Lifting synchronous control system and control method for high-rise steel structure corridor

Abstract

Disclosed in the present invention are a lifting synchronous control system and control method for a high-rise steel structure corridor. The control system comprises a data acquisition module comprising a sensor network, an execution module, and a data-processing and decision-making module comprising a central control unit. The execution module comprises a lifting drive provided with a receiver. The sensor network comprises a coordinate sensor, an inclination angle sensor, a temperature and humidity sensor, and a wind speed sensor. The sensor network continuously acquires coordinate information, inclination angle information, and environment information and sends same to the central control unit. By means of a machine learning or deep learning algorithm, the central control unit performs self-optimization and regulates the lifting drive in real time on the basis of the continuously collected environment data and structural data. In the present invention, by combining dynamic regulation of an intelligent algorithm with the application of an Internet of Things technology, all components in the control system are modularly designed, thereby obviously mitigating the defects of conventional synchronous control systems, and significantly improving the stability of the control system and the capability of resisting the influence of external factors.

Description

High-rise steel structure corridor lifting synchronous control system and control method TECHNICAL FIELD

[0001] The present application relates to the field of building construction technology, more specifically, to a high-rise steel structure corridor lifting synchronous control system and control method. BACKGROUND

[0002] With high-rise buildings becoming more and more the symbol of city skyline, its construction technology is also constantly progressing and innovating. As a key technology in the construction of high-rise steel structure, the development and application of lifting synchronous control system has great significance for ensuring the quality of construction, improving construction efficiency and ensuring construction safety. Early synchronous lifting control relies on manual operation and simple mechanical equipment, which is difficult to control accurately and has low efficiency. With the development of computer technology, sensor technology and automation control technology, the design and implementation of lifting synchronous control system has become more accurate and reliable.

[0003] With the development of technology, lifting synchronous control system is not only applied to the construction of high-rise buildings, but also begins to expand to the fields of large equipment installation, bridge construction, etc., with a wider range of applications. Lifting synchronous control system uses sensors (such as displacement sensors, pressure sensors, etc.) installed on each lifting point of the structure being lifted to real-time sense the position, speed, load and other key parameters of each lifting point. These data are fed back to the central control unit as the basis for adjusting the synchronous motion. The central control unit (usually a computer or a special controller) analyzes all real-time data of the lifting points according to the preset synchronous control algorithm. The control system judges whether to adjust the speed, direction, etc. of the motion of one or more lifting points according to these information to ensure the synchronous motion of all lifting points. Lifting synchronous control system adjusts the speed of each lifting point through drivers (such as motors, hydraulic pumps, etc.) according to the instructions of the central control unit. The lifting synchronous control system continuously monitors the state of each point and adjusts the execution parameters in real time to maintain strict synchronization.

[0004] However, there are still some obvious shortcomings in the lifting synchronous control system, especially its high dependence on environmental factors. This shortcoming not only affects the stability and reliability of the system, but also may increase the construction cost and delay the construction progress.

[0005] Lifting synchronization control systems rely on various sensors to monitor the state of the lifting equipment, such as displacement, speed, pressure, etc. These sensors are very sensitive to environmental conditions. For example, extreme temperature, humidity, vibration and electromagnetic interference can affect the accuracy and reliability of the sensors. Temperature fluctuations can cause changes in the physical properties of the sensor material, affecting the accuracy of its readings. Increased humidity can cause electronic components to short circuit or corrode, affecting the performance of the sensor. In addition, vibration can cause mechanical sensors to misread, while electromagnetic interference can affect the accurate transmission of signals from electronic sensors.

[0006] In addition, lifting synchronization control systems usually rely on wired communication technology to transmit data. Although it can ensure the stability and reliability of data transmission, it also has the disadvantages of high installation and maintenance cost, limited flexibility of wiring, large installation space requirement, and vulnerability to physical damage.

[0007] In low-latitude areas, the stability and safety of high-rise building steel structure corridors face great challenges, including but not limited to the influence of natural conditions such as strong winds, earthquakes, high temperatures and humid environments. The instability and unpredictability of environmental conditions increase the complexity of the construction process. In order to adapt to environmental changes and ensure the accuracy and reliability of the lifting synchronization control system, additional time and resources may be required to adjust and maintain the system. This not only increases construction costs, but also may cause delays in construction progress. Therefore, the traditional high-rise building steel structure corridor synchronization control system has not fully met the needs in these complex environments. Technical problem

[0008] In view of the above defects of the prior art, the present application provides a high-rise steel structure corridor lifting synchronization control system and control method, which significantly improves the defects of the traditional synchronization control system based on intelligent algorithm dynamic regulation and control, combined with Internet of Things technology application and modular design of each component in the system, significantly improves the stability and resistance to external factors of the system, and provides strong technical support for the safety, reliability and functionality of the building. Technical solution

[0009] To achieve the above-mentioned purpose, on the one hand, the present application provides a high-rise steel structure corridor lifting synchronization control system, characterized in that it comprises:

[0010] A data acquisition module comprising a sensor network; the sensor network comprises a coordinate sensor, an inclination sensor, a temperature and humidity sensor, and a wind speed sensor, continuously acquires coordinate information, inclination information and environmental information, and sends them to a data transceiver, which then sends them to a central control unit; the sensor network is installed on the key positioning control points of the lifting steel structure corridor and the lifting lower hanging points of the corridor;

[0011] An execution module, including a lifting driver equipped with a receiver, through which the lifting speed control information sent by the central control unit is received and the lifting speed is controlled;

[0012] A data processing and decision module, including the central control unit and its data transceiver, which collates and counts the coordinate information, the inclination information and the environmental information, checks whether the coordinate information and the inclination information match, determines the overall lifting synchronization of the corridor, automatically calculates the adjustment data of each lifting hanging point and sends it to the receiver on the lifting driver through the data transceiver, and continuously fine-tunes the overall posture of the corridor; the central control unit is based on machine learning or deep learning algorithm, and self-optimizes and real-time regulates the driver according to the continuously collected environmental and structural data.

[0013] Further, the key positioning control point of the steel structure corridor is the reserved fracture of the steel structure corridor splicing.

[0014] Further, the coordinate sensor is arranged at the reserved fracture of the steel structure corridor splicing; and the inclination sensor is arranged at the lifting lower hanging point of the corridor.

[0015] Further, the coordinate sensor performs coordinate positioning based on GPS or BDS.

[0016] Further, the central control unit self-optimizes and real-time regulates the driver according to the continuously collected environmental and structural data, and uploads a large amount of data to the cloud platform, combines cloud computing and edge computing, and further optimizes the efficiency and accuracy of data processing and decision making.

[0017] In another aspect, the application provides a high-rise steel structure corridor lifting synchronization control method, characterized in that a high-rise steel structure corridor lifting synchronization control system as described above is used, including the following steps:

[0018] Step S1, arranging a sensor network and a receiver: the key positioning control point of the lifting steel structure corridor and the lifting lower hanging point of the corridor are installed with the sensor network; and the receiver is installed at the lifting driver;

[0019] Step S2, starting the lifting synchronization control system: in the preparation and inspection work before the lifting of the corridor, the lifting synchronization control system is completely started, whether each unit works normally and whether the data transmission is normal are tested, and the lifting synchronization control system and other equipment are comprehensively checked and debugged; the lifting synchronization control system is started again when the corridor is lifted as a whole, the coordinate information and the inclination information of the corridor are collected by the sensor network and sent to the data transceiver, and then the data transceiver sends them to the central control unit, the central control unit automatically collates and counts the initial data A0 of the corridor lifting, and automatically calculates the adjustment data C0 of each lifting hanging point;

[0020] Step S3, preliminary adjustment of the overall attitude of the corridor: the adjustment data C0 is sent by the data transceiver to the receiver on the lifting driver, for preliminary adjustment of the overall attitude of the corridor, so that the corridor structure is lifted to the designed attitude by the lifting unit; after the overall attitude of the corridor is adjusted, the processing data of the central control unit is initialized, and the coordinate position after adjustment is taken as the initial state data;

[0021] Step S4, formal lifting control: during the formal lifting process, the sensor network continuously acquires coordinate information A1, inclination information B1 and environmental information and sends them to the data transceiver, and then the data transceiver sends them to the central control unit. The central control unit sorts and counts the coordinate information A1, inclination information B1 and environmental information, checks whether the coordinate information A1 and inclination information B1 match, and determines the synchronization of the overall lifting of the corridor, automatically calculates the adjustment data C1 of each lifting point, and sends it to the receiver on the lifting driver through the data transceiver, continuously fine-tunes the overall attitude of the corridor, and ensures the synchronization during the lifting process of the corridor; the central control unit is based on machine learning or deep learning algorithm, and continuously collects environmental and structural data for self-optimization and real-time control of the driver.

[0022] Further, in step S4, the lifting driver fine-tunes the overall attitude of the corridor by adjusting the tension or changing the flexibility distribution.

[0023] Preferably, in step S4, the central control unit continuously collects environmental and structural data for self-optimization and real-time control of the driver, and uploads a large amount of data to the cloud platform, combines cloud computing and edge computing, and further optimizes the efficiency and accuracy of data processing and decision-making.

[0024] Preferably, the central processing unit and the sensor network collect and transmit data through 5G or LoRaWAN communication technology.

[0025] Preferably, the central processing unit and the cloud platform collect and transmit data through 5G or LoRaWAN communication technology. Advantages

[0026] Compared with the prior art, the present application has the following advantages or beneficial effects:

[0027] (1) Improve adaptability and flexibility: the intelligent algorithm dynamic control method can analyze and predict environmental changes such as strong wind, vibration and other natural conditions in real time, and quickly respond to adjust the corridor structure. Compared with traditional technology, this predictive and adaptive lifting can more effectively protect the corridor from adverse effects and ensure the safety of personnel and property.

[0028] (2) Enhancing data processing and decision-making capabilities: Through the application of Internet of Things technology, the sensor network constructed by the present application not only improves the coverage and accuracy of data collection, but also optimizes the data processing process by combining cloud computing and edge computing, improving the speed of data processing and the accuracy of decision-making. Compared with existing technologies, this efficient information processing and analysis capability provides strong support for real-time monitoring and fine management of the corridor.

[0029] (3) Easy to maintain and extend: Modular design makes the system not only easy to maintain and upgrade, but also makes it possible to customize changes for specific needs. When replacing parts or adding new functions, modular construction can greatly reduce complexity and cost, compared with traditional systems, this design significantly improves the sustainability of the system.

[0030] (4) Significantly improve safety and reliability: The present application greatly reduces the potential risks caused by natural disasters or environmental changes through intelligent prediction and response mechanisms. At the same time, the use of Internet of Things technology and modular implementation methods further ensure the stable operation and efficient response of the system, significantly improving the overall safety and reliability compared with existing technologies.

[0031] (5) Optimize resource utilization: By optimizing the adjustment strategy of the corridor through intelligent algorithms, energy can be used more economically, unnecessary physical stress can be reduced, and the structural life can be extended. Compared with traditional technologies that rely on physical adjustments, this optimized resource utilization not only reduces operating costs, but also contributes to environmental sustainability. BRIEF DESCRIPTION OF DRAWINGS

[0032] The present application and its features and advantages will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings. The same reference numbers in all the drawings indicate the same parts. The drawings are not drawn to scale, the emphasis is on illustrating the main idea of the present application.

[0033] Figure 1 is a schematic diagram of the structure of the high-rise steel structure corridor synchronous control system according to an embodiment of the present application;

[0034] Figure 2 is a schematic diagram of the high-rise steel structure corridor synchronous control method according to an embodiment of the present application;

[0035] Among them, 1, central control unit; 2, coordinate sensor; 3, tilt sensor; 4, receiver; 5, data transceiver; 6, lifting driver; 7, steel structure corridor. Embodiment of the present application

[0036] The present application will be further described below in conjunction with the drawings and specific embodiments, but not as a limitation of the present application.

[0037] The sensors, data transceivers, lifting drivers, etc. involved in the following effect embodiments and examples are all independently commercially available, and the control methods used are existing technologies that can be retrieved. Moreover, the settings of the signal control system of the equipment in the following effect embodiments and examples are not fully described, and the details of the signal control system can be clearly understood by those skilled in the art on the premise of understanding the above-mentioned principles of the application. Embodiments

[0038] Referring to FIG. 1, the embodiment discloses a high-rise steel structure corridor lifting synchronous control system, comprising:

[0039] A data acquisition module comprising a sensor network; the sensor network comprises coordinate sensors 2, inclination sensors 3, temperature and humidity sensors, and wind speed sensors, continuously acquires coordinate information, inclination information and environmental information, and sends them to a data transceiver 5, which then sends them to a central control unit 1; the sensor network is installed at key positioning control points of the lifting steel structure corridor and lifting points of the corridor;

[0040] An execution module comprising a lifting driver 6 equipped with a receiver 4, which receives lifting speed control information sent by the central control unit 1 through the receiver 4 and controls the lifting speed;

[0041] A data processing and decision module comprising the central control unit 1 and its data transceiver 5, which collates and counts coordinate information, inclination information and environmental information, checks whether the coordinate information and inclination information match, determines the overall lifting synchronization of the corridor, automatically calculates adjustment data for each lifting point and sends it to the receiver 4 on the lifting driver 6 through the data transceiver 5, and continuously fine-tunes the overall posture of the corridor; the central control unit is based on machine learning or deep learning algorithm, and automatically optimizes and real-time regulates the driver according to the continuously collected environmental and structural data.

[0042] By dividing the system into multiple functional modules, each module can operate independently or work together efficiently according to standardized interfaces. This design not only simplifies the maintenance and upgrade process of the system, making it easier to add new functions or expand existing ones, but also significantly improves the flexibility and reliability of the system. More importantly, modular design allows the system to be customized for specific needs of different architectural steel structure corridors, enabling more precise control. At the same time, the system's perception of environmental parameters is achieved through adaptive learning algorithms, allowing it to automatically adjust the stability strategy of the steel structure corridor in response to environmental factors during synchronous lifting. For example, in the case of strong winds, the system can automatically adjust the stability strategy of the steel structure corridor by adjusting the tension or changing the flexibility distribution to reduce the impact of wind.

[0043] As a preferred technical solution, further: the key positioning control point of the steel structure corridor is the steel structure corridor splicing reserved fracture. More preferably, referring to FIG. 1, the coordinate sensor 2 is arranged at the steel structure corridor splicing reserved fracture; and the inclination sensor 3 is arranged at the corridor lifting lower lifting point. This arrangement can provide more accurate position and attitude information for the central control unit to simulate the lifting process of the steel structure corridor, and the installation position is convenient to realize, reducing the consumption of manual labor.

[0044] As a preferred technical solution, further: the coordinate sensor 2 performs coordinate positioning based on GPS or BDS.

[0045] As a preferred technical solution, further: the central control unit performs self-optimization and real-time regulation and control of the driver according to the continuously collected environmental and structural data, and uploads a large amount of data to the cloud platform, combines cloud computing and edge computing, and further optimizes the efficiency and accuracy of data processing and decision-making. Embodiment

[0046] Referring to FIG. 2, the embodiment discloses a high-rise steel structure corridor lifting synchronization control method, which utilizes the synchronization control system as described in Embodiment 1, and the specific working process is as follows:

[0047] Step S1, arranging a sensor network and a receiver: installing GPS and BDS coordinate sensors 2 and inclination sensors 3 at key positioning control points (mainly steel structure corridor splicing reserved fracture) of the lifting steel structure corridor 7, corridor lifting lower lifting point, and installing temperature and humidity sensors and wind speed sensors near the lifting point to ensure full coverage of data acquisition. A receiver 4 is installed at the lifting driver 6 for receiving lifting speed control information sent by the central control unit 1 and controlling the lifting speed.

[0048] Step S2, starting the lifting synchronization control system: during the preparation and inspection work before the corridor lifting, the lifting synchronization control system is completely started, the normal work of each unit is tested, the normal data transmission is tested, and the overall inspection and debugging work of the whole lifting synchronization control system and other equipment is performed. The lifting synchronization control system is started again during the overall inspection of the corridor lifting, the coordinate information, environmental information and corridor inclination information are collected by the sensor network and sent to the data transceiver 5, then the data transceiver 5 sends the data to the central control unit 1, the central control unit 1 automatically arranges and counts the initial data A0 of the corridor lifting, and automatically calculates the adjustment data C0 of each lifting lifting point.

[0049] Step S3, preliminary adjustment of the overall attitude of the corridor: the adjustment data C0 is sent by the data transceiver 5 to the receiver 4 on the lifting driver 6, for preliminary adjustment of the overall attitude of the corridor, so that the corridor structure is lifted to the designed attitude by the lifting unit. After the overall attitude of the corridor is adjusted, the processing data of the central control unit 1 is initialized, and the adjusted BDS coordinate position is taken as the initial state data.

[0050] Step S4, formal lifting: during the formal lifting process, the sensor network continuously acquires coordinate information A1, inclination information B1, and temperature and humidity, wind speed and sends them to the data transceiver 5, and then to the central control unit 10. The central control unit 1 sorts and counts the coordinate information A1, inclination information B1, and temperature and humidity, wind speed, checks whether the coordinate information A1 and the inclination information B1 match, and determines the synchronization of the overall lifting of the corridor, automatically calculates the adjustment data C1 of each lifting point, and sends it to the receiver 4 on the lifting driver 6 through the data transceiver 5, continuously fine-tunes the overall attitude of the corridor, and ensures the synchronization during the lifting of the corridor.

[0051] From the above description, it can be seen that the dynamic regulation of intelligent algorithms is the core of the control system of the present application. By introducing adaptive learning algorithms such as machine learning and deep learning algorithms, the system can optimize itself based on the continuous collection of environmental and structural data. This process, through real-time monitoring of the state of the corridor (including but not limited to displacement, stress, temperature and humidity, etc.) and changes in the external environment (such as wind speed, temperature difference, etc.), enables the control system to predict and respond to changes in the external environment, ensuring that the steel structure corridor can maintain a stable state under uncertain external conditions, significantly improving the adaptability and response speed of the system.

[0052] The Internet of Things technology plays a crucial role in the present application. By deploying a dense sensor network on the steel structure corridor and using advanced communication technologies (such as 5G, LoRaWAN), efficient data collection and transmission are achieved. These sensors collect various data about the steel structure corridor structure and environment in real time and transmit the data to the central processing unit in real time. The central processing control unit uses these data for intelligent analysis, and then guides the real-time regulation strategy of the steel structure corridor. At the same time, a large amount of data is uploaded to the cloud platform, combining the technical advantages of cloud computing and edge computing, further optimizing the efficiency and accuracy of data processing and decision-making. In this way, the Internet of Things technology not only enhances the data processing capacity of the system, but also improves the real-time and accuracy of decision-making.

[0053] The application of modular design provides a solid foundation for the reliability and maintainability of the system. By dividing the system into multiple functional modules such as data acquisition module, data processing and decision module, execution module, etc., each module can operate independently or work collaboratively through standardized interfaces. This design not only simplifies the maintenance and upgrade process of the system, making it easier to add new functions or expand existing ones, but also significantly improves the flexibility and reliability of the system. More importantly, modular design allows the system to be customized for different building steel structure corridors, enabling more precise control.

[0054] Those skilled in the art should understand that those skilled in the art can realize variations in combination with the prior art and the above embodiments, which are not described here. Such variations do not affect the essential content of the present application and are not described here. Any simple modification, equivalent change and modification made to the above embodiments in accordance with the technical essence of the present application without departing from the technical solution of the present application still belongs to the protection scope of the technical solution of the present application. Industrial applicability

[0055] The high-rise steel structure corridor synchronous control system and control method proposed by the present application realizes a highly intelligent and adaptive building steel structure corridor control scheme. The dynamic regulation of intelligent algorithms provides unprecedented adaptability and reaction speed for the system; the application of Internet of Things technology provides support for real-time and accurate data collection and processing; and modular design ensures the reliability and maintainability of the system. The integration of these technologies enables the system to effectively resist the harsh weather and environmental challenges common in low-latitude regions, significantly improving the stability and safety of high-rise building steel structure corridors, and has broad application prospects.

Claims

1. A high-rise steel structure corridor lifting synchronous control system, characterized in that, The application relates to a high-rise steel structure corridor lifting synchronization control system. The data acquisition module comprises a sensor network; the sensor network comprises a coordinate sensor (2), an inclination sensor (3), a temperature and humidity sensor and a wind speed sensor, continuously acquires coordinate information, inclination information and environmental information, and sends the information to a data transceiver (5) which then sends the information to a central control unit (1); the sensor network is installed at key positioning control points of a steel structure corridor and lifting points under the corridor; The execution module comprises a lifting driver (6) equipped with a receiver (4) which receives lifting speed control information sent by the central control unit (1) and controls the lifting speed; The data processing and decision-making module comprises the central control unit (1) and the data transceiver (5), which collate and count the coordinate information, the inclination information and the environmental information, check whether the coordinate information and the inclination information are matched, determine the overall lifting synchronization of the corridor, automatically calculate adjustment data of each lifting point and send the adjustment data to the receiver (4) of the lifting driver (6) through the data transceiver (5), and continuously fine-tune the overall posture of the corridor; the central control unit is based on a machine learning or deep learning algorithm, and continuously collects environmental and structural data to optimize itself and real-time control the driver.

2. The high-rise steel structure gallery hoisting synchronous control system according to claim 1, characterized in that, The key positioning control points of the steel structure corridor are reserved fracture points of the steel structure corridor splicing.

3. The high-rise steel structure gallery hoisting synchronous control system according to claim 2, characterized in that, The coordinate sensor (2) is arranged at the reserved fracture points of the steel structure corridor splicing; and the inclination sensor (3) is arranged at the lifting points under the corridor.

4. The high-rise steel structure gallery hoisting synchronous control system according to claim 1, characterized in that, The coordinate sensor (2) is based on GPS or BDS for coordinate positioning.

5. The high-rise steel structure gallery hoisting synchronous control system according to claim 1, characterized in that, The central control unit continuously collects environmental and structural data to optimize itself and real-time control the driver, and uploads a large amount of data to a cloud platform, combines cloud computing and edge computing, and further optimizes the efficiency and accuracy of data processing and decision-making.

6. A method for synchronous control of hoisting a corridor of a high-rise steel structure, characterized in that, The application further discloses a high-rise steel structure corridor lifting synchronization control method using the high-rise steel structure corridor lifting synchronization control system. In step S1, the sensor network and the receiver are arranged; in step S2, the lifting synchronization control system is started; in step S3, the lifting synchronization control system is started again when the overall lifting of the corridor is checked; in step S4, the lifting synchronization control system is started again when the lifting of the corridor is completed; and in step S5, the lifting synchronization control system is stopped. ​ Step S3, preliminary adjustment of the overall attitude of the corridor: the adjustment data C0 is sent by the data transceiver to the receiver on the lifting driver, for preliminary adjustment of the overall attitude of the corridor, so that the corridor structure is lifted to the designed attitude by the lifting unit; after the overall attitude of the corridor is adjusted, the processing data of the central control unit is initialized, and the coordinate position after adjustment is taken as the initial state data; Step S4, formal lifting control: during the formal lifting process, the sensor network continuously acquires coordinate information A1, inclination information B1 and environmental information and sends them to the data transceiver, and then the data transceiver sends them to the central control unit. The central control unit sorts and counts the coordinate information A1, inclination information B1 and environmental information, checks whether the coordinate information A1 and inclination information B1 match, and determines the synchronization of the overall lifting of the corridor, automatically calculates the adjustment data C1 of each lifting point, and sends it to the receiver on the lifting driver through the data transceiver, continuously fine-tunes the overall attitude of the corridor, and ensures the synchronization during the lifting process of the corridor; the central control unit is based on machine learning or deep learning algorithm, and automatically optimizes and real-time regulates the driver according to the continuously collected environmental and structural data.

7. The high-rise steel structure gallery hoisting synchronization control method according to claim 6, characterized in that, In the step S4, the central control unit automatically optimizes and real-time regulates the driver according to the continuously collected environmental and structural data, and uploads a large amount of data to the cloud platform at the same time, combines cloud computing and edge computing, and further optimizes the efficiency and accuracy of data processing and decision-making.

8. The high-rise steel structure gallery hoisting synchronization control method according to claim 6, characterized in that, The central processing unit and the sensor network collect and transmit data through 5G or LoRaWAN communication technology.

9. The high-rise steel structure gallery hoisting synchronization control method according to claim 7, characterized in that, The central processing unit and the cloud platform collect and transmit data through 5G or LoRaWAN communication technology.

10. The high-rise steel structure gallery hoisting synchronization control method according to claim 6, characterized in that, In the step S4, the lifting driver fine-tunes the overall attitude of the corridor by adjusting the tension or changing the flexibility distribution.

Images