Water conservancy river channel construction operation management system and method based on data analysis

Abstract

The application discloses a water conservancy river channel construction operation management system and method based on data analysis, relates to the technical field of data analysis, and carries out water area navigation operation risk assessment of each operation area based on water area state data and bottom state data of each operation area; carries out aging degree assessment of each suction dredger based on historical operation efficiency data of each suction dredger; obtains the distribution result of each suction dredger in each operation area according to the water area navigation operation risk assessment result and the aging degree assessment result of each suction dredger, and carries out construction operation according to the distribution result of each suction dredger in each operation area; sending the suction dredger with high aging degree to a low-risk operation area for operation can reduce accident risk, ensure operation safety, prolong the service life of water area operation equipment, optimize the operation efficiency of water area operation equipment, improve resource utilization rate, and reduce the maintenance cost of water area operation equipment.

Description

Technical Field

[0001] This application belongs to the field of data analysis, specifically a data analysis-based management system and method for water conservancy and river channel construction operations. Background Technology

[0002] As the core equipment for dredging projects, trailing suction hopper dredgers suck up mud through rakes placed on both sides or the stern of the hull, operating by simultaneously sucking up mud and navigating. Their hulls are equipped with open-bottom mud compartments, the volume of which directly reflects the vessel's operational capacity. Due to the special operational requirements, the hull structure of these engineering vessels differs significantly from that of conventional vessels. For example, large slots are required at the bow and stern to install equipment such as bridge frames and trolleys. With the rapid development of the shipping industry and the continuous upgrading of dredging equipment technology, the role of suction hopper dredgers in waterway maintenance, port construction, and other fields is becoming increasingly prominent.

[0003] Currently, vessel scheduling and task allocation in dredging operations rely heavily on manual experience, lacking a systematic assessment basis. Traditional production task allocation is typically centered on delivery deadlines, prioritizing urgent tasks or projects with large workloads, but failing to fully consider the compatibility between the environmental characteristics of the operating waters and the actual condition of the vessels. For example, the water conditions (such as current velocity and tides) and bottom conditions (such as hardness and sand content) of different operating areas directly affect navigation safety and dredging efficiency, while the aging of the vessels relates to equipment reliability and operational stability. Existing technologies struggle to comprehensively assess the compatibility between water area risks and vessel performance, leading to blind task allocation: on the one hand, older vessels may be assigned to challenging waters, exacerbating equipment wear and even causing safety accidents; on the other hand, high-performance vessels operating in low-risk areas result in resource waste.

[0004] Although existing research has proposed risk assessment models for ship navigation safety, covering multiple dimensions such as mechanical failure and environmental interference, these methods are still limited to single-dimensional analysis and have not formed a closed loop between water area risk, ship aging, and operation allocation decisions. Therefore, there is an urgent need for an intelligent allocation method that integrates water area environmental data, seabed characteristics, and historical ship operation efficiency. This method can achieve optimal allocation of dredging resources by quantitatively assessing operation risks and ship status, thereby improving operation safety, efficiency, and equipment lifespan. To address the problems raised in this background, this application designs a data analysis-based water conservancy channel construction operation management system and method. Summary of the Invention

[0005] To address the aforementioned technical shortcomings, this application proposes a data analysis-based water conservancy and river channel construction operation management system and method.

[0006] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: This application provides a data analysis-based method for the management of water conservancy river channel construction operations, which includes the following specific steps:

[0007] S1. Obtain water condition data, bottom sediment condition data, and historical operating efficiency data of each dredger in each operating area;

[0008] S2. Conduct a risk assessment of navigation operations in each work area based on the water condition data and bottom sediment condition data of each work area;

[0009] S3. Assess the aging degree of each dredging vessel based on its historical operating efficiency data.

[0010] S4. Based on the risk assessment results of navigation operations in the waters of each work area and the aging assessment results of each dredger, the allocation results of each work area corresponding to each dredger are obtained, and the construction operation is carried out according to the allocation results of each work area corresponding to each dredger.

[0011] It should be noted that, as a preferred technical solution for the data analysis-based water conservancy and river channel construction operation management method, the specific steps of S1 are as follows:

[0012] S11. Acquire water condition data of each work area through sonar detection, including navigable water depth data and obstacle density data in each work area.

[0013] S12. Obtain bottom sediment condition data for each working area using a densitometer and a laser particle size analyzer. The bottom sediment condition data for each working area includes bottom mud density data and bottom particle size data for each working area.

[0014] S13. Obtain historical operational efficiency data for each dredging vessel from the database;

[0015] S14. Store the collected data in the storage component for use in the analysis process.

[0016] It should be noted that, as a preferred technical solution for the data analysis-based water conservancy and river channel construction operation management method, step S2 includes the following specific steps:

[0017] S21. The risk assessment value of water operations in each work area is obtained from the bottom mud density data and bottom particle size data in each work area.

[0018] S22. Obtain the risk assessment results of water operations in each work area, and obtain the risk assessment value of water operations in each work area from the risk assessment results of water operations in each work area.

[0019] S23. Preset the area of ​​each unit in each work area, and obtain the navigation risk assessment value of each work area from the water operation risk assessment value of each work area, the navigable water depth data and obstacle density data of each work area.

[0020] It should be noted that, as a preferred technical solution for the data analysis-based water conservancy and river channel construction operation management method, the specific steps of S21 are as follows: Risk assessment of water operations in each operation area is conducted based on the bottom sediment density data and bottom sediment particle size data. The calculation formula for the risk assessment of the i-th operation area is: ,in, Here is the density data of the bottom sediment mud in the i-th working area. For water density data, This is a reference value for the specific gravity of the mud. This refers to the value where 90% of the sediment particle size values ​​in the i-th working area are greater than a certain value. The value is defined as the percentage of sediment particle sizes greater than 50% in the i-th working area. For reference particle size fluctuation values, The weighting of the bottom sediment mud density ratio, The weighting is based on the proportion of substrate particle size. It should be noted that... and The purpose of this setting is to reflect the mud specific gravity in each working area by the difference between the density of the bottom mud and the density of the clear water. The mud specific gravity affects the stability of the suction dredger during operation. The purpose of this setting is to quantify the mud settling trend; and The purpose of this setting is to consider the impact of bottom sediment particle size on the construction risk of dredging vessel operations. By evaluating the size distribution of bottom sediment particles through the values ​​of 90% and 50% bottom sediment particle size, it is found that large particles will increase the difficulty of dredging vessel operations, while small particles will affect the properties of the mud. The purpose of this setting is to measure the impact of particle size variation on the risk assessment value of water operations. and The purpose of this setting is to dynamically adjust the influence of bottom sediment density and particle size on the risk assessment value of water operations, so as to ensure that the risk assessment value of water operations is more comprehensive and accurate. The purpose of this setting is to reflect the density difference between mud and water; the greater the difference, the stronger the settling trend. The purpose of this setting is to reflect the specific gravity of the mud in each work area. The higher the value, the stronger the mud settling tendency; The purpose of this setting is: to... and The ratio quantifies the settling trend of the mud; The purpose of this setting is to evaluate the size distribution of bottom sediment particles by using the values ​​of 90% and 50% bottom sediment particle size to reflect the settling of bottom sediment slurry during dredging operations. The larger the particle size, the faster the settling speed. The purpose of this setting is to quantify the settling of bottom mud during dredging operations.

[0021] It should be noted that, as a preferred technical solution for the data analysis-based water conservancy and river channel construction operation management method, the specific steps of S23 are as follows: Based on the risk assessment values ​​of waterway operations in each operation area, the navigable water depth data and obstacle density data in each operation area, a risk assessment of navigation operations in the waterway of each operation area is performed. The calculation formula for the risk assessment of navigation operations in the i-th operation area is: Where i is the number corresponding to each work area, i can be any item from 1 to N, and r is the number corresponding to each unit area, r can be any item from 1 to A. Let be the risk assessment value for the water area operation in the i-th operation area. The maximum depth is the value within the r-th unit area of ​​the i-th work region. The minimum depth is the minimum value within the r-th unit area of ​​the i-th work region. For reference depth fluctuation values, 'a' represents the weight of the influence of the working area depth. Let Z be the obstacle density data for the i-th work area, and Z be the set safe density. It should be noted that in this formula... and The purpose of this setting is to measure the difference between the maximum and minimum depth values ​​per unit area in each work area, thereby reflecting the fluctuation of depth in each work area. Large differences in water depth will increase the risk of operation. If the minimum water depth is too shallow or the maximum water depth is too deep, it may cause the dredger to run aground or become unstable. The purpose of setting a is to compare the degree of depth difference between different work areas; the purpose of setting a is to adjust the relative importance of the depth factor in the overall assessment. The purpose of setting Z is to measure the difficulty and efficiency of the operation by using the density of obstacles in each work area; the purpose of setting Z is to measure the difficulty and efficiency of the operation in each work area by using the safe density of obstacles; in this formula Part of the method is to sum the differences between the maximum and minimum depth values ​​per unit area in each work area and then calculate the average value to reflect the fluctuation of depth in each work area. Part of the calculation involves multiplying the risk assessment value of each operating area with the fluctuation of the depth in each operating area to reflect the interaction between the operation and navigation of the dredger in each operating area.

[0022] It should be noted that, as a preferred technical solution for the data-based water conservancy and river channel construction operation management method, the specific steps of S3 are as follows: Based on the historical operating efficiency data of each dredger, the aging degree of each dredger is assessed, wherein the calculation formula for the aging degree assessment of the j-th dredger is: Where j is the number corresponding to each dredging vessel, j can be any one of 1 to M, and k is the number of each historical operation period, k can be any one of 1 to q. For time decay weight, Let J be the operating efficiency of the dredging vessel during the k-th historical operating time period. Let J be the operating efficiency of the j-th dredger during the (k-1)-th historical operating time period. As a reference value for efficiency fluctuations, it should be noted that in this formula... The purpose of this setting is to control the impact of fluctuations in the operating efficiency of dredging vessels over different historical operating periods on the rate of decay of the dredging vessel aging assessment value. More recent historical operating periods... The larger; The absolute value of the difference in the operating efficiency of the dredging vessel in adjacent time periods is calculated to capture the degree of change in the operating efficiency of the dredging vessel in adjacent time periods, thus avoiding the influence of the dimension of the absolute efficiency value. By setting weights and weighted summation, the contribution of recent changes in operational efficiency to the assessment value of the aging degree of the dredging vessel is enhanced. The purpose of this setting is to quantify the dynamic changes in the operating efficiency of the dredging vessel. The purpose of this formula is to quantitatively evaluate the dynamic changes in the efficiency of a single piece of equipment by analyzing the dynamic changes in the operating efficiency of the dredging vessel.

[0023] It should be noted that, as a preferred technical solution for the water conservancy and river channel construction operation management method based on data analysis, the specific steps of S4 are as follows: obtain the risk assessment results of navigation operations in each operation area and the aging assessment results of each dredger; sort the risk assessment values ​​of navigation operations in each operation area in ascending order, and sort the aging assessment values ​​of each dredger in descending order; match each dredger corresponding to the aging assessment results of each dredger with each operation area corresponding to the aging assessment results of each operation area, thereby obtaining the allocation results of each operation area corresponding to each dredger; and carry out construction operations according to the allocation results of each operation area corresponding to each dredger. It should be noted that dispatching dredgers with high aging levels to low-risk operation areas can reduce the risk of accidents and ensure operational safety. Dredgers with high aging levels are prone to failure in high-risk operation areas due to equipment aging. In low-risk areas, the equipment can be kept off-load, avoiding capsizing or collision accidents caused by mechanical failure.

[0024] The water conservancy and river channel construction operation management system based on data analysis is implemented based on the above-mentioned water conservancy and river channel construction operation management method based on data analysis. Specifically, it includes an operation data acquisition module, an operation area risk assessment module, an equipment aging assessment module, and an operation area result allocation module. The operation data acquisition module is used to acquire water area status data, bottom sediment status data, and historical operation efficiency data of each dredger in each operation area.

[0025] The operation area risk assessment module is used to assess the risk of navigation operations in each operation area based on the water condition data and bottom sediment condition data of each operation area.

[0026] The equipment aging assessment module is used to assess the aging of each dredging vessel based on its historical operating efficiency data.

[0027] The operation area result allocation module is used to obtain the operation area allocation results corresponding to each dredger based on the risk assessment results of navigation operations in the waters of each operation area and the aging assessment results of each dredger, and to carry out construction operations based on the operation area allocation results corresponding to each dredger.

[0028] An electronic device includes: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0029] The processor executes the aforementioned data analysis-based water conservancy and river channel construction operation management method by calling the computer program stored in the memory.

[0030] A computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the aforementioned data analysis-based water conservancy and river channel construction operation management method.

[0031] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention acquires water state data, bottom sediment state data, and historical operating efficiency data of each dredger in each operating area; conducts a risk assessment of navigation operations in each operating area based on the water state data and bottom sediment state data; assesses the aging degree of each dredger based on the historical operating efficiency data; obtains the allocation results of each dredger to each operating area based on the risk assessment results of navigation operations in each operating area and the aging degree assessment results of each dredger; and carries out construction operations based on the allocation results of each dredger to each operating area. Dispatching dredgers with high aging degrees to low-risk operating areas can reduce accident risks, ensure operational safety, extend the service life of water operation equipment, optimize the operating efficiency of water operation equipment, improve resource utilization, and reduce the maintenance cost of water operation equipment. Attached Figure Description

[0032] Figure 1 This is a schematic diagram of the overall process of the water conservancy and river channel construction operation management method based on data analysis in this application.

[0033] Figure 2 This is a schematic diagram of step S2 of the data analysis-based water conservancy and river channel construction operation management method of this application.

[0034] Figure 3 This is a schematic diagram of the overall framework of the water conservancy and river channel construction operation management system based on data analysis in this application.

[0035] Figure 4 This is a schematic diagram illustrating the process of obtaining the risk assessment value for waterway navigation operations in the data analysis-based water conservancy and river channel construction operation management method of this application. Detailed Implementation

[0036] To better understand this application, various aspects of this application will be described in more detail with reference to the accompanying drawings.

[0037] To address the technical problems raised in the background art, this application provides a preferred embodiment:

[0038] The specific content of this embodiment is as follows:

[0039] like Figure 1 As shown, the data analysis-based water conservancy river channel construction operation management method includes the following specific steps:

[0040] S1. Obtain water condition data, bottom sediment condition data, and historical operating efficiency data of each dredger in each operating area;

[0041] In this embodiment, the specific steps of S1 are as follows:

[0042] S11. Acquire water condition data of each work area through sonar detection, including navigable water depth data and obstacle density data in each work area.

[0043] S12. Obtain bottom sediment condition data for each working area using a densitometer and a laser particle size analyzer. The bottom sediment condition data for each working area includes bottom mud density data and bottom particle size data for each working area.

[0044] S13. Obtain historical operational efficiency data for each dredging vessel from the database;

[0045] S14. Store the collected data in the storage component for use in the analysis process.

[0046] In one implementation of the present invention, sonar detection is used to acquire water state data of each operating area, including navigable water depth data and obstacle density data of each operating area, for analyzing the navigation difficulty of the dredger in each operating area; densitometer and laser particle size analyzer are used to acquire bottom sediment state data of each operating area, including bottom sediment slurry density data and bottom sediment particle size data of each operating area, for analyzing the sediment settling of bottom sediment slurry during dredger operation; and historical operating efficiency data of each dredger is acquired through a database for analyzing the aging degree of the dredger.

[0047] S2. Conduct a risk assessment of navigation operations in each work area based on the water condition data and bottom sediment condition data of each work area;

[0048] like Figure 2 As shown, in this embodiment, S2 includes the following specific steps:

[0049] S21. The risk assessment value of water operations in each work area is obtained from the bottom mud density data and bottom particle size data in each work area.

[0050] In this embodiment, S21 includes the following specific steps: conducting a risk assessment of water operations in each operating area based on the bottom mud density data and bottom particle size data, wherein the calculation formula for the risk assessment of the i-th operating area is: ,in, Here is the density data of the bottom sediment mud in the i-th working area. For water density data, This is a reference value for the specific gravity of the mud. This refers to the value where 90% of the sediment particle size values ​​in the i-th working area are greater than a certain value. The value is defined as the percentage of sediment particle sizes greater than 50% in the i-th working area. For reference particle size fluctuation values, The weighting of the bottom sediment mud density ratio, The weighting is based on the proportion of substrate particle size. It should be noted that... and The purpose of this setting is to reflect the mud specific gravity in each working area by the difference between the density of the bottom mud and the density of the clear water. The mud specific gravity affects the stability of the suction dredger during operation. The purpose of this setting is to quantify the mud settling trend; and The purpose of this setting is to consider the impact of bottom sediment particle size on the construction risk of dredging vessel operations. By evaluating the size distribution of bottom sediment particles through the values ​​of 90% and 50% bottom sediment particle size, it is found that large particles will increase the difficulty of dredging vessel operations, while small particles will affect the properties of the mud. The purpose of this setting is to measure the impact of particle size variation on the risk assessment value of water operations. and The purpose of this setting is to dynamically adjust the influence of bottom sediment density and particle size on the risk assessment value of water operations, so as to ensure that the risk assessment value of water operations is more comprehensive and accurate. The purpose of this setting is to reflect the density difference between mud and water; the greater the difference, the stronger the settling trend. The purpose of this setting is to reflect the specific gravity of the mud in each work area. The higher the value, the stronger the mud settling tendency; The purpose of this setting is: to... and The ratio quantifies the settling trend of the mud; The purpose of this setting is to evaluate the size distribution of bottom sediment particles by using the values ​​of 90% and 50% bottom sediment particle size to reflect the settling of bottom sediment slurry during dredging operations. The larger the particle size, the faster the settling speed. The purpose of this setting is to quantify the settling of bottom sediment during dredging operations. For example, the benefits and basis of this formula are illustrated: the specific gravity of the sediment is directly related to the risk of sediment settling; a higher specific gravity makes the sediment more prone to settling, leading to pipe blockage and pump overload. Combining the 90% and 50% sediment particle size values ​​with reference particle size fluctuations, the influence of particle size distribution on the risk assessment value of water operations is considered. Setting weights for sediment density and sediment particle size proportions ensures the rationality and accuracy of the assessment results.

[0051] S22. Obtain the risk assessment results of water operations in each work area, and obtain the risk assessment value of water operations in each work area from the risk assessment results of water operations in each work area.

[0052] S23, such as Figure 4 As shown, each unit area is preset in each operation area, and the navigation operation risk assessment value of each operation area is obtained from the water operation risk assessment value of each operation area, the navigable water depth data and obstacle density data of each operation area.

[0053] In this embodiment, S23 includes the following specific steps: assessing the navigation operation risk of each work area based on the risk assessment value of the waterway operation in each work area, the navigable water depth data and obstacle density data in each work area, wherein the calculation formula for the navigation operation risk assessment of the i-th work area is: Where i is the number corresponding to each work area, i can be any item from 1 to N, and r is the number corresponding to each unit area, r can be any item from 1 to A. Let be the risk assessment value for the water area operation in the i-th operation area. The maximum depth is the value within the r-th unit area of ​​the i-th work region. The minimum depth is the minimum value within the r-th unit area of ​​the i-th work region. For reference depth fluctuation values, 'a' represents the weight of the influence of the working area depth. Let Z be the obstacle density data for the i-th work area, and Z be the set safe density. It should be noted that in this formula... and The purpose of this setting is to measure the difference between the maximum and minimum depth values ​​per unit area in each work area, thereby reflecting the fluctuation of depth in each work area. Large differences in water depth will increase the risk of operation. If the minimum water depth is too shallow or the maximum water depth is too deep, it may cause the dredger to run aground or become unstable. The purpose of setting a is to compare the degree of depth difference between different work areas; the purpose of setting a is to adjust the relative importance of the depth factor in the overall assessment. The purpose of setting Z is to measure the difficulty and efficiency of the operation by using the density of obstacles in each work area; the purpose of setting Z is to measure the difficulty and efficiency of the operation in each work area by using the safe density of obstacles; in this formula Part of the method is to sum the differences between the maximum and minimum depth values ​​per unit area in each work area and then calculate the average value to reflect the fluctuation of depth in each work area. Part of the formula reflects the interaction between the dredger's operation and navigation in each work area by multiplying the risk assessment value of the water area in each work area with the depth fluctuation of each work area. For example, the benefits and basis of this formula are illustrated by the following example: This formula calculates the difference between the maximum and minimum depths per unit area in each work area, sums them, and then averages them to obtain the difference between the maximum and minimum depths of each work area. The difference between the maximum and minimum depths of each work area is compared with the reference depth fluctuation value to quantify the navigation difficulty of the dredger in each work area. This difference is then multiplied with the risk assessment value of the water area in each work area to obtain the navigation difficulty of the water area in each work area, which improves the pertinence and accuracy of the water navigation operation risk assessment value.

[0054] S3. Assess the aging degree of each dredging vessel based on its historical operating efficiency data.

[0055] In this embodiment, the specific steps of S3 are as follows: Based on the historical operating efficiency data of each dredging vessel, the aging degree of each dredging vessel is assessed, wherein the calculation formula for the aging degree assessment of the j-th dredging vessel is: Where j is the number corresponding to each dredging vessel, j can be any one of 1 to M, and k is the number of each historical operation period, k can be any one of 1 to q. For time decay weight, Let J be the operating efficiency of the dredging vessel during the k-th historical operating time period. Let J be the operating efficiency of the j-th dredger during the (k-1)-th historical operating time period. As a reference value for efficiency fluctuations, it should be noted that in this formula... The purpose of this setting is to control the impact of fluctuations in the operating efficiency of dredging vessels over different historical operating periods on the rate of decay of the dredging vessel aging assessment value. More recent historical operating periods... The larger; The absolute value of the difference in the operating efficiency of the dredging vessel in adjacent time periods is calculated to capture the degree of change in the operating efficiency of the dredging vessel in adjacent time periods, thus avoiding the influence of the dimension of the absolute efficiency value. By setting weights and weighted summation, the contribution of recent changes in operational efficiency to the assessment value of the aging degree of the dredging vessel is enhanced. The purpose of this setting is to quantify the dynamic changes in the operating efficiency of a dredging vessel. This formula aims to quantitatively evaluate the dynamic changes in the efficiency of a single piece of equipment by analyzing these changes. For example, an illustration demonstrates the benefits and basis of this formula setting: by introducing a time decay weight... This reflects the change in the dredging vessel's operational efficiency over time, making the aging assessment more closely reflect actual conditions; it utilizes efficiency fluctuation reference values. Controlling the differences in operational efficiency across different historical periods ensures the accuracy and comparability of the assessment results; comprehensively evaluating the changes in the operational efficiency of the dredger in different historical periods fully reflects the aging degree of the dredger.

[0056] S4. Based on the risk assessment results of navigation operations in the waters of each work area and the aging assessment results of each dredger, the allocation results of each work area corresponding to each dredger are obtained, and the construction operation is carried out according to the allocation results of each work area corresponding to each dredger.

[0057] In this embodiment, the specific steps of S4 are as follows: obtain the risk assessment results of navigation operations in the waters of each work area and the aging assessment results of each dredger; sort the risk assessment values ​​of navigation operations in the waters of each work area in ascending order, and sort the aging assessment values ​​of each dredger in descending order; and match each dredger corresponding to the aging assessment results of each dredger with each work area corresponding to the aging assessment results of each work area. In this way, the allocation results of each work area corresponding to each dredger are obtained. Construction operations are carried out according to the allocation results of each work area corresponding to each dredger. It should be noted that dispatching dredgers with high aging levels to low-risk work areas can reduce the risk of accidents and ensure operational safety. Dredgers with high aging levels are prone to failure in high-risk work areas due to equipment aging. In low-risk areas, the equipment can be kept from being overloaded, avoiding capsizing or collision accidents caused by mechanical failure.

[0058] It should be noted that the parameters set in this embodiment (such as weights and thresholds) need to be set by those skilled in the art based on relevant experiments. The specific experimental method is as follows: obtain water state data, bottom sediment state data and historical operation efficiency data of each dredger in each operation area, and use them in the steps of this embodiment to conduct navigation operation risk assessment and aging degree assessment of each dredger in each operation area. Obtain the allocation results of each operation area obtained from the navigation operation risk assessment and aging degree assessment of each dredger in each operation area. Import the allocation results of each operation area and the actual operation results into the fitting software for continuous fitting, and output the values ​​of the set parameters (such as weights and thresholds) that match the actual operation results of each operation area allocation results.

[0059] Based on the above implementation, this embodiment has the following advantages over the prior art: This embodiment acquires water state data, bottom sediment data, and historical operating efficiency data of each dredger in each operating area; it conducts a risk assessment of navigation operations in each operating area based on the water state data and bottom sediment data; it assesses the aging degree of each dredger based on the historical operating efficiency data; it obtains the allocation results of each dredger to each operating area based on the risk assessment results of navigation operations in each operating area and the aging degree assessment results of each dredger; and it conducts construction operations based on the allocation results of each dredger to each operating area. Dispatching dredgers with high aging degrees to low-risk operating areas can reduce accident risks, ensure operational safety, extend the service life of water operation equipment, optimize the operating efficiency of water operation equipment, improve resource utilization, and reduce the maintenance cost of water operation equipment.

[0060] like Figure 3 As shown, this embodiment also provides a data analysis-based water conservancy and river channel construction operation management system, which is implemented based on the above-mentioned data analysis-based water conservancy and river channel construction operation management method. Specifically, it includes an operation data acquisition module, an operation area risk assessment module, an equipment aging assessment module, and an operation area result allocation module. The operation data acquisition module is used to acquire water area state data, bottom sediment state data, and historical operation efficiency data of each dredger in each operation area. The operation area risk assessment module is used to assess the navigation operation risk in each operation area based on the water area state data and bottom sediment state data. The equipment aging assessment module is used to assess the aging degree of each dredger based on the historical operation efficiency data. The operation area result allocation module is used to obtain the operation area allocation results corresponding to each dredger based on the navigation operation risk assessment results and the aging degree assessment results of each dredger, and then carry out construction operations according to the operation area allocation results corresponding to each dredger.

[0061] The specific steps for implementing the corresponding functions of each unit module in the data analysis-based water conservancy and river channel construction operation management system of this application can be referred to the steps in the embodiments of the data analysis-based water conservancy and river channel construction operation management method above, and will not be repeated here.

[0062] This embodiment also provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0063] The processor executes the aforementioned data analysis-based water conservancy and river channel construction operation management method by calling the computer program stored in the memory.

[0064] The memory can be used to store instructions, programs, code, code sets, or instruction sets. The memory 310 may include a program storage area and a data storage area. The program storage area may store instructions for implementing an operating system, instructions for at least one function, and instructions for implementing the data analysis-based water conservancy and river channel construction operation management method provided in the above embodiments. The data storage area may store data involved in the data analysis-based water conservancy and river channel construction operation management method provided in the above embodiments.

[0065] The processor may include one or more processing cores. The processor executes instructions, programs, code sets, or instruction sets stored in memory, and calls data stored in memory to perform various functions and process data as described in this application. The processor may be at least one of an application-specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field-programmable gate array (FPGA), a central processing unit (CPU), a controller, a microcontroller, and a microprocessor. It is understood that, for different devices, the electronic devices used to implement the above-described processor functions may also be other types, and the embodiments of this application do not specifically limit this.

[0066] It may also include a communication bus, which can include a pathway for transmitting information between the aforementioned components. The communication bus can be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The communication bus can be divided into address bus, data bus, control bus, etc.

[0067] This embodiment also proposes a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the aforementioned data analysis-based water conservancy and river channel construction operation management method.

[0068] For example, computer-readable storage media can be read-only memory, random access memory, read-only optical disc, magnetic tape, floppy disk, and optical data storage devices.

[0069] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. A 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, all or part of the processes or functions according to the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, 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 and / or wireless network. A computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. Available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. Semiconductor media can be solid-state drives (SSDs).

[0070] The terms “comprising,” “including,” or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0071] The above description is merely a preferred embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the foregoing application concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions claimed in this application.

Claims

1. A data-driven water conservancy channel construction operation management method, characterized in that: include: S1. Obtain water condition data, bottom sediment condition data, and historical operating efficiency data of each dredger in each operating area; S2. Based on the water condition data and bottom sediment condition data of each operation area, conduct a risk assessment of navigation operations in each operation area. S2 includes the following specific steps: S21. Obtain the water operation risk assessment value for each operating area based on the bottom sediment density data and bottom sediment particle size data in each operating area. The specific steps of S21 are as follows: conduct water operation risk assessment for each operating area based on the bottom sediment density data and bottom sediment particle size data in each operating area. The calculation formula for the water operation risk assessment of the i-th operating area is: ,in, Here is the density data of the bottom sediment mud in the i-th working area. For water density data, This is a reference value for the specific gravity of the mud. This refers to the value where 90% of the sediment particle size values ​​in the i-th working area are greater than a certain value. The value is defined as the percentage of sediment particle sizes greater than 50% in the i-th working area. For reference particle size fluctuation values, The weighting of the bottom sediment mud density ratio, The weighting is based on the proportion of substrate particle size. S22. Obtain the risk assessment results of water operations in each work area, and obtain the risk assessment value of water operations in each work area from the risk assessment results of water operations in each work area. S23. Preset unit areas in each work area. Obtain the navigation operation risk assessment value for each work area based on the water operation risk assessment value, navigable water depth data, and obstacle density data. The specific steps of S23 are: Perform a navigation operation risk assessment for each work area based on the water operation risk assessment value, navigable water depth data, and obstacle density data. The calculation formula for the navigation operation risk assessment of the i-th work area is: Where i is the number corresponding to each work area, i can be any item from 1 to N, and r is the number corresponding to each unit area, r can be any item from 1 to A. Let be the risk assessment value for the water area operation in the i-th operation area. The maximum depth is the value within the r-th unit area of ​​the i-th work region. The minimum depth is the minimum value within the r-th unit area of ​​the i-th work region. For reference depth fluctuation values, 'a' represents the weight of the influence of the working area depth. Z represents the obstacle density data for the i-th work area, where Z is the set safe density. S3. Evaluate the aging degree of each dredging vessel based on its historical operating efficiency data. The specific steps of S3 are as follows: Evaluate the aging degree of each dredging vessel based on its historical operating efficiency data, wherein the calculation formula for the aging degree of the j-th dredging vessel is: Where j is the number corresponding to each dredging vessel, j can be any one of 1 to M, and k is the number of each historical operation period, k can be any one of 1 to q. For time decay weight, Let J be the operating efficiency of the dredging vessel during the k-th historical operating time period. Let J be the operating efficiency of the j-th dredger during the (k-1)-th historical operating time period. This serves as a reference value for efficiency fluctuations. S4. Based on the risk assessment results of navigation operations in the waters of each work area and the aging assessment results of each dredger, the allocation results of each work area corresponding to each dredger are obtained, and the construction operation is carried out according to the allocation results of each work area corresponding to each dredger.

2. The water conservancy river channel construction operation management method based on data analysis as described in claim 1, characterized in that, The specific steps of S4 are as follows: obtain the risk assessment results of navigation operations in each work area and the aging assessment results of each dredger; sort the risk assessment values ​​of navigation operations in each work area in ascending order and sort the aging assessment values ​​of each dredger in descending order; match each dredger corresponding to the aging assessment results of each dredger with each work area corresponding to the aging assessment results of each work area, and obtain the work area allocation results corresponding to each dredger in this way; and carry out construction operations according to the work area allocation results corresponding to each dredger.

3. A data-driven water conservancy and river channel construction operation management system, implemented based on the data-driven water conservancy and river channel construction operation management method according to any one of claims 1-2, characterized in that, Specifically, it includes an operation data acquisition module, an operation area risk assessment module, an equipment aging assessment module, and an operation area result allocation module. The operation data acquisition module is used to acquire water state data, bottom sediment state data, and historical operation efficiency data of each dredger in each operation area. The operation area risk assessment module is used to assess the risk of navigation operations in each operation area based on the water condition data and bottom sediment condition data of each operation area. The equipment aging assessment module is used to assess the aging of each dredging vessel based on its historical operating efficiency data. The operation area result allocation module is used to obtain the operation area allocation results corresponding to each dredger based on the risk assessment results of navigation operations in the waters of each operation area and the aging assessment results of each dredger, and to carry out construction operations based on the operation area allocation results corresponding to each dredger.

4. An electronic device, comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; The processor is characterized in that it executes the data analysis-based water conservancy and river channel construction operation management method as described in any one of claims 1-2 by calling a computer program stored in the memory.

5. A computer-readable storage medium, characterized in that, The system stores instructions that, when executed on a computer, cause the computer to perform the data analysis-based water conservancy and river channel construction operation management method as described in any one of claims 1-2.

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