Remote collaborative intelligent microtube fiber blowing control system

Abstract

The invention discloses a remote cooperative intelligent microtube fiber blowing control system, and relates to the technical field of optical fiber communication, and the system comprises the following components: a precise microtube airflow optimization module which selects a special material to make a microtube with a smooth inner wall, and is provided with an inlet guide and an internal turbulence device to construct an airflow channel, according to the invention, through meticulous design of the size of the microtube, inner wall processing and an airflow adjusting structure, it is ensured that airflow in the microtube is stable and efficient, an optical fiber can be effectively pushed to move forwards smoothly, construction stagnation caused by unsmooth airflow is reduced, and the construction quality is improved. Multi-dimensional data such as airflow parameters, equipment operation states and environment parameters in the micropipe are collected and analyzed in real time, operation parameters of all modules are dynamically adjusted according to preset rules and real-time conditions, instructions are accurately responded through a high-performance motor and an air pump, stable and adjustable power is provided, faults and delay in the construction process are reduced, and the construction efficiency is improved. And the optical fiber laying speed is accelerated.

Description

Technical Field

[0001] This invention relates to the field of optical fiber communication technology, specifically to a remotely coordinated intelligent microtube fiber blowing control system. Background Technology

[0002] In today's era of rapid information development, optical fiber communication, with its significant advantages such as large transmission capacity, long transmission distance, and strong anti-interference capability, has become a core component of modern communication networks. As a fundamental link in the construction of optical fiber communication networks, the efficiency and quality of optical fiber laying directly affect the performance and stability of the entire communication network. With the continuous growth of communication demands, optical fiber laying projects face increasingly higher requirements and challenges. Not only do they need to complete the laying task quickly in complex and ever-changing environments, but they also need to ensure that the transmission performance of the optical fiber reaches the optimal standard. Microtube blowing technology, as an advanced optical fiber laying method, lays optical fibers by blowing air into microtubes. It has advantages such as fast construction speed and low interference to the surrounding environment, and has been widely used in the field of optical fiber communication.

[0003] Traditional microtube fiber blowing technology has significant shortcomings in several aspects. Regarding microtube airflow control, the lack of in-depth research on the compatibility between microtube size and fiber outer diameter, as well as effective airflow adjustment methods, makes it difficult to maintain stable and efficient airflow within the microtube. This often leads to obstructions or even jamming during fiber advancement, severely impacting construction efficiency and quality. In terms of remote control, traditional technology lacks effective remote control capabilities, requiring construction personnel to adjust parameters and operate on-site. This not only increases construction difficulty and labor costs but also hinders collaborative operations between different construction points, reducing overall construction efficiency. Furthermore, traditional technology lacks precise measurement and adjustment mechanisms for fiber length control, easily leading to overuse or insufficient fiber laying, resulting in resource waste or failure to meet actual communication needs. These problems make traditional microtube fiber blowing technology unable to meet the high requirements of modern fiber optic communication network construction, necessitating an innovative intelligent control system to solve these challenges. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a remotely collaborative intelligent microtube fiber blowing control system. This system optimizes the microtube size, inner wall treatment, and airflow adjustment structure through a precision microtube airflow optimization module, achieving stable and efficient airflow control within the microtube. An AI intelligent analysis and decision-making module collects and analyzes data in real time, providing intelligent decision support for the system. A wireless remote communication and control module enables stable communication and remote control between the system and a remote control terminal. A power drive and auxiliary operation module provides stable power and auxiliary functions to ensure smooth fiber advancement. A cable length precision control and resource management module monitors fiber length in real time, enabling precise laying and effective resource management. This invention improves construction efficiency, enhances construction quality, enables remote collaborative operations, and saves resources, providing an efficient, precise, and remotely controllable solution for fiber optic communication construction.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a remotely coordinated intelligent microtube fiber blowing control system, which includes the following components: Precision microtube airflow optimization module: The microtube with a smooth inner wall is made of special material. An inlet guide and an internal turbulence device are set to build an airflow channel. The airflow parameters are controlled by sensors and valves to adapt to different fiber blowing requirements. AI Intelligent Analysis and Decision Module: Integrates multi-source data, extracts features after preprocessing, compares and evaluates the system status with the standard, generates decision instructions based on preset goals and rules, and compares and evaluates the system status with the standard model, generates decision instructions based on preset goals and rules, and monitors the execution effect. Wireless remote communication and control module: Customize and optimize the wireless communication protocol, select high-performance modules and adapt terminal software, consider the impact of environmental interference on signal strength and the correction of errors by error correction coding, and realize remote control command interaction and system status feedback. Power drive and auxiliary operation module: A high-precision servo motor is selected and configured with a drive control circuit, paired with a high-power air pump, air tank and optimized air circuit, and a vibration device with adjustable vibration parameters is installed. The influence of load changes on motor torque and the synergistic propulsion force of air blowing and vibration are considered to ensure fiber optic propulsion. Cable length precision control and resource management module: Uses high-precision measuring devices to measure length in real time, compares with target length to adjust drive parameters for precise length control, predicts resource consumption rate based on historical data and simulation experiments, establishes a database to manage fiber optic resources, dynamically allocates resources according to project needs and risks, and assists in decision-making.

[0006] Furthermore, the precision microtube airflow optimization module monitors and adjusts airflow parameters via sensors and regulating valves, and its parameter adjustment formula is as follows: ,in, It is the airflow regulation coefficient, used to adjust the opening degree of the airflow regulating valve. It is the speed deviation adjustment weighting coefficient. It is the highest flow velocity of the airflow inside the microtube. It is the current airflow velocity inside the microtube. It is the pressure deviation adjustment weighting coefficient. It is the current airflow pressure inside the microtube. It is the reference airflow pressure, which is an ideal pressure value determined based on experience or experiments.

[0007] Furthermore, the aforementioned It is the highest airflow velocity inside the microtube, and its calculation formula is: ,in, This is the fiber propulsion coefficient, which is related to the fiber material and surface roughness, reflecting the influence of the fiber's inherent properties on the required airflow velocity for propulsion. The outer diameter of the optical fiber affects its stress and propulsion in the airflow. It is the airflow pressure at the microtube inlet, which is the power source propelling the airflow and optical fiber forward. It is the dynamic viscosity of air, reflecting the viscous resistance characteristics of air. It is the length of the microtubule.

[0008] Furthermore, the AI ​​intelligent analysis and decision-making module installs pressure sensors, temperature sensors, and speed sensors inside the microtube, at the motor, and at the air pump to collect physical parameter data. It also incorporates image recognition technology, using high-definition cameras installed at the inlet and outlet of the microtube to collect the appearance and propulsion status of the optical fiber in real time. Simultaneously, it combines environmental sensors, including temperature and humidity sensors and air pressure sensors, to acquire surrounding environmental parameters. This multi-source data is fused and preprocessed to remove noise and outliers, and key feature information is extracted. This feature information is then compared and analyzed with pre-established standard datasets and empirical models to evaluate the current operating status and performance of the system. Based on the analysis results of the data features, combined with preset construction goals and rules, corresponding decision instructions are automatically generated.

[0009] Furthermore, the AI ​​intelligent analysis and decision-making module evaluates the current operating status and performance of the system using the following evaluation formula: ,in, It is a comprehensive evaluation indicator used to assess the current operating status and performance of the fiber blowing system. It refers to the speed at which the optical fiber is laid. The faster the speed, the longer the length of optical fiber can be laid in a given time. Energy efficiency refers to the energy consumed per unit length of optical fiber laid. It refers to the fiber damage rate, which is the proportion of damaged fiber length to the total length of fiber laid. It is an environmental adaptability indicator, reflecting the system's operational stability under different environmental conditions. , , , These are the weighting coefficients for each evaluation factor, adjusted according to different construction sites and needs, reflecting the importance of each evaluation factor in the comprehensive evaluation.

[0010] Furthermore, the power drive and auxiliary operation module uses a servo motor with high speed accuracy, high torque output, and fast response capability as the power source for fiber propulsion. A dedicated motor drive control circuit is designed, employing power electronic devices and control strategies to achieve precise control of motor speed and torque. By receiving control commands, the motor power is adjusted in real time. A high-power, high-flow air compressor is provided as the air source for the air blowing unit, and a large-capacity air tank is also provided to ensure stable air blowing pressure during fiber blowing. Pressure and flow sensors are installed at key locations in the air path to monitor and adjust the air blowing pressure and flow in real time. In addition, a novel vibration device is designed, using electromagnetic drive or eccentric wheel drive principles to generate vibrations of different frequencies and amplitudes. The vibration frequency and amplitude of the vibration device are adjusted by the control system. Based on the fiber propulsion and the structural characteristics of the microtube, the vibration parameters are adjusted in real time to achieve the best auxiliary effect.

[0011] Furthermore, the power drive and auxiliary operation module receives control commands and adjusts the motor power in real time, using the following adjustment formula: ,in, This is the adjusted motor power, which is dynamically adjusted according to actual conditions. This is the motor's base power, the power value of the motor under initial settings. It is the resistance change adjustment coefficient. It is the difference between the current propulsion drag and the foundation propulsion drag. It is a fundamental obstacle to advancement. It is a temperature change adjustment coefficient. It is the difference between the current ambient temperature and the baseline ambient temperature. It is the base ambient temperature.

[0012] Furthermore, the power drive and auxiliary operation module monitors and adjusts the air blowing pressure and flow rate in real time, and its air blowing pressure adjustment formula is as follows: ,in, It is the air-blowing characteristic coefficient, obtained by conducting experiments on the air pump and air piping system, measuring pressure values ​​at different flow rates, and fitting the data. It refers to the airflow rate, which is measured using a flow sensor. It is the cross-sectional area of ​​the trachea.

[0013] Furthermore, the cable length precision control and resource management module predicts the resource consumption rate based on historical data and simulation experiments, and its prediction formula is as follows: ,in, It is the fiber optic resource consumption rate, predicting the rate at which fiber optic resources will be consumed over a future period of time. In the time interval The length of optical fiber used internally, It is a time interval. This is the resource resistance influence coefficient, which reflects the impact of changes in fiber propulsion resistance on the consumption rate. It is the difference between the current propulsion drag and the average propulsion drag. It is the average propulsion resistance.

[0014] Compared with existing technologies, this remote collaborative intelligent microtube fiber blowing control system has the following advantages: I. This invention, through meticulous design of the microtube size, inner wall treatment, and airflow regulation structure, ensures stable and efficient airflow within the microtube, effectively propelling the optical fiber smoothly forward, reducing construction delays caused by airflow obstruction, and collecting and analyzing multi-dimensional data such as airflow parameters, equipment operating status, and environmental parameters within the microtube in real time. Based on preset rules and real-time conditions, it dynamically adjusts the operating parameters of each module, providing stable and adjustable power through high-performance motors and air pumps that precisely respond to commands, reducing malfunctions and delays during construction, accelerating optical fiber laying speed, thereby significantly shortening construction time and improving overall construction efficiency.

[0015] Second, this invention effectively avoids the waste of optical fiber resources and reduces construction costs through precise cable length control and resource management capabilities. By employing a high-precision length measuring device, the system monitors the optical fiber laying length in real time and accurately compares it with the preset target length to ensure that the optical fiber laying length accurately meets the standard. At the same time, the module statistically analyzes the optical fiber usage in real time, recording the laying length and remaining length of each optical fiber segment in detail. Once insufficient remaining optical fiber length is detected, the system will immediately issue an alarm to remind construction personnel to replenish it in time, effectively avoiding the overuse of optical fiber due to improper length control, realizing the rational utilization and conservation of resources, and reducing construction costs.

[0016] Other advantages, objectives and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination or study, or may be learned from the practice of the invention. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0018] Figure 1 A schematic diagram of a remotely collaborative intelligent microtube fiber blowing control system; Figure 2 This is a flowchart of a remotely collaborative intelligent microtube fiber blowing control system. Detailed Implementation

[0019] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0020] Example 1 In urban communication network upgrade and renovation projects, a large number of optical fibers need to be laid in the existing underground pipeline network to meet the growing demand for high-speed data transmission. However, the underground pipeline environment is extremely complex, with many bends and branches, and the pipeline lengths vary. Some areas also have problems such as old pipeline damage and narrowness. This places high demands on optical fiber laying technology. At the same time, due to the scarcity of urban underground space resources, it is also necessary to minimize the impact on the surrounding environment and other underground facilities during the construction process.

[0021] High-strength, low-friction composite microtubes are selected. This material not only has good flexibility, which can adapt to the bending and deformation of underground pipelines, but also has excellent corrosion resistance, allowing for long-term stable use in underground humid and acidic / alkaline environments. The inner wall of the microtube is processed with special precision technology to control its surface roughness to an extremely low level, which can effectively reduce the resistance to fiber propulsion. A trumpet-shaped airflow guide device is set at the inlet of the microtube. Its unique design can guide the external airflow into the microtube evenly and stably, avoiding turbulence at the inlet. At the same time, carefully designed airflow baffles are installed at certain intervals along the axis inside the microtube. The shape and angle of these baffles have been optimized through multiple simulations and experiments, which can enable the airflow to form a stable spiral flow pattern inside the microtube, thereby better wrapping and propelling the optical fiber forward.

[0022] High-precision sensors installed at different locations (inlet, middle section, and outlet) of the microtube monitor airflow pressure and velocity in real time. These sensors are characterized by high precision and high sensitivity, and can quickly and accurately reflect changes in airflow parameters. The flow rate and pressure of the airflow entering the microtube are precisely adjusted by a regulating valve. The regulating valve adopts advanced intelligent control technology and can automatically adjust its opening degree based on the information fed back by the sensors.

[0023] When determining the optimal airflow velocity within the microtube, the formula is used. Among them, the fiber propulsion coefficient The values ​​were derived through multiple simulated fiber blowing experiments on optical fibers of different materials and surface treatments, combined with experimental data fitting and analysis. These values ​​will vary depending on the characteristics of the optical fiber, including its outer diameter. The airflow pressure at the microtube inlet was directly measured using high-precision measuring tools. The dynamic viscosity of air is obtained in real time by a pressure sensor installed at the inlet. The microtube length was calculated based on environmental temperature and humidity conditions. It is then determined by accurate measurement using measuring tools.

[0024] According to the calculation Combined with real-time monitoring of the current airflow velocity inside the microtube and the reference airflow pressure determined through numerous experiments and experience. and real-time monitoring of the current airflow pressure inside the microtube Using the airflow regulation coefficient formula To adjust the airflow, for weight and The determination was first made by building a simulated fiber blowing system in a laboratory environment and conducting multiple tests under different conditions. and Experiments were conducted using value combinations to observe the time required for airflow velocity and pressure within the microtube to reach a steady state, as well as the fluctuations after stabilization. The combination that resulted in the fastest stabilization and minimal fluctuations was selected as the initial weight. During actual installation, if significant fluctuations in airflow velocity were observed, it indicates that the current... The value may be too small; the system will automatically increase it appropriately. This enhances the adjustment capability against speed deviations; if pressure fluctuations are significant, the adjustment should be increased accordingly. Meanwhile, the system continuously collects data from the actual fiber blowing process, and through long-term data analysis, identifies the factors that optimize the overall performance of the system. and The weights are continuously optimized and adjusted within a certain range to ensure stable airflow within the microtube and provide a favorable propulsion environment for optical fibers.

[0025] Multiple high-precision sensors, including pressure, temperature, and speed sensors, are installed in key components such as the microtube, motor, and air pump. Simultaneously, high-definition cameras and environmental monitoring equipment collect multi-source data. The high-definition cameras capture the real-time appearance of the optical fiber, detecting defects such as bending and wear. The environmental monitoring equipment monitors parameters such as temperature, humidity, and air pressure in the surrounding environment. The collected data is preprocessed to remove noise and outliers, and then key feature information is extracted using advanced data mining and analysis algorithms. These features are compared and analyzed with standard datasets to evaluate the system's current operating status and performance. When the optical fiber is obstructed or an abnormality is detected, the system automatically generates decision commands to adjust parameters such as motor speed and air pressure. For example, when a slight bend is detected in the optical fiber, the system automatically increases the weight of the optical fiber defect factor and adjusts other parameters accordingly to ensure the optical fiber can pass smoothly through the area.

[0026] The wireless remote communication and control module was customized with a wireless communication protocol suitable for this project. This protocol was optimized for the characteristics of the urban underground environment, featuring high reliability and low latency. A 4G communication module was selected for remote communication. Considering the weak signal in some underground areas of the city, signal enhancement processing was performed on the communication module. Based on the construction site environment and communication distance requirements, the transmission power and antenna position were reasonably configured. Simulation tests were conducted using professional signal simulation software to ensure that the signal could cover the entire construction area. Dedicated control software was installed on the remote control terminal. This software has a user-friendly interface, allowing construction personnel to monitor and operate the system in real time. The software interface is simple and intuitive, displaying various parameters and equipment status in real time. Construction personnel can adjust parameters and control equipment by clicking with a mouse or touching the screen.

[0027] The power drive and auxiliary operation module uses a high-speed, high-precision, high-torque servo motor as its power source. This servo motor features fast response and high-precision control, enabling it to quickly adjust speed and torque according to system commands. A dedicated drive control circuit is designed to achieve precise control. The drive control circuit adopts advanced digital signal processing technology, which can monitor the motor's operating status in real time and make adjustments as needed. It is equipped with a high-power air compressor and air tank, optimizes the air circuit system, and installs a high-efficiency filter to ensure stable and clean air blowing pressure. In addition, an adjustable vibration assist device is set up to adjust the vibration frequency and amplitude in real time according to the fiber optic cable advancement. The vibration assist device uses electromagnetic drive technology to generate vibrations of different frequencies and amplitudes. When the fiber optic cable encounters significant resistance or when there are bends or narrow sections in the microtube, the vibration assist device is activated in time to help the fiber optic cable pass smoothly.

[0028] When adjusting motor power, use the motor power adjustment formula. Among them, the basic power The difference between the current propulsion resistance and the basic propulsion resistance is determined by the model and specifications of the selected servo motor. The foundation propulsion resistance is measured and calculated in real time by force sensors installed at relevant locations. This is obtained by recording the initial resistance during fiber propulsion in a normal fiber blowing experiment, and the difference between the current ambient temperature and the base ambient temperature. The base ambient temperature is measured and calculated in real time by a temperature sensor. The weights were recorded at the beginning of the experiment. and First, theoretical calculations are used to determine the theoretical impact of propulsion resistance and ambient temperature changes on motor power, based on the motor's physical characteristics and mechanical principles. Preliminary values ​​are then derived. In actual operation, the motor's built-in sensors monitor changes in power, resistance, and temperature in real time. Based on this real-time data, the system automatically adjusts... and The system will periodically evaluate the motor's operating performance, such as its efficiency and heat generation. If the motor is found to be inefficient or overheating under certain operating conditions, it indicates that the current weight settings may be unreasonable, and the system will adjust accordingly. and Adjustments were made to ensure sufficient power for fiber propulsion. When determining the air blast pressure, a formula for matching air blast pressure and flow rate was used. Among them, the air blowing characteristic coefficient Experiments were conducted on the air pump and air tubing system to measure pressure values ​​at different flow rates. The air blowing flow rate was then obtained by fitting the data. The cross-sectional area of ​​the air tube can be measured using a flow sensor installed in the air circuit. Based on the dimensions of the air tube, a geometric formula is used to calculate the required pressure. The system then adjusts the operating status of the air pump according to the calculation results to provide the appropriate air blowing pressure.

[0029] The cable length precision control and resource management module employs a high-precision length measuring device based on laser ranging principles. This device features high precision and stability, enabling real-time measurement of fiber optic cable laying length. The system compares the measured data with a preset target length and automatically adjusts power parameters as it approaches the target, achieving precise control. During the measurement process, considering the bending and irregularities of underground pipelines, the system corrects the measurement data to ensure accuracy. A fiber optic resource management database is established to record fiber optic usage and inventory status. This database utilizes an advanced database management system, allowing for real-time updates and queries of fiber optic information. Based on historical data and simulation experiments, the system predicts fiber optic resource consumption rates and continuously optimizes based on actual consumption, rationally allocating fiber optic replenishment to avoid resource waste. The prediction formula... , where, in the time interval Fiber optic length used inside The time interval is obtained by recording the fiber lengths at the beginning and end of the time interval using a length measuring device and then subtracting the two lengths; The resource resistance impact coefficient is determined by the system's clock records. First, by analyzing historical data, the rate of optical fiber resource consumption under different propulsion resistances was statistically analyzed. Then, combined with simulation results, the difference between the current propulsion resistance and the average propulsion resistance was preliminarily determined. The average propulsion resistance is obtained by measuring the current propulsion resistance using a force sensor and subtracting it from the average propulsion resistance. It is obtained by statistically averaging the propulsion resistance measurements over a period of time. During the project implementation, through real-time monitoring and analysis of fiber optic usage, the system can predict the remaining amount of fiber optics in advance and issue timely replenishment reminders to ensure the smooth progress of the project.

[0030] Example 2 In the construction of wind farms in mountainous areas, with the increasing number of wind turbine units and the demand for intelligent management, it is necessary to lay communication optical cables to connect each wind turbine unit and the control center. Mountainous terrain is complex, with large undulations, including many steep slopes, deep canyons, and dense forests. At the same time, the climate is extremely changeable, with frequent severe weather such as strong winds, rainstorms, and lightning. These factors have brought great challenges to the laying of optical cables. In addition, due to the fragile ecological environment in mountainous areas, environmental protection requirements must be strictly followed during construction to minimize damage to the natural environment.

[0031] To address the complex and harsh environment of mountainous areas, a highly flexible microtube material was selected. This material not only bends naturally with the terrain in areas with significant elevation changes, reducing the risk of breakage or damage, but also possesses excellent UV resistance and weather resistance, maintaining stable performance under extreme climatic conditions such as prolonged exposure to wind, sun, rain, and frost. The inner wall of the microtube undergoes special treatment to achieve an extremely high level of surface smoothness, significantly reducing friction during fiber optic cable deployment. To adapt to the diverse terrain of mountainous areas, the airflow guidance and turbulence structure within the microtube were optimized. At the microtube inlet, an airflow guide device with a specific angle and shape is installed, effectively guiding external airflow smoothly into the microtube based on different terrain slopes and wind directions. To avoid airflow turbulence, a series of airflow deflectors with shapes and angles optimized through multiple trials are rationally arranged inside the microtube. The arrangement and placement of these deflectors fully consider the complexity of mountainous terrain. For example, when passing through valleys or other areas with strong winds, the deflectors can make the airflow form a more stable and powerful spiral flow pattern, better wrapping and propelling the optical cable forward. Throughout the laying process, high-precision sensors installed at different locations (inlet, middle section, and outlet) of the microtube monitor the airflow pressure and velocity in real time and accurately. Intelligent regulating valves are used to precisely regulate the airflow and pressure entering the microtube. The regulating valves can automatically adjust their opening based on real-time data from the sensors to ensure that the airflow inside the microtube is always in a stable and suitable state.

[0032] Various types of high-precision sensors, including pressure sensors, temperature sensors, speed sensors, humidity sensors, and air pressure sensors, are installed inside the microtubes, in key components such as motors and air pumps, and in the surrounding environment. High-definition cameras are also placed at important locations to capture the real-time appearance of the optical cable, such as for defects like bends, wear, and scratches, as well as the cable's progress. The collected multi-source data undergoes preprocessing to remove noise and outliers, ensuring accuracy and reliability. Data mining techniques are used to extract key features from the data, which are then compared and analyzed against pre-established standard datasets and empirical models to accurately assess the system's current operating status and performance. When anomalies are detected, the system can quickly and accurately generate corresponding decision commands, adjusting motor speed, air pressure, and vibration assist device parameters in a timely manner to cope with various complex situations and ensure the smooth progress of the laying process.

[0033] The wireless remote communication and control module takes into full account the complex terrain of mountainous areas, the susceptibility of signals to obstruction and interference, and the extremely weak communication signals in some areas. It adopts LoRa communication technology, which has advantages such as low power consumption, long-distance communication, and strong penetration capabilities, enabling stable signal transmission in mountainous environments. To further optimize communication performance, the communication protocol has been specially customized. This protocol has undergone several optimizations for the special environment of mountainous areas, such as adding signal error correction and retransmission mechanisms to improve the reliability of data transmission. Furthermore, specially developed control software is installed on the remote control terminal. This software has a simple, intuitive, and easy-to-use user interface, allowing construction personnel to monitor the system's operating status in real time, including parameters of various equipment, fiber optic cable laying progress, environmental parameters, etc. Simultaneously, it enables convenient operation of various functions, such as adjusting equipment parameters and starting or stopping equipment.

[0034] The power drive and auxiliary operation module utilizes a high-performance motor specifically designed for harsh environments. This motor boasts excellent heat dissipation and protection levels, enabling stable operation in harsh conditions such as high temperatures, high humidity, and sandstorms in mountainous areas. It also features high speed accuracy and high torque output, allowing for rapid and accurate adjustment of speed and torque according to system commands, providing powerful and stable power for fiber optic cable propulsion. A drive control circuit employs digital signal processing technology and intelligent control algorithms. This circuit monitors the motor's operating status in real time, including parameters such as current, voltage, speed, and temperature, and makes precise adjustments based on actual conditions. Furthermore, it is equipped with overcurrent, overvoltage, overheat, and overload protection mechanisms. It features multiple protection functions to ensure the motor operates within a safe range. It is equipped with a high-power, high-flow air compressor and air tank to provide a stable air source for the air-blowing unit. The air circuit system has been comprehensively optimized, using high-strength, corrosion-resistant air pipes and connectors to ensure the air circuit's sealing and reliability. Additionally, it is equipped with a flexibly adjustable vibration assist device. This device uses advanced electromagnetic drive technology to generate vibrations of different frequencies and amplitudes. Depending on the fiber optic cable's progress and the characteristics of the mountainous terrain, such as when passing through areas with many rocks or rugged terrain, the control system adjusts the vibration frequency and amplitude of the vibration assist device in real time to help the fiber optic cable smoothly pass through these difficult sections.

[0035] The cable length precision control and resource management module employs a length measurement device based on a high-precision encoder counting principle. This device boasts extremely high measurement accuracy and stability, enabling real-time and accurate measurement of the cable laying length. Considering the complexity of mountainous terrain, the system performs special processing on the measurement data, correcting for measurement errors caused by terrain undulations and bends to ensure the accuracy of the measurement results. Furthermore, a comprehensive optical cable resource management database has been established, recording detailed information for each roll of optical cable, such as brand, specifications, length, production date, batch number, usage status (including used length, remaining length, location, and usage time), and inventory status (such as inventory quantity and storage location). During project implementation, the system precisely compares the real-time measured cable laying length with the preset target length. When the cable laying length approaches the target length, the system automatically adjusts relevant parameters of the power drive and auxiliary operation modules, such as reducing motor speed and air blowing pressure, gradually slowing down the cable's advance speed to achieve precise control of the cable length.

[0036] In analyzing the consumption rate of optical cable resources, in-depth analysis of historical data and simulation experiments under different terrain and climate conditions accurately predict the consumption rate of optical cable resources. Based on the consumption rate, a reasonable plan for replenishing optical cables is arranged, avoiding waste and shortage of optical cables and ensuring the smooth progress of the project. At the same time, a detailed statistical analysis of the use of optical cables provides a strong reference for subsequent project planning and resource management.

[0037] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A remote collaborative intelligent micro tube blowing control system, characterized in that, The system comprises the following components: Precise micro-tube airflow optimization module: Select special materials to make the inner wall of the micro-tube smooth, set up an inlet guide and internal turbulence device to build an airflow channel, monitor and adjust the valve to control the airflow parameters through the sensor, so that it can adapt to different fiber blowing needs; AI intelligent analysis and decision-making module: Fusion of multi-source data, feature extraction after preprocessing, comparison with standard evaluation system state, generation of decision-making instructions based on preset goals and rules, comparison with standard model to evaluate system state, generation of decision-making instructions based on preset goals and rules and monitoring of execution effect; Wireless remote communication and control module: Customized and optimized wireless communication protocol, high-performance modules and terminal software, consideration of environmental interference on signal strength and error correction coding on error correction, implementation of remote control instruction interaction and system state feedback; Power drive and auxiliary operation module: Select high-precision servo motor and configure drive control circuit, match high-power air pump, gas tank and optimized gas path, install adjustable vibration parameters vibration device, consider the influence of load change on motor torque and the synergistic propulsion force of air blowing and vibration, ensure fiber propulsion; Cable length precise control and resource management module: Use high-precision measuring device to measure length in real time, compare target length to adjust drive parameters to control length accurately, predict resource consumption rate based on historical data and simulation experiment, establish database to manage optical fiber resources, dynamically allocate resources according to project demand risk and assist decision-making.

2. A remote collaborative intelligent tube blowing control system according to claim 1, wherein, The precise micro-pipe airflow optimization module monitors and adjusts the valve to control the airflow parameters through the sensor, and the parameter adjustment formula is: Wherein, is the airflow adjustment coefficient, used to adjust the opening of the airflow adjustment valve, is the speed deviation adjustment weight coefficient, is the highest flow rate of the airflow in the micro-pipe, is the current airflow speed in the micro-pipe, is the pressure deviation adjustment weight coefficient, is the current airflow pressure in the micro-pipe, is the reference airflow pressure, which is an ideal pressure value determined by experience or experiment.

3. A remote collaborative intelligent tube blowing control system as claimed in claim 2, wherein, The is the maximum flow rate of airflow in the microtube, and its calculation formula is: wherein, is the fiber propulsion coefficient, which is related to the fiber material and surface roughness, and reflects the influence of the fiber's own characteristics on the required airflow speed for propulsion, is the outer diameter of the fiber, which affects the stress and propulsion of the fiber in the airflow, is the airflow pressure at the microtube inlet, which is the source of power to drive the airflow and the fiber forward, is the dynamic viscosity of air, reflecting the viscous resistance characteristics of air, is the length of the microtube.

4. A remote collaborative intelligent tube blowing control system as claimed in claim 1, wherein, The AI intelligent analysis and decision-making module installs pressure sensors, temperature sensors and rotation speed sensors at the micro-tube, motor and air pump parts to collect physical parameter data, introduces image recognition technology, installs high-definition cameras at the micro-tube inlet and outlet to collect the appearance state and propulsion of the optical fiber in real time, combines environmental sensors including temperature and humidity sensors and air pressure sensors to obtain surrounding environmental parameters, processes these multi-source data, removes noise and outliers, extracts key feature information from the data, compares the feature information with the pre-established standard data set and experience model for analysis, evaluates the current running state and performance of the system, generates corresponding decision-making instructions based on the analysis results of the data features and the preset construction goals and rules.

5. A remote collaborative intelligent tube blowing control system as claimed in claim 4, wherein, The AI intelligent analysis and decision module evaluates the current running state and performance of the system, and the evaluation formula is: Wherein, is a comprehensive evaluation index for evaluating the running state and performance of the current fiber blowing system, is the advancing speed of the optical fiber, the faster the speed, the longer the length of the optical fiber laid in a certain time, is the energy consumption efficiency, the energy consumed for laying a unit length of optical fiber, is the damage rate of the optical fiber, that is, the proportion of the damaged optical fiber length to the total laid optical fiber length, is an environmental adaptability index reflecting the running stability of the system under different environmental conditions, , , , The weight coefficients of each evaluation factor are respectively adjusted according to different construction sites and requirements, reflecting the importance of each evaluation factor in the comprehensive evaluation.

6. A remote collaborative intelligent tube blowing control system as claimed in claim 1, wherein, The power drive and auxiliary operation module selects a servo motor with high rotation speed precision, large torque output and fast response capability as the power source of the optical fiber pushing, and designs a special motor drive control circuit, adopts power electronic devices and control strategy to realize accurate control of the motor rotation speed and torque, adjusts the power of the motor in real time through receiving control instructions, and is equipped with a high-power and high-flow air compressor as the air source of the air blowing unit, and a large-capacity air tank is arranged to ensure that stable air blowing pressure can be provided during the fiber blowing process. At the same time, pressure sensors and flow sensors are installed at key positions of the air path to monitor the air blowing pressure and flow in real time and adjust them in real time. In addition, a new type of vibration device is designed, which adopts electromagnetic drive or eccentric wheel drive principle to generate vibrations of different frequencies and amplitudes, and adjusts the vibration frequency and amplitude of the vibration device through the control system. According to the pushing situation of the optical fiber and the structural characteristics of the micro tube, the vibration parameters are adjusted in real time to achieve the best auxiliary effect.

7. A remote collaborative intelligent tube blowing control system as claimed in claim 6, wherein, The power driving and auxiliary operation module adjusts the power of the motor in real time by receiving control instructions, and the adjustment formula is: Wherein, is the adjusted motor power, which is dynamically adjusted according to the actual situation, is the basic power of the motor, which is the power value of the motor under the initial setting, is the resistance change adjustment coefficient, is the difference between the current propulsion resistance and the basic propulsion resistance, is the basic propulsion resistance, is the temperature change adjustment coefficient, is the difference between the current environmental temperature and the basic environmental temperature, is the basic environmental temperature.

8. A remote collaborative intelligent tube blowing control system as claimed in claim 1, wherein, The power driving and auxiliary operation module monitors and adjusts the air blowing pressure and flow in real time, and the air blowing pressure adjustment formula is: wherein, is the air blowing characteristic coefficient, by experiment on the air pump and air pipe system, measuring the pressure value under different flow, fitting the data to get, is the air blowing flow, using the flow sensor to measure the air blowing gas flow, is the cross-sectional area of the air pipe.

9. A remote collaborative intelligent tube blowing control system as claimed in claim 1, wherein, The cable length precision control and resource management module predicts the resource consumption rate based on historical data and simulation experiments. The prediction formula is as follows: ,in, It is the fiber optic resource consumption rate, predicting the rate at which fiber optic resources will be consumed over a future period of time. In the time interval The length of optical fiber used internally, It is a time interval. This is the resource resistance influence coefficient, which reflects the impact of changes in fiber propulsion resistance on the consumption rate. It is the difference between the current propulsion drag and the average propulsion drag. It is the average propulsion resistance.

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