Water conservancy construction project management system based on data analysis

Abstract

The invention relates to the technical field of construction management, in particular to a water conservancy construction project management system based on data analysis, and the system comprises a water flow monitoring module which collects water flow data in a construction area in real time through a sensor; the meteorological data acquisition module is used for acquiring surrounding future precipitation, performing correlation analysis on the future precipitation and the water flow data and predicting a future water level change trend; the construction progress management unit divides the construction progress into a plurality of construction stages, and the construction stages are uploaded by site construction managers in real time; the data analysis module is used for identifying the influence of the water flow change trend on the specific construction stage; and the self-adaptive water flow regulation module is used for formulating water flow management measures according to an analysis result of the correlation influence model. According to the method, visual quantitative indexes are provided for construction managers, and resource allocation and construction scheduling are optimized, so that the construction management efficiency is remarkably improved, and the occurrence probability of progress delay and safety accidents is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of construction management, and in particular to a water conservancy construction project management system based on data analysis. Background Art

[0002] Water conservancy construction projects usually involve complex hydrological conditions, such as river flow velocity, water level fluctuations and rainfall, which have a direct and significant impact on construction progress, resource allocation and construction safety. However, the existing water conservancy construction project management system still has the following technical bottlenecks in dynamically responding to water flow changes, meteorological changes and construction progress coordination:

[0003] Current water conservancy construction management mostly relies on traditional monitoring equipment to collect water flow and meteorological data. The data is scattered and lacks intelligent integration. Especially in complex construction areas, key parameters such as water level, flow velocity and flow cannot form a comprehensive and real-time dynamic monitoring network, making it difficult for managers to perceive sudden water flow changes and their potential impacts in a timely manner.

[0004] The specific impact of water flow changes on construction progress and construction stages is often overlooked. Currently, most systems separate water flow management from construction scheduling and lack a model that can quantify the dynamic impact of water flow changes on construction plans. This disconnect leads to construction delays and safety accident risks.

[0005] Traditional water flow management methods are usually based on static construction plans and lack flexibility and adaptability. When water flow changes dramatically (such as during floods or heavy rainfall), the drainage equipment or water flow regulation equipment of the existing system cannot be adjusted intelligently based on real-time monitoring data, and often requires manual intervention, which is time-consuming and inefficient, and may even cause greater safety hazards. Summary of the invention

[0006] The invention provides a water conservancy construction project management system based on data analysis.

[0007] Water conservancy construction project management system based on data analysis, including:

[0008] Water flow monitoring module: collects water flow data in the construction area in real time through sensors, including river flow rate, water flow, and water level changes;

[0009] Meteorological data acquisition module: By establishing a data interface with the meteorological monitoring center, it obtains the surrounding future precipitation, and correlates the future precipitation with the water flow data to predict the future water level change trend;

[0010] Construction progress monitoring module: establish a construction progress management unit, in which the construction progress is divided into multiple construction stages, which are uploaded in real time by on-site construction management personnel;

[0011] Data analysis module: establish the correlation and influence model between the water flow and water level change trend and the construction progress, and identify the impact of the water flow change trend on the specific construction stage;

[0012] Adaptive water flow regulation module: Based on the analysis results of the correlation impact model, water flow management measures are formulated. The measures include adjusting the water flow direction in the construction area and adjusting water flow management equipment, such as pumps and gates, to cope with sudden water flow changes and ensure a stable construction environment.

[0013] Optionally, the water flow monitoring module collects water flow data in the construction area in real time through multiple sensors and flow meters installed in the construction area. The sensors include a water level sensor, a flow rate sensor and a flow meter. The water level sensor is used to monitor real-time changes in water level, the flow rate sensor is used to collect river flow rate data in real time, and the flow meter is used to measure changes in river water flow.

[0014] Optionally, the data interface in the meteorological data acquisition module conducts two-way communication with the data platform of the meteorological monitoring center through a network connection to obtain precipitation forecast data for the next 24 to 72 hours; the meteorological data acquisition module correlates the acquired future precipitation data with the water flow data collected by the water flow monitoring module, combines the water flow change trend and the precipitation data in the meteorological forecast, and uses a prediction algorithm to calculate the future water level change trend, thereby providing a basis for water flow management and construction progress adjustment, and predicting the possible impact of water level changes in advance.

[0015] Optionally, the correlation analysis between precipitation and water flow is expressed as: Q(t)=α·P(t)+β, wherein Q(t) is the water flow (or flow velocity) at time t, P(t) is the precipitation at time t, α is the coefficient of the influence of precipitation on water flow, indicating the degree of influence of unit precipitation change on water flow, β is a constant term, indicating the water flow in the absence of precipitation, and the optimal values ​​of α and β can be obtained through regression analysis of historical data;

[0016] By obtaining the future precipitation data: P(t+1), P(t+2), …, P(t+n), where n represents the time step of future prediction, combined with the known water flow Q(t), a prediction algorithm is used to predict the water level change trend. The prediction algorithm is expressed as:

[0017] Among them, H(t+n) is the predicted water level at time t+n, γ is the coefficient of flow and water level change, which represents the impact of unit flow on water level. is the accumulation of water flow in the next n time steps.

[0018] Optionally, the construction progress monitoring module specifically includes:

[0019] Construction phase division: According to the overall plan of the construction project, the construction progress is divided into multiple construction phases. Each construction phase includes corresponding construction tasks, resource allocation and estimated completion time. The construction phases are divided according to construction sites (foundation construction, structure construction, decoration construction), construction contents (excavation, concrete pouring, equipment installation) or time nodes;

[0020] Progress management platform: The construction progress management unit uses an integrated digital platform, which supports construction management personnel to access construction progress information in real time through mobile terminals, tablets or computers;

[0021] Real-time data upload: Construction site managers upload the actual progress data of each construction stage in real time through the digital platform. The uploaded data includes the completion ratio, actual time, and details of completed tasks of the current construction stage.

[0022] The construction progress management unit generates a comparison report between the actual progress and the planned progress by analyzing the data uploaded in real time, and the report includes the progress deviation of each construction stage.

[0023] Optionally, the impact of the identified water flow change trend on a specific construction stage in the data analysis module includes the construction progress delay rate D s and construction safety risk index R s , D s represents the progress delay rate of construction stage s, R s Represents the safety risk index of construction stage s, establishes the water level change trend H(t+n) and the construction progress delay rate D s and construction safety risk index R s The associated impact model includes a schedule delay rate model and a construction safety risk index model. The schedule delay and safety risks of a specific construction stage are quantitatively analyzed through the dynamic impact of water level changes on the construction stage.

[0024] Optionally, the schedule delay rate model is expressed as: D s =g1(H(t+n),T p ,S c ), where H(t+n) is the predicted water level change trend, T p is the planned completion time of construction phase s, S c is the characteristic parameter set of construction stage s, g1 is the regression function obtained through model training, including:

[0025] Current task type (foundation excavation, concrete pouring);

[0026] Resource usage (machinery, equipment, manpower);

[0027] The urgency of the construction period (whether the stage task is urgent);

[0028] Based on the schedule delay rate model, the schedule delay rate D s Calculated as: Among them, T p is the planned completion time, T a is the actual completion time.

[0029] Optionally, the construction safety risk index model is expressed as: R s =g2(H(t+n),V s ), where V s is the risk sensitivity parameter of construction stage s, g2 is the classification function, obtained through training, and the construction safety risk index R is calculated based on the construction safety risk index model. s , quantify the impact of water level change trend on safety hazards during the construction phase, calculated as:

[0030] R s =α1·ΔH(t+n)+α2·V s , where α1 is the sensitivity coefficient of water level change to safety risk (the risk value increases with each 1m rise in water level), α2 is the sensitivity coefficient of risk characteristics during the construction phase to safety risk, and V s is the risk sensitivity parameter of the construction phase, including the task exposure level (such as whether personnel are required to go into the water for operation) and the equipment type (such as whether heavy equipment is used); according to the calculated R s , classify the safety risks during the construction phase:

[0031] R s ≤1: low risk;

[0032] 1 <R s ≤3: medium risk;

[0033] R s >3: High risk.

[0034] Optionally, the adaptive water flow regulation module is based on D s and R s Determine target priorities and classification decisions, the target priority determination includes:

[0035] If R s >3: Take safety measures to reduce the direct impact of water flow on the construction area;

[0036] If D s >30% and R s ≤3: With the goal of ensuring construction progress, priority should be given to reducing the resistance of the drainage system or optimizing the direction of water flow.

[0037] Optionally, the classification decision specifically includes:

[0038] D s ≤10%,R s ≤1, low impact: that is, the change in water flow has no obvious impact on the construction, and the current water flow management equipment operation status is maintained;

[0039] 10% <D s ≤30%,1 <R s ≤3, medium impact: the drainage system will be partially optimized or the water flow direction will be adjusted to reduce the potential impact;

[0040] D s >30% or R s >3. For serious impacts: comprehensively adjust the water flow direction in the construction area, adjust the water flow management equipment, and give priority to ensuring construction safety.

[0041] Beneficial effects of the present invention:

[0042] The present invention quantifies the specific impact of water level change trends on construction progress and safety risks by constructing a progress delay rate model and a construction safety risk index model. The progress delay rate model can dynamically calculate the time deviation of water level changes on the construction plan, and the construction safety risk index model performs a graded assessment of the risk sensitivity of construction tasks. This dual-model collaborative analysis method can not only provide construction managers with intuitive quantitative indicators, but also identify risk points in real time during the construction process, optimize resource allocation and construction scheduling, thereby significantly improving construction management efficiency and reducing the probability of progress delays and safety accidents.

[0043] The present invention combines the analysis results of the progress delay rate and the safety risk index through an adaptive water flow regulation module, and utilizes target priority analysis and classification decision-making intelligence to generate a dynamic water flow management strategy, including optimizing the drainage system, adjusting the water flow direction, and real-time regulation of water pumps, gates and other equipment. It can quickly respond to sudden changes in water flow, ensure the stability of the construction environment, and reduce construction delays and waste of resources.

[0044] The present invention forms a closed-loop management system from real-time monitoring to intelligent regulation by integrating a water flow monitoring module, a meteorological data acquisition module, a construction progress monitoring module and a data analysis module. The construction progress monitoring module performs fine division and dynamic management of the construction stages, and combines the correlation analysis of water flow monitoring and meteorological data to provide an accurate prediction basis for the construction plan. The data analysis module identifies the impact of water flow changes on the progress and safety of a specific construction stage through a correlation impact model, and provides reliable decision support for construction scheduling. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0046] Figure 1 This is a schematic diagram of the functional modules of a management system according to an embodiment of the present invention;

[0047] Figure 2 Schematic diagram of an association influence model according to an embodiment of the present invention. DETAILED DESCRIPTION

[0048] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. At the same time, it is explained here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments, and those skilled in the art may also adopt other alternatives to implement some known technologies; and the accompanying drawings are only for more specific description of the embodiments, and are not intended to specifically limit the present invention.

[0049] It should be noted that the references to "one embodiment", "an embodiment", "an exemplary embodiment", "some embodiments" and the like in the specification indicate that the embodiments described may include specific features, structures or characteristics, but not every embodiment may include the specific features, structures or characteristics. In addition, when a specific feature, structure or characteristic is described in conjunction with an embodiment, it should be within the knowledge of a person skilled in the art to implement such feature, structure or characteristic in conjunction with other embodiments (whether or not explicitly described).

[0050] In general, a term can be understood, at least in part, from its use in context. For example, depending, at least in part, on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending, at least in part, on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0051] like Figure 1-Figure 2 As shown, the water conservancy construction project management system based on data analysis includes:

[0052] Water flow monitoring module: collects water flow data in the construction area in real time through sensors, including river flow rate, water flow, and water level changes;

[0053] Meteorological data acquisition module: By establishing a data interface with the meteorological monitoring center, it obtains the surrounding future precipitation, and correlates the future precipitation with the water flow data to predict the future water level change trend;

[0054] Construction progress monitoring module: establish a construction progress management unit, in which the construction progress is divided into multiple construction stages, which are uploaded in real time by on-site construction management personnel;

[0055] Data analysis module: establish the correlation and influence model between the water flow and water level change trend and the construction progress, and identify the impact of the water flow change trend on the specific construction stage;

[0056] Adaptive water flow regulation module: Based on the analysis results of the correlation impact model, water flow management measures are formulated, including adjusting the water flow direction in the construction area and adjusting water flow management equipment (such as water pumps, gates, etc.) to cope with sudden water flow changes and ensure a stable construction environment.

[0057] The water flow monitoring module collects water flow data in the construction area in real time through multiple sensors and flow meters installed in the construction area. The sensors include water level sensors, flow velocity sensors and flow meters. The water level sensor is used to monitor the real-time changes of the water level, the flow velocity sensor is used to collect the river flow velocity data in real time, and the flow meter is used to measure the changes in the river water flow. The sensors and flow meters transmit the collected water flow data to the system data processing unit through wireless transmission for subsequent analysis and processing to support water flow management and dynamic adjustment of construction progress.

[0058] The data interface in the meteorological data acquisition module conducts two-way communication with the data platform of the meteorological monitoring center through a network connection to obtain precipitation forecast data for the next 24 to 72 hours; the meteorological data acquisition module correlates the acquired future precipitation data with the water flow data collected by the water flow monitoring module, combines the water flow change trend with the precipitation data in the meteorological forecast, and uses the prediction algorithm to calculate the future water level change trend, providing a basis for water flow management and construction progress adjustment, and predicting the possible impact of water level changes in advance.

[0059] The correlation analysis between precipitation and water flow is expressed as: Q(t) = α·P(t) + β, where Q(t) is the water flow (or flow velocity) at time t, P(t) is the precipitation at time t, α is the coefficient of the influence of precipitation on water flow, indicating the degree of influence of unit precipitation change on water flow, and β is a constant term, indicating the water flow in the absence of precipitation. Through the regression analysis of historical data, the optimal values ​​of α and β can be obtained;

[0060] By obtaining the future precipitation data: P(t+1), P(t+2), …, P(t+n), where n represents the time step of future prediction, combined with the known water flow Q(t), a prediction algorithm is used to predict the water level change trend. The prediction algorithm is expressed as:

[0061] Among them, H(t+n) is the predicted water level at time t+n, γ is the coefficient of flow and water level change, which represents the impact of unit flow on water level. is the accumulation of water flow in the next n time steps.

[0062] The construction progress monitoring module specifically includes:

[0063] Construction phase division: According to the overall plan of the construction project, the construction progress is divided into multiple construction phases. Each construction phase includes corresponding construction tasks, resource allocation and estimated completion time. The construction phases are divided according to the construction site (foundation construction, structure construction, decoration construction), construction content (excavation, concrete pouring, equipment installation) or time nodes;

[0064] Progress management platform: The construction progress management unit uses an integrated digital platform, which supports construction management personnel to access construction progress information in real time through mobile terminals, tablets or computers;

[0065] Real-time data upload: Construction site managers upload the actual progress data of each construction stage in real time through the digital platform. The uploaded data includes the completion ratio, actual time, and details of completed tasks of the current construction stage.

[0066] The construction progress management unit generates a comparison report between the actual progress and the planned progress by analyzing the real-time uploaded data. The report includes the progress deviation of each construction stage.

[0067] The impact of water flow change trends on specific construction stages in the data analysis module includes the construction progress delay rate D s and construction safety risk index R s , D s represents the progress delay rate of construction stage s, R s Represents the safety risk index of construction stage s, establishes the water level change trend H(t+n) and the construction progress delay rate D s and construction safety risk index R s The associated impact model includes a schedule delay rate model and a construction safety risk index model. Through the dynamic impact of water level changes on the construction stage, the schedule delay and safety risks of the specific construction stage are quantitatively analyzed.

[0068] The schedule delay rate model is expressed as: D s=g1(H(t+n),T p ,S c ), where H(t+n) is the predicted water level change trend, T p is the planned completion time of construction phase s, S c is the characteristic parameter set of construction stage s, g1 is the regression function obtained through model training, including:

[0069] Current task type (foundation excavation, concrete pouring);

[0070] Resource usage (machinery, equipment, manpower);

[0071] The urgency of the construction period (whether the stage task is urgent);

[0072] Based on the schedule delay rate model, the schedule delay rate D s Calculated as: Among them, T p is the planned completion time, T a is the actual completion time: T a =T p +k1·ΔH(t+n)+k2·S c , k1 is the sensitivity coefficient of water level change to time delay, which represents the impact of unit water level change on construction delay, and k2 is the impact coefficient of construction stage characteristics on delay.

[0073] The construction safety risk index model is expressed as: R s =g2(H(t+n),V s ), where V s is the risk sensitivity parameter of construction stage s, g2 is the classification function, obtained through training, and the construction safety risk index R is calculated based on the construction safety risk index model. s , quantify the impact of water level change trend on safety hazards during the construction phase, calculated as:

[0074] R s =α1·ΔH(t+n)+α2·V s , where α1 is the sensitivity coefficient of water level change to safety risk (the risk value increases with each 1m rise in water level), α2 is the sensitivity coefficient of risk characteristics during the construction phase to safety risk, and V s is the risk sensitivity parameter of the construction phase, including the task exposure level (such as whether personnel are required to go into the water for operation) and the equipment type (such as whether heavy equipment is used); according to the calculated R s , classify the safety risks during the construction phase:

[0075] R s ≤1: low risk;

[0076] 1 <Rs ≤3: medium risk;

[0077] R s >3: High risk.

[0078] The specific training and training model selection of g1 and g2 are as follows:

[0079] 1. Data preparation:

[0080] 1.1 Water flow and water level change data:

[0081] The actual measured water level change trend H(t+n);

[0082] Historical precipitation, flow and velocity data, linked to water level trends.

[0083] 1.2. Construction stage characteristic data:

[0084] The planned completion time of each construction phase is T p ;

[0085] Actual completion time T a ;

[0086] Stage characteristic parameter S c and the risk sensitivity parameter V s .

[0087] 1.3. Actual impact data:

[0088] The actual schedule delay rate for each construction stage

[0089] Actual safety risk level R during the construction phase s actual (Determined from on-site safety incident statistics or expert evaluation).

[0090] To train g1 and g2, the data needs to be labeled:

[0091] is the target variable of g1;

[0092] R s actual is the target variable of g2.

[0093] 2. Feature Engineering:

[0094] 2.1 Characteristics of the schedule delay rate model (g1):

[0095] Input features:

[0096] ΔH(t+n): predicted water level change;

[0097] Tp : Planned completion time;

[0098] S c : Characteristic parameters of the construction phase.

[0099] Target variable:

[0100] 2.2 Characteristics of the construction safety risk index model (g2):

[0101] Input features:

[0102] ΔH(t+n): predicted water level change;

[0103] V s : Risk sensitivity parameters during the construction phase.

[0104] Target variable: R s actual : Generated through security event statistics in historical data or expert evaluation.

[0105] 2.4, Feature preprocessing:

[0106] Normalize numerical features;

[0107] Encode categorical features (task type).

[0108] 3. Model selection:

[0109] The model type of the schedule delay rate model (g1) adopts a time series model to capture the characteristics of the time series; the loss function is: The construction safety risk index model (g2) adopts the support vector machine classification model;

[0110] The loss function is expressed as:

[0111]

[0112] 4. Model training:

[0113] Data partitioning: Divide the dataset into training set (70%), validation set (15%) and test set (15%);

[0114] Use grid search to optimize the model’s hyperparameters;

[0115] Training process: Train □1 and □2 separately, and iteratively optimize model parameters based on the loss function.

[0116] Validation and testing: The performance of the model is evaluated through the validation set, and the generalization ability of the model is evaluated using the test set.

[0117] Adaptive water flow regulation module based on Ds and R s Determine target priorities and classification decisions. Target prioritization includes:

[0118] If R s >3: Take safety measures to reduce the direct impact of water flow on the construction area;

[0119] If D s >30% and R s ≤3: With the goal of ensuring construction progress, priority should be given to reducing the resistance of the drainage system or optimizing the direction of water flow.

[0120] Classification decisions include:

[0121] D s ≤10%,R s ≤1, low impact: that is, the change in water flow has no obvious impact on the construction, and the current water flow management equipment operation status is maintained;

[0122] 10% <D s ≤30%,1 <R s ≤3, medium impact: the drainage system will be partially optimized or the water flow direction will be adjusted to reduce the potential impact;

[0123] D s >30% or R s >3. For serious impacts: comprehensively adjust the water flow direction in the construction area, adjust the water flow management equipment, and give priority to ensuring construction safety.

[0124] Classification decision elaboration applies to a tiered implementation strategy:

[0125] When the impact is low, there is no need to take large-scale actions, thus saving resources;

[0126] Limited optimization measures are taken when the impact is moderate;

[0127] In case of serious impact, initiate comprehensive adjustment and emergency measures.

[0128] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0129] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A water conservancy construction project management system based on data analysis, characterized in that: include: Water flow monitoring module: collects water flow data in the construction area in real time through sensors, including river flow rate, water flow, and water level changes; Meteorological data acquisition module: By establishing a data interface with the meteorological monitoring center, it obtains the surrounding future precipitation, and correlates the future precipitation with the water flow data to predict the future water level change trend; Construction progress monitoring module: establish a construction progress management unit, in which the construction progress is divided into multiple construction stages, which are uploaded in real time by on-site construction management personnel; Data analysis module: establish the correlation and influence model between the water flow and water level change trend and the construction progress, and identify the impact of the water flow change trend on the specific construction stage; Adaptive water flow regulation module: Based on the analysis results of the correlation impact model, water flow management measures are formulated, including adjusting the water flow direction in the construction area and adjusting the water flow management equipment to cope with sudden water flow changes to ensure a stable construction environment.

2. The water conservancy construction project management system based on data analysis according to claim 1 is characterized in that: The water flow monitoring module collects water flow data in the construction area in real time through multiple sensors and flow meters installed in the construction area. The sensors include a water level sensor, a flow rate sensor and a flow meter. The water level sensor is used to monitor the real-time changes of the water level, the flow rate sensor is used to collect the flow rate data of the river in real time, and the flow meter is used to measure the changes in the water flow of the river.

3. The water conservancy construction project management system based on data analysis according to claim 1 is characterized in that: The data interface in the meteorological data acquisition module communicates bidirectionally with the data platform of the meteorological monitoring center through a network connection to obtain the precipitation forecast data within the next 24 to 72 hours; The meteorological data acquisition module performs correlation analysis on the acquired future precipitation data and the water flow data collected by the water flow monitoring module, and calculates the future water level change trend using a prediction algorithm in combination with the water flow change trend and precipitation data in the meteorological forecast.

4. The water conservancy construction project management system based on data analysis according to claim 3 is characterized in that: The correlation analysis between precipitation and water flow is expressed as: Q(t)=α·P(t)+β, where Q(t) is the water flow at time t, P(t) is the precipitation at time t, α is the coefficient of the influence of precipitation on water flow, and β is a constant term, which represents the water flow in the absence of precipitation; By obtaining the future precipitation data: P(t+1), P(t+2), …, P(t+n), where n represents the time step of future prediction, combined with the known water flow Q(t), a prediction algorithm is used to predict the water level change trend. The prediction algorithm is expressed as: Among them, H(t+n) is the predicted water level at time t+n, γ is the coefficient of flow and water level change, which represents the impact of unit flow on water level. is the accumulation of water flow in the next n time steps.

5. The water conservancy construction project management system based on data analysis according to claim 1 is characterized in that: The construction progress monitoring module specifically includes: Construction phase division: According to the overall plan of the construction project, the construction progress is divided into multiple construction phases. Each construction phase includes corresponding construction tasks, resource allocation and estimated completion time. The construction phases are divided according to construction locations, construction contents or time nodes; Progress management platform: The construction progress management unit uses an integrated digital platform, which supports construction management personnel to access construction progress information in real time through mobile terminals, tablets or computers; Real-time data upload: Construction site managers upload the actual progress data of each construction stage in real time through the digital platform. The uploaded data includes the completion ratio, actual time, and details of completed tasks of the current construction stage. The construction progress management unit generates a comparison report between the actual progress and the planned progress by analyzing the data uploaded in real time, and the report includes the progress deviation of each construction stage.

6. The water conservancy construction project management system based on data analysis according to claim 4 is characterized in that: The impact of the identified water flow change trend on the specific construction stage in the data analysis module includes the construction progress delay rate D s and construction safety risk index R s , D s represents the progress delay rate of construction stage s, R s Represents the safety risk index of construction stage s, establishes the water level change trend H(t+n) and the construction progress delay rate D s and construction safety risk index R s The associated impact model includes a schedule delay rate model and a construction safety risk index model. The schedule delay and safety risks of a specific construction stage are quantitatively analyzed through the dynamic impact of water level changes on the construction stage.

7. The water conservancy construction project management system based on data analysis according to claim 6 is characterized in that: The schedule delay rate model is expressed as: D s =g1(H(t+n),T p ,S c ), where H(t+n) is the predicted water level change trend, T p is the planned completion time of construction phase s, S c is the characteristic parameter set of construction stage s, g1 is the regression function obtained through model training, including: Current task type; Resource usage; Urgency of construction period; Based on the schedule delay rate model, the schedule delay rate D s Calculated as: Among them, T p is the planned completion time, T a is the actual completion time.

8. The water conservancy construction project management system based on data analysis according to claim 7 is characterized in that: The construction safety risk index model is expressed as: R s =g2(H(t+n),V s ), where V s is the risk sensitivity parameter of construction stage s, g2 is the classification function, obtained through training, and the construction safety risk index R is calculated based on the construction safety risk index model. s , quantify the impact of water level change trend on safety hazards during the construction phase, calculated as: R s =α1·ΔH(t+n)+α2·V s , where α1 is the sensitivity coefficient of water level change to safety risk, α2 is the sensitivity coefficient of risk characteristics during the construction phase to safety risk, and V s is the risk sensitivity parameter of the construction phase, including task exposure and equipment type; according to the calculated R s , classify the safety risks during the construction phase: R s ≤1: low risk; 1 <R s ≤3: medium risk; R s >3: High risk.

9. The water conservancy construction project management system based on data analysis according to claim 8 is characterized in that: The adaptive water flow regulation module is based on D s and R s Determine target priorities and classification decisions, the target priority determination includes: If R s >3: Take safety measures to reduce the direct impact of water flow on the construction area; If D s >30% and R s ≤3: With the goal of ensuring construction progress, priority should be given to reducing the resistance of the drainage system or optimizing the direction of water flow.

10. The water conservancy construction project management system based on data analysis according to claim 9 is characterized in that: The classification decision specifically includes: D s ≤10%,R s ≤1, low impact: that is, the change in water flow has no obvious impact on the construction, and the current water flow management equipment operation status is maintained; 10% <D s ≤30%,1 <R s ≤3, medium impact: the drainage system will be partially optimized or the water flow direction will be adjusted to reduce the potential impact; D s >30% or R s >3. For serious impacts: comprehensively adjust the water flow direction in the construction area, adjust the water flow management equipment, and give priority to ensuring construction safety.

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