3976 results about "Road construction" patented technology

The invention relates to the technical field of road safety, in particular to a road construction safety self-adaptive warning broadcast system and method, and the method comprises the steps: collecting environment parameters of a construction region in real time; detecting dynamic traffic parameters of vehicles around the construction area; tracking a real-time position and a movement track of the construction machinery, and monitoring a safe area border crossing behavior of a constructor; predicting a dynamic risk level in the construction area based on the environmental parameters, the dynamic traffic parameters, the construction machinery motion trail and the personnel border crossing state, and generating a grading response strategy; and outputting a self-adaptive warning signal according to the grading response strategy. According to the method, the problems that a traditional early warning model depends on one-dimensional parameters, the static threshold misjudgment rate is high and the response delay is large are effectively solved, and accurate quantification and real-time early warning of the construction machinery and vehicle conflict risk are achieved through multi-source data fusion and dynamic probability calculation.

The invention relates to the technical field of municipal road construction, and discloses a municipal road construction section scheduling optimization method and system based on artificial intelligence, and the method comprises the steps: collecting the multi-source dynamic data of a construction region through Internet of Things equipment and a satellite remote sensing technology, and constructing a time sequence database; a multi-objective optimization model is established, and an initial scheduling scheme is generated by adopting a non-dominated sorting genetic algorithm with the goal of minimizing construction period, resource waste and traffic jam influence. Dynamically adjusting the priority of the construction section by using a reinforcement learning algorithm, and updating a construction task sequence; a graph neural network is utilized to detect space-time conflicts of construction sections, and conflict-free scheduling constraint conditions are generated; and optimizing resource allocation based on mixed integer linear programming, simulating a construction process in combination with a digital twinborn technology, correcting a construction progress deviation by using a Kalman filtering algorithm, and outputting a final scheduling instruction. According to the invention, optimization of municipal road construction section scheduling is realized, the construction period is effectively shortened, resource waste is reduced, and traffic jam is relieved.

The invention provides a road construction project carbon emission ratio toughness analysis method, and belongs to the technical field of carbon emission, machine learning and big data analysis and mining, and the method comprises the steps: obtaining a historical change trend of a carbon emission ratio from historical data of a road construction project, and constructing a dynamic change model of the carbon emission ratio in combination with real-time monitoring data; determining the influence degree and the action mechanism of the interference factors on the carbon emission ratio dynamic change model by analyzing the interaction relationship between the carbon emission ratio and the interference factors; key fluctuation characteristics are extracted from the corrected change trend of the carbon emission ratio, and whether fluctuation of the carbon emission ratio exceeds an acceptable range or not is judged in combination with a preset threshold value; if the fluctuation of the carbon emission ratio exceeds a preset threshold value, performing noise reduction processing on the data by adopting an adaptive filtering algorithm to generate noise-reduced carbon emission ratio data; and training the segmented analysis result by adopting a random forest model in a machine learning algorithm to generate a prediction model of the carbon emission ratio.

The invention relates to the field of road construction, and discloses a machine vision-based fabricated pavement precast slab flatness measurement method, which comprises the following steps of: positioning and marking an assembled fabricated precast slab area; generating point cloud data through three-dimensional scanning, and carrying out denoising processing and feature extraction; calculating the elevation of each point on the surface of the precast slab according to the feature data, identifying elevation change and generating flatness evaluation data; performing gray level detection on the three-dimensional point cloud data, and further analyzing a defect area in combination with elevation data; and utilizing the Gaussian process regression model to predict the elevation of the unscanned area or the boundary area, and finally outputting a flatness evaluation result. Through the scheme of the invention, efficient and accurate detection of the surface flatness of the prefabricated slab can be realized, feedback and adjustment suggestions are provided for construction, the detection precision is effectively improved, and the construction cost is reduced.

The invention provides a road line selection optimization method, system and device based on AI and quantitative parameter constraint, and a storage medium. The method comprises the following steps: establishing a road line selection initial preset parameter library; a high-precision remote sensing technology, an unmanned aerial vehicle, a GIS database and a traffic monitoring system are utilized to collect quantitative data, and data preprocessing is automatically carried out; a deep learning model is developed and trained, parameter values in historical cases are automatically identified and calculated, the identified and calculated parameters are trained and learned, and a deep learning result is fed back to a quantitative parameter set; a multi-factor target evaluation index system is constructed, and evaluation index values of all candidate schemes are obtained; and providing a decision support tool to help a user to understand the advantages and disadvantages of each scheme and recommend an optimal line scheme meeting all quantitative parameter constraints. According to the invention, the line selection efficiency and accuracy can be improved, the compliance of the line selection scheme in the aspects of technology, safety, environment and the like is ensured, and an efficient, economic and environment-friendly line selection scheme is provided for a road construction project.

The invention is suitable for the technical field of flying dust monitoring, and provides a road construction site all-weather flying dust online monitoring method and system, and the method comprises the following steps: collecting flying dust data and wind power information through a sensor; the particulate matter concentration is judged, and the particulate matter concentration exceeding the standard and the corresponding coordinate position, wind speed data and wind direction data are screened out; determining a flying dust source area according to the coordinate position, the wind speed data and the wind direction data; a road transportation monitoring video is called, and the area where the transportation vehicle is located is determined according to the time information and the road transportation monitoring video; a road construction map is called, and the area where the transport vehicle is located is marked in the road construction map; and comparing and analyzing the flying dust source area with a road construction map, determining a potential flying dust source position, and sending the potential flying dust source position to an inspection terminal. According to the invention, the flying dust pollution source can be accurately tracked, and the inspection personnel can quickly position the potential flying dust pollution source according to the information.

The invention relates to the technical field of road construction quality control, in particular to an asphalt mixing station intelligent monitoring method and system based on Internet of Things data, and aims to solve the problems that in the prior art, technological parameters of an asphalt mixing station cannot be dynamically optimized, state vectors cannot be structured and defined as action spaces, and the working efficiency of the asphalt mixing station cannot be improved. The stability and convergence efficiency of strategy updating cannot be ensured, and long-term optimal control cannot be realized; the state and action space is constructed through the reinforcement learning strategy construction module, the multi-target reward function is combined, the reinforcement learning model is trained through the PPO algorithm, dynamic optimization of the technological parameters of the asphalt mixing station is achieved, the environment perception and regulation and control capacity of the model is enhanced through the structured state and the executable action, and the dynamic optimization of the technological parameters of the asphalt mixing station is achieved. The weighted reward mechanism overall plans quality, energy consumption and stability, and the PPO algorithm ensures efficient and stable training and supports long-term optimal control.

The invention discloses a construction monitoring system for a municipal asphalt road, relates to the technical field of road construction, and optimizes the road construction process through four modules of whole-process data acquisition, edge analysis and decision, dynamic quality detection and dynamic feedback control. And collecting data of each construction stage in real time. Real-time analysis is carried out through a BP multi-target decision network, the construction process is adjusted, quality detection is carried out on the surface layer and the deep layer of a road through a lightweight detection model, and defect marking and thermodynamic diagram display are carried out through a BIM platform. And on the basis of analysis and detection results, a fuzzy PID algorithm and a near-end strategy optimization algorithm are adopted, construction parameters are adjusted in real time, and construction quality and efficiency optimization are ensured. The problems that an existing sampling detection method is difficult to comprehensively cover a construction area, the quality problems of different levels cannot be visually displayed, and timely processing of constructors is affected are solved, and comprehensive monitoring, real-time analysis and intelligent adjustment of the road construction process can be achieved.

The invention relates to the technical field of railway engineering construction, and discloses a complex region railway engineering construction road intelligent line selection and evaluation decision method, which comprises the following steps: S1, in combination with terrain environment conditions and construction technology standards of a construction road, constructing an improved HAO plane line shape mathematical model, designing plane line shape constraint conditions, and constructing a line shape model; and establishing a line comprehensive cost model as an optimization objective function, and searching an optimal plane linear position parameter in a target area by using a particle swarm optimization algorithm. Compared with other intelligent line selection methods, the method can quickly evaluate and decide the advantages and disadvantages of the route scheme while quickly generating the horizontal and vertical section line shape of the construction road, optimizes the design process, facilitates the shortening of the construction period of the construction road, can remarkably reduce the workload of site survey and manual design, and improves the construction efficiency. The working efficiency and benefits of line selection design are practically improved, the investment of line selection cost is reduced, use is convenient, and the degree of dependence on equipment performance is low.

The invention relates to the technical field of carbon emission accounting, in particular to a road engineering carbon emission analysis method based on multi-source heterogeneous data fusion. The method comprises the following steps: collecting carbon emission factor multi-source heterogeneous data; performing multi-source heterogeneous data anomaly identification and correction processing on the carbon emission factor multi-source heterogeneous data to generate carbon emission factor multi-source heterogeneous standard data; performing carbon emission factor cross-modal global connection fusion processing on the carbon emission factor multi-source heterogeneous standard data to generate carbon emission factor global fusion feature data; establishing an optimization relation model of actual working condition carbon emission accounting based on the carbon emission factor global fusion feature data, and generating an optimization carbon emission accounting relation model; and performing carbon emission intelligent accounting operation on the road construction project based on the optimized carbon emission accounting relation model. According to the method, the accurate accounting of the carbon emission of the road engineering is realized by carrying out fusion analysis on the multi-source heterogeneous data.

The invention relates to the technical field of resource management, in particular to an intelligent road construction control system and method, and the system comprises a resource distribution optimization module which carries out the statistics of equipment working hours and task demands of subarea road sections based on pavement materials and construction equipment, matches the available working hours and task demands of the equipment, and calculates a manual working hour distribution difference value; and comparing the equipment availability with the manual availability. According to the invention, by matching the working hours and task requirements of pavement materials and construction equipment, optimizing resource allocation, reducing resource waste and redundancy, adjusting the working time between tasks and the resource utilization rate sequence, preferentially meeting the key task requirements, improving the task execution efficiency, and evaluating the material supply period and the equipment allocation conflict; task intervals and equipment plans are dynamically adjusted, delay caused by insufficient resources is reduced, task coordination is optimized in combination with time nodes and equipment distribution, environment change and equipment deviation are monitored, task and resource allocation is adjusted in real time, and construction efficiency and continuity are improved.

The invention relates to the technical field of intelligent traffic, in particular to an intelligent road cone traffic early warning system. The problems that in the prior art, an intelligent road cone is single in function, and warning strategies cannot be intelligently adjusted according to real-time road conditions and construction environment changes are solved. The intelligent road cone is arranged and used for being deployed on a road construction or accident site to warn vehicles, collecting road environment information through a sensor and conducting risk assessment and early warning on the vehicles according to the detected vehicle information; the control center is used for integrating the monitoring information of the intelligent road cones and dynamically adjusting a placement scheme and an early warning strategy of the intelligent road cones; and the user terminal is used for receiving the early warning information from the intelligent road cone and the control center and sending an alarm to a user. Through cooperation of the intelligent road cone, the control center and the user terminal, effective safety early warning and guidance are ensured to be performed on vehicles passing through the construction area during construction, accident risks are reduced, and traffic management efficiency is improved.

The invention provides a road material automatic identification system and method based on multi-source remote sensing data fusion. The system comprises a remote sensing data acquisition module, a data preprocessing module, a wave band selection module, an image enhancement module, an image fusion module, a road extraction module, a feature extraction module, a feature optimization module, a classification and recognition module, a result post-processing module and a user interaction module. According to the road material automatic identification system and method based on multi-source remote sensing data fusion, image data of different sensors are fused, and advanced image processing and machine learning technologies are combined, so that high-precision and automatic identification of road materials is realized; therefore, the requirements of the fields of urban planning, road construction, maintenance and the like can be met.

The invention relates to the technical field of construction stage management, in particular to a BIM-based road construction digital management system, which comprises a component parameter acquisition module, a process topology construction module, a state trigger mapping module, a logic conflict judgment module and a scheduling path adjustment module. According to the method, through continuous collection and analysis of the component state, dynamic monitoring of the connection state, geometric intersection and contact time is achieved, the construction change sensing capacity is improved, the dependency relationship is constructed in combination with component space adjacency and time overlapping, the dispatching path and field matching degree is enhanced, and through linkage updating of the component state and model attributes, the construction efficiency is improved. According to the method, the execution state is visual and controllable, scheduling reconstruction is carried out after time dependence conflicts are recognized, synchronous updating of model views is completed, a closed-loop dynamic scheduling mechanism is formed, the task allocation accuracy, the flow connection efficiency and the field scheduling response capability are integrally improved, and the real-time performance and the intelligent level of construction management are enhanced.

The invention belongs to the technical field of road construction, and particularly relates to a copper-doped tailing pavement base material as well as a proportion confirmation method and application thereof. The preparation method comprises the following steps: S1, preparing raw materials; s2, a compaction test method is adopted, and the void ratio of the compacted aggregate wrapped with the cement mortar is calculated; s3, according to the volume filling principle, the gravels form a basic framework, the void ratio of the gravels in the compaction state is measured, cement adhesive cement adheres to aggregate, the aggregate is filled in gaps of the framework formed by the gravels, and finally the blending proportion of the copper tailings, the gravels and the aggregate is determined by combining the composition mechanism and volume parameters of the mixture; and S4, calculating the using amount of the steel slag composite cementing material mucilage according to the thickness of the steel slag composite cementing material mucilage wrapping film and the specific surface area of the copper tailings. A skeleton filling theoretical method is adopted, the shrinkage effect of the filler in the skeleton is controlled, the cracking risk is reduced, and meanwhile the high strength is achieved.

The invention is suitable for the technical field of road construction, and provides a roadbed settlement safety monitoring method and system, and the method comprises the steps: obtaining measurement equipment, and obtaining equipment information according to the equipment; obtaining basic information according to the measurement equipment information, obtaining a confidence scoring function according to the basic information, and fusing the equipment measurement results according to the fusion weight coefficient to obtain a fusion result; constructing settlement time sequence data according to a fusion result, constructing an anomaly detection model by combining key change characteristics, if the settlement rate is judged to continuously exceed a set threshold value, performing early warning prompt, and marking the stage as a potential mutation interval; and according to the risk label, a cause tracing suggestion is provided, and according to the identified settlement trend state and the risk level, the scheme of each monitoring point is adjusted, so that the problem that the roadbed settlement process cannot be detected in time in the existing roadbed settlement detection process is solved. And when the settlement exceeds a threshold value, timely discovery and processing cannot be carried out.

The invention relates to the technical field of municipal construction quality tracking, in particular to a municipal road construction quality tracking monitoring management platform. The system comprises a road surface data monitoring unit, and the road surface data monitoring unit monitors road surface basic data based on a sensor monitoring module; the construction monitoring unit is used for monitoring the asphalt penetration, the operation track of the construction machinery and the vibration frequency of the construction machinery; performing multi-source data fusion on the monitored data based on a multi-source fusion algorithm; constructing a comprehensive risk scoring model based on the fused comprehensive features; and the road risk early warning unit analyzes the road construction quality and performs risk early warning through a multi-modal road analysis model based on the road surface basic data, the asphalt penetration and the mechanical parameters monitored by the construction monitoring unit in real time. A crack-construction-environment dynamic correlation model is constructed, the dynamic interaction strength of crack characteristics and construction parameters is calculated through a cross attention mechanism, and a high-risk area is accurately positioned.

The invention relates to the field of sampling, in particular to a drilling and sampling device for road construction. The sampler comprises a frame and a sampling assembly arranged on the frame, the sampling assembly comprises a drilling cylinder and an inner cylinder, a plurality of drilling tools are hinged to the lower end of the drilling cylinder, the inner cylinder is coaxially inserted into the drilling cylinder, the inner cylinder is of a grating structure and comprises a first cylinder body and a second cylinder body, and a film is arranged in the inner cylinder. When a road surface part is drilled, the drilling tool is in a horizontal state, the contact area between the drilling tool and the road surface is large, large cutting supporting force can be kept, a drilling barrel is prevented from being stressed and deformed, when a roadbed part is drilled, the drilling tool is in an upright state, the contact area between the drilling tool and the roadbed is small, the cutting speed is increased, and the cutting efficiency is improved, so that different drilling requirements are met; meanwhile, when the roadbed part is cut, the inner cylinder is inserted into the roadbed in advance to support the roadbed, after drilling is finished, the thin film is pulled open to wrap the sample core, it is guaranteed that the distribution state of all layers of structures of the sample core is accurate, and the authenticity of the sample is guaranteed.

The invention relates to the technical field of big data monitoring, in particular to a highway environmental protection construction monitoring method and system based on big data, and the method comprises the following steps: calculating the spatial distance between sensors based on the geographic position information of a data collection point and the raised dust concentration distribution and particulate matter monitoring value of a road construction environment, and calculating the spatial distance between sensors; and connecting sensor nodes with a direct adjacency relation through difference calculation and normalization processing. According to the invention, through probability density calculation and time sequence analysis, abnormal edge screening, abnormal change detection precision improvement, misjudgment reduction, abnormal edge connection node position and space density calculation, high-density area and cluster center determination, accurate positioning of pollution points is realized, and the method is suitable for the real-time monitoring of the pollution points in combination with monitoring data change trend and diffusion path tracing. The method comprises the following steps: reconstructing a pollution diffusion chain, determining a pollution propagation range, optimizing pollution treatment, accurately identifying a pollution source through weight association degree and gradient analysis between path nodes, reducing monitoring blind areas, and providing comprehensive support for construction monitoring.

The invention provides a highway construction safety inspection method and system based on an unmanned aerial vehicle field, and the method comprises the following steps: collecting the data of a highway construction scene through a collection terminal, and carrying out the preprocessing of the collected real-time data; inputting the preprocessed data into a path planning module, calculating the patrol path weight of the unmanned aerial vehicle, and generating an optimal patrol path; the data is input into an anomaly detection module for edge calculation, and when abnormal information is detected, the abnormal information is fed back to a path planning module to implement path adjustment; and inputting abnormal information into a cloud image processing model, carrying out mutual learning through a knowledge distillation mechanism, training a cloud teacher model by utilizing incremental data, and deploying a trained student model in an anomaly detection module. According to the method, complex environment changes are coped with through reinforcement learning and a self-evaluation algorithm, and efficient detection is realized through an incremental framework and knowledge distillation balance precision and speed; the whole scene is covered through an air-fixed point-moving three-in-one mode, and multi-mode cooperation is achieved.

The invention discloses dust falling equipment for municipal road construction and a using method, and relates to the technical field of construction dust falling, the dust falling equipment comprises a chassis and universal wheels fixedly installed on the periphery of the bottom of the chassis, the top of the chassis is fixedly connected with a top plate, the dust falling equipment further comprises a water tank, a driving mechanism is fixedly connected to one side of the top of the top plate, and the driving mechanism is arranged on one side of the water tank; a spraying mechanism is arranged on the other side of the top of the top plate; the pressure pump is fixedly installed on one side of the top of the water tank, the end, away from the pressure pump, of the drainage pipe is connected with a telescopic pipe, and a spraying barrel is installed on the top of the top plate; the driving mechanism comprises an upper box body, and the bottom of the drainage pipe is connected with a connecting pipe; the spraying mechanism comprises a cam and a flange plate, the interior of the flange plate is connected with a rack in a sliding mode, and the problems that transverse swing adjustment and vertical swing adjustment of the device are adjusted through a servo motor and an electric hydraulic push rod respectively, operation is inconvenient, the adjustment efficiency is not high, and more energy is consumed are solved.

The invention provides a road construction carbon emission monitoring method, which belongs to the technical field of electric digital data processing, and comprises the following steps: establishing a monitoring network through a multi-source sensor, collecting equipment operation, material consumption and construction activity data by using an Internet of Things terminal, and calculating carbon emission in combination with a carbon emission factor database to form a fingerprint spectrum. Edge calculation is adopted to carry out time sequence analysis to recognize abnormal points, a neural unit jump algorithm and a multi-head attention architecture are applied to carry out fine adjustment on a pre-training model, and a jump threshold value is calculated through a specific function. And introducing a distributed gradient descent optimization equation to integrate data of multiple construction sites to protect privacy, and generating a monitoring report including total carbon emission, intensity and emission reduction suggestions. And by adaptively adjusting the monitoring time interval, the carbon emission monitoring precision and efficiency are improved. The pre-training model adopts a multi-layer time convolutional network structure, and the adaptability to a specific construction scene is improved through unsupervised pre-training and supervised fine tuning.

The invention discloses a regional highway road network habitat quality evaluation method and system, and aims to construct a habitat feature library reflecting habitat spatial features and a biological utilization mode by integrating remote sensing image data and biological activity trajectory data. Identifying an ecological fault zone caused by road network cutting by adopting a space fracture analysis technology, quantifying the barrier strength of the road and determining an influence range; analyzing and extracting a key migration gallery by using a species migration network, and evaluating a landscape connectivity condition; a restoring force loss area is identified through ecological restoring force evaluation, and the habitat degradation dynamic state is revealed in combination with time sequence analysis; establishing a multi-scale space evaluation system, and fusing the quality grading sequence and gallery optimization information to generate a habitat quality evaluation matrix; and finally, a complete habitat quality grading scheme is formed through spatial interpolation and natural breakpoint grading, comprehensive evaluation of the habitat quality of the regional highway network is realized, and a scientific basis is provided for ecological protection planning and road construction decision making.

The utility model discloses a highway base layer compactness detection sampling device, which relates to the field of road construction and comprises a drill cylinder, a first cavity and a second cavity are arranged in the cylinder wall of the drill cylinder, a sleeve is sleeved on the top of the drill cylinder in a sliding manner, the cylinder wall of the sleeve is positioned in the first cavity, and a plurality of elastic steel sheets which are circumferentially distributed at equal intervals are fixedly connected to the bottom of the sleeve. The elastic steel sheet extends into the second cavity, a push-pull mechanism used for driving the sleeve to move relative to the drilling barrel is arranged on the bearing plate, and a squeezing and pushing mechanism used for pushing out a sample in the drilling barrel is installed on the push-pull mechanism. After the drilling barrel completes soil drilling and sampling, the push-pull mechanism drives the sleeve to move downwards, the sleeve drives the elastic steel sheets to move downwards, and the elastic steel sheets are extruded and bent and then seal the bottom end of the drilling barrel, so that a sample is prevented from falling off in the upward moving process of the drilling barrel, and the integrity of the sample is ensured; the sample in the drill cylinder is pushed out through the extruding and pushing mechanism, the drill cylinder does not need to be opened manually, operation is more convenient, and the possibility that the sample is broken is reduced.

The invention discloses a multi-parameter fusion inclinometry safety monitoring method, and relates to the technical field of data processing, and the method comprises the steps: integrating an inclinometer, a displacement sensor, a stress sensor and a temperature sensor to construct a multi-sensing monitoring array, monitoring a road construction process at a fixed point, collecting and obtaining multi-source monitoring data, and carrying out offset compensation and fluctuation trend analysis. Acquiring a multi-source monitoring deviation value and a multi-source monitoring fluctuation curve; performing road inclination trend prediction through an inclination prediction plug-in; and if the inclination prediction angle exceeds the preset scalar, generating an early warning signal and carrying out construction early warning. The technical problems that in the prior art, a traditional inclination survey safety monitoring method is difficult to comprehensively and accurately monitor the road inclination condition, the inclination trend cannot be predicted in real time, and the real-time performance and accuracy of construction monitoring are low are solved, and the purposes that potential risks are recognized in time through multi-parameter fusion monitoring and real-time inclination trend prediction are achieved. And the real-time performance and the accuracy of construction monitoring are improved.

The invention relates to the technical field of road surface detection, and particularly discloses a road surface water seepage detection device for road construction, which comprises a measuring cylinder, a first valve, a second valve, a base, a rotating assembly and a supporting seat, the bottom side of the measuring cylinder is provided with a water outlet, and the bottom side of the base is provided with a groove; a first mounting hole and a second mounting hole which are communicated with the groove are formed in the top side of the base, the first mounting hole is communicated with one port of the first valve, the other port of the first valve is communicated with a water outlet of the measuring cylinder, and the second mounting hole is communicated with one port of the second valve; according to the road surface water seepage detection device for road construction, liquid paraffin is adopted for blocking a road surface outside the water seepage range, operation is easy, time is short, and meanwhile the influence of road surface runoff on water seepage detection is reduced.

The invention belongs to the technical field of asphalt mixtures, and relates to a high-dosage RAP low-temperature hot mix plant recycled SMA-13 asphalt mixture and a preparation process thereof, and the low-temperature hot mix plant recycled SMA-13 asphalt mixture comprises the following components by weight: 50-60 parts of an asphalt mixture reclaimed material; 30-40 parts of modified steel slag aggregate; 3-5 parts of SBS modified asphalt; 0.02 to 0.06 part of a low-temperature asphalt modifier; 3-8 parts of superfine slag powder; 0.2 to 0.5 part of lignin fiber; and 1-2 parts of a self-made asphalt regenerant. The limitation of the traditional RAP doping amount is broken through, the highest doping amount reaches 70%, the steel slag recycled aggregate replaces natural aggregate, the consumption of raw materials and the emission of waste are remarkably reduced, and the steel slag recycled aggregate meets the target requirements of the new era of dual-carbon strategy and sustainable development; and the method is particularly suitable for winter construction, heavy traffic roads and green road construction in iron and steel industry areas, and has technical advancement and engineering practicability.

The utility model relates to the field of road construction, and discloses a dust falling device for asphalt road construction, which comprises a support frame, the lower end of the support frame is fixedly connected with a base, the front end of the outer arc surface of the support frame is fixedly connected with a light-transmitting plate, and the upper end of the support frame is provided with a rotary spraying device. A dustproof device is arranged at the lower end of the rotary spraying device, the rotary spraying device comprises a rotary bin, a sealing bearing is fixedly connected to the lower end of the inner surface of the rotary bin, and a water inlet pipe is fixedly connected to the end, away from the rotary bin, of the sealing bearing. Through the arrangement of the rotating bin, the sealing bearing, the water inlet pipe, the water pump, the water tank and the spray head, the rotating bin can be pushed to rotate through the counter-acting force of water mist sprayed out of the spray head after the water pump pressurizes water, and the spray head can synchronously rotate along with the rotating bin in the rotating process, so that the dust falling spraying range of the device is expanded; and the spraying process does not depend on external environment wind power.

The invention belongs to the technical field of wind power plants, and provides a wind power plant equipment type selection and arrangement optimization method and system. The method comprises the following steps: determining a matched wind turbine generator type according to the wind speed level and trust level requirements of a wind power plant; rasterizing an area in a preset wind power plant boundary, setting each grid vertex as a fan location point, and optimizing a wind turbine generator arrangement scheme of a determined type by taking the maximum power generation capacity of the whole wind power plant as an optimization target to obtain a micro-siting layout scheme; based on a preset noise evaluation model, correcting the post-micrositing layout scheme; taking a site in the boundary of the wind power plant with the lowest total cost as a site selection result of the booster station; and based on related information of a wind power plant site selection map, determining optimal results of a wind power plant road and a current collection line by taking the minimum total cost of road construction and the minimum project amount of the current collection line as targets, and finally obtaining a wind power plant equipment type selection and arrangement optimization scheme.

The invention relates to the technical field of data processing, and discloses a road construction equipment scheduling method, device and equipment and a storage medium. Road identification information and road construction equipment configuration information of a target road construction task are obtained, and road construction content matched with the road identification information and the road construction equipment configuration information are used for scheduling road construction equipment; determining ideal construction progress information of a plurality of road construction procedures, and considering the total construction duration and the total scheduling path by utilizing an established construction scheduling map and a construction deadline period matched with the road identification information; the method comprises the steps of generating an execution sequence including a plurality of road construction procedures in a plurality of road construction sections and a construction execution standard time period, and finally driving construction management personnel to execute road construction equipment scheduling among the road construction sections. Reasonable scheduling of road construction equipment during construction of a plurality of construction roads in a road construction task is realized.