Nuclear power civil engineering and installation construction process management method and system based on AI

Abstract

The invention discloses a nuclear power civil engineering and installation construction process management method and system based on AI, and relates to the field of construction management. Comprising a data acquisition module and a data transmission network, the data acquisition module comprises multiple types of communication sensors arranged on a construction site, and the communication sensors are used for acquiring construction data; the central management base station receives the construction data collected by the sensor, processes the data and realizes monitoring and management of a construction site; the data storage module is used for storing the collected data; and the BIM three-dimensional model is established according to the collected data, and a construction progress prediction module is arranged in the BIM three-dimensional model and is used for predicting the construction progress. According to the method, the three-dimensional model is established based on the BIM technology, then the construction speed is calculated according to the actual construction progress in combination with experience, and finally the construction is predicted in combination with the multi-dimensional function, so that the construction process can be reliably planned and optimized, and the construction efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of construction management, and in particular to an AI-based nuclear power civil engineering and installation construction process management method and system. Background Art

[0002] Nuclear power projects can enrich the country's energy structure, reduce dependence on a single energy source, and thus enhance the security and stability of energy supply. Especially in areas with energy shortages or unstable energy supply, nuclear power has become an important means to ensure energy security. Therefore, construction management is particularly important during the installation and construction of nuclear power civil engineering.

[0003] After searching, the Chinese patent publication number CN116050693A discloses a nuclear power construction management system, including: engineering management module, material machinery and equipment management module, personnel management module, BIM management module, cost management module, decoration management module, quality management module and safety management module. The engineering management module is used to manage engineering construction; the material machinery and equipment management module is used to manage material machinery and equipment; the personnel and labor management module is used to manage personnel and labor; the BIM management module is used to manage the BIM model of the nuclear power construction project; the cost management module is used to manage the cost of nuclear power construction; the quality management module is used to manage the quality of nuclear power construction; the safety management module is used to manage the safety of nuclear power construction.

[0004] The above patent has the following deficiencies: it cannot predict the construction process, and thus cannot achieve pre-intervention, and has certain limitations.

[0005] To this end, the present invention proposes an AI-based nuclear power civil engineering and installation construction process management method and system. Summary of the invention

[0006] The purpose of the present invention is to solve the shortcomings of the prior art and to propose an AI-based nuclear power civil engineering and installation construction process management method and system.

[0007] In order to achieve the above object, the present invention adopts the following technical solutions:

[0008] An AI-based nuclear power civil engineering and installation construction process management system, including:

[0009] A data acquisition module and a data transmission network, which include multiple types of communication sensors arranged at the construction site, and use the communication sensors to collect construction data;

[0010] The central management base station receives the construction data collected by sensors and processes the data to monitor and manage the construction site;

[0011] A data storage module, which is used to store the collected data;

[0012] BIM three-dimensional model is established based on the collected data, and the BIM three-dimensional model has a built-in construction progress prediction module, which is used to predict the construction progress.

[0013] An AI-based nuclear power civil engineering and installation construction process management method includes the following steps:

[0014] S1: Sensor installation and data transmission network construction. Install multiple types of sensors at key nodes of building structures, operating locations of construction equipment, and activity areas of construction personnel. Use the best communication-based method to establish communication connections between sensors and between sensors and between sensors and the central management base station.

[0015] S2: Data reception and preprocessing, after the central management base station receives the data from the sensor, it classifies the data and then performs normalization processing;

[0016] S3: Data monitoring and alarm. The administrator sets the data threshold range collected by each sensor according to the location of the sensor and the actual working environment, and compares the real-time collected data. If it exceeds the threshold range, an alarm is issued;

[0017] S4: BIM three-dimensional model establishment and prediction: establish a three-dimensional building model of the entire construction process based on the collected data, and predict the construction progress based on the environmental data collected by the data acquisition module;

[0018] S5: Data storage, prediction of the data generated in steps S1-S4.

[0019] Preferably: in the step S1, the method based on optimal communication includes the following steps:

[0020] S11: Assign a unique identifier M to each sensor and obtain the communication capability P of the sensor M ;

[0021] S12: establishing a three-dimensional space model, and dividing the three-dimensional space model where the sensor is located into a plurality of non-overlapping three-dimensional space regions V;

[0022] S13: In each area V, the optimal communication sensor is calculated, and the remaining sensor data in the area V is transmitted to the optimal communication sensor, and then the optimal communication sensor packages the data and sends it to the central management base station.

[0023] Preferably: in the step S13, the method for calculating the optimal communication sensor includes the following steps:

[0024] S131: Calculate the communication distance L between the sensor and the central management base station and the air signal loss rate f according to the established three-dimensional model;

[0025] S132: Obtaining the thickness D of the obstacle for communication transmission and the signal loss rate q through the obstacle according to the three-dimensional model;

[0026] S133: Calculate the total signal loss rate G according to the formula G=D*q+(LD)f;

[0027] S134: According to the formula Calculate the priority Z of each vehicle, k1 and k2 are G and P respectively M The weights are preset by the administrator.

[0028] Preferably: the step S4 comprises the following steps:

[0029] S41: Based on the data collected by the sensors and combined with surveying and mapping technology, a 3D BIM model of the entire nuclear power construction site is established, and key construction nodes of the nuclear power construction site are determined;

[0030] S42: Determine the construction speed using an algorithm based on multidimensional data association;

[0031] S43: Perform construction simulation based on the construction speed and established construction process, and edit the construction progress percentage and time consumption when reaching each key construction node, and then make a construction progress forecast.

[0032] Preferably: the step S42 includes the following steps:

[0033] S421: Based on past construction experience, a multi-dimensional correlation function model V=f(A, B, C, D, E, F) of the construction speed V with respect to temperature A, humidity B, rainfall C, wind speed D, wind direction E, and number of construction personnel F is established;

[0034] S422: Estimate the construction speed for each time period based on the weather forecast and the number of construction workers.

[0035] Preferably: in the step S43, the construction progress prediction includes the following steps:

[0036] S431: During the construction process, determine the estimated time t1 and the actual construction time t2 of each construction node;

[0037] S432: Determine the construction node to be predicted and the construction volume of the predicted construction node from the current construction status;

[0038] S433: The construction speed is predicted based on the weather forecast and the number of construction workers, and then the progress is predicted based on the construction volume to determine the predicted time.

[0039] Preferably: in the step S433, the time prediction formula for progress prediction is: Where Q is the construction volume, V is the construction speed, k i is the ratio of the actual construction time to the estimated construction time of the previous construction node from the current construction progress. i k i The weight coefficient of .

[0040] Preferably: in the step S33,

[0041] Preferably: in the step S33,

[0042] The beneficial effects of the present invention are:

[0043] 1. The present invention establishes a three-dimensional model based on BIM technology, then calculates the construction speed according to the actual construction progress combined with experience, and finally predicts the construction in combination with multidimensional functions, so as to reliably plan and optimize the construction process and increase construction efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 This is a flow chart of an AI-based nuclear power civil engineering and installation construction process management method proposed by the present invention. DETAILED DESCRIPTION

[0045] The technical solution of the present invention is further described in detail below in conjunction with specific implementation methods.

[0046] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", and "set" should be understood in a broad sense, for example, they can be fixedly connected or set, or detachably connected or set, or integrally connected or set. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0047] Embodiment 1:

[0048] An AI-based nuclear power civil engineering and installation construction process management system, which includes:

[0049] A data acquisition module and a data transmission network, which include multiple types of communication sensors arranged at the construction site, and use the communication sensors to collect construction data;

[0050] The central management base station receives the construction data collected by sensors and processes the data to monitor and manage the construction site;

[0051] A data storage module, which is used to store the collected data;

[0052] BIM three-dimensional model is established based on the collected data, and the BIM three-dimensional model has a built-in construction progress prediction module, which is used to predict the construction progress.

[0053] Embodiment 2:

[0054] An AI-based nuclear power civil engineering and installation construction process management method includes the following steps:

[0055] S1: Sensor installation and data transmission network construction. Install multiple types of sensors at key nodes of building structures, operating locations of construction equipment, and activity areas of construction personnel. Use the best communication-based method to establish communication connections between sensors and between sensors and between sensors and the central management base station.

[0056] S2: Data reception and preprocessing, after the central management base station receives the data from the sensor, it classifies the data and then performs normalization processing;

[0057] S3: Data monitoring and alarm. The administrator sets the data threshold range collected by each sensor according to the location of the sensor and the actual working environment, and compares the real-time collected data. If it exceeds the threshold range, an alarm is issued;

[0058] S4: BIM three-dimensional model establishment and prediction: establish a three-dimensional building model of the entire construction process based on the collected data, and predict the construction progress based on the environmental data collected by the data acquisition module;

[0059] S5: Data storage, prediction of the data generated in steps S1-S4.

[0060] In the step S1, the method based on optimal communication includes the following steps:

[0061] S11: Assign a unique identifier M to each sensor and obtain the communication capability P of the sensor M ;

[0062] S12: establishing a three-dimensional space model, and dividing the three-dimensional space model where the sensor is located into a plurality of non-overlapping three-dimensional space regions V;

[0063] S13: In each area V, the optimal communication sensor is calculated, and the remaining sensor data in the area V is transmitted to the optimal communication sensor, and then the optimal communication sensor packages the data and sends it to the central management base station.

[0064] In the step S13, the method for calculating the optimal communication sensor includes the following steps:

[0065] S131: Calculate the communication distance L between the sensor and the central management base station and the air signal loss rate f according to the established three-dimensional model;

[0066] S132: Obtaining the thickness D of the obstacle for communication transmission and the signal loss rate q through the obstacle according to the three-dimensional model;

[0067] S133: Calculate the total signal loss rate G according to the formula G=D*q+(LD)f;

[0068] S134: According to the formula Calculate the priority Z of each vehicle, k1 and k2 are G and P respectively M The weights are preset by the administrator.

[0069] The step S4 comprises the following steps:

[0070] S41: Based on the data collected by the sensors and combined with surveying and mapping technology, a 3D BIM model of the entire nuclear power construction site is established, and key construction nodes of the nuclear power construction site are determined;

[0071] S42: Determine the construction speed using an algorithm based on multidimensional data association;

[0072] S43: Perform construction simulation based on the construction speed and established construction process, and edit the construction progress percentage and time consumption when reaching each key construction node, and then make a construction progress forecast.

[0073] The step S42 includes the following steps:

[0074] S421: Based on past construction experience, a multi-dimensional correlation function model V=f(A, B, C, D, E, F) of the construction speed V with respect to temperature A, humidity B, rainfall C, wind speed D, wind direction E, and number of construction personnel F is established;

[0075] S422: Estimate the construction speed for each time period based on the weather forecast and the number of construction workers.

[0076] In the step S43, the construction progress prediction includes the following steps:

[0077] S431: During the construction process, determine the estimated time t1 and the actual construction time t2 of each construction node;

[0078] S432: Determine the construction node to be predicted and the construction volume of the predicted construction node from the current construction status;

[0079] S433: The construction speed is predicted based on the weather forecast and the number of construction workers, and then the progress is predicted based on the construction volume to determine the predicted time.

[0080] In the step S433, the time prediction formula for progress prediction is: Where Q is the construction volume, V is the construction speed, k i is the ratio of the actual construction time to the estimated construction time of the previous construction node from the current construction progress. i k i The weight coefficient of .

[0081] In the step S33,

[0082] Embodiment 3:

[0083] An AI-based nuclear power civil engineering and installation construction process management method includes the following steps:

[0084] S1: Sensor installation and data transmission network construction. Install multiple types of sensors at key nodes of building structures, operating locations of construction equipment, and activity areas of construction personnel. Use the best communication-based method to establish communication connections between sensors and between sensors and between sensors and the central management base station.

[0085] S2: Data reception and preprocessing, after the central management base station receives the data from the sensor, it classifies the data and then performs normalization processing;

[0086] S3: Data monitoring and alarm. The administrator sets the data threshold range collected by each sensor according to the location of the sensor and the actual working environment, and compares the real-time collected data. If it exceeds the threshold range, an alarm is issued;

[0087] S4: BIM three-dimensional model establishment and prediction: establish a three-dimensional building model of the entire construction process based on the collected data, and predict the construction progress based on the environmental data collected by the data acquisition module;

[0088] S5: Data storage, prediction of the data generated in steps S1-S4.

[0089] In the step S1, the method based on optimal communication includes the following steps:

[0090] S11: Assign a unique identifier M to each sensor and obtain the communication capability P of the sensor M ;

[0091] S12: establishing a three-dimensional space model, and dividing the three-dimensional space model where the sensor is located into a plurality of non-overlapping three-dimensional space regions V;

[0092] S13: In each area V, the optimal communication sensor is calculated, and the remaining sensor data in the area V is transmitted to the optimal communication sensor, and then the optimal communication sensor packages the data and sends it to the central management base station.

[0093] In the step S13, the method for calculating the optimal communication sensor includes the following steps:

[0094] S131: Calculate the communication distance L between the sensor and the central management base station and the air signal loss rate f according to the established three-dimensional model;

[0095] S132: Obtaining the thickness D of the obstacle for communication transmission and the signal loss rate q through the obstacle according to the three-dimensional model;

[0096] S133: Calculate the total signal loss rate G according to the formula G=D*q+(LD)f;

[0097] S134: According to the formula Calculate the priority Z of each vehicle, k1 and k2 are G and P respectively M The weights are preset by the administrator.

[0098] The step S4 comprises the following steps:

[0099] S41: Based on the data collected by the sensors and combined with surveying and mapping technology, a 3D BIM model of the entire nuclear power construction site is established, and key construction nodes of the nuclear power construction site are determined;

[0100] S42: Determine the construction speed using an algorithm based on multidimensional data association;

[0101] S43: Perform construction simulation based on the construction speed and established construction process, and edit the construction progress percentage and time consumption when reaching each key construction node, and then make a construction progress forecast.

[0102] The step S42 includes the following steps:

[0103] S421: Based on past construction experience, a multi-dimensional correlation function model V=f(A, B, C, D, E, F) of the construction speed V with respect to temperature A, humidity B, rainfall C, wind speed D, wind direction E, and number of construction personnel F is established;

[0104] S422: Estimate the construction speed for each time period based on the weather forecast and the number of construction workers.

[0105] In the step S43, the construction progress prediction includes the following steps:

[0106] S431: During the construction process, determine the estimated time t1 and the actual construction time t2 of each construction node;

[0107] S432: Determine the construction node to be predicted and the construction volume of the predicted construction node from the current construction status;

[0108] S433: The construction speed is predicted based on the weather forecast and the number of construction workers, and then the progress is predicted based on the construction volume to determine the predicted time.

[0109] In the step S433, the time prediction formula for progress prediction is: Where Q is the construction volume, V is the construction speed, k i is the ratio of the actual construction time to the estimated construction time of the previous construction node from the current construction progress. i k i The weight coefficient of .

[0110] In the step S33,

[0111] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. An AI-based nuclear power civil engineering and installation construction process management system, characterized in that: include: A data acquisition module and a data transmission network, which include multiple types of communication sensors arranged at the construction site, and use the communication sensors to collect construction data; The central management base station receives the construction data collected by sensors and processes the data to monitor and manage the construction site; A data storage module, which is used to store the collected data; BIM three-dimensional model is established based on the collected data, and the BIM three-dimensional model has a built-in construction progress prediction module, which is used to predict the construction progress.

2. A method for managing the process of nuclear power civil engineering and installation construction based on AI, which is the method for implementing the management system of the process of nuclear power civil engineering and installation construction based on AI according to claim 1, characterized in that: The following steps are involved: S1: Sensor installation and data transmission network construction. Install multiple types of sensors at key nodes of building structures, operating locations of construction equipment, and activity areas of construction personnel. Use the best communication-based method to establish communication connections between sensors and between sensors and between sensors and the central management base station. S2: Data reception and preprocessing, after the central management base station receives the data from the sensor, it classifies the data and then performs normalization processing; S3: Data monitoring and alarm. The administrator sets the data threshold range collected by each sensor according to the location of the sensor and the actual working environment, and compares the real-time collected data. If it exceeds the threshold range, an alarm is issued; S4: BIM three-dimensional model establishment and prediction: establish a three-dimensional building model of the entire construction process based on the collected data, and predict the construction progress based on the environmental data collected by the data acquisition module; S5: Data storage, prediction of the data generated in steps S1-S4.

3. According to claim 2, a method for managing the nuclear power civil engineering and installation process based on AI is characterized in that: In the step S1, the method based on optimal communication includes the following steps: S11: Assign a unique identifier M to each sensor and obtain the communication capability P of the sensor M ; S12: establishing a three-dimensional space model, and dividing the three-dimensional space model where the sensor is located into a plurality of non-overlapping three-dimensional space regions V; S13: In each area V, the optimal communication sensor is calculated, and the remaining sensor data in the area V is transmitted to the optimal communication sensor, and then the optimal communication sensor packages the data and sends it to the central management base station.

4. The AI-based nuclear power civil engineering and installation construction process management method according to claim 3 is characterized in that: In the step S13, the method for calculating the optimal communication sensor includes the following steps: S131: Calculate the communication distance L between the sensor and the central management base station and the air signal loss rate f according to the established three-dimensional model; S132: Obtaining the thickness D of the obstacle for communication transmission and the signal loss rate q through the obstacle according to the three-dimensional model; S133: Calculate the total signal loss rate G according to the formula G=D*q+(LD)f; S134: According to the formula Calculate the priority Z of each vehicle, k1 and k2 are G and P respectively M The weights are preset by the administrator.

5. The AI-based nuclear power civil engineering and installation construction process management method according to claim 2 is characterized in that: The step S4 comprises the following steps: S41: Based on the data collected by the sensors and combined with surveying and mapping technology, a 3D BIM model of the entire nuclear power construction site is established, and key construction nodes of the nuclear power construction site are determined; S42: Determine the construction speed using an algorithm based on multidimensional data association; S43: Perform construction simulation based on the construction speed and established construction process, and edit the construction progress percentage and time consumption when reaching each key construction node, and then make a construction progress forecast.

6. The AI-based nuclear power civil engineering and installation construction process management method according to claim 5 is characterized in that: The step S42 includes the following steps: S421: Based on past construction experience, a multi-dimensional correlation function model V=f(A, B, C, D, E, F) of the construction speed V with respect to temperature A, humidity B, rainfall C, wind speed D, wind direction E, and number of construction personnel F is established; S422: Estimate the construction speed for each time period based on the weather forecast and the number of construction workers.

7. The AI-based nuclear power civil engineering and installation construction process management method according to claim 5 is characterized in that: In the step S43, the construction progress prediction includes the following steps: S431: During the construction process, determine the estimated time t1 and the actual construction time t2 of each construction node; S432: Determine the construction node to be predicted and the construction volume of the predicted construction node from the current construction status; S433: The construction speed is predicted based on the weather forecast and the number of construction workers, and then the progress is predicted based on the construction volume to determine the predicted time.

8. The AI-based nuclear power civil engineering and installation construction process management method according to claim 7 is characterized in that: In the step S433, the time prediction formula for progress prediction is: Where Q is the construction volume, V is the construction speed, k i is the ratio of the actual construction time to the estimated construction time of the previous construction node from the current construction progress. i k i The weight coefficient of .

9. The AI-based nuclear power civil engineering and installation construction process management method according to claim 8 is characterized in that: In the step S33, 10. The AI-based nuclear power civil engineering and installation construction process management method according to claim 8 is characterized in that: In the step S33,

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