Intelligent construction management method and system for hydraulic engineering

Abstract

The invention belongs to the technical field of water conservancy projects, and discloses a water conservancy project intelligent construction management method and system. A hydrological data set and an equipment data set are collected and preprocessed, the hydrological data set comprises regional water level data, regional flow data and regional rainfall data, and the equipment data set comprises equipment supply data, manual 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 a construction efficiency reference value, and processing the construction classification result and the construction efficiency reference value to obtain a scheduling decision result; the hydrological data set, the equipment data set, the construction reference value, the construction classification result and the construction efficiency reference value are stored, and generally, the method has the remarkable advantages of being high in auxiliary data analysis capacity, good in auxiliary decision making effect and high in information guarantee degree.

Description

Technical Field

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

[0002] Water conservancy projects usually refer to projects built to eliminate water disasters and develop and utilize water resources. They are divided into flood control projects, farmland water conservancy projects, hydropower projects, waterways and port projects, water supply and drainage projects, environmental water conservancy projects, and tidal flat reclamation projects according to their service objects. Water conservancy projects that can serve multiple goals such as flood control, water supply, irrigation, and power generation at the same time are called comprehensive utilization water conservancy projects. Water conservancy projects require the construction of dams, dikes, spillways, sluices, water inlets, channels, ferries, rafts, fishways and other different types of hydraulic structures to achieve their goals. Thanks to the rapid development of my country's economy in recent years, water conservancy projects have also grown rapidly with the rapid development of the economy. Under the current general direction of informatization and intelligent management, how to improve the efficiency, accuracy and safety of large projects such as water conservancy projects has become a major problem that managers need to face.

[0003] The patent application with the publication number CN118278614B discloses a digital intelligent construction management method and system for water conservancy projects. It reduces construction costs by distinguishing geological conditions and allocating different construction resources. It evaluates the construction area by calculating the construction environment index and reduces the damage to land resources caused by construction. It adjusts the construction plan by calculating the land load and ensures the safety of construction. It reduces the possibility of geological disasters and structural damage and enhances construction quality by comparing the bearing index and bearing threshold.

[0004] Although the above-mentioned digital intelligent construction management method and system for water conservancy projects can provide a certain reference for the foundation of water conservancy project construction to a certain extent through analysis of the construction environment, the construction of water conservancy projects itself is a huge project. During the construction process, manual management is very likely to have coordination problems among managers due to the large amount of various types of data, thereby causing management accidents due to excessive management labor costs and time costs. Therefore, managers are required to balance the environmental changes in the construction process and the construction efficiency, thereby reducing construction risks.

[0005] In view of this, the present invention proposes a water conservancy project intelligent construction management method and system 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-mentioned purpose, the present invention provides the following technical solutions:

[0007] 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.

[0008] Furthermore, the methods of collecting the hydrological data set and the equipment data set include:

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

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

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

[0012] 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;

[0013] By connecting to the equipment management platform, we collect 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 substitute them into the calculation formula: Obtain equipment maintenance data, where Ai is the failure rate of the current type of equipment, Bi is the required maintenance time for the current type of equipment, and N is the total number of equipment;

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

[0015] 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;

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

[0017] 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;

[0018] 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;

[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] Ordinary construction text messages include explanations that the water volume in the designated area is moderate and the construction conditions are affected, requiring management personnel to set up drainage facilities, ensure dryness in the construction area, monitor the changes in water levels in the designated area in real time, and set the construction volume in preset time units based on the construction efficiency reference value;

[0031] The poor construction text message includes a description of the high water volume and poor construction conditions in the designated area, requiring management personnel to shorten the total construction time, add drainage facilities and formulate emergency plans based on the total construction time and construction efficiency reference values;

[0032] Pack the best construction SMS, ordinary construction SMS and poor construction SMS to get the scheduling decision result;

[0033] A data storage module, used for storing hydrological data sets, equipment data sets, construction reference values, construction classification results and construction efficiency reference values;

[0034] Furthermore, the step of storing includes:

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

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

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

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

[0039] R5: Pack the construction information shard data, hash value and storage location as an upload record, and record the upload record on the blockchain ledger;

[0040] Further, S1: collecting hydrological data sets and equipment data sets and preprocessing them, the hydrological data sets include regional water level data, regional flow data and regional rainfall data, and the equipment data sets include equipment supply data, manual supply data and equipment maintenance data;

[0041] S2: Analyze the hydrological data set to obtain construction reference values, and classify the construction reference values ​​to obtain construction classification results;

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

[0043] S4: storing the hydrological data set, the equipment data set, the construction reference value, the construction classification result and the construction efficiency reference value.

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

[0045] The present invention obtains construction reference values ​​through analysis of hydrological data sets, which can effectively assist management personnel to intuitively and clearly understand the environmental status of the construction area. Through the construction classification results, the water storage problem in the construction area can be intelligently displayed, which is convenient for subsequent data analysis. Through the scheduling decision results, management personnel can be assisted to take corresponding decision-making measures in the shortest time, which greatly reduces construction risks. Through the blockchain storage of project construction-related information, data security can be effectively guaranteed and the risk of information leakage can be reduced. Generally speaking, the present invention has the significant advantages of strong auxiliary data analysis capabilities, good auxiliary decision-making effects and high information security. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 A schematic diagram of an intelligent construction management system for water conservancy projects according to the present invention;

[0047] Figure 2 It is a schematic diagram of an intelligent construction management method for water conservancy projects according to the present invention. DETAILED DESCRIPTION

[0048] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0049] Example 1

[0050] See also Figure 1 As shown, the intelligent construction management system for water conservancy projects described in this embodiment includes:

[0051] 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.

[0052] Furthermore, the methods for collecting hydrological data sets and equipment data sets include:

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

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

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

[0056] 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;

[0057] By connecting to the equipment management platform, we collect 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 substitute them into the calculation formula: Obtain equipment maintenance data, where Ai is the failure rate of the current type of equipment, Bi is the required maintenance time for the current type of equipment, and N is the total number of equipment;

[0058] The preprocessing methods 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] Further steps to analyze the hydrological dataset 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: 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;

[0063] 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.

[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 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;

[0075] Ordinary construction text messages include explanations that the water volume in the designated area is moderate and the construction conditions are affected, requiring management personnel to set up drainage facilities, ensure dryness in the construction area, monitor the changes in water levels in the designated area in real time, and set the construction volume in preset time units based on the construction efficiency reference value;

[0076] The poor construction text message includes a description of the high water volume and poor construction conditions in the designated area, requiring management personnel to shorten the total construction time, add drainage facilities and formulate emergency plans based on the total construction time and construction efficiency reference values;

[0077] Pack the best construction SMS, ordinary construction SMS and poor construction SMS to get the scheduling decision result;

[0078] A data storage module, used for storing hydrological data sets, equipment data sets, construction reference values, construction classification results and construction efficiency reference values;

[0079] Furthermore, the step of storing includes:

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

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

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

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

[0084] R5: Pack the construction information shard data, hash value and storage location as an upload record, and record the upload record on the blockchain ledger;

[0085] The beneficial effects of this embodiment are that by analyzing the hydrological data set, construction reference values ​​are obtained, which can effectively assist management personnel to intuitively and clearly understand the environmental status of the construction area. Through the construction classification results, the water storage problem in the construction area can be intelligently displayed, which is convenient for subsequent data analysis. Through the scheduling decision results, management personnel can be assisted to take corresponding decision-making measures in the shortest time, greatly reducing construction risks. By storing project construction-related information on the blockchain, data security can be effectively guaranteed and the risk of information leakage can be reduced. In general, the present invention has the significant advantages of strong auxiliary data analysis capabilities, good auxiliary decision-making effects and a high degree of information security.

[0086] Example 2

[0087] See also Figure 2 As shown, the part not described in detail in this embodiment is described in Example 1, and a method for intelligent construction management of a water conservancy project is provided, including: S1: collecting a hydrological data set and an equipment data set, and preprocessing them, 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, manual 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 the construction efficiency reference value, process the construction classification result and the construction efficiency reference value to obtain the scheduling decision result;

[0090] S4: storing the hydrological data set, the equipment data set, the construction reference value, the construction classification result and the construction efficiency reference value.

[0091] Example 3

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

[0093] Since the electronic device introduced in this embodiment is an electronic device used to implement a water conservancy project intelligent construction management method in the embodiment of this application, based on the water conservancy project intelligent construction management method introduced in the embodiment of this application, the technical personnel of this field can understand the specific implementation of the electronic device of this embodiment and its various variations, so how the electronic device implements the method in the embodiment of this application is not described in detail here. As long as the technical personnel of this field implement the electronic device used in the water conservancy project intelligent construction management method in the embodiment of this application, it belongs to the scope of protection of this application.

[0094] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and thresholds in the formula are set by technicians in this field according to actual conditions.

[0095] The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technical users in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope 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; The data storage module is used to store hydrological data sets, equipment data sets, construction reference values, construction classification results and construction efficiency reference values.

2. According to claim 1, the intelligent construction management system for water conservancy projects is characterized in that: 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 connecting to the equipment management platform, we collect 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 substitute them into the calculation formula: Obtain equipment maintenance data, where Ai is the failure rate of the current type of equipment, Bi is the required maintenance time for the current type of equipment, and N is the total number of equipment; The preprocessing methods include data cleaning and data denoising.

3. The intelligent construction management system for water conservancy projects according to claim 2 is characterized in that: 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.

4. The intelligent construction management system for water conservancy projects according to claim 3 is characterized in that: 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; Small water volume signals, medium water volume signals and large water volume signals are packaged to obtain construction classification results.

5. The intelligent construction management system for water conservancy projects according to claim 4 is characterized in that: The device data set can be 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.

6. The intelligent construction management system for water conservancy projects according to claim 5 is characterized in that: The methods for processing the construction classification results and the construction efficiency reference values ​​include: 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; 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; Ordinary construction text messages include explanations that the water volume in the designated area is moderate and the construction conditions are affected, requiring management personnel to set up drainage facilities, ensure dryness in the construction area, monitor the changes in water levels in the designated area in real time, and set the construction volume in preset time units based on the construction efficiency reference value; The poor construction text message includes a description of the high water volume and poor construction conditions in the designated area, requiring management personnel to shorten the total construction time, add drainage facilities and formulate emergency plans based on the total construction time and construction efficiency reference values; The optimal construction text messages, ordinary construction text messages and poor construction text messages are packaged to obtain the scheduling decision results.

7. The intelligent construction management system for water conservancy projects according to claim 6 is characterized in that: The step of storing includes: R1: Based on the construction project time or construction project number, the hydrological data set, equipment data set, construction reference value, construction classification result and construction efficiency reference value are packaged to obtain the construction information data set; R2: Based on blockchain storage technology, the construction information data set is sharded to obtain construction information shard data; R3: Based on the hash algorithm, calculate the construction information fragment data to obtain the hash value of the construction information fragment data; R4: Copy the construction information shard data and hash value, generate K redundant copies, and upload the construction information shard data, hash value and redundant copies to the blockchain network for storage; R5: Package the construction information shard data, hash value and storage location as an upload record, and record the upload record on the blockchain ledger.

8. A method for intelligent construction management of a water conservancy project, implemented according to an intelligent construction management system for a water conservancy project according to any one of claims 1 to 7, characterized in that: S1: 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. S2: Analyze the hydrological data set to obtain construction reference values, and classify the construction reference values ​​to obtain construction classification results; S3: Analyze the equipment data set to obtain the construction efficiency reference value, process the construction classification result and the construction efficiency reference value to obtain the scheduling decision result; S4: storing 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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