High-altitude power equipment installation method based on self-adaptive adjustment
By arranging sensors on site installation and using intelligent management systems and adaptive adjustment strategies, the problem of insufficient wind speed monitoring during traditional installation is solved, efficient and safe installation of high-altitude power equipment is achieved, and installation accuracy and construction safety are improved.
Patent Information
- Application Number
- CN202510800912.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-16
- Publication Date
- 2025-08-08
AI Technical Summary
Traditional high-altitude power equipment lacks accurate wind speed monitoring and effective response strategies in complex terrain, resulting in equipment shaking and overturning, installation accuracy and construction safety are difficult to ensure, data management is chaotic and lacks systematic analysis.
Ultrasonic wind speed sensors, digital temperature and humidity sensors and light sensors are arranged on site for installation of high-altitude power equipment, data processing and strategy generation are carried out through intelligent management systems, adaptive adjustments are performed in combination with servo motors and precision transmission mechanisms, and task scheduling and resource allocation are optimized using support vector machines and genetic algorithms, and installation process is monitored and recorded in real time.
Accurate environmental perception, adaptive strategy generation, reliable execution and in-depth data analysis are realized, which improves installation quality and safety, improves resource utilization and construction efficiency, and reduces costs and risks.
Smart Images
Figure FT_1
Abstract
Description
Technical Field
[0001] The invention belongs to the technical field of high-altitude power equipment installation, and in particular relates to a high-altitude power equipment installation method based on adaptive adjustment. Background Art
[0002] As power infrastructure construction continues to advance, the installation of high-altitude power equipment such as transmission towers and substation equipment is becoming increasingly critical. However, the traditional high-altitude power equipment installation model has many drawbacks. At installation sites in complex terrain such as mountainous areas, wind speed changes frequently and is difficult to predict. Traditional methods lack accurate wind speed monitoring and effective response strategies, which often lead to shaking or even overturning of equipment during installation, seriously affecting installation accuracy and construction safety. Data management during the installation process is chaotic, data records are scattered and lack systematic analysis, which seriously restricts the development and progress of high-altitude power equipment installation technology.
[0003] Therefore, a high-altitude power equipment installation method based on adaptive adjustment is designed to solve the above problems. Summary of the Invention
[0004] In order to solve the problems raised in the above background technology, the present invention provides a method for installing high-altitude power equipment based on adaptive adjustment, which can effectively solve the problems raised in the above background technology.
[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for installing high-altitude power equipment based on adaptive adjustment, comprising: Sensor installation and data collection: At the high-altitude power equipment installation site, an ultrasonic wind speed sensor is installed on the windward side of the tower top and fixed with a stainless steel clamp. A digital temperature and humidity sensor is installed in a cool and ventilated place in the middle of the tower and fixed with an L-shaped anti-corrosion bracket. The light sensor is fixed on a concrete base with a leveling device. At the same time, position and attitude sensors are installed at the center of gravity, key joints, and load-bearing components of the equipment. Data is collected and transmitted to the intelligent management system via a 5G communication module. Data processing and strategy generation for the intelligent management system. The intelligent management system uses an environmental impact analysis algorithm based on a support vector machine and a genetic algorithm to process and analyze data, and generates adaptive adjustment strategies based on equipment performance and installation requirements. The installation equipment executes the adaptive adjustment strategy. The installation equipment receives and executes the adaptive adjustment strategy through an actuator composed of a servo motor, a precision transmission mechanism and an intelligent control system; Installation task scheduling and resource allocation, the intelligent management system uses genetic algorithms to schedule installation tasks and allocate resources based on installation task requirements, equipment status and environmental conditions; Installation process data recording and analysis: The intelligent management system records the installation process data in real time and conducts in-depth analysis after the task is completed; Remote monitoring and exception handling: operators remotely monitor the installation site through terminal equipment, and the intelligent management system issues alarms for abnormal situations and activates emergency response plans. As a preferred method of high-altitude power equipment installation based on adaptive adjustment of the present invention, the environmental impact analysis algorithm based on support vector machine includes data normalization processing, using radial basis kernel function to build a model and optimize parameters, and identifying the degree of influence of environmental factors on the installation process. As a preferred method of high-altitude power equipment installation based on adaptive adjustment of the present invention, the genetic algorithm encodes installation tasks, equipment resources and personnel skill information into chromosomes, takes the shortest task completion time, the highest resource utilization and the lowest installation cost as multi-objective functions, and iteratively optimizes through selection, crossover and mutation operations. As a preferred method for installing high-altitude power equipment based on adaptive adjustment of the present invention, in the actuator of the installation equipment, the adjustment bracket adopts ball screw and linear guide transmission, the servo motor drives the ball screw through an elastic coupling to achieve bracket angle and height adjustment, the lifting equipment adopts worm gear, worm, wire rope, and drum transmission, and the servo motor drives the worm gear through the reducer to control the lifting speed and rope tension. As a preferred method for installing high-altitude power equipment based on adaptive adjustment of the present invention, the sensor is calibrated with a standard instrument in a standard wind tunnel, a high-precision temperature and humidity calibration box and a standard lighting environment before installation, and is calibrated on-site every month after installation. As a preferred method of high-altitude power equipment installation based on adaptive adjustment of the present invention, the adaptive adjustment strategy includes adjusting the operating speed and stability control parameters of the installation equipment according to the wind speed, and controlling the opening of the auxiliary lighting equipment according to the light intensity. As a preferred method of high-altitude power equipment installation based on adaptive adjustment of the present invention, the intelligent management system first divides the task priorities when scheduling installation tasks and allocating resources, then allocates them based on the available resources of the equipment and the skills of the personnel, and dynamically adjusts according to actual conditions.
[0006] As a preferred embodiment of the high-altitude power equipment installation method based on adaptive adjustment of the present invention, the intelligent management system uses a machine learning algorithm to perform in-depth analysis of the installation process data, including predicting equipment failures and optimizing personnel training programs. As a preferred embodiment of the high-altitude power equipment installation method based on adaptive adjustment of the present invention, the abnormal conditions include equipment failures and personnel safety accidents. As a preferred method of high-altitude power equipment installation based on adaptive adjustment of the present invention, the intelligent management system includes a data receiving module, a data analysis and processing module, a strategy generation module, a task scheduling module, a data recording and analysis module and an emergency processing module.
[0007] Compared with the prior art, the present invention has the following beneficial effects: the structure of the present invention is scientific and reasonable, and it is safe and convenient to use: 1. Intelligent Environmental Perception and Accurate Data Support: By strategically deploying ultrasonic wind speed sensors, digital temperature and humidity sensors, light sensors, and position and attitude sensors at the high-altitude power equipment installation site, and employing a rigorous calibration mechanism, we ensure the accuracy and reliability of collected environmental and equipment data. This data is encrypted and transmitted to the intelligent management system in real time via a 5G communication module, providing a solid data foundation for subsequent analysis and decision-making. This aligns with the core elements of data processing and management in G06Q and helps companies achieve refined control over the installation process. 2. Efficient Adaptive Strategy Generation: The intelligent management system, based on a support vector machine-based environmental impact analysis algorithm and working in conjunction with a genetic algorithm, can deeply analyze the impact of environmental factors on the installation process and accurately identify trends in equipment stability and installation accuracy under varying environmental conditions. Combining equipment performance with installation requirements, it rapidly generates adaptive adjustment strategies, such as reducing equipment speed when wind speeds are too high, enhancing stability control, and enabling auxiliary lighting when sunlight is insufficient. This effectively ensures a safe and efficient installation process, elevating the company's intelligent management capabilities during project execution, and meeting G06Q's requirements for business process optimization. 3. Intelligent Task Scheduling and Optimal Resource Allocation: Utilizing genetic algorithms, we scientifically schedule installation tasks and allocate resources. We encode information about tasks, equipment resources, and personnel skills into chromosomes. Guided by multi-objective functions, we iteratively optimize through selection, crossover, and mutation operations. This prioritizes tasks, optimally matches equipment and personnel, and dynamically adjusts based on actual conditions. This significantly improves resource utilization, shortens task completion time, and reduces installation costs, generating significant economic benefits for the enterprise. This is highly consistent with the business philosophy of resource management and optimization in G06Q.
[0008] 4. Reliable actuators ensure precise operation: The actuators of the installation equipment utilize servo motors and precision transmission mechanisms, such as the ball screw and linear guide drive for the adjustment bracket and the worm gear and wire rope drum drive for the hoisting equipment. Combined with an intelligent control system, these actuators enable precise adjustment of bracket angle and height, hoisting speed, and rope tension. Driven by intelligent management system strategies, the actuators perform stably and precisely, ensuring reliable operation of the installation equipment in complex environments, improving installation quality and efficiency, providing enterprises with reliable technical support, and enhancing the execution process in commercial operations. 5. In-depth data analysis drives continuous improvement: The intelligent management system records installation process data in real time and conducts in-depth machine learning analysis to predict equipment failures, plan maintenance plans in advance, and reduce equipment downtime. By analyzing the behavioral patterns of personnel operation data, personnel training programs are optimized to improve operational standards and skills. This enables continuous improvement and optimization of the installation process, driving intelligent upgrades to enterprise management, and aligns with the G06Q concept of data analysis-driven decision-making and management improvement. 6. Remote monitoring and emergency response to ensure safe operations: Operators can remotely monitor the installation site through terminal devices. The intelligent management system will promptly alert users to abnormal situations such as equipment failures and personnel safety accidents, and automatically initiate emergency response plans, providing all-round safety protection for the installation process, reducing safety risks, minimizing accident losses, and ensuring the smooth progress of enterprise projects, reflecting the application value of G06Q in safety management and risk prevention and control. BRIEF DESCRIPTION OF THE DRAWINGS
[0009] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 The present invention is a flow chart of a method for installing high-altitude power equipment based on adaptive adjustment. DETAILED DESCRIPTION
[0010] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.
[0011] like Figure 1 As shown, the present invention provides a technical solution, a method for installing high-altitude power equipment based on adaptive adjustment, including: sensor installation and data acquisition, data processing and strategy generation of the intelligent management system, installation equipment execution of adaptive adjustment strategy, installation task scheduling and resource allocation, installation process data recording and analysis, and remote monitoring and exception handling.
[0012] At the installation site of high-altitude power equipment, the ultrasonic wind speed sensor is installed on the windward side of the top of the tower 20 cm away from the edge and fixed with a stainless steel clamp. The contact part between the clamp and the tower is lined with an anti-slip rubber pad to ensure that the sensor is stable and not affected by the vibration of the tower, so that it can accurately measure the wind speed and direction at high altitude. The digital temperature and humidity sensor is installed in a cool and ventilated place 8-10 meters in the middle of the tower. It is fixed to the inside of the tower angle steel with an L-shaped anti-corrosion bracket to avoid direct sunlight and local heat sources to ensure the accuracy of temperature and humidity data. The light sensor is fixed on a 1.5-meter-high concrete base and installed in an open area without obstructions at the installation site. The base is equipped with a horizontal adjustment device to ensure that the sensor surface is always level to accurately measure the light intensity. At the same time, the position and attitude sensors are installed at the center of gravity, key joints and load-bearing components of the equipment. They are connected to the main body of the equipment through waterproof sealing joints to collect the position and attitude data of the equipment in real time. The collected data is transmitted to the intelligent management system through the 5G communication module. It should be noted that all sensors require rigorous calibration before installation. The wind speed sensor is placed in a standard wind tunnel and compared with the measurements of a high-precision anemometer at different wind speed settings (such as 2m / s, 5m / s, and 10m / s), with errors corrected using software algorithms. The temperature and humidity sensor is placed in a high-precision temperature and humidity calibration chamber and calibrated against data from a standard thermometer and hygrometer at different temperature and humidity settings (such as 20°C / 60%RH and 30°C / 80%RH). The light sensor undergoes multi-point comparison calibration with a standard light meter under the same lighting conditions. After installation, on-site calibration is performed monthly, using portable calibration equipment to test and fine-tune sensor data in real time to ensure the accuracy and reliability of data collection. The collected data is transmitted in real time to the intelligent management system via a 5G communication module in an encrypted format. The intelligent management system incorporates a support vector machine (SVM)-based environmental impact analysis algorithm and a genetic algorithm. The SVM algorithm performs classification and regression analysis on environmental data (such as wind speed, temperature and humidity, and light intensity) and installed equipment data (such as location, posture, and operating parameters) by finding the optimal hyperplane in a high-dimensional space. First, the collected data is normalized to eliminate dimensional differences. A radial basis kernel function is then used to construct the SVM model. Using a large amount of historical installation data as training samples, the model's performance is optimized by adjusting the penalty factor and kernel function parameters, enabling it to accurately identify the impact of different combinations of environmental factors on the installation process. For example, this algorithm can determine equipment stability and installation accuracy trends under specific wind speed, temperature, and humidity conditions. A genetic algorithm is used for installation task scheduling and resource allocation. It encodes information such as installation tasks, equipment resources, and personnel skills into chromosomes, with the multi-objective goal of minimizing task completion time, maximizing resource utilization, and minimizing installation costs. Through a selection operation, optimal chromosomes are selected based on the fitness function. A crossover operation swaps genes from selected chromosomes to create new individuals. A mutation operation randomly alters genes in chromosomes to increase population diversity. After multiple rounds of iterative calculations, the optimal task scheduling and resource allocation solution is obtained, including determining the priority of each installation task and allocating appropriate installation equipment and personnel. The strategy generation module combines the analysis results of the SVM algorithm with the performance parameters and installation requirements of the installation equipment to generate adaptive adjustment strategies. For example, if the SVM algorithm determines that the current wind speed exceeds the equipment's safe operating threshold, the strategy generation module generates a strategy to reduce the installation equipment's operating speed and enhance stability control (such as increasing the bracket support angle or adding counterweights). If insufficient light intensity affects installation operations, the strategy generation module generates a strategy to activate auxiliary lighting.
[0013] The actuator built into the mounting device consists of a servo motor, a precision transmission mechanism, and an intelligent control system. A high-torque, high-response AC servo motor is used to power the actuator. For mounting devices with adjustable brackets, a ball screw-linear guide transmission mechanism is used. The servo motor is connected to the ball screw via an elastic coupling. When the intelligent control system receives the adaptive adjustment strategy, it sends a control signal to rotate the servo motor. The ball screw converts the rotational motion into linear motion of the slider on the linear guide, thereby driving the bracket's angle and height adjustment, achieving precise changes in the device's posture with an adjustment accuracy of up to ±0.1°.
[0014] For hoisting equipment, a worm gear wire rope drum drive mechanism is used. A servo motor drives the worm gear mechanism through a reducer. The deceleration and torque-increasing effect of the worm gear drives the wire rope drum, achieving precise control of hoisting speed and rope tension. The intelligent control system, based on a programmable logic controller (PLC), receives adjustment strategies from the intelligent management system and precisely executes the corresponding actions by controlling the servo motor's speed, direction, and torque, ensuring stable operation of the installation equipment in various environments and task requirements. The intelligent management system's task scheduling module utilizes a genetic algorithm to dynamically schedule installation tasks and allocate resources based on task requirements, real-time equipment status, and environmental conditions. First, all installation tasks are prioritized, taking into account factors such as urgency, construction difficulty, and impact on the overall project progress. Then, through iterative optimization using the genetic algorithm, tasks are optimally allocated to different installation equipment and personnel, taking into account the equipment's available resources (such as operating hours, load capacity, and current location) and personnel skill levels. During task execution, the progress of each task is monitored in real time. In the event of environmental changes or equipment failures, the genetic algorithm is reactivated for dynamic adjustments, ensuring optimal resource allocation and improving installation efficiency. During the installation process, the intelligent management system's data recording and analysis module records in real time the operating data of the installed equipment (such as motor speed, torque, and operating hours), environmental data (wind speed, temperature and humidity, and light intensity), and operator operation data (operation time, steps, and instructions). After the installation task is completed, machine learning algorithms are used to conduct in-depth analysis of the recorded data. Through fault tree analysis and anomaly detection algorithms, potential failures are predicted from equipment operating data, allowing for the development of preemptive maintenance plans. By analyzing behavioral patterns in operator operation data, irregularities are identified, and personnel training programs are optimized, achieving continuous improvement and optimization of the installation process. Operators can remotely log into the intelligent management system via mobile phones, tablets, and other devices to view real-time video footage, equipment status, and environmental data from the installation site. When the system detects an abnormality, such as equipment failure or a personal safety incident, the emergency response module immediately issues an audible and visual alarm and notifies relevant personnel via text message or app push notifications. Furthermore, based on the type and severity of the abnormality, the system automatically initiates the corresponding emergency response plan. For example, in the event of an equipment failure, a fault diagnosis report and repair instructions are provided. In the event of a personal safety incident, rescue procedures are initiated and first aid measures are recommended, ensuring a safe installation process. Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.
Claims
1. A method for installing high-altitude power equipment based on adaptive adjustment, characterized in that: include: Sensor installation and data collection: At the high-altitude power equipment installation site, an ultrasonic wind speed sensor is installed on the windward side of the tower top and fixed with a stainless steel clamp. A digital temperature and humidity sensor is installed in a cool and ventilated place in the middle of the tower and fixed with an L-shaped anti-corrosion bracket. The light sensor is fixed on a concrete base with a leveling device. At the same time, position and attitude sensors are installed at the center of gravity, key joints, and load-bearing components of the equipment. Data is collected and transmitted to the intelligent management system via a 5G communication module. Data processing and strategy generation for the intelligent management system. The intelligent management system uses an environmental impact analysis algorithm based on a support vector machine and a genetic algorithm to process and analyze data, and generates adaptive adjustment strategies based on equipment performance and installation requirements. The installation equipment executes the adaptive adjustment strategy. The installation equipment receives and executes the adaptive adjustment strategy through an actuator composed of a servo motor, a precision transmission mechanism and an intelligent control system; Installation task scheduling and resource allocation, the intelligent management system uses genetic algorithms to schedule installation tasks and allocate resources based on installation task requirements, equipment status and environmental conditions; Installation process data recording and analysis: The intelligent management system records the installation process data in real time and conducts in-depth analysis after the task is completed; Remote monitoring and exception handling: operators remotely monitor the installation site through terminal equipment, and the intelligent management system issues alarms for abnormal situations and activates emergency response plans.
2. The method for installing high-altitude power equipment based on adaptive adjustment according to claim 1, characterized in that: The environmental impact analysis algorithm based on the support vector machine includes normalizing data, building a model using a radial basis kernel function and optimizing parameters, and identifying the degree of influence of environmental factors on the installation process.
3. The method for installing high-altitude power equipment based on adaptive adjustment according to claim 1, characterized in that: The genetic algorithm encodes installation tasks, equipment resources and personnel skills information into chromosomes, takes the shortest task completion time, the highest resource utilization and the lowest installation cost as multi-objective functions, and iteratively optimizes through selection, crossover and mutation operations.
4. The method for installing high-altitude power equipment based on adaptive adjustment according to claim 1, characterized in that: In the actuator of the installation equipment, the adjustment bracket adopts ball screw and linear guide transmission, and the servo motor drives the ball screw through the elastic coupling to achieve bracket angle and height adjustment. The lifting equipment adopts worm gear, worm, wire rope and drum transmission, and the servo motor drives the worm gear through the reducer to control the lifting speed and rope tension.
5. The method for installing high-altitude power equipment based on adaptive adjustment according to claim 1, characterized in that: The sensor is calibrated in a standard wind tunnel, a high-precision temperature and humidity calibration box and a standard lighting environment in comparison with a standard instrument before installation, and is calibrated on-site every month after installation.
6. The method for installing high-altitude power equipment based on adaptive adjustment according to claim 1, characterized in that: The adaptive adjustment strategy includes adjusting the operating speed and stability control parameters of the installation equipment according to the wind speed, and controlling the auxiliary lighting equipment to turn on according to the light intensity.
7. The method for installing high-altitude power equipment based on adaptive adjustment according to claim 1, characterized in that: When scheduling installation tasks and allocating resources, the intelligent management system first divides the task priorities, then allocates them based on the available equipment resources and personnel skills, and dynamically adjusts them according to actual conditions.
8. The method for installing high-altitude power equipment based on adaptive adjustment according to claim 1, characterized in that: The intelligent management system uses machine learning algorithms to conduct in-depth analysis of installation process data, including predicting equipment failures and optimizing personnel training programs.
9. The method for installing high-altitude power equipment based on adaptive adjustment according to claim 1, characterized in that: The abnormal conditions include equipment failures and personnel safety accidents.
10. The method for installing high-altitude power equipment based on adaptive adjustment according to claim 1, characterized in that: The intelligent management system includes a data receiving module, a data analysis and processing module, a strategy generation module, a task scheduling module, a data recording and analysis module and an emergency processing module.