161 results about "Industrial area" patented technology

The invention discloses an industrial area atmospheric environment monitoring management system and method, and relates to the technical field of industrial Internet of Things environment monitoring, and the method comprises the steps: triggering polarization imaging to scan a target region based on the time-space information of an abnormal event signal, obtaining the polarization characteristic data of a pollution plume, and generating a spatial distribution characteristic parameter; inputting the sound pressure abnormal indexes and the spatial distribution characteristic parameters into an industrial equipment leakage causal model, calculating a pollution source confidence coefficient, and when the pollution source confidence coefficient reaches a process safety dynamic threshold value, obtaining an industrial equipment traceability result and a leakage level; according to the traceability result of the industrial equipment and the leakage level, a hierarchical control instruction is obtained, meanwhile, the actually measured attenuation rate of the industrial pollutants is calculated, and the dynamic response effect is verified; according to the method, cross-modal fusion modeling is carried out on acoustic abnormal information and pollutant spatial distribution characteristics, so that the technical limitation that pollution source positioning is carried out by depending on a static empirical formula traditionally is broken through.

The invention relates to the technical field of cathode protection, in particular to a method for optimizing cathode protection of a complex buried pipe network under current interference, which comprises the following steps of: collecting data of soil resistivity, pipeline material and environment humidity from differentiated industrial areas by adopting an on-site sampling mode, and analyzing the variation and relevance of the data to obtain the cathode protection of the complex buried pipe network. And obtaining environmental parameter characteristics. According to the invention, through the scene test adjustment model of the simulation environment, various complex interference conditions can be accurately corresponding, the distribution of current and potential can be optimized, the stability of the cathode protection system in the variable interference environment is improved, and through the simulation of the electromagnetic field data and the multi-round simulation test, the fine adjustment of the current and potential parameters is realized; the anti-corrosion effect of the buried pipe network and the overall efficiency of the system are remarkably improved, long-term safety and stability of the buried pipe network in a complex current interference environment are ensured through real-time monitoring and adjustment, and the service life of facilities is remarkably prolonged.

The invention relates to the technical field of agricultural development, and discloses a characteristic rural industry green planning system combined with economic analysis, and the system comprises a data collection and analysis module which is used for collecting and integrating policy information, environment data, economic data and market demand information; the environment evaluation and grading module is used for dividing the rural industrial area into a green multi-dominant production area, a pollution-free multi-dominant production area, a green less-dominant production area and a pollution-free less-dominant production area; the industrial planning module is used for designing production, processing, packaging and supply chain schemes of characteristic agricultural products and constructing a brand construction scheme in combination with regional historical and cultural characteristics; the economic analysis module is used for analyzing economic benefits of the industry, evaluating risks and providing an optimization scheme; and the intelligent auxiliary decision-making module simulates economic and ecological influences of different planning schemes. According to the method, intelligent and dynamic planning is realized through reinforcement learning, linear planning and a system dynamics model, and the scheme is quickly adjusted according to real-time environment, economy and policy data.

The invention relates to the field of urban public transport deployment, and provides a public transport network matching method and system based on an urban space structure, which divides urban areas by constructing a traffic model, identifies areas with dense demands on the basis of power consumption density, and provides a public transport network matching method and system based on the urban space structure. And the coverage condition of the existing public transport network on the areas with dense demands is evaluated, and uncovered areas are identified. For the uncovered areas, the information of stores and companies in the map data is used to subdivide the uncovered areas into a plurality of types of areas. A bus rapid transit system is additionally arranged in a commercial district to improve transportation efficiency, a peak period special line is additionally arranged in an office building area to meet commuting requirements, a customized bus special line is provided in an industrial district to meet requirements of specific periods and routes, and a conventional bus route is additionally arranged in a residential district to improve daily travel. Accurate matching between the urban space structure and the public transport demand is realized, and the coverage rate and efficiency of public transport service are improved.

The invention discloses an outdoor environment health monitoring method based on an olfactory chip, and relates to the technical field of environment health monitoring. A traditional sensor and an olfactory chip are adopted at a monitoring node at the same time, so that synchronous acquisition of temperature, humidity, gas concentration and complex smell fingerprints is realized; the limitation of identifying multi-component pollutants in a complex environment of an industrial area by a single data source is fundamentally made up; the traditional method is difficult to distinguish cross interference of various gases, however, in the invention, a deep neural network is combined with an attention mechanism to extract implicit features of sensing data, and data cross correction is realized through space-time correlation analysis, so that the accuracy of pollutant identification is remarkably improved; further introducing a graph neural network to carry out modeling on spatio-temporal data of each monitoring node, capturing space structure information of the whole monitoring network, and forming a fusion feature vector with relatively high distinguishing capability; the problem of signal cross interference when various malodorous gases are mixed in an industrial area is effectively solved.

The invention discloses an LNG (liquefied natural gas) station site selection method and device based on multi-scene dynamic coupling, a computer and a storage medium, belongs to the technical field of LNG infrastructure planning and intelligent transportation, and solves the technical problem that LNG station site selection is difficult to accurately predict under multi-scene dynamic change. The method comprises the following steps: collecting multi-scene site selection data of the LNG filling station; data processing is carried out, and a space-time fusion big data medium table is constructed; constructing a long short-term memory network LSTM and reinforcement learning RL coupling model, and obtaining a real-time demand prediction result; a multi-constraint site selection optimization model is constructed, and an LNG gas station candidate site set is obtained; performing optimization through scene classification and feature modeling and defining a multi-scene layout criterion to obtain an LNG gas station candidate set adaptive to multiple scenes; according to the method, the site selection planning of the LNG filling station is realized by fusing the requirements and constraints of multiple scenes such as high speed, suburban, city and industrial districts, and the method is suitable for the field of administrative planning of the government and site selection planning of gas supply enterprises on the LNG filling station.

The invention discloses an underwater acoustic-magnetic multi-modal fusion processing method, which comprises the following steps: carrying out preprocessing and time-space alignment on collected sonar and magnetic data, and extracting a morphological feature vector and a magnetic feature vector of a pipeline; based on a pipeline route trend, calculating an optimal matching path of a sonar contour and a magnetic force abnormal zone through dynamic time warping, establishing acoustic-magnetic mapping, and fusing features to generate a joint vector; finally, the type and state of the pipeline are judged according to the combined characteristics, and the problem that in a near-shore port and an industrial area water area, due to the interference of construction waste and the influence of a pipeline coating layer, a single sonar is difficult to accurately detect the pollution discharge pipeline and the cable is solved. According to the method, the complementarity of acoustic and magnetic characteristics is utilized, the accuracy of pipeline detection in a complex scene is improved, and reliable data support is provided for operation and maintenance of near-shore water area pipelines.

The invention discloses an industrial park comprehensive energy system low-carbon planning method considering a production process, and the method comprises the following steps: 1, obtaining the production line condition of an industrial park, and constructing a production line model; 2, determining to-be-planned equipment and parameters, and constructing a lower-layer planning operation model considering short-term uncertainty; 3, determining medium and long term uncertainty parameters, and constructing a medium and long term uncertainty set; step 4, determining a multi-objective optimization model; 5, searching a Pareto leading edge by using multi-target reinforcement learning based on a decomposition technology; and 6, selecting a proper Pareto frontier solution, and substituting the Pareto frontier solution into the lower-layer planning operation model to obtain a corresponding planning result. The invention aims to realize low-carbon transformation of an integrated energy system (IRIES) in an industrial area so as to cope with carbon reduction, emission reduction and challenges in a carbon dense area.

The invention belongs to the technical field of industrial area green land planning, and discloses a GIS-based industrial green land carbon evaluation decision system and method, which perform integrated scheme decision by acquiring multi-source dynamic data, performing space unit division, predicting dynamic carbon emission, identifying hot spot areas and time, and comprehensively considering factors such as vegetation characteristics and budget constraints. According to the method, dynamic changes of industrial development in an industrial area, staged green land construction budget and time sequence characteristics of vegetation growth can be comprehensively considered, and a green land planning scheme for realizing carbon sink benefit and cost input optimization matching in a planning period is generated.

The invention discloses an unmanned aerial vehicle countering method and device based on sound wave resonance, and the method employs sound waves to interfere with a camera anti-shake compensation device of an unmanned aerial vehicle and an unmanned aerial vehicle flight control system, thereby enabling a camera of the unmanned aerial vehicle to achieve the fuzzy video shooting and out-of-control flight, and achieving the countering of the unmanned aerial vehicle. And personal life safety is prevented from being threatened or normal operation of nearby civil electronic equipment is prevented from being interfered. The method and device provided by the invention can be used for low-cost-efficiency-ratio countering of malicious unmanned aerial vehicles in densely distributed areas of population and buildings such as urban living quarters, commercial districts and industrial districts, and privacy information of individuals and enterprises is protected from being stolen by malicious persons.

The invention relates to the technical field of urban carbon emission intelligent management, and discloses an AI-based urban carbon emission intelligent management system and method. Comprising an urban industrial carbon emission data processing module, an urban traffic carbon emission data processing module, a resident energy use carbon emission data processing module, an urban carbon sink data processing module, a carbon emission gathering module and a carbon emission processing demand module. According to the method, the total amount of carbon emission of an industrial area of a current city and a corresponding industrial area in a collection period, the number of traveling vehicles and the total traveling kilometers in the collection period are combined with the total amount of fuel gas and coal used by residents in the current city in the collection period and the total greening area of the city; and meanwhile, early warning and management are carried out according to the urban carbon emission indexes and the urban carbon emission total amount, so that the actual condition of the carbon emission is measured in time, and early warning is carried out according to the actual condition.

The invention provides a high-performance concrete anticorrosive paint and a preparation method of a coating, and relates to the technical field of building materials and corrosion prevention. The coating is composed of a component A and a component B, the component A comprises epoxy resin, a composite solvent, an organic solvent, a dispersant, fumed silica and a leveling agent, and the component B comprises an epoxy hardener, a conductive polymer dispersion liquid and an organic solvent. The composite solvent is formed by compounding one or more of orthotitanate, phosphate and orthosilicate with an ester, ketone, alcohol, aromatic hydrocarbon, aliphatic hydrocarbon or ether organic solvent. The preparation method of the anticorrosive coating comprises the following steps: preparing the component A and the component B, mixing to form a coating, applying the coating to the surface of concrete, and curing. The coating is compact in structure and strong in adhesive force, can obviously improve the durability and corrosion resistance of concrete in extreme environments such as high salinity and high acid, and is particularly suitable for infrastructure protection in coastal and heavy corrosion industrial areas.

The invention relates to a marine pollution monitoring method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a regional map corresponding to each sewage draining exit, determining a residential area and an industrial area based on the regional map, determining an aquaculture area based on a marine area, and determining the inspection sequence of each sewage draining exit based on the three areas. The unmanned aerial vehicle is controlled to fly to the position above each sewage draining exit according to the inspection sequence to collect a first image of each sewage draining exit, the emission grade of each sewage draining exit is determined based on the inspection sequence and the first image, and the unmanned aerial vehicle is controlled to fly to the position above the ocean area corresponding to each sewage draining exit to obtain a second image, and determining a floating object pollution level of each sea area based on the second image, and determining a sampling priority of each sea area based on the emission level and the floating object pollution level. The sampling sequence of the sea area where each sewage draining exit is located is determined according to the specific conditions of the sewage draining exits and the areas where the sewage draining exits are located, and the severely polluted areas are found in time.

The invention discloses an improved multi-target particle swarm solving multi-spatio-temporal integrated energy system scheduling method. A flow chart is as shown in Figure 1. The method particularly relates to the fields of operational research, comprehensive energy systems, multi-objective optimization and the like. The method comprises a model part and a solving algorithm part, the model is a comprehensive energy system scheduling mathematical model of industrial district, commercial district and residential district collaborative scheduling multi-time scale rolling optimization, and objective functions are the lowest cost and the lowest carbon emission respectively; a solution algorithm is an improved multi-target particle swarm optimization algorithm, and compared with a traditional algorithm, a local search mechanism is introduced, a storage system is adjusted, and self-adaptive adjustment of inertia weight is achieved. According to the model, the expansion machine is added, redundant natural gas pressure energy is utilized, meanwhile, compared with a traditional algorithm, the algorithm is higher in diversity, higher in speed and higher in quality, and the problems that an existing comprehensive energy system is complex in environment, excessive in uncertainty, single in target and the like are effectively solved.

The invention relates to the field of industrial energy consumption data monitoring, in particular to a hydroelectric energy consumption data monitoring method and system based on edge computing, and the method comprises the steps: preprocessing the historical data of water meters and electricity meters in an industrial region, carrying out the clustering analysis to form a water meter cluster and an electricity meter cluster, and deploying an isolated forest model on an edge node corresponding to each cluster. And training a model by using a clustering result, and updating a model weight according to new data so as to adapt to data change. And inputting real-time data into the updated model, and calculating an abnormal score to evaluate whether the energy consumption data is abnormal or not, thereby realizing accurate hydroelectric energy consumption monitoring. According to the method, the adaptability and accuracy of hydroelectric energy consumption anomaly detection are remarkably improved by training and deploying the isolated forest models on the edge nodes for different equipment clusters and dynamically updating the model weight in combination with the similarity of the new data set.

The invention discloses a parallel operation control system for multiple fuel generator units, and relates to the technical field of parallel operation control, the system collects unit operation data in real time through a sensor, and an operation steady state data set is obtained after data preprocessing; calculating an operation steady-state function index ywt based on the operation steady-state data set, and performing parallel operation conformity evaluation on the operation steady-state function index ywt and a preset operation steady-state safety threshold Z; calculating a load distribution index fhf and the actual output power sjg of the unit when the parallel operation requirement is met; performing unit load evaluation according to the load execution rate zxl, and judging whether the load state is abnormal or not; and when the unit load is abnormal, the off-line decision module determines whether to execute off-line and parallel operation instructions by combining the total demand load to of the industrial area and the residual unit load capacity sf. According to the system, through multi-module collaborative optimization, the parallel operation stability and the load management efficiency are improved, and the reliability and the economical efficiency of the power generation system are ensured.

The invention relates to the technical field of elevator guide rail measurement, in particular to an elevator rail straightness detection device and method. Comprising a magnetic rail climbing trolley, a calibration target, a laser calibrator and an industrial area-array camera, the magnetic rail climbing trolley is adsorbed and mounted at one end of the guide rail and can move in the length direction of the guide rail; the calibration target is installed on the magnetic type rail climbing trolley, and a coordinate system is arranged on the calibration target; the laser calibrator is arranged at one end, which is not provided with the magnetic type rail climbing trolley, of the guide rail, faces the calibration target and is used for emitting laser on the calibration target; the industrial area-array camera is installed on the magnetic type rail climbing trolley and used for shooting the calibration target once every set time interval. The guide rail to be installed can be detected and rechecked before the guide rail is installed, and the straightness of the guide rail in the whole hoistway can be detected after the guide rail is installed, so that the straightness detection of a single guide rail can be conveniently and quickly completed on a construction site and in the elevator hoistway.

The invention relates to the technical field of data encryption, in particular to an industrial internet data processing method and system based on big data, and the method comprises the steps: obtaining each data sequence of each industrial region in an industrial park; any two data sequences are respectively marked as a first data sequence and a second data sequence, and sequences with the same length and corresponding to the same time sequence interval are randomly extracted for U times from the first data sequence and the second data sequence; obtaining prediction correlation according to the sequence under each random extraction frequency in the first data sequence and the second data sequence; obtaining a frequent sequence set between the first data sequence and the second data sequence according to the predicted correlation distribution between the data sequences; constructing a binary tree of the first data sequence according to the frequent sequence set among the data sequences; and generating an initial plaintext state matrix according to the characteristics of the binary tree of each data sequence, and improving an AES encryption algorithm so as to realize big data encryption optimization security protection. According to the invention, the security of industrial data encryption is improved.

The invention provides an artificial board production method and system based on a digital informatization platform, and relates to the technical field of production technology.The artificial board production system comprises an artificial board base material base arranged in a forestry resource-rich area and used for processing forest resources and plant fiber raw materials into an artificial board base material of a shaving board or a fiberboard; the printing, dipping and pressing industrial area and the artificial board base material base are arranged in a centralized mode, and the printing unit comprises a plurality of sets of photogravure printing machines and is used for printing body paper to form artificial board facing decorative paper; the glue dipping unit is used for dipping the printed artificial board decorative paper into a hot-melt melamine glue solution through a glue dipping tank; the pressing and pasting unit is used for performing high-temperature oil pressing on the artificial board base material and the impregnated artificial board facing decorative paper to form a finished board; an intelligent logistics system for centralized production process management and control is used for carrying out intelligent automatic linkage on equipment of a printing unit, an impregnation unit and a pressing and pasting unit, the production cost of an integrated industrial area is greatly reduced, and high-quality management and control can be carried out.

The invention belongs to the technical field of intelligent sensing monitoring and micro-nano energy, and discloses an intelligent acid rain sensing monitoring method and system based on a total-current nano generator. The method comprises the following steps: preparing a total-current nano-generator as a sensing core element, and generating a characteristic electric signal corresponding to a pH value through the action with acid rain; constructing an intelligent algorithm processing module based on a ResNet 18-1D convolutional neural network (CNN), and performing multi-dimensional feature extraction and pH value intelligent classification on the collected electric signals; and displaying the electric signal waveform characteristics and the pH recognition result in real time through a visual interaction interface. According to the invention, the full-current nano generator is combined with the deep learning technology, the technical bottlenecks that a traditional acid rain detection method depends on a large professional instrument, needs external power supply support and is complex in operation process are broken through, and in-situ, rapid and intelligent monitoring of the acid rain pH value is realized. And an efficient and reliable solution is provided for real-time monitoring of acid rain in industrial areas and outdoor environments.

The invention discloses an electricity-heat-hydrogen multi-microgrid system optimization scheduling method suitable for considering uncertainty. According to the method, firstly, an electricity-heat-hydrogen multi-microgrid system architecture is constructed, and the system is divided into an industrial area and a residential area which have independent energy production and load requirements; an equipment model in the system is established, and uncertainty modeling is carried out on solar irradiance and wind speed by adopting beta distribution and Weibull distribution according to photovoltaic and fan output fluctuation. On the basis of the model, a cost objective function of the system is constructed, and the cost objective function covers productivity consumption, maintenance, faults and energy procurement cost. Finally, a robust optimization algorithm based on an alternating direction multiplier method is adopted, the global optimization problem is decomposed into local optimization problems of all the subnets, supply and demand balance is achieved through information exchange, and the adaptive output power of all the devices is obtained. According to the method, the influence of renewable energy source volatility on equipment output is fully considered, and the energy utilization efficiency is improved and the system operation cost is reduced by cooperatively scheduling power, heat and hydrogen resources.

The invention relates to the technical field of heat supply system remote monitoring, and discloses an intelligent heat meter remote data acquisition method based on edge calculation. The method comprises the following four steps: constructing a user-device double-causal network model, realizing an anomaly detection and attribution mechanism based on causal reasoning, developing an interpretable anomaly report generation system and realizing a predictive maintenance suggestion system. By constructing the double-causal network reflecting the causal relationship between the user behavior and the system physical state, accurate attribution of abnormal data is realized, user behavior changes and equipment faults can be accurately distinguished, the diagnosis accuracy is improved, the false alarm rate is reduced, and the user experience is improved. The system is particularly suitable for remote monitoring and maintenance management of heat supply systems of large residential districts, commercial buildings and industrial districts and remote or difficult-to-reach heat supply stations.

The invention relates to an industrial area risk management and control technology, in particular to an industrial plant area environment risk management and control system, which comprises the following steps: firstly, carrying out statistical analysis on accident points of each area in a plant area, then evaluating the risk level of each accident point, and then analyzing the overall area risk index of the area according to each accident point; a corresponding accident monitoring terminal is arranged at each accident point to carry out real-time risk factor monitoring on each accident point, real-time monitoring of risks of each area in a factory area is realized, abnormity is found in time and early warning is carried out, accident information is displayed through an alarm display module, and a corresponding maintenance route is planned. And the safety management efficiency of the factory area is improved while the fault occurrence rate of the factory area is reduced.

The invention relates to the technical field of environment monitoring, and discloses an environment-friendly environment monitoring system, which collects static and dynamic data through a fixed monitoring station and a mobile device, realizes frequency adaptive calibration by adopting a linear interpolation or spline interpolation algorithm, and constructs a fusion data matrix of time-space alignment; matching an optimal environment evaluation model based on an optimization algorithm (such as an eagle algorithm), and dynamically selecting a prediction algorithm in combination with pollution characteristics; a differential response strategy is triggered through a multi-stage early warning mechanism (yellow / orange / red), a pollution source positioning map and an emergency scheme are synchronously generated, and'monitoring-analysis-disposal 'closed-loop management is realized. The method can be applied to the scenes of urban atmosphere, river water quality, industrial area multi-parameter pollution and the like, the monitoring precision (the omission ratio is reduced by more than or equal to 25%), the response speed (the early warning push is less than or equal to 8 seconds) and the resource utilization efficiency (the energy consumption is reduced by 20-35%) are effectively improved, and a high-reliability solution is provided for intelligent environmental protection.

The invention provides a carbon neutralization zoning simulation method, system and device based on a smart city, and relates to the technical field of carbon neutralization simulation, and the method mainly comprises the steps: carrying out the planning zoning of a map of a tested city; calculating the carbon emission of each partition and carrying out visualization processing to obtain geographic space data; calculating the carbon sink amount of each partition; collecting output value basic data of each industry of the detected partition and marking the output value basic data in geographic space data; carbon emission basic data, carbon sink basic data and output value basic data which are regularly acquired by a smart city system are stored in a smart city database based on a time sequence; predicting the future carbon emission, carbon sink and output value of the measured subarea; constructing a time sequence dynamic optimization model, and solving an industrial area layout scheme through a parallelization genetic algorithm; and generating suggestion information. According to the scheme, a quantifiable and adjustable carbon management tool is provided for overall planning of urban territorial space, and the scheme is particularly suitable for low-carbon planning and treatment of high-density coastal cities.

The present invention relates to the production of a sound-insulating textile surface comprising two fabric layers laminated to each other with the coated surfaces remaining on the inner surface, while the fabric surfaces remain on the outer surface. Providing benefits such as preventing noise pollution, improving sound acoustics and increasing privacy in many sectors from construction sites to production facilities, from homes to offices, from automobiles to industrial areas. The versatility of this fabric offers significant advantages, both aesthetically and functionally.

The present invention relates to the production of a sound-insulating textile surface comprising two fabric layers laminated to each other with the coated surfaces remaining on the inner surface, while the fabric surfaces remain on the outer surface. Providing benefits such as preventing noise pollution, improving sound acoustics and increasing privacy in many sectors from construction sites to production facilities, from homes to offices, from automobiles to industrial areas. The versatility of this fabric offers significant advantages, both aesthetically and functionally.

The present invention provides a method, system and medium for classified control of heavy metal pollution in cultivated land, relating to the technical field of environmental protection, including: obtaining remote sensing image data of a strictly controlled area for heavy metal pollution, and dividing the strictly controlled area into multiple plots with different environmental conditions by using the object-oriented method; constructing multiple suitability constraint conditions for the control measures in the strictly controlled area by using the distance to the town, the distance to the industrial area, the slope, the production capacity, the control measures and the area variable; taking the expenditure cost, the cultivated land area and the safety utilization rate of various control measures in the strictly controlled area as the constraint conditions of the control measures in the strictly controlled area, and combining with the suitability constraint conditions to obtain the classified control measures with the minimum total cost in the strictly controlled area for heavy metal pollution. The above method helps to realize the zonal and block management of cultivated land polluted by heavy metals.

1. The name of this design product: stainless steel vacuum breaker valve. 2. Application of the product with this design: Pipe valves used in urban water supply stations, construction sites, industrial areas, etc. 3. The design key point of this appearance design product lies in the shape. 4. The picture or photo that best illustrates the key points of the design: main view.

The application belongs to the technical field of industrial green land planning, and discloses a GIS-based industrial green land carbon assessment decision system and method. Through acquisition of multi-source dynamic data, spatial unit division, prediction of dynamic carbon emission, identification of hot spot areas and time, and integrated scheme decision considering factors such as vegetation characteristics and budget constraints, the system can comprehensively consider the dynamic changes of industrial development, the budget of green land construction in different stages, and the time sequence characteristics of vegetation growth, and generate a green land planning scheme that optimally matches carbon sink benefits and cost input within a planning period.