Subway electromechanical installation environment-friendly regulation and control system capable of efficiently utilizing resources

Abstract

The invention discloses a subway electromechanical installation environment-friendly regulation and control system with efficient resource utilization, and relates to the technical field of subway electromechanical systems, and the technical scheme comprises the following steps: integrating each professional building information model through a digital twinborn building module, and injecting physical rules and behavior logic to form a dynamic simulation virtual model; space conflict detection and four-dimensional construction simulation optimization are carried out by using an installation simulation and collaborative design module; synchronizing real-time monitoring data to the virtual model through a multi-source data synchronization and fusion module; and the artificial intelligence optimization control module executes model prediction control and real-time feedback correction based on the updated model to generate an equipment control instruction. According to the method, the problems of resource waste, low construction efficiency and inaccurate operation energy consumption caused by disjunction of design, construction and operation stages in the prior art are solved, and efficient resource utilization, construction process optimization and accurate energy-saving and environment-friendly regulation and control of the operation stage in the whole life cycle from construction to operation are realized.

Description

Technical Field

[0001] This invention relates to the field of metro electromechanical system technology, specifically to an efficient resource utilization metro electromechanical installation environmental control system. Background Technology

[0002] Currently, the field of subway electromechanical installation and control generally faces the problem of disconnect between the design, construction, and operation stages. During the design phase, different disciplines typically use independent Building Information Models (BIMs) for their designs, lacking a unified data integration platform. This information silo phenomenon makes it difficult to detect spatial conflicts and logical inconsistencies between different disciplines in the early stages, often only revealing themselves during the construction phase. This results in numerous design changes and rework, increasing construction costs and leading to waste of materials and energy.

[0003] During the construction and installation phase, traditional schedule management relies heavily on two-dimensional drawings and Gantt charts, lacking effective integration with three-dimensional models. This makes it difficult to simulate and optimize dynamic conflicts in complex scenarios such as construction sequence, hoisting paths for large equipment, and cross-operations between different professional teams. The consequences include frequent issues such as improper work sequence coordination, machinery waiting, and idle personnel on construction sites, which not only slows down the project schedule but also generates significant unnecessary energy consumption and carbon emissions during construction.

[0004] Once subway environmental control systems enter the operational phase, they often employ relatively delayed feedback mechanisms. These systems typically rely on setting fixed thresholds or simple timed strategies to regulate equipment such as ventilation and air conditioning, failing to proactively and adaptively adjust to real-time changes in passenger flow and environmental parameters. This passive response mode struggles to cope with environmental load fluctuations caused by short-term, dramatic changes in passenger flow within subway stations. It can easily lead to overcooling or heating in some areas, while environmental quality in other areas fails to meet standards, resulting in low energy efficiency and hindering the achievement of refined energy conservation and environmental protection goals. Summary of the Invention

[0005] The purpose of this invention is to provide a highly efficient resource utilization environmental control system for subway electromechanical installation. Its core lies in constructing a virtual model that integrates information from various disciplines and possesses dynamic simulation capabilities. This model spans the entire lifecycle of design, construction, and operation. During the design and construction phases, the system optimizes the installation process through four-dimensional simulation, avoiding conflicts and waste from the outset. During the operation phase, the system utilizes real-time data to drive model predictive control, achieving precise and forward-looking control of electromechanical equipment. This integrates traditionally isolated phases into a continuous closed loop, realizing efficient resource utilization throughout the entire process from construction to operation. By pre-verifying and optimizing in a virtual environment, construction rework and energy waste are significantly reduced. Simultaneously, precise control during the operation phase significantly reduces energy consumption and improves environmental comfort, ultimately achieving sustainable environmental goals and solving the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A highly efficient resource-utilizing environmental control system for subway electromechanical installation includes:

[0008] The digital twin building module is used to integrate building information models from various disciplines and inject physical rules and behavioral logic to form a virtual model with dynamic simulation capabilities.

[0009] Install the simulation and collaborative design module, connect it with the digital twin building module, and use the virtual model for spatial conflict detection, automatic route optimization, computational fluid dynamics simulation, and four-dimensional construction process simulation optimization;

[0010] The multi-source data synchronization and fusion module, connected to the digital twin construction module, is used to receive real-time monitoring data through the edge computing gateway and synchronize the cleaned and aligned data to the virtual model to keep its state updated.

[0011] The artificial intelligence optimization control module is connected to the multi-source data synchronization and fusion module and the digital twin construction module. It is used to perform model predictive control and real-time feedback correction based on the updated virtual model and generate equipment control commands.

[0012] Preferably, the process of injecting physical rules and behavioral logic in the digital twin construction module includes:

[0013] Assign mathematical models of performance curves based on physical laws to air conditioning units, fans, chillers, water pumps, and power equipment;

[0014] Establish quantitative relationships between operating parameters such as air volume, air pressure, water supply, water delivery rate, power supply, and power.

[0015] The material, thermal conductivity, and roughness physical properties of the pipeline system are labeled, and the performance curve mathematical model is used to simulate the operating characteristics of real equipment in a virtual environment. The physical properties lay the foundation for subsequent thermal simulation calculations, thereby enabling the virtual model to dynamically respond to changes in physical laws.

[0016] Preferably, the process of the installation simulation and collaborative design module for four-dimensional construction process simulation and optimization includes:

[0017] The construction schedule is broken down into a series of logically related micro-tasks. Each micro-task defines its duration, required personnel, machinery and equipment, and material resources, and is associated with the corresponding model components in the virtual model. This association allows the construction schedule to be accurately mapped and visualized in the three-dimensional spatial model.

[0018] Preferably, the installation simulation and collaborative design module also constructs a virtual construction timeline, automatically calculates the optimal construction sequence path based on the logical relationship between micro-tasks, and drives the model components in the virtual model to dynamically display their installation status. The dynamic display includes the status changes of the model components from "not started" to "in progress" and then to "completed", thereby intuitively showing the entire construction and installation process of the electromechanical system.

[0019] Preferably, the installation simulation and collaborative design module is also used in the four-dimensional construction process simulation to detect the transportation path, working radius, availability and limitations of hoisting space of large equipment, as well as the connection relationship between micro-tasks, so as to determine whether there is interference between equipment and process.

[0020] Preferably, the workflow of the multi-source data synchronization and fusion module includes:

[0021] The edge computing gateway receives real-time passenger flow data from monitoring cameras, environmental data collected from environmental sensors, and operational status data uploaded by the devices themselves.

[0022] The environmental data includes at least wind speed, air volume, temperature, humidity, carbon dioxide concentration, and PM10 monitoring data.

[0023] Preferably, after receiving the data, the multi-source data synchronization and fusion module cleans and aligns the data with timestamps, and then drives the corresponding virtual building in the virtual model to update its state parameters.

[0024] Preferably, the process of the artificial intelligence optimization control module executing model predictive control includes:

[0025] Predict passenger flow density in different areas during future periods based on historical passenger flow patterns and real-time station entry numbers;

[0026] The passenger flow density prediction data is input into the simulation environment of the virtual model to simulate the environmental load and corresponding equipment requirements in advance.

[0027] Generate a forward-looking optimal control command sequence based on the simulation results.

[0028] Preferably, the process by which the artificial intelligence optimization control module performs real-time feedback correction includes:

[0029] The measured values ​​from the environmental sensors are compared with the predicted values ​​in the virtual model.

[0030] When a deviation occurs, a fine-tuning command for the electromechanical control parameters is issued to the actuators of the electromechanical equipment on site;

[0031] After the command is executed, the feedback data from the environmental sensors continues to be monitored to observe changes in deviation, forming a continuous optimization closed loop.

[0032] Preferably, the building information models of various specialties integrated by the digital twin construction module are integrated under a unified data standard, and the specialties include at least civil engineering, HVAC, water supply and drainage, electrical, fire protection and environmental and equipment monitoring systems.

[0033] Compared with the prior art, the beneficial effects of the present invention are:

[0034] 1. This invention deeply integrates various professional building information models under a unified standard. By injecting equipment performance curve models based on physical laws and pipe material properties, it creates a virtual test field with dynamic simulation capabilities. This enables the system to perform high-fidelity functional verification and construction simulation before construction, optimizing the design from the source and avoiding rework and resource waste caused by design conflicts or improper construction sequence in traditional methods.

[0035] 2. This invention combines four-dimensional construction process simulation with micro-task management. By decomposing the overall schedule into micro-tasks that are precisely associated with model components and dynamically simulating their execution process on a virtual timeline, the system can proactively detect static spatial conflicts and dynamic construction interferences, thereby calculating the optimal construction sequence and resource scheduling scheme. This not only improves construction efficiency but also minimizes on-site downtime and machinery waiting time, reducing energy consumption and carbon emissions during the construction phase.

[0036] 3. This invention is based on a hybrid mechanism of model predictive control and real-time feedback correction using digital twins. Through a multi-source data synchronization module, real-time passenger flow, environmental and equipment data are continuously input to keep the virtual model synchronized with the physical model. The artificial intelligence module uses this high-fidelity model to predict future loads and pre-simulate the effects of different control strategies, generating forward-looking optimal control commands. When actual operation deviates from the prediction, the system can immediately start a feedback loop for fine-tuning, forming a continuous optimization closed loop. This not only achieves lean control of operational energy consumption but also ensures a comfortable and stable environment. Attached Figure Description

[0037] Fig. 1 This is a schematic diagram of the system module structure of the present invention;

[0038] Fig. 2 This is a schematic diagram of the system workflow of the present invention. Detailed Implementation

[0039] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0040] To address the issues of resource waste, low construction efficiency, and inaccurate operational energy consumption caused by the disconnect between the design, construction, and operation phases in existing technologies, please refer to [link to relevant documentation]. Figs. 1-2 This embodiment provides the following technical solution:

[0041] An efficient resource utilization environmental control system for subway electromechanical installation includes a digital twin construction module, an installation simulation and collaborative design module, a multi-source data synchronization and fusion module, and an artificial intelligence optimization control module.

[0042] I. Digital Twin Construction Module

[0043] The digital twin building module is used to integrate building information models from various disciplines and inject physical rules and behavioral logic to form a virtual model with dynamic simulation capabilities, as detailed below:

[0044] Digital twins are based on a unified data standard and use a building information model that integrates all building information models, including civil engineering, HVAC, water supply and drainage, electrical, fire protection, environmental and equipment monitoring systems, as their geometric foundation to ensure the accuracy of spatial and logical relationships.

[0045] The key step in creating a digital twin is to inject physical rules and behavioral logic into the aforementioned building information model. Specifically, this involves assigning a mathematical model of the performance curves of air conditioning units, fans, chillers, water pumps, electrical equipment, and other energy-consuming equipment based on physical laws, and establishing quantitative relationships between operating parameters such as air volume, air pressure, water supply, water delivery rate, power supply, and power. This allows the digital twin to simulate the operating characteristics of real equipment in a virtual environment. It also involves labeling the piping system with physical properties such as material, thermal conductivity, and roughness, laying the foundation for subsequent thermal simulation calculations.

[0046] The above settings enable this virtual building information model to have dynamic simulation capabilities, forming a virtual test field for subsequent optimization and control operations, serving as the calculation basis for all subsequent operations.

[0047] II. Installation of Simulation and Collaborative Design Modules

[0048] The installation simulation and collaborative design module is connected to the digital twin construction module. The simulation capabilities of the digital twin are used for functional verification and four-dimensional construction process simulation optimization, as detailed below:

[0049] After completing spatial conflict detection and automatic routing optimization, computational fluid dynamics simulation is performed on the ventilation duct network to analyze airflow organization, temperature distribution and pressure loss under different operating conditions, thereby optimizing duct diameter design and vent layout, reducing system operating resistance from the design source and achieving long-term energy saving.

[0050] During the installation and construction of subway electromechanical systems, a four-dimensional simulation accurate to the minute is performed in the digital twin. The four-dimensional simulation combines the three-dimensional building information model with a detailed construction schedule. Specifically, the construction schedule is decomposed into a series of logically related micro-tasks. Each micro-task defines its duration, required personnel, machinery and equipment, and material resources. The micro-tasks are precisely associated with the corresponding model components in the digital twin.

[0051] In addition, the module creates a virtual construction timeline and automatically calculates an optimal construction sequence path based on the logical relationships between micro-tasks. Driven by the virtual timeline, the model components in the digital twin dynamically display their installation status, from "not started" to "in progress" and then to "completed", thus intuitively showing the construction and installation process of the entire station's electromechanical system.

[0052] This simulation module not only checks for static spatial conflicts but also detects dynamic construction conflicts, automatically simulating various construction schemes. Specifically, it detects the transportation path, working radius, availability and limitations of hoisting space for large equipment, as well as the connection relationships between micro-tasks, determining whether interference will occur between equipment and processes, and analyzing the feasibility of different professional teams working simultaneously in the same confined space. Through repeated simulations, it calculates the optimal construction sequence of micro-tasks, the travel route of large machinery, and the resource scheduling scheme.

[0053] Finally, the 4D simulation outputs a visualized construction plan, which accurately shows the micro-tasks that need to be completed at each time period of the day, as well as the specific deployment locations and movement paths of personnel and machinery.

[0054] The above system settings can minimize on-site downtime and machinery waiting time, thereby saving energy during the construction phase and avoiding unnecessary resource consumption.

[0055] III. Multi-source data synchronization and fusion module

[0056] The multi-source data synchronization and fusion module is connected to the digital twin construction module and is used to synchronize the collected data to the virtual model to keep its state updated, as detailed below:

[0057] This module receives real-time passenger flow data from monitoring cameras, environmental data collected from environmental sensors, and operational status data uploaded by the device itself via an edge computing gateway. The environmental data includes at least wind speed, airflow, temperature, humidity, carbon dioxide concentration, and PM10 monitoring data.

[0058] After being cleaned and timestamped, this data then drives the corresponding virtual building in the digital twin to update its state parameters, ensuring that the virtual building remains synchronized with the physical building entity and that the digital twin is always a highly faithful dynamic mirror of the physical entity.

[0059] IV. Artificial Intelligence Optimization Control Module

[0060] The AI-optimized control module is connected to the multi-source data synchronization and fusion module and the digital twin construction module. It is used to perform predictive control and real-time feedback correction based on the updated digital twin, and generate equipment control commands.

[0061] The AI-powered optimization control module employs a hybrid mechanism combining model predictive control and real-time feedback. First, the AI ​​algorithm predicts passenger flow density in different areas over the next 15 to 30 minutes based on historical passenger flow patterns and real-time passenger numbers. Next, the system inputs the predicted passenger flow density data for each area into the simulation environment of the digital twin, pre-simulating the environmental load and corresponding equipment requirements. Finally, based on the simulation results, a forward-looking optimal control command sequence is generated.

[0062] When a deviation occurs between the sensor's measured and predicted values, the system initiates a real-time feedback loop. This loop compares the measured values ​​with the predicted values ​​in the digital twin and issues fine-tuning commands for the electromechanical control parameters. These commands are immediately sent to the actuators of the electromechanical equipment on-site, thus completing an intervention. After the action is executed, the system continues to monitor the feedback data from environmental sensors, observing whether the deviation decreases, increases, or remains unchanged after the command is applied. This forms a continuous optimization closed loop of prediction, simulation, execution, and feedback, ensuring that the control is both forward-looking and adaptable to real-time changes.

[0063] In summary, the system integrates design, installation, and operation through a continuous closed-loop optimization process. A wealth of real-world operational data accumulated during the operation phase, such as equipment energy consumption, fault records, and control effectiveness, is recorded and analyzed by the system. This data is fed back to the digital twin, which can be used to calibrate and optimize its internal models and algorithms, making its simulation predictions increasingly accurate. When system upgrades or new lines are needed, the initial design parameters and equipment selection can be optimized based on this validated data, forming a continuously improving, full lifecycle resource utilization optimization closed loop, thereby achieving sustainable environmental goals throughout the entire process from construction to operation.

[0064] Working Principle: The system operates based on a continuous closed-loop optimization process that organically integrates the design, installation, and operation phases. First, the digital twin construction module integrates building information models from various disciplines, including civil engineering, HVAC, water supply and drainage, electrical, fire protection, and environmental and equipment monitoring systems, and injects physical rules and behavioral logic into them to form a virtual model with dynamic simulation capabilities, serving as the computational basis for subsequent operations.

[0065] The installation simulation and collaborative design module utilizes the aforementioned virtual model for functional verification and four-dimensional construction process simulation optimization. This module decomposes the construction schedule into micro-tasks and associates them with model components. Driven by a virtual timeline, it dynamically simulates the installation process, detects spatial and dynamic construction conflicts, optimizes the construction sequence and resource scheduling, thereby reducing energy waste.

[0066] The multi-source data synchronization and fusion module receives real-time passenger flow, environmental data, and equipment operation status data through the edge computing gateway. After cleaning and timestamp alignment, the data is synchronized to the virtual model to ensure that it is consistent with the physical entity and maintain the fidelity of the digital twin.

[0067] The AI-powered optimization control module is based on an updated digital twin and employs a mechanism that combines model predictive control with real-time feedback. This module predicts future passenger flow density, simulates environmental load and equipment demand in a virtual environment, and generates forward-looking control commands. When the measured values ​​deviate from the predicted values, a feedback loop is initiated to fine-tune electromechanical parameters, forming a continuous optimization closed loop of prediction, simulation, execution, and feedback.

[0068] The actual data accumulated during the operation phase is fed back into the digital twin to calibrate models and algorithms, optimize initial design parameters and equipment selection, thereby achieving efficient resource utilization and environmental protection goals throughout the entire life cycle from construction to operation.

[0069] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0070] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention.

Claims

1. A highly efficient resource-utilizing environmental control system for subway electromechanical installation, characterized in that, include: The digital twin building module is used to integrate building information models from various disciplines and inject physical rules and behavioral logic to form a virtual model with dynamic simulation capabilities. Install the simulation and collaborative design module, connect it with the digital twin building module, and use the virtual model for spatial conflict detection, automatic route optimization, computational fluid dynamics simulation, and four-dimensional construction process simulation optimization; The multi-source data synchronization and fusion module, connected to the digital twin construction module, is used to receive real-time monitoring data through the edge computing gateway and synchronize the cleaned and aligned data to the virtual model to keep its state updated. The artificial intelligence optimization control module is connected to the multi-source data synchronization and fusion module and the digital twin construction module. It is used to perform model predictive control and real-time feedback correction based on the updated virtual model and generate equipment control commands.

2. The efficient resource utilization environmental control system for subway electromechanical installation according to claim 1, characterized in that, The process of injecting physical rules and behavioral logic in the digital twin construction module includes: Assign mathematical models of performance curves based on physical laws to air conditioning units, fans, chillers, water pumps, and power equipment; Establish quantitative relationships between operating parameters such as air volume, air pressure, water supply, water delivery rate, power supply, and power. Label the material, thermal conductivity, and roughness physical properties of the piping system.

3. The efficient resource utilization environmental control system for subway electromechanical installation according to claim 1, characterized in that, The process of optimizing the four-dimensional construction process through the installation simulation and collaborative design module includes: The construction schedule is broken down into logically related micro-tasks. Each micro-task defines its duration, required personnel, machinery and equipment, and material resources, and associates them with the corresponding model components in the virtual model.

4. The efficient resource utilization environmental control system for subway electromechanical installation according to claim 3, characterized in that, The installation simulation and collaborative design module also constructs a virtual construction timeline, automatically calculates the optimal construction sequence path based on the logical relationship between micro-tasks, and drives the model components in the virtual model to dynamically display the installation status.

5. The efficient resource utilization environmental control system for subway electromechanical installation according to claim 3, characterized in that, In the four-dimensional construction process simulation, the installation simulation and collaborative design module is also used to detect the transportation path, working radius, availability and limitations of hoisting space of large equipment, as well as the connection relationship between micro-tasks, in order to determine whether there is interference between equipment and processes.

6. The efficient resource utilization environmental control system for subway electromechanical installation according to claim 1, characterized in that, The workflow of the multi-source data synchronization and fusion module includes: The edge computing gateway receives real-time passenger flow data from monitoring cameras, environmental data collected from environmental sensors, and operational status data uploaded by the devices themselves. The environmental data includes at least wind speed, air volume, temperature, humidity, carbon dioxide concentration, and PM10 monitoring data.

7. The efficient resource utilization environmental control system for subway electromechanical installation according to claim 6, characterized in that, After receiving the data, the multi-source data synchronization and fusion module cleans and aligns the data with timestamps, and then drives the corresponding virtual building in the virtual model to update its state parameters.

8. The efficient resource utilization environmental control system for subway electromechanical installation according to claim 1, characterized in that, The process of the AI ​​optimization control module executing model predictive control includes: Predict passenger flow density in different areas during future periods based on historical passenger flow patterns and real-time station entry numbers; The passenger flow density prediction data is input into the simulation environment of the virtual model to simulate the environmental load and corresponding equipment requirements in advance. Generate a forward-looking optimal control command sequence based on the simulation results.

9. A high-efficiency resource utilization environmental protection control system for subway electromechanical installation according to claim 8, characterized in that, The process by which the artificial intelligence optimization control module performs real-time feedback correction includes: The measured values ​​from the environmental sensors are compared with the predicted values ​​in the virtual model. When a deviation occurs, a fine-tuning command for the electromechanical control parameters is issued to the actuators of the electromechanical equipment on site; After the command is executed, the feedback data from the environmental sensors continues to be monitored to observe changes in deviation, forming a continuous optimization closed loop.

10. A high-efficiency resource utilization environmental protection control system for subway electromechanical installation according to claim 1, characterized in that, The digital twin building module integrates various professional building information models under a unified data standard. The professional models include at least civil engineering, HVAC, water supply and drainage, electrical, fire protection, and environmental and equipment monitoring systems.

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