Vegetation bag slope protection engineering construction digital production management system

Abstract

The invention relates to the technical field of slope protection ecological environment protection, in particular to a digital production management system for vegetation bag slope protection engineering construction. The system comprises the following modules: a construction preparation module used for inputting and storing measurement and calculation data; the construction stage module is used for respectively outputting control signals and receiving feedback data according to a preset operation process; the operation process comprises the steps of topsoil field building, smashing and screening, planting soil mixing, plant-growing bag packaging, plant-growing bag conveying and stacking, stacking operation point position setting, plant-growing bag unloading control and plant-growing bag conveying and stacking control. The quality control module is used for receiving the quality detection data and judging whether laying meets preset requirements or not according to the quality detection data; the data management module is used for storing data of other modules and performing analysis based on the stored data; and the maintenance module is used for data storage and control output in the maintenance stage. And the construction efficiency of the vegetation bag slope protection project is improved through the system and matched construction operation machinery.

Description

Technical Field

[0001] The present invention relates to the technical field of slope ecological environment protection, in particular to a digital production management system for the construction of vegetation bag slope protection projects. Background Art

[0002] During the construction of highways, slope protection is an important link to ensure highway safety. Traditional slope protection methods mainly include shotcrete slope protection, concrete slope protection, and vegetation slope protection, etc. Among them, vegetation slope protection has been receiving increasing attention due to its environmental protection and aesthetic advantages. Vegetation bag slope protection is a new type of vegetation slope protection method, which has advantages such as preventing soil erosion and enhancing slope stability. However, the traditional construction method of vegetation bag slope protection has problems such as low construction efficiency, high labor intensity, and high management difficulty. There is an urgent need for an efficient mechanized construction production management method and system to improve construction efficiency and management level.

[0003] The patent "Assembled Ecological Slope Protection System and Construction Method" (Publication No. CN116043878A) is disclosed in the prior art. This solution discloses an assembled ecological slope protection system and construction method. The system includes a plurality of herbaceous vegetation belts and a plurality of shrub vegetation belts, which are arranged alternately in sequence, and a plurality of hydrophobic channels are constructed at intervals along the transverse direction of the slope protection. A plurality of self-controlled filtering units are installed at intervals along the extension direction in each of the hydrophobic channels. The middle parts of each herbaceous vegetation belt and each shrub vegetation belt between the two hydrophobic channels arch upward along the slope surface. The two sides of each herbaceous vegetation belt and shrub vegetation belt extend obliquely from their respective middle parts to the hydrophobic channels on both sides; the method mainly completes the construction of the above system through equipment and manual labor. This invention ensures that the vegetation on the slope has high drought and waterlogging resistance, and avoids the problem of soil erosion on the slope protection when the precipitation is large. At the same time, it can improve the water retention capacity of the slope protection and increase the nutrients of the slope protection.

[0004] The patent "Ecological shotcrete and anchor protection structure and construction method with reverse installation of vegetation bags in reserved holes" (Publication No. CN116290028A) provides an ecological shotcrete and anchor protection structure and construction method with reverse installation of vegetation bags in reserved holes. The high-steep rocky slope is divided into upper, middle and lower three-level slopes. The top-level slope adopts U-shaped anchor bolt mesh cover steel bars combined with thick base materials of tubular vegetation belts for slope ecological protection, so that the thick base materials of tubular vegetation belts are closely attached to the original slope surface, reducing the load of the top slope and avoiding the falling of vegetation bags and the vegetation base materials for spraying due to gravity and rainfall scouring; the bottom-level slope and the middle-level slope both adopt anchor frame beams combined with steel pressing frames to fix the vegetation bags for slope ecological protection, avoiding the problem that the vegetation bags are easy to slide along the slope under the action of gravity and rainwater; reserved holes and drainage structures are provided in each slope layer, providing sufficient growth space for plant roots while timely discharging the seepage water and rainwater in the slope, improving the survival rate of plants, having good slope protection effect, low cost and high safety, and achieving good technical and economic benefits.

[0005] The defect of the above public solution is that it only gives a method to solve local problems, lacks systematicness for the vegetation bag slope protection project, needs to consider the characteristics of highway slopes and give adaptive improvements, and there is a lack of information means in the existing methods. The construction of vegetation bags mainly relies on manual labor, and there are problems such as low efficiency and high cost of manual bagging operation, large labor intensity in the manual stacking process, uncontrollable stacking quality, complex on-site conditions, and large management difficulty in the operation area. Summary of the Invention

[0006] In order to improve the construction efficiency of vegetation bags on highway slopes, reduce the cost of vegetation bag layout, and reduce the management difficulty, a digital production management system for the construction of vegetation bag slope protection project is proposed to conduct full digital management on the construction process of vegetation bags.

[0007] In order to achieve the above purpose, the following technical solutions are proposed: A digital production management system for the construction of vegetation bag slope protection project, including: A construction preparation module for inputting measurement data; A construction stage module that outputs control signals respectively according to the pre-set operation process and receives feedback data; the operation process includes: establishing a topsoil yard, crushing and screening, mixing planting soil, packaging vegetation bags, conveying and stacking vegetation bags, setting stacking operation points, controlling the unloading of vegetation bags, and controlling the conveying and stacking of vegetation bags; A quality control module for receiving quality inspection data and judging whether the laying meets the preset requirements according to the quality inspection data; A maintenance module for storing data in the maintenance stage and controlling output; A data management module for storing the data of other modules and analyzing based on the stored data.

[0008] As an optimal solution, the construction preparation module receives the input survey data and calculates the construction area, slope information (such as slope, length, width, side arc, etc.), earthwork volume, the number of vegetation bags required, the best positions and best paths of operation areas such as the topsoil yard crushing and screening area, and the estimated construction time.

[0009] As an optimal solution, the construction area includes a topsoil stacking area, a crushing operation area, a screened soil material stacking area, a vegetation bag loading and transporting area, a planting soil mixing area, a vegetation bag weighing, packaging and sealing area, and an automatic conveying and stacking area.

[0010] As an optimal solution, the construction stage module is used to record the number of bags filled, weight, and time during the vegetation bag weighing and packaging stage; record the operation points and transportation trajectories during the vegetation bag transport vehicle loading and transfer stage; during the unloading stage, it is used to control the loading and unloading equipment to place the vegetation bags at the end of the conveyor belt; during the vegetation bag conveying and stacking control stage, it is used to calculate the grasping speed and quantity according to the stacking speed and the moving speed of the operation vehicle.

[0011] As an optimal solution, the construction stage module and the conveying and stacking vehicle cooperate to complete the following steps: The system assigns operation tasks, and the conveying and stacking vehicle arrives at the operation area according to the position coordinates of the operation area; The turntable of the conveying and stacking vehicle rotates to adjust the conveyor belt to a preset position, and the rotation angle of the turntable meets the preset working requirements; The hydraulic cylinder of the conveying and stacking vehicle extends to adjust the angle of the conveyor belt so that the conveyor belt reaches the preset working angle; the extension length L1 is determined according to the actual operation requirements; The telescopic conveyor belt of the conveying and stacking vehicle extends, and the extension length L2 meets the requirement of being able to convey the vegetation bags to the designated stacking position; The rear feeding conveyor belt is adjusted to an appropriate angle α to ensure that the vegetation bags can be conveyed from the rear feeding conveyor belt to the telescopic conveyor belt; The vegetation bags are conveyed at a speed v at the feeding end, and the vegetation bags are manually assisted to be stacked at the discharging end. After one bag is stacked, the transverse trolley automatically traverses a bag distance d1 and continues to stack until the stacking of a transverse section is completed; The telescopic conveyor belt retracts by a length L3 to meet the operation requirements of transverse stacking, and the stacking operation is completed in sequence until the operation of this working area is completed; the retraction length L3 is determined by the number of rows and spacing of the stacking; When the telescopic conveyor belt is completely retracted and there are no vegetation bags being conveyed on the conveyor bag, the angle of the feeding end conveyor belt is restored to the initial state; The oil cylinder retracts, causing the telescopic conveyor bag to fall onto the mounting frame, and the extension length L1 of the hydraulic cylinder becomes 0; The turntable rotates back to the original position. At this time, the rotation angle θ1 of the turntable becomes 0, and the translation trolley returns to the initial position, and the moving distance d2 of the translation trolley becomes 0; After completing the folding and playback work of the equipment, the vehicle starts and moves forward to the next working site.

[0012] As a preferred solution, it further includes a fault monitoring system for the equipment. The fault monitoring system for the equipment includes mechanical component monitoring, electrical system monitoring, and safety protection device monitoring; the mechanical component monitoring includes conveyor belt status monitoring, turntable monitoring, hydraulic cylinder monitoring, telescopic belt conveyor monitoring, and rear-end feeding belt conveyor monitoring; the electrical system monitoring includes motor monitoring and electrical control system monitoring; the safety protection device monitoring includes emergency stop device monitoring, anti-slip protection monitoring, overload protection monitoring, and safety protection device monitoring.

[0013] As a preferred solution, the maintenance module is used for ecological restoration of the wound surface of the vegetation bags on the highway slope, and the restoration method includes the following steps: S1, collect the growth condition parameters of the vegetation bags and construct a vegetation bag growth data set; the growth condition parameters include vegetation bag parameters, maintenance parameters during the growth process of the vegetation bags, and environmental parameters; S2, calculate the ecological restoration contribution of the plants in each vegetation bag in the vegetation bag growth data set; the ecological restoration contribution includes the germination rate, greening degree, and ecological restoration weighted contribution index of the plants; S3, use the growth condition parameters as input parameters, use the ecological restoration contribution as output parameters, construct a training set, and input the training set into a pre-constructed highway construction wound surface repair analysis model for training to obtain an optimal highway construction wound surface repair analysis model; S4, input the predicted growth condition parameters into the optimal highway construction wound surface repair analysis model to obtain the predicted ecological restoration contribution, design a vegetation bag production plan and a vegetation bag maintenance plan according to the predicted ecological restoration contribution, and stack the vegetation bags on the road section corresponding to the environmental parameters.

[0014] As a preferred solution, the greening degree is the sum of the projected areas of the plant leaves per unit area.

[0015] As a preferred solution, the calculation steps of the weighted contribution index include: Count the types of plants per unit area; Calculate the contribution weighted index of each single plant of each type per unit area to the ecological restoration function of the wound surface of the slope vegetation bag during different time periods; the contribution weighted index is determined by the role of the plant in stabilizing the soil, improving the water and heat conditions, and restoring the ecological function; Add the product of the quantity of each type of plant per unit area and its corresponding weighted index to obtain the ecological restoration weighted contribution index.

[0016] As a preferred solution, the highway construction wound repair analysis model consists of three layers in total: 1 input layer, 1 output layer, and 3 fully connected hidden layers; The nodes of the input layer include the dosage of plant seeds, the dosage of growth additives, the amount of water for maintenance and replenishment, the amount of fertilizer for maintenance and topdressing, the height of the vegetation bag, and the width of the vegetation bag; The nodes of the output layer include the germination rate, the greening degree, and the weighted contribution index; The training steps of the highway construction wound repair analysis model include: Initializing the connection weights and thresholds; Calculating the outputs of each node in the hidden layer and the output layer according to the selected learning input mode; Calculating the new connection weights and thresholds; Updating the learning input mode, and according to the updated learning input mode, calculating the outputs of each node in the hidden layer and the output layer again until the number of training times reaches the set value.

[0017] Compared with the prior art, the beneficial effects of the present invention are as follows: The management system of the present invention solves the problems of high on-site manual labor intensity, low operation efficiency, and high costs; solves the problems of complex on-site operation environment and process flow and difficult management through a digital management system; improves the construction efficiency of the vegetation bag slope protection project through the process method and supporting construction machinery. Brief Description of the Drawings

[0018] Figure 1 It is a schematic flow chart of the method for ecological restoration of the wound surface of the vegetation bag on the highway slope of the present invention; Figure 2 It is a schematic structural block diagram of the system for ecological restoration of the wound surface of the vegetation bag on the highway slope of the present invention; Figure 3 It is a schematic topological structure diagram of the highway construction wound repair analysis model; Figure 4 It is an experimental data table obtained by using the method for ecological restoration of the highway construction wound surface. Detailed Embodiments

[0019] The present invention will be further described in detail below in conjunction with test examples and specific embodiments. However, it should not be understood that the scope of the above-mentioned subject matter of the present invention is limited to the following embodiments, and all technologies implemented based on the content of the present invention belong to the scope of the present invention.

[0020] Embodiment 1 The digital production management system for the construction of the vegetation bag slope protection project, the schematic flow chart is as Figure 1 shown, and includes: A construction preparation module for inputting measurement data; The construction stage module outputs control signals respectively according to the pre-set operation process and receives feedback data; the operation process includes: establishing a topsoil yard, crushing and screening, mixing planting soil, packaging vegetation bags, transporting and stacking vegetation bags, setting stacking operation points, controlling the unloading of vegetation bags, and controlling the transportation and stacking of vegetation bags. The quality control module is used to receive quality inspection data and judge whether the laying meets the preset requirements according to the quality inspection data. The maintenance module is used for data storage and control output during the maintenance stage. The data management module is used to store the data of other modules and perform analysis based on the stored data.

[0021] Furthermore, the quality control module also scans the slope where the vegetation bags have been stacked, records and compares data such as the slope and radian before and after stacking, the covering distance of each layer of vegetation bags, density, and the deviation between the actual stacking quantity and the system-predicted quantity, and judges whether the stacking meets the specific construction requirements. If not, the system gives a prompt for the area where the stacking quality does not meet the requirements.

[0022] 1. Construction preparation stage Generally speaking, this stage mainly realizes: surveying the construction site to determine the construction area and operation plan, surveying the site by drone to determine the construction area layout, and calculating key production information such as the area of the operation area, the amount of soil used, and the number of vegetation bags to be consumed according to the survey data.

[0023] Furthermore, the drone conducts aerial photography and scanning of the construction site by carrying equipment such as high-definition cameras and lidar. It cruises over the construction site at a preset flight path and altitude to obtain omnidirectional images and spatial data. The content of the survey data: topographic data, such as elevation information, slope, aspect, etc. The three-dimensional data of the terrain can be accurately obtained through lidar scanning. Boundary data, determining the boundary range of the construction site, including natural boundaries (such as rivers, mountains, etc.) and artificial boundaries (such as fences, walls, etc.). Obstacle data, such as the location and size of obstacles such as large stones, trees, and buildings that may affect the construction.

[0024] Determine the construction area layout according to the survey data and the initial design plan drawing. Let the area of the construction area be S, and obtain information such as the slope (i), aspect (a), etc. of the topographic data through surveying, and then calculate the area S of the operation area according to the topographic data and the surveyed boundary range.

[0025] Assume the length of the construction area is L and the width is W. For a regular area, S = L×W can be approximately obtained. Calculate the amount of soil used V according to the area S of the operation area and the average soil covering thickness H (determined by measuring the elevation difference at multiple representative locations in the construction area using the drone lidar). The relationship is V = S×H.

[0026] Let the volume of each vegetation bag be V bag , which is determined by the specifications of the vegetation bags. The number of vegetation bags N required is related to the soil usage volume V and the volume V of the vegetation bags bag by the relationship N = V÷V bag .

[0027] As an optimal solution, the standard construction area can be divided into a topsoil stacking area, a crushing operation area, a screened soil material stacking area, a vegetation bag shipping and loading area, a planting soil mixing area, a vegetation bag weighing, packaging and sealing area, and an automatic conveying and stacking area.

[0028] Prepare the required construction equipment and materials, including vegetation bags, mechanical equipment (such as soil crushers, packaging and sealing machines, transfer equipment, conveying and stacking equipment, and grass seed sowing equipment, etc.), and planting substrates, etc.

[0029] Establish a construction management system, input the measured data into the management system, and set various construction parameters and management authorities.

[0030] 2. Mechanized construction stage The standard operation process is as follows: (1) According to the situation around the construction site, establish a topsoil yard and collect topsoil; (2) The crushing operation area conducts crushing and screening according to appropriate particle sizes; (3) According to the soil conditions, supplement nutrients to the soil in the planting soil mixing area; (4) The vegetation bag weighing, packaging and sealing area uniformly bags the products (product standardization); (5) The vegetation bag transport vehicle loads the bagged vegetation bags; (6) Transfer to the stacking operation point and park beside the construction vehicle; (7) The unloading device grabs the vegetation bags and places them at the end of the conveyor belt; (8) Complete automatic conveying and stacking through the construction operation vehicle; (9) The construction operation vehicle completes the multi-column stacking of vegetation bags from low to high within the operation area; the construction vehicle moves forward to the next construction point for cyclic construction.

[0031] Furthermore, during the filling process of the vegetation bags, set the sensor technical parameters on the relevant equipment to automatically record, store and transmit real-time bagging quantity n, weight m, time t and other parameters. Assume that the bagging quantity per unit time is n / t, and the total bagging quantity is related to the number of vegetation bags N required for construction. As the construction progresses, n gradually approaches N.

[0032] During the transportation process, the position and speed information of the transport vehicle are monitored in real time. Let the speed of the transport vehicle be V1, and the position and speed information of the construction vehicle. Let the speed of the construction vehicle be V2. Automatically calculate the transportation time T between the two, and T = d÷(V1 + V2) (the two vehicles are moving towards each other) can be obtained according to the distance d between the two.

[0033] During the laying and fixing process, sensors and control systems are set up to automatically calculate the grasping speed and quantity according to the stacking speed V3 and the moving speed V2 of the vehicle. Let the grasping speed be V4 and the grasping quantity be q. The grasping speed and quantity interact with the stacking speed and the moving speed of the vehicle to jointly ensure the laying quality and efficiency, and ensure that the number of vegetation bags laid matches the required number N for construction.

[0034] In the intelligent monitoring system, the stacking quantity n stack 、time t stack and speed V3 and other information are recorded in real time, and a feedback control system is formed with the production parameters between the bagging system, the transport vehicle, and the construction vehicle. For example, the stacking quantity n stack is related to parameters such as the bagging quantity n, the transportation time T, and the moving speed V2 of the vehicle. Through feedback control, the production parameters of each system are automatically coordinated to achieve adaptive collaborative production.

[0035] Use mechanical equipment for filling the vegetation bags (control system part: set relevant sensor components to automatically record, store, and transmit real-time bagging quantity, weight, time and other parameters) and transportation (control system part: monitor the position and speed information of the transport vehicle and the construction vehicle in real time, and automatically calculate the transportation time between the two), reducing the labor intensity of workers.

[0036] Lay and fix the vegetation bags through automated equipment (control system part: set sensors and control systems to automatically calculate the grasping speed and quantity according to the stacking speed and the moving speed of the vehicle, and feedback control realizes real-time adaptive matching with the conveying and stacking processes), ensuring the laying quality and efficiency.

[0037] Use the intelligent monitoring system to monitor the construction progress and quality in real time (set sensors and control systems to record the stacking quantity, time, speed and other information in real time, and form a feedback control system with the production parameters between the bagging system, the transport vehicle, and the construction vehicle, and the production parameters of each system are automatically coordinated to achieve adaptive collaborative production), and adjust the construction plan in time.

[0038] 3. Quality control stage Use equipment such as sensors and drones to detect the construction quality to ensure that the laying of the vegetation bags meets the design requirements. Analyze the detection results and rectify problems in time.

[0039] Use devices such as sensors and drones to detect the construction quality, for example, detect indicators such as the flatness and tightness of the vegetation bags laid. Let the detection indicator be Q, which is related to factors such as the laying state of the vegetation bags and the design requirements. If the detection result does not meet the design requirements, make timely rectifications. During the rectification process, parameters such as the number of bags filled and the laying speed may be affected, thus being associated with the data in other stages.

[0040] 4. Data management stage Upload the construction data, quality inspection data, and management data to the construction management system for centralized management and analysis. Optimize the construction process through big data analysis to improve management efficiency.

[0041] Upload the construction data (such as the area S of the operation area, the volume V of the soil used, the number N of vegetation bags, etc.), quality inspection data (detection indicator Q, etc.), and management data to the construction management system for centralized management and analysis. Optimize the construction process through big data analysis to improve management efficiency. For example, adjusting the construction parameters according to the analysis results may affect data such as the covering thickness H and the volume V of the vegetation bags bag and further affect the calculation of other data and the construction process.

[0042] 5. Maintenance stage Use drones to regularly check the state of the vegetation bags to ensure the normal growth of plants and that the bags are not damaged or displaced. According to the weather and seasonal changes, reasonably arrange maintenance work such as irrigation, fertilization, and weeding to ensure the healthy growth of the plants in the vegetation bags (using means such as scanning the emergence rate, drought degree, and color comparison to feedback the growth situation; elaborate on the judgment mechanism). According to the data monitored by the sensors, reasonably dispatch the irrigation vehicles for spraying to avoid over-irrigation or under-irrigation.

[0043] Furthermore, use drones to regularly check the state of the vegetation bags, and use means such as scanning the emergence rate, drought degree, and color comparison to feedback the growth situation. Let the emergence rate be R and the drought degree indicator be D, which are related to the growth state of the plants in the vegetation bags. According to the weather and seasonal changes, reasonably arrange maintenance work such as irrigation, fertilization, and weeding. Let parameters such as the irrigation amount I, the fertilization amount F, and the weeding frequency C interact with the emergence rate R and the drought degree indicator D to ensure the healthy growth of the plants in the vegetation bags.

[0044] According to the data monitored by the sensors, reasonably dispatch the irrigation vehicles for spraying. Let the irrigation vehicle dispatch parameter be G, which is related to factors such as the irrigation amount I and the plant growth state, to avoid over-irrigation or under-irrigation.

[0045] Embodiment 2 For a mechanized construction production management method for a highway slope vegetation bag slope protection project in Embodiment 1, a software for mechanized construction production management of a highway slope vegetation bag slope protection project is also proposed. The flowchart of the software for mechanized construction production management of a highway slope vegetation bag slope protection project is as shown in Figure 2 and mainly includes the following contents: 1. Construction preparation stage The unmanned aerial vehicle conducts a survey of the construction site to determine the construction area and operation plan, and calculates key production information (such as the area of the operation area, the amount of soil used, the number of vegetation bags, etc.). Divide the standard construction area, prepare construction equipment and materials, establish a construction management system, input the calculated data, and set construction parameters and management permissions.

[0046] 2. Mechanized construction stage Establish a topsoil yard and collect topsoil. Conduct crushing and screening in the crushing operation area. Supplement nutrients in the planting soil mixing area. Uniformly bag in the vegetation bag weighing, packaging and sealing area, and sensors record parameters such as the number of bags, weight, and time. The vegetation bag transport vehicle loads and transports to the stacking operation point. The unloading device places the vegetation bag at the end of the conveyor belt. The automatic conveying and stacking are completed through the construction operation vehicle. The sensors and control system calculate the grasping speed and quantity according to the stacking speed and the moving speed of the operation vehicle, and perform real-time adaptive matching with the conveying and stacking processes. The construction operation vehicle completes the multi-column stacking of vegetation bags from low to high within the operation area, the construction vehicle moves forward to the next construction point, and the construction is cycled. The intelligent monitoring system monitors the construction progress and quality in real time, and each system automatically coordinates production parameters to achieve adaptive collaborative production.

[0047] 3. Quality control stage Use equipment such as sensors and unmanned aerial vehicles to detect the construction quality. Analyze the detection results and rectify problems in a timely manner.

[0048] 4. Data management stage Upload the construction data, quality inspection data, and management data to the construction management system. Optimize the construction process through big data analysis and improve the management efficiency.

[0049] 5. Maintenance stage Use the unmanned aerial vehicle to regularly check the status of the vegetation bags and feedback the growth situation. Arrange maintenance work such as irrigation, fertilization, and weeding reasonably according to weather and seasonal changes. Reasonably dispatch irrigation vehicles for spraying according to the data monitored by the sensors.

[0050] In the software, the data relationship of the automatic conveying and stacking equipment is as follows: I. Explanation of data relationship Let the job task number be T, the location coordinates of the working area be (X, Y), the rotation angle of the turntable be θ1, the extended length of the hydraulic cylinder be L1, the extended length of the telescopic belt conveyor be L2, the angle of the rear feeding belt conveyor be α, the conveying speed of the vegetation bags be v, the distance that the transverse trolley moves for one bag spacing be d1, the length that the telescopic belt conveyor retracts each time be L3, and the distance that the translation trolley moves be d2.

[0051] 1. After the system assigns job task T, the conveying and stacking vehicle arrives at the working area according to the location coordinates (X, Y) of the working area.

[0052] 2. The turntable rotates to adjust the conveying belt to a suitable position. At this time, the rotation angle θ1 of the turntable meets specific working requirements, and the angle is fixed after the turntable stops rotating.

[0053] 3. The hydraulic cylinder extends to adjust the angle of the conveying belt so that the conveying belt reaches a suitable working angle. The extended length L1 is determined according to the actual operation requirements, and the length remains unchanged after the hydraulic cylinder is locked.

[0054] 4. The telescopic belt conveyor extends, and the extended length L2 should meet the requirement of being able to convey the vegetation bags to the specified stacking position.

[0055] 5. The rear feeding belt conveyor is adjusted to a suitable angle α to meet the feeding needs and ensure that the vegetation bags can be smoothly conveyed from the rear feeding belt conveyor to the telescopic belt conveyor.

[0056] 6. The feeding end starts to convey the vegetation bags at a speed of v, and the manual assistance for stacking the vegetation bags is carried out at the discharging end. After completing the stacking of one bag, the transverse trolley automatically transverses a bag spacing d1 and continues stacking until the stacking of a transverse section is completed.

[0057] 7. The telescopic belt conveyor retracts a certain length L3 to meet the operation requirements of the second-row transverse stacking. The stacking operation is completed in sequence until the operation of this working section is completed. The determination of the retracted length L3 should consider the requirements of the number of stacking rows and the spacing.

[0058] 8. When the telescopic belt conveyor is completely retracted and there are no vegetation bags being conveyed on the conveying belt, the angle of the feeding-end conveyor belt is restored to the initial state.

[0059] 9. The hydraulic cylinder retracts, causing the telescopic conveyor belt to fall onto the mounting frame. At this time, the extended length L1 of the hydraulic cylinder becomes 0 and it is stably placed.

[0060] 10. The turntable rotates back to the original position. At this time, the rotation angle θ1 of the turntable becomes 0, the translation trolley returns to the initial position, and the moving distance d2 of the translation trolley becomes 0.

[0061] 11. After completing the folding and playback work of the equipment, the vehicle starts and moves forward to the next working site.

[0062] II. Monitoring and Control of Key Information 1. During the operation of the equipment, sensors are added to continuously monitor key parameters such as the rotation angle θ1 of the turntable, the extension length L1 of the hydraulic cylinder, and the extension length L2 of the telescopic belt conveyor, to ensure that the equipment is adjusted to the accurate working position.

[0063] 2. Control the moving speed of the transverse trolley to match the conveying speed v of the vegetation bags and the stacking progress, to improve the stacking efficiency and quality.

[0064] III. Fault Monitoring System of Equipment I. Monitoring of Mechanical Components 1. Monitoring of Conveyor Belt Status Check whether the conveyor belt has wear, tear, fracture, etc. Sensors can be installed to detect the thickness change and surface damage degree of the conveyor belt. For example, use ultrasonic sensors to detect the thickness of the conveyor belt and give an alarm when the thickness is lower than the set threshold.

[0065] Monitor the deviation of the conveyor belt. Install deviation sensors to send signals in time when the conveyor belt deviates from the normal running track, so as to adjust the equipment and prevent further damage.

[0066] Detect the tension of the conveyor belt. Real-time monitor the tension of the conveyor belt through tension sensors to ensure that the tension is within the appropriate range, and avoid the decrease of conveying efficiency or equipment damage caused by being too loose or too tight.

[0067] 2. Monitoring of Turntable Monitor whether the rotation angle of the turntable is accurate. Install angle sensors to ensure that the turntable can adjust the conveyor belt to the appropriate position. If the angle deviation is too large, it may affect the conveying effect and the stability of the equipment.

[0068] Check whether the rotation mechanism of the turntable works properly. For example, monitor the running state of the motor and the tension of the transmission chain, etc., to prevent jamming or failure.

[0069] 3. Monitoring of Hydraulic Cylinder Detect whether the telescopic length of the hydraulic cylinder meets the requirements. Install displacement sensors to real-time monitor the extension and retraction lengths of the hydraulic cylinder to ensure that the equipment can be adjusted to the correct working angle and height.

[0070] Monitor the pressure of the hydraulic system. Detect the working pressure of the hydraulic system through pressure sensors. When the pressure is abnormal, it may mean that there is leakage or other faults in the hydraulic cylinder.

[0071] 4. Monitoring of Telescopic Belt Conveyor Check whether the telescopic mechanism is smooth. Monitor the extension and retraction processes of the telescopic belt conveyor to ensure that there is no jamming or abnormal resistance. Travel switches or proximity sensors can be installed to detect the telescopic position.

[0072] Detect the driving device of the belt conveyor. Monitor the operating status, speed, current and other parameters of the motor to determine whether the driving device is working properly. If the motor overheats, is overloaded, etc., stop the machine in time for inspection.

[0073] 5. Monitoring of the rear-end feeding belt conveyor Monitor the angle adjustment mechanism of the feeding belt conveyor. Ensure that the angle can be accurately adjusted as needed to meet the feeding requirements. Angle sensors and motor feedback signals can be used to monitor the accuracy of angle adjustment.

[0074] Check the conveying capacity of the belt conveyor. Monitor parameters such as the speed and flow rate of the belt to ensure a smooth feeding process without blockage or accumulation.

[0075] II. Monitoring of the electrical system 1. Motor monitoring Monitor the operating status of the motor, including parameters such as speed, current, and temperature. Use a motor monitor or sensor to collect these data in real time, and issue an alarm in a timely manner when the motor shows abnormalities. For example, when the current is too large, it may mean that the motor is overloaded, and when the temperature is too high, it may indicate poor heat dissipation of the motor.

[0076] Check the start and stop control of the motor. Ensure that the motor can start and stop normally without abnormal start-up delay or shutdown failure.

[0077] 2. Monitoring of the electrical control system Monitor the power supply of the control system. Check whether the power supply voltage is stable to prevent damage to the equipment caused by voltage fluctuations. Voltage sensors and voltage stabilizers can be installed to ensure the reliability of the power supply.

[0078] Check the signal transmission of the control system. Ensure that sensor signals and control instructions can be accurately transmitted without interference or signal loss. For example, use shielded cables and signal amplifiers to improve the signal quality.

[0079] Monitor the logic function of the control system. Regularly conduct functional tests on the control system to ensure that various control logics are correctly executed, such as the rotation of the turntable, the control of the hydraulic cylinder, and the start and stop of the belt conveyor.

[0080] III. Monitoring of safety protection devices 1. Monitoring of the emergency stop device Check whether the emergency stop button works properly. Regularly test the response time and reliability of the button to ensure that it can stop the machine quickly in case of an emergency.

[0081] Monitor the interlock function of the emergency stop system. Ensure that when the equipment has serious faults or dangerous situations, the emergency stop device can be automatically triggered and stop the operation of all related equipment.

[0082] 2. Anti-slip Protection Monitoring For equipment used for long-distance downhill transportation, anti-slip protection is crucial. Install anti-slip sensors to monitor the friction between the conveyor belt and the material. When the friction is insufficient, an alarm is issued and corresponding anti-slip measures are taken, such as increasing the conveyor belt tension or adjusting the conveying speed.

[0083] 3. Overload Protection Monitoring Monitor the load condition of the equipment. When the load exceeds the set value, the overload protection device is automatically activated. For example, use a current sensor to detect the motor current. When the current exceeds the rated value, cut off the power supply or reduce the conveying speed.

[0084] 4. Safety Protection Device Monitoring Detect whether devices such as safety fences and protective covers of the equipment are in good condition. Ensure that these devices can effectively prevent personnel from contacting moving parts and avoid safety accidents.

[0085] Monitor the interlock function of the safety protection device. When the safety protection device is opened or damaged, the equipment should automatically stop to ensure personnel safety.

[0086] IV. Data Acquisition and Analysis 1. Sensor Data Acquisition: Install various sensors, such as temperature sensors, pressure sensors, displacement sensors, etc., to collect the operation data of the equipment in real time. These data can be transmitted to the central controller of the monitoring system by wired or wireless means.

[0087] 2. Data Storage and Analysis: Store the collected data in a database for historical data analysis and fault diagnosis. Data analysis software can be used to process the data to find the trends and potential problems in the equipment operation. Through data analysis, a fault prediction model is established. Based on the operation data of the equipment and historical fault records, predict possible faults and take preventive measures in advance.

[0088] 3. Remote Monitoring and Alarm: Establish a remote monitoring system to enable operators to monitor the operation status of the equipment in real time. Remote monitoring can be achieved through the Internet or mobile devices to detect faults in a timely manner and take measures.

[0089] When a fault occurs in the equipment, the monitoring system should issue an audible and visual alarm and send the fault information to relevant personnel. The alarm information should include the fault type, location, and severity, etc., for timely repair.

[0090] Example 3 The mechanized construction production management method for the slope greening bag slope protection project of highways also includes an ecological restoration method for highway construction wounds, so as to continue subsequent maintenance and management after the construction of slope greening bags on highways. The flowchart of the ecological restoration method for highway construction wounds is as shown in Figure 3 shown, and the process includes: S1. Record the growth condition parameters of the trial-planted greening bags, and construct a greening bag growth data set; the growth condition parameters include greening bag parameters, maintenance parameters and environmental parameters during the growth of the greening bags. S2. Calculate the ecological restoration contributions of the plants in each greening bag in the greening bag growth data set; the ecological restoration contributions include the germination rate, greening degree and ecological restoration weighted contribution index of the plants. S3. Use the growth condition parameters as input parameters and the ecological restoration contributions as output parameters to construct a training set, and input the training set into a pre-constructed highway construction wound repair analysis model for training to obtain an optimal highway construction wound repair analysis model. S4. Input the predicted growth condition parameters into the optimal highway construction wound repair analysis model to obtain the predicted ecological restoration contributions. Stack the greening bags on the sections corresponding to the environmental parameters according to the predicted ecological restoration contributions, and design a greening bag production plan and a greening bag maintenance plan. The highway construction wound repair analysis model is a BP neural network.

[0091] As a preferred solution of the present invention, the greening degree is the sum of the projected areas of plant leaves per unit area.

[0092] As a preferred solution of the present invention, the calculation steps of the weighted contribution index include: First, count the types of plants per unit area. Then calculate the contribution weighted index of each single plant of each type per unit area to the system function at different time periods; the contribution weighted index is determined by the effects of the plants on stabilizing the soil, improving the water and heat conditions, and restoring the system function. Add the products of the quantities of each type of plant per unit area and their corresponding weighted indices to obtain the ecological restoration weighted contribution index.

[0093] As a preferred solution of the present invention, the greening bag parameters include the dosage of plant seeds, the dosage of growth additives, and the size of the greening bags; the maintenance parameters include the amount of supplementary water for maintenance and the amount of top dressing for maintenance; the environmental parameters include the slope orientation, the planting month, the precipitation, the slope land characteristics, the stripping thickness of the topsoil, and the highway wound construction method.

[0094] As a preferred embodiment of the present invention, when constructing the training set, the growth condition parameters with importance scores not lower than the selection threshold are selected as the input parameters; The calculation of the importance score includes: using the random forest algorithm, taking the growth condition parameters as indicators and extracting samples therefrom to construct a decision tree, and calculating the importance scores of the respective parameters in the growth condition parameters.

[0095] As a preferred embodiment of the present invention, the training of the road construction wound surface repair analysis model in step S4 includes: Initializing the connection weights and thresholds; Calculating the outputs of the respective nodes in the hidden layer and the output layer according to the selected learning input mode; Calculating new connection weights and thresholds; Updating the learning input mode, and according to the updated learning input mode, calculating the outputs of the respective nodes in the hidden layer and the output layer again until the number of training times reaches the set value.

[0096] As a preferred embodiment of the present invention, designing the vegetation bag production plan and the vegetation bag maintenance plan according to the evaluation result in step S4 includes: If the predicted ecological restoration contributions are all not lower than the evaluation index threshold, then according to the vegetation bag parameters in the predicted growth condition parameters corresponding to the predicted ecological restoration contributions, the vegetation bags are manufactured, and the vegetation bag maintenance plan is designed according to the maintenance parameters; If there is a predicted ecological restoration contribution lower than the evaluation index threshold, then update the vegetation bag parameters and the maintenance parameters of the predicted ecological restoration contribution, re-input the updated predicted ecological restoration contribution into the optimal road construction wound surface repair analysis model, obtain the updated predicted ecological restoration contribution and compare it with the evaluation index threshold again.

[0097] In step 3, the road construction wound surface and environmental evaluation indicators include: the road wound surface construction method, the slope orientation, the slope soil characteristics, the precipitation, the maintenance water supplement, and the top dressing amount.

[0098] The road wound surface construction method is divided into: cut slope and fill slope; the slope orientation is the normal orientation of the slope, which can be measured by a compass; the slope soil characteristics mainly distinguish the soil hardness and the soil base layer type; the precipitation uses the data of the meteorological station closest to the planting location; the maintenance water supplement amount and the top dressing amount are recorded according to the actual situation.

[0099] In step 3, the evaluation indicators of the plant's contribution to ecological restoration are divided into four categories according to the degree of refinement: The first item is the germination rate A1, that is, the germination rate of plant seeds in the planting soil per unit volume at different times, which is used to characterize the seed germination efficiency.

[0100] The second item is the greening degree A2, which is the sum of the projected areas of plant leaves per unit area. Using this index to roughly evaluate the contribution of plants to ecological restoration, one can take photos along the slope normal through manual investigation and identify the projected areas of plant leaves through image processing. For large-scale planting areas, methods such as drone photography can be used to calculate the greening projected area of plants.

[0101] Measurement method of greening degree A2: An embodiment: First, the drone takes photos at an appropriate height and angle to obtain an image of the slope surface. Specific software is used to process the image, including correcting the scale and projection, and stitching the images to form a complete slope surface model.

[0102] Then, through digital surface model (DSM) technology, a digital surface model is generated from the image. This can be automatically completed by software, generating a point cloud based on the captured image and then constructing a three-dimensional model from the point cloud. According to the digital surface model, the area of the slope can be calculated. This step usually requires using specific software or algorithms to calculate the accurate area value based on the three-dimensional model.

[0103] Finally, accuracy evaluation and error analysis are performed on the calculated slope area to ensure the accuracy and reliability of the measurement results. Existing software that can be used includes: Smar3D, OneButton, inpho, etc. The software can automatically process a large amount of image data and overcome problems such as unstable drone flight attitude and large image distortion.

[0104] An embodiment: The lower slope of highway engineering has specific slope requirements according to grades, and the determination of the drone shooting angle can be assisted by setting signs on the slope surface.

[0105] Including: setting up vertical poles parallel to the slope normal on the slope surface. When the projected area of the vertical pole recognized by the drone is the smallest, it can be confirmed that the film taken at this shooting angle is an image of the frontal view of the slope surface, thus accelerating the calculation steps of the greening rate and improving the calculation speed and accuracy.

[0106] The third item is the weighted contribution index A3. Since different plants have significant differences in their effects on slope stability and the restoration of system functions, especially when there are many types of plant seeds in the vegetation bags, which are composed of shrubs, flowers, and grasses, using a unified evaluation index cannot accurately reflect the contribution of plants to ecological restoration. To evaluate the ecological restoration contribution of vegetation bags more precisely, the ecological restoration weighted contribution index is defined. First, the quantity Qi of various plants per unit area is counted, and then the weighted contribution index of a single plant to the system function at different time periods is established, which is determined by comprehensively considering the roles of plants in aspects such as stabilizing the soil, improving hydrothermal conditions, and restoring system functions. Here, i represents the plant number, and t is the plant growth height. Then, by adding the products of the quantities of different plants and their weighted indices, the ecological restoration weighted contribution index per unit area is obtained, and its calculation formula is as follows: Based on past experience and test conditions, determine the thresholds of the above parameters for different growth stages of plants: A 1,min 、A 2,min 、A 3,min 。For example, A 1,min is 90%, A 2,min is 80%, and A 3,min is 90%.

[0107] The dataset construction includes: Using a memory and a processor, construct datasets of vegetation bag solutions, surrounding environments, and vegetation growth indicators through MySQL.

[0108] Among them, MySQL is a typical relational database, which has the characteristics of small volume, fast speed, low cost, and open source code, and is most suitable for WEB applications and scientific computing. Therefore, MySQL is used for the DBMS of the database management system for vegetation bag design indicators, surrounding environments, and vegetation growth indicators. The database takes uploading and storing vegetation bag indicators and slope vegetation growth data as the core, and is divided into 5 functional modules: the home page, vegetation bag design materials, highway surrounding environment materials, vegetation bag growth materials, and vegetation bag maintenance materials, involving 12 items of relevant data such as topsoil stripping thickness d, vegetation bag width w, vegetation bag length l, vegetation bag height h, the dosage rn of various plant seeds, the dosage ra of growth additives, highway wound construction methods, slope orientation, slope soil characteristics, precipitation, maintenance water supply, and topdressing amount.

[0109] Database Logical Structure Design: Logical structure design is to convert the conceptual model completed in the conceptual structure design stage into a data model that can be supported by the selected database management system (DBMS). Here, mainly convert the E-R model into a relational schema. First, determine the ID tag of the highway slope according to the mileage ID and highway slope name of the highway slope. Then, determine the mileage range corresponding to the slope according to this ID. Next, combine the specific mileage name to determine the ID of the mileage, so as to find the relevant data of the corresponding mileage. The database logical structure of the database logical structure table of the slope vegetation bags is shown in Table 1: Table 1 Database Logical Structure Table of Slope Vegetation Bags The database design tool for this database is Navicat Premium 15. Navicat Premium is a set of database development tools that allows you to connect to MySQL, MariaDB, MongoDB, SQL Server, Oracle, PostgreSQL, and SQLite databases from a single application. It is compatible with cloud databases such as Amazon RDS, Amazon Aurora, Amazon Redshift, Microsoft Azure, Oracle Cloud, MongoDB Atlas, Alibaba Cloud, Tencent Cloud, and Huawei Cloud. This comprehensive front-end tool provides an intuitive and powerful graphical interface for database management, development, and maintenance. Through it, you can quickly and easily create, manage, and maintain databases.

[0110] The database management software tool for this database is MySQL. MySQL is a DBMS (database management system) developed by MySQL AB in Sweden and currently belongs to Oracle. MySQL is the most popular relational database management system (a relational database is a database built on the basis of a relational database model, which uses concepts and methods such as set algebra to process data in the database). Due to its small size, fast speed, low total cost of ownership, especially the feature of open source code, developers of general small and medium-sized websites choose MySQL as the website database. MySQL uses the SQL language for operations.

[0111] The database of vegetation bag indicators, the growth environment around the highway, and the growth of slope vegetation takes data upload and online data viewing as the core, and is divided into 5 functional modules: home page, vegetation bag design materials, highway surrounding environment materials, vegetation bag growth materials, and vegetation bag maintenance materials. After the user logs in to the system through the login interface, the page defaultly displayed on the main interface is the home page, which is convenient for users to understand the data volume of the database and various statistical data.

[0112] When the user clicks on "Vegetation Bag Design Data" in the upper navigation bar, they can be redirected to the vegetation bag design data page. On the left side of the page, a list of the names of existing slopes in the current database is displayed. The user can preload the slope information of the corresponding slope onto the page by clicking on the corresponding slope name. Then, by clicking on the "Click to Load File" button under one of the five cards in the center of the page, the selected file can be previewed.

[0113] Step 4: Input the proposed vegetation bag plan, design parameters of the highway wound surface, environmental characteristics, and maintenance plan into the prediction model. Using machine learning methods, analyze the importance of each factor through the processor, and then establish an efficient highway ecological restoration evaluation model to achieve obtaining an ideal vegetation bag design and maintenance plan for a specific section by adjusting various indicators and influencing factors: Among them, in order to improve the accuracy and operation efficiency of the prediction model, it is necessary to evaluate the influence degree of each growth situation index in the storage on the growth situation of slope vegetation, and then select the growth situation indexes that have a significant impact on the growth situation of slope vegetation, and use the random forest in machine learning to analyze the importance of each factor.

[0114] In machine learning, random forest is an ensemble learning method that contains multiple decision trees. It randomly generates multiple classifiers (decision trees), learns independently, and makes predictions. Random forest has a fast training speed, strong generalization ability, and strong anti-interference ability. It has a wide range of applications and good effects in the index screening of highly discrete data and missing data. The importance of each specific index is represented by its variable importance measure (VIM).

[0115] Use X1, X2, X3...Xn to represent the n indexes considered, and randomly extract training samples to construct decision trees. After sampling, calculate the prediction error rate of the remaining samples in the sample library. These remaining samples are called out-of-bag data (OOB). Then randomly replace the observed values of variable Xj, reconstruct the decision tree, and recalculate the prediction error rate of the OOB data. Finally, calculate the difference in the error rates of the two OOB data before and after replacement. The normalized average value of all decision trees is used as the VIM of variable Xj, and the calculation formula is as follows: Among them, is the i number of OOB data in the th decision tree; is an indicator function that is equal to 1 when two numbers are equal and equal to 0 when they are not equal; p is the true result of the OOB data for the th iteration of thei The prediction results of the OOB data for the p th iteration of a decision tree; After random replacement, the prediction results of the OOB data for the i th iteration of a decision tree. When the variable p ... is not present in X j the i decision trees, ... The VIM of the variable X j in the random forest is defined as: where n is the number of decision trees in the random forest.

[0116] For the random forest algorithm, the VIM of each influencing factor was calculated, and the calculation results are shown in the following table.

[0117] Taking a certain highway in the southwestern region of China as an example, the importance scoring results obtained from the research are as shown in Table 2, the calculation results of the importance scores of each influencing factor: Table 2 Calculation results of the importance scores of each influencing factor As can be seen from Table 2, the importance scores of 6 influencing factors, namely the plant seed dosage rn, the growth additive dosage ra, the maintenance water replenishment amount, the maintenance topdressing amount, the height h of the vegetation bag, and the width w of the vegetation bag, are all greater than 0.6. The importance scores of these 3 influencing factors are significantly higher than those of other influencing factors such as the slope orientation, and the importance scores of these influencing factors are all less than 0.1. Therefore, the plant seed dosage rn, the growth additive dosage ra, the maintenance water replenishment amount, the maintenance topdressing amount, the height h of the vegetation bag, and the width w of the vegetation bag are selected as the input indicators of the prediction model.

[0118] A highway construction wound repair analysis model is established, including: Taking the plant seed dosage rn, the growth additive dosage ra, the maintenance water replenishment amount, the maintenance topdressing amount, the height h of the vegetation bag, and the width w of the vegetation bag as input parameters, and taking the germination rate A1, the greening degree A2, and the weighted contribution index A3 as target parameters, a storage processing module is adopted, and a highway construction wound repair analysis model is established through machine learning.

[0119] Among them, the machine learning prediction model adopts the BP neural network. As a relatively typical machine learning algorithm, the main structure of the BP neural network consists of an input layer, one or more hidden layers, and an output layer. Each layer is composed of several neurons (nodes), and the output value of each node is determined by the input value, activation function, and threshold. The learning process of the network includes two processes: forward propagation of information and backpropagation of error, and the weights of the neurons in each layer are modified layer by layer to reduce the error. This cycle continues until the error of the output result meets the accuracy requirements. Under the conditions of reasonable structure and appropriate weights, using the error gradient descent algorithm to minimize the mean square error between the network output value and the actual output value, the BP neural network can theoretically approximate any nonlinear continuous function. The specific implementation steps are as follows: ① Initialize the connection weights and thresholds.

[0120] ② According to the selected learning input pattern, calculate the outputs of the nodes in the hidden layer and the output layer. The Relu function is used as the activation function of the hidden layer, and the Tanh function is used as the activation function of the output layer.

[0121] The expression of the Relu function is as follows: The expression of the Tanh function is as follows: ③ Calculate the new connection weights and thresholds. The update calculation method of the neuron threshold is as follows: Among them, t is the number of training iterations; is the learning rate of the t th training iteration; is the error of the k th node in the output layer; is the threshold of the k th node in the output layer; is the error of the j th node in the hidden layer; is the threshold of the j th node in the hidden layer.

[0122] The update calculation method of the neuron weight is as follows: Among them, t is the number of training iterations; is the weight updated from the hidden layer to the output layer; is the weight updated from the input layer to the hidden layer.

[0123] ④ Update the learning input mode and re - execute the second step to train the neural network until the final number of training times reaches the set value.

[0124] The neural network model designed to predict the growth state of vegetation bags contains three layers in total: 1 input layer, 1 output layer, and 3 fully - connected hidden layers. Among them, the input layer contains 6 nodes, the output layer contains 3 nodes, and the 3 hidden layers contain 576 nodes, 1280 nodes, and 576 nodes respectively.

[0125] After establishing the highway ecological restoration analysis model, by inputting appropriate vegetation bag parameters, surrounding environment parameters, and maintenance parameters, the growth evaluation indices A1, A2, and A3 of plants in different sections during the key growth periods can be obtained. On the one hand, this parameter needs to be greater than the threshold values A 1,min 、A 2,min 、A 3,min , and on the other hand, an implementation plan with better economic effects can be obtained by adjusting the vegetation bag and maintenance parameters.

[0126] Example 4 The highway construction wound ecological restoration method in Example 3 was used for verification. According to the data of a certain highway and the slopes of a certain 4# plot community, the BP neural network was used to predict the germination rate A1, greening rate A2, and weighted contribution index A3 of the slopes of three sections: the interchange A ramp of the second section of a certain highway, the third section of a certain highway, and the slope of a certain 4# plot community, and compared with the actual situation on - site. The experimental data table is as Figure 4 shown. The results show that the average prediction error of the slope germination rate A1 is 6.0%, the average prediction error of the greening rate A2 is 4.0%, and the average prediction error of the weighted contribution index A3 is 16.7%. The prediction results indicate that the constructed BP neural network model has good prediction performance.

[0127] Finally, it should be noted that the above - described embodiments in detail are only preferred practices of the present invention and cannot be used to limit the scope of the rights of the present invention. Making equivalent substitutions for the technical solutions recorded in the foregoing embodiments does not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and the description of the present invention.

Claims

1. The digital production management system for the construction of vegetation bag slope protection projects is characterized by: include: Construction preparation module, used to enter measurement data; The construction phase module outputs control signals and receives feedback data according to the pre-set operation process; The operation process includes: establishing a topsoil field, crushing and screening, planting soil mixing, vegetation bag packaging, vegetation bag transportation and stacking, stacking operation point setting, vegetation bag unloading control, and vegetation bag transportation and stacking control; The quality control module is used to receive quality inspection data and determine whether the laying meets the preset requirements based on the quality inspection data; the maintenance module is used to store data and control output during the maintenance stage; The data management module is used to store data from other modules and perform analysis based on the stored data.

2. The digital production management system for the construction of vegetation bag slope protection engineering as claimed in claim 1 is characterized in that: The construction preparation module receives the input survey data, and calculates the construction area, slope information, soil usage, number of vegetation bags required, optimal location and optimal path of the work area, estimated construction time, etc. based on the survey data.

3. The digital production management system for the construction of vegetation bag slope protection engineering as claimed in claim 2 is characterized in that: The construction area includes the topsoil stacking area, the crushing operation area, the screened soil stacking area, the planting soil mixing area, the vegetation bag weighing, packaging and sealing area, the vegetation bag shipping area, and the automatic conveying and stacking area.

4. The digital production management system for the construction of vegetation bag slope protection engineering as claimed in claim 1 is characterized in that: The construction phase module is used to record the number, weight, and time of bagging during the weighing and packaging phase of the vegetation bags; and to record the operation points and transportation tracks during the loading and transportation phase of the vegetation bag transport vehicle; During the unloading stage, it is used to control the loading and unloading equipment to place the vegetation bags on the end of the conveyor belt; during the vegetation bag conveying and stacking control stage, it is used to calculate the grabbing speed and quantity based on the stacking speed and the moving speed of the work vehicle.

5. The digital production management system for the construction of vegetation bag slope protection engineering as claimed in claim 4 is characterized in that: The construction phase module cooperates with the transport and stacking vehicle to complete the following steps: The system assigns the work tasks, and the transport stacking vehicles arrive at the work area according to the location coordinates of the work area; The turntable of the conveying and stacking vehicle rotates, and the conveying belt is adjusted to the preset position. The rotation angle of the turntable meets the preset working requirements; The hydraulic cylinder of the conveying and stacking vehicle is pushed out to adjust the angle of the conveying belt so that the conveying belt reaches the preset working angle; the push-out length L1 is determined according to the actual operation requirements; The telescopic belt conveyor of the transport and stacking vehicle is extended, and the extension length L2 meets the requirement of being able to transport the vegetation bags to the designated stacking position; Adjust the rear feeding belt conveyor to the appropriate angle α to ensure that the vegetation bags can be transported from the rear feeding belt conveyor to the telescopic belt conveyor; The feeding end conveys the vegetation bags at a speed of v, and the unloading end manually assists in stacking the vegetation bags. After one bag is stacked, the transverse moving trolley automatically moves horizontally by a bag distance d1 and continues stacking until one transverse interval stacking is completed; The retractable belt conveyor retracts to a length of L3, which meets the requirements of horizontal stacking operations, and completes the stacking operations in sequence until the work in the working area is completed; the retracted length L3 is determined by the number of rows and spacing of the stacking; When the telescopic belt conveyor is fully retracted and there is no vegetation bag on the conveyor bag, restore the angle of the conveyor belt at the feeding end to the initial state; The oil cylinder retracts, causing the telescopic conveying bag to fall onto the mounting frame, and the hydraulic cylinder ejection length L1 becomes 0; The turntable rotates back to its original position, at which time the turntable rotation angle θ1 becomes 0, the translation trolley returns to the initial position, and the translation trolley moving distance d2 becomes 0; After completing the folding and replaying of the equipment, the vehicle starts and moves forward to the next work site.

6. The digital production management system for the construction of vegetation bag slope protection engineering as described in any one of claims 1 to 5, characterized in that: It also includes a fault monitoring system for the equipment, which includes mechanical component monitoring, electrical system monitoring, and safety protection device monitoring; the mechanical component monitoring includes conveyor belt status monitoring, turntable monitoring, hydraulic cylinder monitoring, telescopic belt conveyor monitoring, and rear-end feeding belt conveyor monitoring; the electrical system monitoring includes motor monitoring and electrical control system monitoring; the safety protection device monitoring includes emergency stop device monitoring, anti-slip protection monitoring, overload protection monitoring, and safety protection device monitoring.

7. The digital production management system for the construction of vegetation bag slope protection engineering as described in any one of claims 1 to 5, characterized in that: The maintenance module is used for ecological restoration of the wound surface of the vegetation bag on the highway slope, and the restoration method includes the following steps: S1, collecting growth parameters of the vegetation bag and constructing a vegetation bag growth data set; the growth parameters include vegetation bag parameters and maintenance parameters and environmental parameters of the vegetation bag during the growth process; S2, calculating the ecological restoration contribution of the plants in each vegetation bag in the vegetation bag growth data set; the ecological restoration contribution includes the germination rate, greening degree and ecological restoration weighted contribution index of the plants; S3, using the growth condition parameter as an input parameter and the ecological restoration contribution as an output parameter to construct a training set, and inputting the training set into a pre-constructed highway construction wound repair analysis model for training to obtain an optimal highway construction wound repair analysis model; S4, input the predicted growth parameters into the optimal highway construction wound repair analysis model to obtain the predicted ecological restoration contribution, design a vegetation bag production plan and a vegetation bag maintenance plan based on the predicted ecological restoration contribution, and stack the vegetation bags on the road section corresponding to the environmental parameters.

8. The digital production management system for the construction of vegetation bag slope protection engineering according to claim 7 is characterized in that: The greening degree is the sum of the projected areas of plant leaves per unit area.

9. The digital production management system for the construction of vegetation bag slope protection engineering according to claim 8 is characterized in that: The calculation steps of the weighted contribution index include: Count the number of plant species per unit area; Calculate the weighted index of contribution of each type of single plant per unit area to the ecological restoration function of the slope vegetation bag wound surface in different time periods; the weighted index of contribution is determined by the role of plants in stabilizing soil, improving water and heat conditions, and restoring ecological functions; The weighted contribution index of ecological restoration is obtained by adding the number of each type of plant per unit area and the product of its corresponding weighted index.

10. The digital production management system for the construction of vegetation bag slope protection engineering according to claim 7 is characterized in that: The highway construction wound repair analysis model consists of three layers: 1 input layer, 1 output layer and 3 fully connected hidden layers; The nodes of the input layer include the amount of plant seeds, the amount of growth additives, the amount of water for maintenance and replenishment, the amount of fertilizer for maintenance and topdressing, the height of the planting bag and the width of the planting bag; The nodes of the output layer include germination rate, green degree and weighted contribution index; The training steps of the highway construction wound repair analysis model include: Initialize connection weights and thresholds; According to the selected learning input mode, the output of each node in the hidden layer and the output layer is calculated; Calculate new connection weights and thresholds; Update the learning input mode, and calculate the output of each node in the hidden layer and the output layer again according to the updated learning input mode until the number of training times reaches the set value.

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