An intelligent construction management method and system for water conservancy projects

Abstract

The present invention belongs to the technical field of water conservancy engineering, and discloses a method and system for intelligent construction management of water conservancy projects; collecting a hydrological data set and an equipment data set, and performing preprocessing. The hydrological data set includes regional water level data, regional flow data, and regional rainfall data, and the equipment data set includes equipment supply data, labor supply data, and equipment maintenance data; analyzing the hydrological data set to obtain construction reference values, and classifying the construction reference values to obtain a construction classification result; analyzing the equipment data set to obtain construction efficiency reference values, and processing the construction classification result and the construction efficiency reference values to obtain a scheduling decision result; storing the hydrological data set, the equipment data set, the construction reference values, the construction classification result, and the construction efficiency reference values. Generally speaking, the present invention has the remarkable advantages of strong ability to assist in data analysis, good effect of assisting in decision-making, and high degree of information guarantee.

Description

Technical Field

[0001] The present invention relates to the technical field of water conservancy projects. More specifically, the present invention relates to an intelligent construction management method and system for water conservancy projects. Background Art

[0002] A water conservancy project generally refers to a project built to eliminate water disasters and develop and utilize water resources. According to its service objects, it is divided into flood control projects, farmland water conservancy projects, hydropower projects, waterway and port projects, water supply and drainage projects, environmental water conservancy projects, beach reclamation projects, etc. A water conservancy project that can serve multiple objectives such as flood control, water supply, irrigation, and power generation at the same time is called a comprehensive utilization water conservancy project. Water conservancy projects need to build different types of hydraulic structures such as dams, dikes, spillways, sluice gates, intakes, channels, aqueducts, raft channels, and fishways to achieve their objectives. Thanks to the rapid economic development in China in recent years, water conservancy projects have also grown rapidly with the rapid economic development. In the current trend of informatization and intelligent management, how to improve the efficiency, accuracy, and safety of large-scale projects such as water conservancy projects has become a major problem that managers need to face.

[0003] The patent with the application publication number CN118278614B discloses a digital intelligent construction management method and system for water conservancy projects. By distinguishing the geological conditions, different construction resources are allocated, thereby reducing the construction cost. By calculating the construction environment index, the construction area is evaluated to reduce the damage to land resources caused by construction. By calculating the land load, the construction plan is adjusted to ensure the safety of construction. By comparing the bearing index and the bearing threshold, the possibility of geological disasters and structural damage is reduced, and the construction quality is enhanced.

[0004] Although the above-mentioned digital intelligent construction management method and system for water conservancy projects provide certain reference for the foundation of water conservancy project construction to a certain extent through the analysis of the construction environment, the construction of water conservancy projects itself is an extremely large project. During the construction process, manual management is extremely prone to coordination problems among managers due to a large amount of various data, resulting in management accidents due to excessive management labor costs and time costs. Therefore, managers need to balance the environmental change factors and construction efficiency during the construction process, thereby reducing the construction risk.

[0005] In view of this, the present invention proposes an intelligent construction management method and system for water conservancy projects to solve the above problems. Summary of the Invention

[0006] In order to overcome the above-mentioned defects of the prior art and to achieve the above object, the present invention provides the following technical solutions:

[0007] A data acquisition module for collecting hydrological data sets and equipment data sets and performing preprocessing. The hydrological data sets include regional water level data, regional flow data, and regional rainfall data. The equipment data sets include equipment supply data, manual supply data, and equipment maintenance data;

[0008] Further, the methods for collecting hydrological data sets and equipment data sets include:

[0009] By installing a pressure water level gauge, collecting the average value of the water level height in a specified area to obtain regional water level data;

[0010] By installing a current meter, collecting the flow velocity of the water flow in a specified area to obtain regional flow data;

[0011] By installing a rain gauge, collecting the total real-time precipitation in a specified area to obtain regional rainfall data;

[0012] By docking with the construction management platform, collecting the total number of construction equipment and the total number of construction personnel in the project to obtain equipment supply data and manual supply data;

[0013] By docking with the equipment management platform, collecting the total types of equipment, the total number of equipment, the failure rate of each type of equipment, and the required maintenance time of each type of equipment, and substituting them into the calculation formula: To obtain equipment maintenance data, where Ai is the failure rate of the current type of equipment, Bi is the required maintenance time of the current type of equipment, and N is the total number of equipment;

[0014] The methods for performing preprocessing include data cleaning and data denoising;

[0015] A data processing module for analyzing the hydrological data set to obtain construction reference values and classifying the construction reference values to obtain construction classification results;

[0016] Further, the steps for analyzing the hydrological data set include:

[0017] Q1: By substituting into the calculation formula: Ba = Bb×C1 + Bc×C2 + Bd×C3 to obtain the real-time environment reference value, where Bb is the regional water level data, Bc is the regional flow data, Bd is the regional rainfall data, and C1, C2, and C3 are the weight factors corresponding to the regional water level data, regional flow data, and regional rainfall data respectively;

[0018] Q2: Collect M groups of historical environment reference values as a sample set, divide the sample set into a training set of 70%M, a test set of 15%M, and a validation set of 15%M. Based on the sample set, construct a feature vector, use keras to define the input layer, hidden layer, and output layer. The feature vector is used as the input layer data, and the construction reference value is used as the output layer data;

[0019] Q3: Build an original warning model based on the sample set, train the original warning model to obtain an initial warning model, test and verify the initial warning model using the test set and validation set, and output an initial warning model that meets the preset accuracy. The warning model is one of the logistic regression model, naive Bayes model, or support vector machine model.

[0020] Q4: Input the real-time environmental reference value into the initial warning model and output the construction reference value;

[0021] Furthermore, the methods for classifying the construction reference values include:

[0022] The construction condition threshold interval (W1, W2) is preset. When the construction reference value is less than W1, a small water volume signal is generated. When the construction reference value is greater than W1 and less than W2, a medium water volume signal is generated. When the construction reference value is greater than W2, a large water volume signal is generated.

[0023] The small water volume signal includes a group of fields indicating that the water volume in the specified area is relatively small, the medium water volume signal includes a group of fields indicating that the water volume in the specified area is average, and the large water volume signal includes a group of fields indicating that the water volume in the specified area is relatively large;

[0024] Pack small water volume signals, medium water volume signals and large water volume signals to obtain construction classification results;

[0025] Intelligent scheduling module, which is used to analyze the equipment data set to obtain the construction efficiency reference value, process the construction classification results and the construction efficiency reference value, and obtain the scheduling decision result;

[0026] Further, the device data set is analyzed by substituting into the calculation formula: The construction efficiency reference value is obtained, where Eb is the construction efficiency coefficient, Ec is the labor coordination coefficient, Ed is the labor supply data, and Ef is the optimal labor coefficient;

[0027] Furthermore, the methods for processing the construction classification results and the construction efficiency reference values include:

[0028] When the construction classification result is a small water volume signal, the optimal construction SMS is sent to the management personnel through the communication unit; when the construction classification result is a medium water volume signal, the ordinary construction SMS is sent to the management personnel through the communication unit; when the construction classification result is a large water volume signal, the poor construction SMS is sent to the management personnel through the communication unit;

[0029] The optimal construction message includes explaining that the amount of water in the designated area is small and the construction conditions are good, requiring management personnel to adjust the number of equipment used, the working hours of construction personnel and reduce the use of water resources based on the total construction time and construction efficiency reference value;

[0030] The normal construction text message includes instructions that the water storage in the specified area is medium and the construction conditions are affected, and requires the management personnel to set up drainage facilities, ensure the dryness in the construction area, and monitor the water level changes in the specified area in real time, and set the construction volume per preset time unit with reference to the construction efficiency reference value;

[0031] The poor construction text message includes instructions that the water storage in the specified area is high and the construction conditions are poor, and requires the management personnel to shorten the total construction duration, increase drainage facilities, and formulate an emergency plan according to the total construction duration and the construction efficiency reference value;

[0032] Package the optimal construction text message, the normal construction text message, and the poor construction text message to obtain the dispatching decision result;

[0033] The data storage module is used to store the hydrological data set, the equipment data set, the construction reference value, the construction classification result, and the construction efficiency reference value;

[0034] Furthermore, the steps of storage include:

[0035] R1: Based on the construction project time or the construction project number, package the hydrological data set, the equipment data set, the construction reference value, the construction classification result, and the construction efficiency reference value to obtain the construction information data set;

[0036] R2: Based on the blockchain storage technology, slice the construction information data set to obtain the construction information slice data;

[0037] R3: Based on the hash algorithm, calculate the construction information slice data to obtain the hash value of the construction information slice data;

[0038] R4: Copy the construction information slice data and the hash value, generate K redundant copies, and upload the construction information slice data, the hash value, and the redundant copies to the blockchain network for storage;

[0039] R5: Package the construction information slice data, the hash value, and the storage location, record it as the upload record, and record the upload record on the ledger of the blockchain;

[0040] Furthermore, S1: Collect the hydrological data set and the equipment data set and perform preprocessing. The hydrological data set includes regional water level data, regional flow data, and regional rainfall data. The equipment data set includes equipment supply data, labor supply data, and equipment maintenance data;

[0041] S2: Analyze the hydrological data set to obtain the construction reference value, and classify the construction reference value to obtain the construction classification result;

[0042] S3: Analyze the equipment dataset to obtain a construction efficiency reference value, process the construction classification result and the construction efficiency reference value to obtain a scheduling decision result;

[0043] S4: Store the hydrological dataset, equipment dataset, construction reference value, construction classification result and construction efficiency reference value.

[0044] The technical effects and advantages of a water conservancy project intelligent construction management method and system of the present invention:

[0045] Through the analysis of the hydrological dataset, the present invention obtains a construction reference value, which can effectively assist managers in intuitively and clearly understanding the environmental status of the construction area. Through the construction classification result, the water storage problem in the construction area can be intelligently presented, facilitating subsequent data analysis. Through the scheduling decision result, managers can be assisted to take corresponding decision-making means in the shortest time, greatly reducing construction risks. Through the blockchain storage of project construction-related information, the security of data can be effectively guaranteed, reducing the risk of information leakage. Generally speaking, the present invention has the remarkable advantages of strong data analysis assistance ability, good decision-making assistance effect and high information guarantee level. Description of the Drawings

[0046] Figure 1 It is a schematic diagram of a water conservancy project intelligent construction management system of the present invention;

[0047] Figure 2 It is a schematic diagram of a water conservancy project intelligent construction management method of the present invention. Detailed Embodiments

[0048] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0049] Embodiment 1

[0050] Please refer to Figure 1 As shown, a water conservancy project intelligent construction management system described in this embodiment includes:

[0051] A data acquisition module for collecting hydrological and equipment datasets and performing preprocessing. The hydrological dataset includes regional water level data, regional flow data and regional rainfall data, and the equipment dataset includes equipment supply data, labor supply data and equipment maintenance data;

[0052] Further, the methods for collecting hydrological and equipment datasets include:

[0053] By installing a pressure water level gauge, the average water level height in the specified area is collected to obtain the regional water level data;

[0054] By installing a current meter, the flow velocity of the water flow in the specified area is collected to obtain the regional flow data;

[0055] By installing a rain gauge, the total real-time precipitation in the specified area is collected to obtain the regional rainfall data;

[0056] By docking with the construction management platform, the total number of construction equipment and the total number of construction personnel of the project are collected respectively to obtain the equipment supply data and the labor supply data;

[0057] By docking with the equipment management platform, the total types of equipment, the total number of equipment, the failure rate of each type of equipment, and the required maintenance time of each type of equipment are collected and substituted into the calculation formula: The equipment maintenance data is obtained, where Ai is the failure rate of the current type of equipment, Bi is the required maintenance time of the current type of equipment, and N is the total number of equipment;

[0058] The ways of preprocessing include data cleaning and data denoising;

[0059] The data processing module is used to analyze the hydrological data set to obtain the construction reference value and classify the construction reference value to obtain the construction classification result;

[0060] Furthermore, the steps of analyzing the hydrological data set include:

[0061] Q1: The real-time environmental reference value is obtained by substituting into the calculation formula: Ba = Bb×C1 + Bc×C2 + Bd×C3, where Bb is the regional water level data, Bc is the regional flow data, Bd is the regional rainfall data, and C1, C2, and C3 are the weight factors corresponding to the regional water level data, regional flow data, and regional rainfall data respectively;

[0062] Q2: M groups of historical environmental reference values are collected as the sample set. The sample set is divided into a training set of 70%M, a test set of 15%M, and a validation set of 15%M. Based on the sample set, a feature vector is constructed, and the input layer, hidden layer, and output layer are defined using keras. The feature vector is used as the input layer data, and the construction reference value is used as the output layer data;

[0063] Q3: Based on the sample set, an original warning model is constructed, the original warning model is trained to obtain an initial warning model, and the initial warning model is tested and verified using the test set and the validation set, and an initial warning model that meets the preset accuracy is output. The warning model is one of the logistic regression model, the naive Bayes model, or the support vector machine model;

[0064] Q4: Input the real-time environmental reference value into the initial warning model and output the construction reference value;

[0065] Further, the methods for classifying the construction reference values include:

[0066] The construction condition threshold interval (W1, W2) is preset. When the construction reference value is less than W1, a small water volume signal is generated. When the construction reference value is greater than W1 and less than W2, a medium water volume signal is generated. When the construction reference value is greater than W2, a large water volume signal is generated.

[0067] The small water volume signal includes a group of fields indicating that the water volume in the specified area is relatively small, the medium water volume signal includes a group of fields indicating that the water volume in the specified area is average, and the large water volume signal includes a group of fields indicating that the water volume in the specified area is relatively large;

[0068] Pack small water volume signals, medium water volume signals and large water volume signals to obtain construction classification results;

[0069] Intelligent scheduling module, which is used to analyze the equipment data set to obtain the construction efficiency reference value, process the construction classification results and the construction efficiency reference value, and obtain the scheduling decision result;

[0070] Further, the device data set is analyzed by substituting the calculation formula: The construction efficiency reference value is obtained, where Eb is the construction efficiency coefficient, Ec is the labor coordination coefficient, Ed is the labor supply data, and Ef is the optimal labor coefficient;

[0071] It should be explained that the construction efficiency coefficient is the construction output of each device within the preset time unit; the labor coordination coefficient is the impact of the number of personnel on the construction output, that is, when the number of personnel is small, increasing the number of construction personnel can increase the construction output, and when the number of personnel is large, the construction output may be reduced due to the increase in the time cost of communication, coordination and management; the optimal labor coefficient is the number of personnel that achieves the highest construction output;

[0072] Furthermore, the methods for processing the construction classification results and the construction efficiency reference values include:

[0073] When the construction classification result is a small water volume signal, the optimal construction SMS is sent to the management personnel through the communication unit; when the construction classification result is a medium water volume signal, the ordinary construction SMS is sent to the management personnel through the communication unit; when the construction classification result is a large water volume signal, the poor construction SMS is sent to the management personnel through the communication unit;

[0074] The optimal construction text message includes instructions on the small water volume and good construction conditions in the specified area, and requires the management personnel to adjust the number of equipment used, the working hours of construction personnel, and reduce the water resource usage according to the total construction time and the reference value of construction efficiency;

[0075] The general construction text message includes instructions on the medium water volume and affected construction conditions in the specified area, and requires the management personnel to set up drainage facilities, ensure the dryness in the construction area, and monitor the water level changes in the specified area in real time, and set the construction volume per preset time unit according to the reference value of construction efficiency;

[0076] The poor construction text message includes instructions on the high water volume and poor construction conditions in the specified area, and requires the management personnel to shorten the total construction duration, increase drainage facilities, and formulate emergency plans according to the total construction duration and the reference value of construction efficiency;

[0077] Package the optimal construction text message, the general construction text message, and the poor construction text message to obtain the dispatching decision result;

[0078] The data storage module is used to store the hydrological data set, the equipment data set, the construction reference value, the construction classification result, and the construction efficiency reference value;

[0079] Furthermore, the steps of storage include:

[0080] R1: Based on the construction project time or construction project number, package the hydrological data set, the equipment data set, the construction reference value, the construction classification result, and the construction efficiency reference value to obtain the construction information data set;

[0081] R2: Based on the blockchain storage technology, slice the construction information data set to obtain the construction information slice data;

[0082] R3: Based on the hash algorithm, calculate the construction information slice data to obtain the hash value of the construction information slice data;

[0083] R4: Copy the construction information slice data and the hash value to generate K redundant copies, and upload the construction information slice data, the hash value, and the redundant copies to the blockchain network for storage;

[0084] R5: Package the construction information slice data, the hash value, and the storage location, record it as the upload record, and record the upload record on the ledger of the blockchain;

[0085] In this embodiment, the beneficial effects are as follows: By analyzing the hydrological data set, construction reference values can be obtained, which can effectively assist managers in intuitively and clearly understanding the environmental status of the construction area. Through the construction classification results, the water storage volume problem in the construction area can be intelligently presented, facilitating subsequent data analysis. Through the scheduling decision-making results, managers can be assisted in taking corresponding decision-making measures in the shortest time, greatly reducing construction risks. By storing the information related to project construction on the blockchain, the security of data can be effectively guaranteed, and the risk of information leakage can be reduced. Generally speaking, the present invention has the remarkable advantages of strong ability to assist in data analysis, good effect in assisting decision-making, and high degree of information guarantee.

[0086] Embodiment 2

[0087] Please refer to Figure 2 As shown in the figure, for the parts not described in detail in this embodiment, please refer to the description content of Embodiment 1. A method for intelligent construction management of water conservancy projects is provided, including: S1: Collect the hydrological data set and the equipment data set, and perform preprocessing. The hydrological data set includes regional water level data, regional flow data, and regional rainfall data. The equipment data set includes equipment supply data, labor supply data, and equipment maintenance data;

[0088] S2: Analyze the hydrological data set to obtain construction reference values, and classify the construction reference values to obtain construction classification results;

[0089] S3: Analyze the equipment data set to obtain construction efficiency reference values, and process the construction classification results and the construction efficiency reference values to obtain scheduling decision-making results;

[0090] S4: Store the hydrological data set, the equipment data set, the construction reference values, the construction classification results, and the construction efficiency reference values.

[0091] Embodiment 3

[0092] This embodiment publicly provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, it realizes the operation mode of the above-provided method for intelligent construction management of water conservancy projects.

[0093] Since the electronic device introduced in this embodiment is the electronic device adopted for implementing a method for intelligent construction management of a water conservancy project in the embodiments of the present application, based on the method for intelligent construction management of a water conservancy project introduced in the embodiments of the present application, those skilled in the art can understand the specific implementation manners and various variations of the electronic device in this embodiment. Therefore, the specific implementation of how this electronic device implements the method in the embodiments of the present application will not be described in detail herein. As long as those skilled in the art implement the electronic device adopted for a method for intelligent construction management of a water conservancy project in the embodiments of the present application, it falls within the scope of protection of the present application.

[0094] The above formulas are all dimensionless and take their numerical values for calculation. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain a formula that is closest to the actual situation. The preset parameters and threshold selection in the formulas are set by those skilled in the art according to the actual situation.

[0095] The above description is only a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. Any technical solutions falling within the concept of the present invention belong to the scope of protection of the present invention. It should be noted that for ordinary technical users in the technical field, several improvements and refinements made without departing from the principle of the present invention should also be regarded as within the scope of protection of the present invention.

Claims

1. An intelligent construction management system for water conservancy projects, characterized in that, include: The data collection module is used to collect hydrological data sets and equipment data sets and perform preprocessing. The hydrological data sets include regional water level data, regional flow data and regional rainfall data. The equipment data sets include equipment supply data, manual supply data and equipment maintenance data. The data processing module is used to analyze the hydrological data set to obtain the construction reference value, and classify the construction reference value to obtain the construction classification result; Intelligent scheduling module, which is used to analyze the equipment data set to obtain the construction efficiency reference value, process the construction classification results and the construction efficiency reference value, and obtain the scheduling decision result; A data storage module, used for storing hydrological data sets, equipment data sets, construction reference values, construction classification results and construction efficiency reference values; Ways to collect hydrological and equipment datasets include: By installing a flow meter, the flow velocity of water in a specified area is collected to obtain regional flow data; By installing rain gauges, the real-time total precipitation in a specified area is collected to obtain regional rainfall data; By connecting to the construction management platform, the total number of construction equipment and the total number of construction personnel of the project are collected to obtain equipment supply data and labor supply data; By docking with the device management platform, collect the total types of devices, the total number of devices, the failure rate of each type of device, and the required maintenance time of each type of device, and substitute them into the calculation formula: Obtain the device maintenance data, where Ai is the failure rate of the current type of device, Bi is the required maintenance time of the current type of device, and N is the total number of devices; The preprocessing methods include data cleaning and data denoising; The steps to analyze a hydrological dataset include: Q1: The real-time environmental reference value is obtained by substituting into the calculation formula: Ba = Bb × C1 + Bc × C2 + Bd × C3, where Bb is the regional water level data, Bc is the regional flow data, Bd is the regional rainfall data, and C1, C2 and C3 are the weight factors corresponding to the regional water level data, regional flow data and regional rainfall data respectively; Q2: Collect M groups of historical environmental reference values as sample sets, divide the sample sets into 70%M training sets, 15%M test sets and 15%M validation sets, construct feature vectors based on the sample sets, use keras to define the input layer, hidden layer and output layer, use feature vectors as input layer data, and use construction reference values as output layer data; Q3: Build an original warning model based on the sample set, train the original warning model to obtain an initial warning model, test and verify the initial warning model using the test set and validation set, and output an initial warning model that meets the preset accuracy. The warning model is one of the logistic regression model, naive Bayes model, or support vector machine model. Q4: Input the real-time environmental reference value into the initial warning model and output the construction reference value; Ways to categorize construction reference values include: The construction condition threshold interval (W1, W2) is preset. When the construction reference value is less than W1, a small water volume signal is generated. When the construction reference value is greater than W1 and less than W2, a medium water volume signal is generated. When the construction reference value is greater than W2, a large water volume signal is generated. The small water volume signal includes a group of fields indicating that the water volume in the specified area is relatively small, the medium water volume signal includes a group of fields indicating that the water volume in the specified area is average, and the large water volume signal includes a group of fields indicating that the water volume in the specified area is relatively large; Pack small water volume signals, medium water volume signals and large water volume signals to obtain construction classification results; The ways to analyze the device dataset include substituting into the calculation formula: Obtain the construction efficiency reference value, where Eb is the construction efficiency coefficient, Ec is the manual coordination coefficient, Ed is the manual supply data, and Ef is the optimal manual coefficient; The ways to process the construction classification results and the construction efficiency reference values include: When the construction classification result is a small water volume signal, send an optimal construction text message to the management personnel through the communication unit. When the construction classification result is a medium water volume signal, send a normal construction text message to the management personnel through the communication unit. When the construction classification result is a large water volume signal, send a poor construction text message to the management personnel through the communication unit; The optimal construction text message includes an explanation that the water storage volume in the specified area is small and the construction conditions are good, and requires the management personnel to adjust the number of equipment used, the working hours of construction personnel, and reduce the water resource usage according to the total construction time and the construction efficiency reference value; The normal construction text message includes an explanation that the water storage volume in the specified area is medium and the construction conditions are affected, and requires the management personnel to set up drainage facilities, ensure the dryness in the construction area, and monitor the change of the water level in the specified area in real time, and set the construction volume per preset time unit according to the construction efficiency reference value; The poor construction text message includes an explanation that the water storage volume in the specified area is high and the construction conditions are poor, and requires the management personnel to shorten the total construction duration, increase drainage facilities, and formulate an emergency plan according to the total construction duration and the construction efficiency reference value; Package the optimal construction text message, the normal construction text message, and the poor construction text message to obtain the dispatching decision result.

2. The intelligent construction management system for water conservancy projects according to claim 1, characterized in that The steps for storage include: R1: Based on the construction project time or the construction project number, package the hydrological data set, the equipment data set, the construction reference value, the construction classification result, and the construction efficiency reference value to obtain the construction information data set; R2: Based on the blockchain storage technology, slice the construction information data set to obtain the sliced construction information data; R3: Based on the hash algorithm, calculate the sliced construction information data to obtain the hash value of the sliced construction information data; R4: Copy the sliced construction information data and the hash value to generate K redundant copies, and upload the sliced construction information data, the hash value, and the redundant copies to the blockchain network for storage; R5: Package the sliced construction information data, the hash value, and the storage location, record it as the upload record, and record the upload record in the ledger of the blockchain.

3. An intelligent construction management method for water conservancy projects, implemented according to the intelligent construction management system for water conservancy projects described in any one of claims 1-2, characterized in that, S1: Collect the hydrological data set and the equipment data set and perform preprocessing. The hydrological data set includes regional water level data, regional flow data, and regional rainfall data. The equipment data set includes equipment supply data, labor supply data, and equipment maintenance data; S2: Analyze the hydrological data set to obtain the construction reference value, and classify the construction reference value to obtain the construction classification result; S3: Analyze the equipment data set to obtain the construction efficiency reference value, and process the construction classification result and the construction efficiency reference value to obtain the dispatching decision result; S4: Store the hydrological data set, the equipment data set, the construction reference value, the construction classification result, and the construction efficiency reference value.

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