A water conservancy project safety monitoring system based on 5G and BeiDou technology

Abstract

The present invention relates to the technical field of water conservancy project safety monitoring, and specifically discloses a water conservancy project safety monitoring system based on 5G and Beidou technology. The system includes: a satellite image acquisition module, which obtains satellite image information of the water conservancy project based on Beidou technology; a cloud server, which is used to receive the satellite image information, identify and analyze the satellite image information, obtain the water level contour line and the water conservancy facility contour line, and analyze the first water level information based on the water level contour line; water level monitoring equipment, which is used to perform on-site monitoring of the water level and obtain the second water level information; an error analysis module, which is used to analyze the contour deviation based on the first water level information and the second water level information; an early warning module, which is used to fine-tune the water conservancy facility contour line based on the contour deviation, and make an early warning judgment based on the contour deviation after fine-tuning; the system can improve the accuracy of identification, analysis and judgment, and improve the accuracy of water conservancy facility monitoring.

Description

Technical Field

[0001] The present invention relates to the technical field of water conservancy project safety monitoring technology, and specifically to a water conservancy project safety monitoring system based on 5G and Beidou technologies. Background Art

[0002] With the popularization and application of 5G technology, the Internet of Things technology has made rapid progress. In terms of water conservancy project monitoring, based on 5G technology and combined with my country's Beidou satellite navigation system and a variety of data collection terminals, water conservancy safety monitoring has developed in the direction of intelligence and automation.

[0003] The existing intelligent water conservancy monitoring system based on Beidou technology mainly obtains satellite image information of water areas through Beidou satellites, and monitors the actual conditions of water conservancy projects in combination with monitoring terminals set up around the water areas. For example, piezometers are set at different locations on the dam. When seepage pressure signals are detected, early warning of dam safety is achieved by uploading data technology to monitoring stations or cloud servers.

[0004] However, although Beidou satellites have higher positioning accuracy than the GPS positioning system, they still have higher requirements for their positioning accuracy in water conservancy monitoring. At the same time, the area parameters of the water area will dynamically affect the analysis process of satellite images, resulting in large errors in the detection process. Summary of the Invention

[0005] The purpose of this invention is to provide a water conservancy project safety monitoring system based on 5G and BeiDou technologies to solve the following technical problems:

[0006] How to improve the accuracy of monitoring of water conservancy facilities.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] A water conservancy project safety monitoring system based on 5G and BeiDou technologies, the system comprising:

[0009] Satellite image acquisition module, which obtains satellite image information of water conservancy projects based on Beidou technology;

[0010] The cloud server is used to receive satellite image information, identify and analyze the satellite image information, obtain water level contour lines and water conservancy facility contour lines, and analyze the first water level information based on the water level contour lines;

[0011] Water level monitoring equipment, used for on-site monitoring of the water level and obtaining second water level information;

[0012] an error analysis module, configured to analyze a contour deviation based on the first water level information and the second water level information;

[0013] The early warning module is used to fine-tune the contour line of the water conservancy facility according to the contour deviation, and to make early warning judgments based on the contour deviation after fine-tuning.

[0014] In one embodiment, the process of analyzing the first water level information is as follows:

[0015] The water area is divided into blocks, and a water level function Level(S) is established for each block, where S is the water area of the block;

[0016] The water area S of the block is obtained according to the water level contour line, and the water area S is substituted into the water level function Level(S) to obtain the first water level information.

[0017] In one embodiment, the process of fine-tuning the contour of the water conservancy facility is as follows:

[0018] The contour deviation is trained based on the deviation between the contour lines of water conservancy facilities collected in historical data and the corresponding actual contour lines of water conservancy facilities to obtain an error judgment model;

[0019] The obtained contour deviation is input into the error judgment model to obtain the fine-tuning amount;

[0020] Fine-tune the contour line of the water conservancy facility according to the fine-tuning amount to obtain the contour line of the water conservancy facility after fine-tuning, compare the contour line of the water conservancy facility after fine-tuning with the standard contour line, and make an early warning judgment based on the comparison result.

[0021] In one embodiment, the system further includes:

[0022] Edge computing devices are distributed around the water area to receive image information and perform analysis;

[0023] The cloud platform is connected to all edge computing devices to obtain the analysis results of edge computing devices and perform early warning analysis;

[0024] The computing allocation module is used to allocate edge computing devices based on the results of the block water area warning analysis.

[0025] In one embodiment, the allocation process of edge computing devices is as follows:

[0026] The edge computing device receives the image information of the corresponding water area and the corresponding rainfall information of the area according to the preset period;

[0027] Through edge devices, early warning analysis of image information and rainfall information is performed to obtain early warning values for the water area.

[0028] Sort the water areas in the block according to the warning values from large to small, adjust the preset cycle according to the ranking, and obtain the dynamic cycle;

[0029] Allocate edge computing devices based on the frequency of dynamic cycles.

[0030] In one embodiment, the calculation process of the warning value is:

[0031] By formula Calculate the warning value E;

[0032] Among them, R is the rainfall, R0 is the rainfall reference value; S is the water area value of the block; v S () is the function of the water area changing with rainfall and water level speed, v0() is the function of the water area of the block changing with the speed of water level; S abn is the water area value of abnormal water changes; S0 is the reference value of the abnormal water area of the block; μ and γ are preset proportional coefficients.

[0033] In one embodiment, the process of edge computing device allocation according to dynamic periodic frequency is as follows:

[0034] The amount of calculation P used to analyze the water area of the prediction block according to the dynamic cycle cal ;

[0035] According to the order of dynamic cycle frequency, P cal The maximum computing capacity P of the edge computing device corresponding to the water area of this block max Make a comparison;

[0036] If P cal >P max , then the remaining computing amount P of the adjacent edge computing device ar Make a judgment:

[0037] If P ar ≥P cal -P max , sharing the computational load through adjacent edge computing devices;

[0038] Otherwise, the computation load is shared by adjacent edge computing devices and P ar -(P cal -P max ) performs cloud computing on part of the computation and sends the cloud computing results to the cloud platform.

[0039] In one embodiment, the system further includes an intelligent inspection module;

[0040] The intelligent inspection module is used to adjust the number of inspectors in each water area according to the size of the warning value.

[0041] In one embodiment, the process of adjusting the number of inspectors is as follows:

[0042] Arrange a basic number of patrol officers for each water area;

[0043] By formula The number of additional patrol officers for the i-th water area is obtained;

[0044] Where m is the total number of water areas in the block, i∈[1,m]; E i is the warning value of the water area in the i-th block; N as To increase the total number of inspectors.

[0045] Beneficial effects of the present invention:

[0046] (1) The present invention utilizes water level information from field monitoring, combined with image information acquired by satellite, to achieve comparison between image contours and actual contours, and then fine-tune the identified contours of water conservancy facilities through the contour deviation between the two, thereby improving the accuracy of identification, analysis and judgment, and thus improving the accuracy of monitoring of water conservancy facilities.

[0047] (2) The present invention can dynamically allocate computing devices according to the early warning analysis status of each water area, and can effectively use edge computing devices to share a large amount of computing power, thereby realizing the priority analysis and judgment process of abnormal water areas, and improving the intelligence of water area monitoring and management. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The present invention will be further described below with reference to the accompanying drawings.

[0049] Figure 1 It is a schematic block diagram of the water conservancy project safety monitoring system of the present invention. DETAILED DESCRIPTION

[0050] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0051] See also Figure 1 As shown, in one embodiment, a water conservancy project safety monitoring system based on 5G and BeiDou technology is provided, the system comprising:

[0052] Satellite image acquisition module, which obtains satellite image information of water conservancy projects based on Beidou technology;

[0053] The cloud server is used to receive satellite image information, identify and analyze the satellite image information, obtain water level contour lines and water conservancy facility contour lines, and analyze the first water level information based on the water level contour lines;

[0054] Water level monitoring equipment, used for on-site monitoring of the water level and obtaining second water level information;

[0055] an error analysis module, configured to analyze a contour deviation based on the first water level information and the second water level information;

[0056] The early warning module is used to fine-tune the contour line of the water conservancy facility according to the contour deviation, and to make early warning judgments based on the contour deviation after fine-tuning.

[0057] Through the above technical solution, the water level information monitored on the spot is combined with the image information obtained by the satellite to realize the comparison between the image contour line and the actual contour line, and then the contour line of the identified water conservancy facility is fine-tuned through the contour deviation between the two, thereby improving the accuracy of identification, analysis and judgment, and thus improving the accuracy of monitoring of water conservancy facilities.

[0058] It should be noted that the satellite image recognition in the above scheme is realized through the visual recognition algorithm commonly used in the existing technology. By adjusting the contrast and grayscale processing of the satellite image, and then using the edge recognition algorithm, the contour lines of the water area and the contour lines of water conservancy facilities can be obtained; this process will not be repeated.

[0059] It should also be noted that the on-site monitoring method of the water level can be obtained through the water level monitoring instrument in the prior art, and this process will not be repeated in this embodiment.

[0060] As an embodiment of the present invention, the process of analyzing the first water level information is as follows:

[0061] The water area is divided into blocks, and a water level function Level(S) is established for each block, where S is the water area of the block;

[0062] The water area S of the block is obtained according to the water level contour line, and the water area S is substituted into the water level function Level(S) to obtain the first water level information.

[0063] Through the above technical solution, this embodiment establishes a correspondence between the water area and water level information for different water blocks in advance, namely the water level function Level (S), and then divides the water area into blocks, analyzes and judges each water block, and analyzes and judges based on the water level function of each water block. This can more accurately establish the relationship between the water level and the water area, thereby realizing the process of obtaining the first water level information through the water area.

[0064] It should be noted that the water level function Level(S) is selectively set according to the historical information of the block water area.

[0065] As an embodiment of the present invention, the process of fine-tuning the outline of the water conservancy facility is as follows:

[0066] The contour deviation is trained based on the deviation between the contour lines of water conservancy facilities collected in historical data and the corresponding actual contour lines of water conservancy facilities to obtain an error judgment model;

[0067] The obtained contour deviation is input into the error judgment model to obtain the fine-tuning amount;

[0068] Fine-tune the contour line of the water conservancy facility according to the fine-tuning amount to obtain the contour line of the water conservancy facility after fine-tuning, compare the contour line of the water conservancy facility after fine-tuning with the standard contour line, and make an early warning judgment based on the comparison result.

[0069] Through the above technical solution, this embodiment provides a specific fine-tuning process of the water conservancy facility contour line. By using machine learning technology, the contour deviation is trained based on the deviation between the water conservancy facility contour line collected in historical data and the corresponding actual water conservancy facility contour line to obtain an error judgment model. The contour deviation is then input into the error judgment model to obtain the fine-tuning amount. The water conservancy facility contour line is then fine-tuned by the fine-tuning amount to obtain a more accurate water conservancy facility contour line after fine-tuning, which is then compared with the standard contour line. Obviously, when the water conservancy facility contour line deviates from the standard contour line after fine-tuning, and the deviation value exceeds the error range value, it indicates that the water conservancy facility has a high safety risk, so an early warning is issued.

[0070] It should be noted that, in the above technical solution, the contour deviation is obtained by comparing the overlap of the water area contour lines corresponding to the first water level information and the second water level information. The specific comparison process is implemented by the existing technology and will not be elaborated here. In addition, the machine training process in this embodiment is also implemented by the machine training model commonly used in the existing technology and will not be described in detail here. The fine-tuning amount in this embodiment is the specific numerical value of the offset, and the direction is determined by the comparison result. In addition, the error range in the early warning judgment process in this embodiment is obtained based on empirical data.

[0071] As an embodiment of the present invention, the system further includes:

[0072] Edge computing devices are distributed around the water area to receive image information and perform analysis;

[0073] The cloud platform is connected to all edge computing devices to obtain the analysis results of edge computing devices and perform early warning analysis;

[0074] The computing allocation module is used to allocate edge computing devices based on the results of the block water area warning analysis.

[0075] Through the above technical solution, the use of edge computing devices combined with the cloud platform can quickly and accurately monitor the water conservancy conditions and water conservancy settings in real time. Among them, the edge computing devices are set up around the water area and can receive image information and analyze it. The cloud platform is connected to all edge computing devices, and can obtain the results of the edge computing device analysis and perform early warning analysis; then, through the calculation allocation module, the computing devices are dynamically allocated according to the early warning analysis status of each block of water area, which can effectively use the edge computing devices to share a large amount of computing, thereby realizing the priority analysis and judgment process of abnormal water areas, and improving the intelligence of water area monitoring and management.

[0076] It should be noted that in the above scheme, the specific layout of the edge computing equipment is selectively set according to the specific conditions of the water area and its surroundings, and is not limited in this embodiment; when the computing amount exceeds the capacity of the edge computing equipment, it can also be achieved through cloud computing.

[0077] As an embodiment of the present invention, the allocation process of edge computing devices is as follows:

[0078] The edge computing device receives the image information of the corresponding water area and the corresponding rainfall information of the area according to the preset period;

[0079] Through edge devices, early warning analysis of image information and rainfall information is performed to obtain early warning values for the water area.

[0080] Sort the water areas in the block according to the warning values from large to small, adjust the preset cycle according to the ranking, and obtain the dynamic cycle;

[0081] Allocate edge computing devices based on the frequency of dynamic cycles.

[0082] Through the above technical solution, this embodiment provides a method for allocating edge computing devices. Specifically, the edge computing device receives the image information of the corresponding block water area and the rainfall information corresponding to the area according to a preset period; the edge device conducts warning analysis on the image information and rainfall information to obtain the warning value of the block water area; the larger the warning value, the greater the risk of the water condition in the area, so the block water area is sorted from large to small according to the warning value, and the preset period is adjusted according to the sorting to obtain a dynamic period. Obviously, the greater the risk, the higher the frequency of analysis and judgment of the area. At the same time, the higher the frequency of analysis and judgment, the higher the demand for edge computing devices. Therefore, allocating edge computing devices according to the frequency of the dynamic period can adaptably meet the needs according to the actual situation, improve the speed of analysis and calculation, and at the same time, reduce the pressure on cloud computing, thereby improving the timeliness of the warning.

[0083] As an embodiment of the present invention, the calculation process of the warning value is:

[0084] By formula Calculate the warning value E;

[0085] Among them, R is the rainfall, R0 is the rainfall reference value; S is the water area value of the block; v S () is the function of the water area changing with rainfall and water level speed, v0() is the function of the water area changing with water level speed; S abn is the water area value of abnormal water changes; S0 is the reference value of the abnormal water area of the block; μ and γ are preset proportional coefficients.

[0086] Through the above technical solution, this embodiment provides a calculation process of the warning value, through the formula Obtain, among which, Indicates abnormal rainfall conditions. Indicates the abnormal conditions of water areas with water level changes under different water areas; It indicates that abnormal changes have occurred within the water area, so the warning value E can reflect the safety risk status of water facilities.

[0087] It should be noted that the change function v in the above technical solution S () and v0() are obtained based on historical data analysis, R0 and S0 are selectively set based on the location of the water area and the conditions of the water conservancy facilities, and the preset proportional coefficients μ and γ are selectively set based on historical experience data.

[0088] As an embodiment of the present invention, the process of edge computing device according to dynamic periodic frequency allocation is as follows:

[0089] The amount of calculation P used to analyze the water area of the prediction block according to the dynamic cycle cal ;

[0090] According to the order of dynamic cycle frequency, P cal The maximum computing capacity P of the edge computing device corresponding to the water area of this block max Make a comparison;

[0091] If P cal >P max , then the remaining computing amount P of the adjacent edge computing device ar Make a judgment:

[0092] If P ar ≥P cal -P max , sharing the computational load through adjacent edge computing devices;

[0093] Otherwise, the computation load is shared by adjacent edge computing devices and P ar -(P cal -P max) performs cloud computing on part of the computation and sends the cloud computing results to the cloud platform.

[0094] Through the above technical solution, this embodiment provides a method for allocating edge computing devices. Specifically, according to the order of dynamic cycle frequency, P cal The maximum computing capacity P of the edge computing device corresponding to the water area of this block max Compare; if P cal >P max , it means that the amount of computation has exceeded the computing capacity of the corresponding edge computing device, so the remaining computation amount P of the adjacent edge computing device is ar Make a judgment: If P ar ≥P cal -P max , the adjacent edge computing devices can share part of the computing load; otherwise, the overflowing computing load can be realized through cloud computing, thereby realizing a fast and accurate analysis process of the water conditions and improving the timeliness of the early warning.

[0095] As an embodiment of the present invention, the system further includes an intelligent inspection module;

[0096] The intelligent inspection module is used to adjust the number of inspectors in each water area according to the size of the warning value.

[0097] The process of adjusting the number of inspectors is as follows:

[0098] Arrange a basic number of patrol officers for each water area;

[0099] By formula The number of additional patrol officers for the i-th water area is obtained;

[0100] Where m is the total number of water areas in the block, i∈[1,m]; E i is the warning value of the water area in the i-th block; N as To increase the total number of inspectors.

[0101] Through the above technical solution, this embodiment also sets up an intelligent inspection module to dynamically adjust the number of inspectors according to the specific conditions of the water area and the corresponding water conservancy facilities, thereby realizing an intelligent adaptive inspection process. Specifically, the number of inspectors in each water area is adjusted according to the size of the warning value. First, the basic number of inspectors is arranged for each water area; then, the formula is used to calculate the number of inspectors. The number of additional patrol officers for the i-th water area is obtained; where m is the total number of water areas in the block, i∈[1,m]; E i is the warning value of the water area in the i-th block; N asIn order to increase the total number of inspectors, on the basis of meeting the basic inspection requirements of different water areas, the number of inspectors is dynamically adjusted according to the size of the warning value to adaptively meet the inspection needs.

[0102] In the above technical solution, the number of additional inspectors and the basic number of people in each water area are selectively set by the relevant water conservancy departments based on specific conditions and are not limited here.

[0103] The above is a detailed description of an embodiment of the present invention. However, the content described is only a preferred embodiment of the present invention and should not be considered to limit the scope of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A water conservancy project safety monitoring system based on 5G and BeiDou technology, characterized in that: The system comprises: Satellite image acquisition module, which obtains satellite image information of water conservancy projects based on Beidou technology; The cloud server is used to receive satellite image information, identify and analyze the satellite image information, obtain water level contour lines and water conservancy facility contour lines, and analyze the first water level information based on the water level contour lines; Water level monitoring equipment, used for on-site monitoring of the water level and obtaining second water level information; an error analysis module, configured to analyze a water area contour deviation based on the first water level information and the second water level information; The early warning module is used to fine-tune the contour of water conservancy facilities according to the deviation of the water area contour and make early warning judgments based on the deviation of the contour after fine-tuning; The system also includes: edge computing devices distributed around the water area for receiving and analyzing image information; The cloud platform is connected to all edge computing devices to obtain the analysis results of edge computing devices and perform early warning analysis; The computing allocation module is used to allocate edge computing devices based on the results of the block water area warning analysis; The allocation process of edge computing devices is as follows: the edge computing devices receive image information and rainfall information of the corresponding water area according to a preset period; Through edge devices, early warning analysis of image information and rainfall information is performed to obtain early warning values for the water area. Sort the water areas in the block according to the warning values from large to small, adjust the preset cycle according to the ranking, and obtain the dynamic cycle; Allocate edge computing devices based on the frequency of dynamic cycles; The calculation process of the warning value is: Calculate the warning value E; Where R is the rainfall, is the rainfall baseline value; S is the water area value of the block; is the function of water area changing with rainfall and water level velocity, is the function of the speed at which the water area of the block changes with the water level; is the water area value of abnormal changes in water areas; It is the reference value of abnormal area of water area in the block; 、 is the preset scale factor.

2. The water conservancy project safety monitoring system based on 5G and BeiDou technology according to claim 1 is characterized in that: The process of first water level information analysis is: The water area is divided into blocks, and a water level function Level(S) is established for each block, where S is the water area of the block; The water area S of the block is obtained according to the water level contour line, and the water area S is substituted into the water level function Level(S) to obtain the first water level information.

3. The water conservancy project safety monitoring system based on 5G and BeiDou technology according to claim 1 is characterized in that: The process of fine-tuning the outline of water conservancy facilities is as follows: The water area contour deviation is trained based on the deviation between the water conservancy facility contour lines collected in historical data and the corresponding actual water conservancy facility contour lines to obtain an error judgment model; The obtained water contour deviation is input into the error judgment model to obtain the fine-tuning amount; Fine-tune the contour line of the water conservancy facility according to the fine-tuning amount to obtain the contour line of the water conservancy facility after fine-tuning, compare the contour line of the water conservancy facility after fine-tuning with the standard contour line, and make an early warning judgment based on the comparison result.

4. The water conservancy project safety monitoring system based on 5G and BeiDou technology according to claim 1 is characterized in that: The process of edge computing device frequency allocation based on dynamic cycle is as follows: The amount of calculation required to analyze the water area of the prediction block according to the dynamic cycle ; In order of the dynamic cycle frequency, The maximum computing capacity of the edge computing device corresponding to the water area of this block Make a comparison; like > , then the remaining computing power of the adjacent edge computing devices Make a judgment: If P ar ≥P cal -P max , sharing the computational load through adjacent edge computing devices; Otherwise, the computation load is shared by adjacent edge computing devices and P ar -(P cal -P max ) performs cloud computing on part of the computation and sends the cloud computing results to the cloud platform.

5. The water conservancy project safety monitoring system based on 5G and BeiDou technology according to claim 4 is characterized in that: The system also includes an intelligent inspection module; The intelligent inspection module is used to adjust the number of inspectors in each water area according to the size of the warning value.

6. The water conservancy project safety monitoring system based on 5G and BeiDou technology according to claim 5 is characterized in that: The process of adjusting the number of inspectors is as follows: Arrange a basic number of patrol officers for each water area; By formula The number of additional patrol officers for the i-th water area is obtained; Where m is the total number of water areas in the block, i∈[1,m]; is the warning value of the water area in the i-th block; To increase the total number of inspectors.

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