the leakage analysis results of the corresponding position and the water flow threat anomaly analysis results of the corresponding position includes the following specific contents: Obtain the calculated permeability anomaly coefficient of this monitoring and the permeability anomaly coefficient of the previous monitoring moment, and at the same time obtain the abnormal value of water flow threat within the interval; Substitute the calculated abnormal permeability coefficient of this monitoring, the abnormal permeability coefficient of the previous monitoring moment and the abnormal value of water flow threat in the interval time into the leakage risk assessment value calculation formula to calculate the leakage risk assessment value, where the leakage risk assessment value calculation formula is: Among them, Hstz is the permeability anomaly coefficient of this monitoring, and Hstc is the permeability anomaly coefficient of the previous monitoring time.

5. A water conservancy and hydropower dam leakage detection method based on intelligent sensor as claimed in claim 4, characterized in that: The leakage risk warning through the leakage risk assessment result includes the following specific contents: comparing the calculated leakage risk assessment value with the set leakage risk assessment threshold, and comparing the permeability abnormality coefficient monitored this time with the set permeability abnormality threshold, if the leakage risk assessment value is greater than or equal to the set leakage risk assessment threshold and / or the permeability abnormality coefficient monitored this time is greater than or equal to the set permeability abnormality threshold, then a leakage risk warning is issued to remind the management personnel to perform maintenance on the leakage part; If the leakage risk assessment value is less than the set leakage risk assessment threshold and the permeability anomaly coefficient of this monitoring is less than the set permeability anomaly threshold, no leakage risk warning will be issued.

6. A method for detecting water conservancy and hydropower dam leakage based on intelligent sensors as claimed in claim 5, characterized in that: The specific contents of installing sensors at monitoring positions of the dam to collect humidity data and construction specifications of corresponding positions of the dam, and simultaneously obtaining water flow data of the corresponding positions of the dam are as follows: humidity sensors are set at positions on the dam that need to be detected to collect humidity at the monitoring positions, and the humidity is mapped to the three-dimensional model of the dam to construct a humidity model of each position of the dam; at the same time, the construction specification data of the corresponding positions of the dam are obtained, wherein the construction specification data include the strength, thickness data and anti-seepage grade data of the components of each monitoring point area; the water flow impact data of the corresponding positions of the dam are obtained, wherein the water flow impact data include water flow impact velocity and impact force data, and the obtained data are stored in a storage module.

7. A water conservancy and hydropower dam leakage detection system based on intelligent sensors, which is implemented based on the water conservancy and hydropower dam leakage detection method based on intelligent sensors as claimed in any one of claims 1 to 6, characterized in that: It specifically includes a data acquisition module, a leakage analysis module, a water flow threat anomaly analysis module, a leakage hazard assessment module and a hazard warning module; The data acquisition module is used to install sensors at the monitoring position of the dam to collect humidity data and construction specifications of the corresponding position of the dam, and to obtain water flow data of the corresponding position area of ​​the dam; The leakage analysis module is used to perform leakage analysis at the corresponding position based on the humidity data at the corresponding position of the dam and the construction specifications at the corresponding position; The water flow threat anomaly analysis module is used to perform water flow threat anomaly analysis at a corresponding location based on water flow data in an area corresponding to a dam location; The leakage risk assessment module is used to perform leakage risk assessment based on the leakage analysis results of the corresponding position and the water flow threat anomaly analysis results of the corresponding position; The risk warning module is used to issue a leakage risk warning based on the leakage risk assessment result.

8. An electronic device comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; It is characterized in that the processor executes the water conservancy and hydropower dam leakage detection method based on intelligent sensors as described in any one of claims 1 to 6 by calling the computer program stored in the memory.

9. A computer-readable storage medium, characterized in that: Instructions are stored, and when the instructions are executed on a computer, the computer is caused to execute a water conservancy and hydropower dam leakage detection method based on an intelligent sensor as described in any one of claims 1 to 6.

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