47 results about "Urban solid waste" patented technology

A system and method for assessing surface methane concentrations through surface emissions monitoring utilizing unmanned aerial vehicles at municipal solid waste landfills. The method uses a combination of UAV-based and ground-based SEM techniques to measure methane concentrations at the surface of a landfill, to calculate zone-average methane concentrations on the surface and to identify methane leaks at landfill cover penetrations.

The present invention provides a method for washing chlorine bypass dust with water, which can reduce the selenium concentration in the wastewater discharged when chlorine bypass dust is washed with water, while keeping costs for equipment and chemicals down. [Solution] A method for washing chlorine bypass dust, comprising a slurrying step of adding washing water to chlorine bypass dust to form a slurry, and a solid-liquid separation step of separating the liquid phase from the slurry, wherein the slurry further contains municipal solid waste incineration fly ash in addition to the chlorine bypass dust, and the municipal solid waste incineration fly ash accounts for 15% by mass or more and 80% by mass or less of the total amount of the chlorine bypass dust and the municipal solid waste incineration fly ash.

The application discloses a kind of urban solid waste incineration process furnace temperature robust prediction method, comprising the following steps: S1, according to the initial furnace temperature model of preset training set is established;S2, assume that the prior distribution of noise in training data follows skew t distribution, the output weight and the set of hyperparameters of model are iteratively optimized by maximum likelihood estimation and expected conditional maximum algorithm, establish furnace temperature prediction model;S3, furnace temperature in incineration process is predicted by furnace temperature prediction model.The process data of urban solid waste incineration process is obtained in real time, and the furnace temperature prediction model based on robust random configuration network is established, the prior distribution of asymmetric abnormal value in incineration process operation data is simulated by skew t distribution with heavy tail characteristics, and the output weight of furnace temperature prediction model is solved by maximum likelihood estimation method, the robustness of furnace temperature prediction model to abnormal data is improved, and the real-time accurate prediction of urban solid waste incineration process furnace temperature is realized.

The invention relates to a construction material (S), wherein the construction material (S) comprises at least cement clinker (ZK) and at least one water hardening additive (X), wherein at least one water hardening additive (X) is mixed with the cement clinker (ZK) and is not a component of the cement clinker (ZK) itself. [0002] According to the invention, the at least one water hardening additive (X) contains conventionally ground and processed municipal solid waste incineration ash (gHMVA), wherein the conventionally ground and processed municipal solid waste incineration ash (gHMVA) has a particle size of < 200 μm, and contains thermally incinerated municipal solid waste (H), and is not subject to any material alteration and / or thermal treatment except during the incineration of the municipal solid waste (H) and / or after the conventional incineration and processing of the municipal solid waste (H).

The embodiment of the invention provides a high-temperature heat storage structure based on solid waste-based variable stiffness support and dynamic stress compensation and a preparation method of the high-temperature heat storage structure. The heat storage structure comprises a core assembly filled with a solid-waste-based composite phase change material, an intelligent regulation and control assembly arranged on the periphery of the core assembly in a sleeving mode, a variable-rigidity flexible constraint assembly arranged on the periphery of the intelligent regulation and control assembly in a sleeving mode, and a heat blocking assembly arranged at the upper end of the core assembly in a sealed mode. Wherein the intelligent regulation and control assembly performs self-regulation according to the detected strain information of the core assembly and generates deformation for compensating thermal stress. The solid-waste-based high-energy-storage phase-change material is used as a core material of the core assembly to store heat, so that the urban solid waste emission can be effectively reduced, the environmental pollution is reduced, and the environmental protection is facilitated.

Method for regulating and / or controlling lightweight packaging and / or municipal solid waste processing plants by changing a material flow, wherein the processing plant is first fed with material to be processed using a mobile technology, wherein the material is subsequently broken up and / or shredded by means of a shredder to form a uniform material flow on a conveying technology, wherein the material is then fed to at least one sorting stage using a conveying technology, wherein the following is used as a measurement variable of the method: - a fill level of a hopper of the shredder and / or - the volume flow rate of the material flow, wherein the measured quantity is measured contactlessly using sensor technology, wherein the following is used as the control and / or regulated variable of the process: - the shredding behavior of the shredder via its load capacity, and / or - the feeding of the processing plant with the mobile technology, and / or - Changes to plant operating parameters, where a feeding signal for the supply of the system is communicated to a loading personnel by means of a warning message.

The application relates to a solid waste incineration process furnace temperature and flue gas oxygen content multi-target prediction method and system, and belongs to the technical field of solid waste incineration. The method comprises the following steps: collecting characteristic data of an incinerator, and collecting the furnace temperature and the flue gas oxygen content at the current moment, and constructing a training set and a test set; training a random configuration network prediction model based on the training set of the incinerator; inputting the test set into the trained prediction model, and recording the output value of the prediction model, so as to verify the prediction accuracy of the prediction model. The method can improve the prediction accuracy of the change trend of the furnace temperature and the flue gas oxygen content in the urban solid waste incineration process, so that the on-site operator can timely master the incineration working condition of the solid waste in the furnace, thereby guaranteeing the optimization control of the incineration process.

The invention belongs to the technical field of urban solid waste incineration, and provides an intelligent control method for the position of a combustion line in the urban solid waste incineration process, and the method comprises the steps of control quantity increment calculation, node increment learning, structure simplification, parameter compensation, and inter-layer parameter and intra-layer parameter updating. According to the method, incremental learning and a self-adaptive SPU strategy are embedded in the IT2FBNN, so that the calculation burden is remarkably reduced, and the control precision is improved and the controller structure is compact on the premise of ensuring the stability of the system.

The invention belongs to the technical field of urban solid waste incineration process dynamic optimization, and particularly relates to an urban solid waste incineration process dynamic optimization method and system based on multi-target particle swarm autonomous evolution. The method comprises the following steps: firstly, based on a random configuration integrated network, establishing an operation index model of nitrogen oxide emission concentration and waste heat power generation power; secondly, on the basis of a multi-target particle swarm optimization algorithm, a dynamic optimization strategy with the hearth temperature and the flue gas oxygen content as decision variables is developed; meanwhile, a particle distant parent hybridization strategy is introduced, and crossover variation is performed on population genes through particle swarm grid division, so that the diversity of the population is kept. And finally, a utility function is defined, the optimal set value of the hearth temperature and the optimal set value of the flue gas oxygen content are solved, and multi-target dynamic optimization of urban solid waste incineration is achieved.

Processes for removing oil and other organics especially lipids from process steams comprising lipids, brown grease, and water is disclosed and a process to remove metals and organics from leachate from landfills and other waste sites that generate contaminated water streams. The processes may involve adjusting pH and using electrical fields generated by a device comprising electrodes to induce gas bubbles. The gas bubbles facilitate movement toward the surface of the solution where they may be skimmed off and recovered. Processes are also described that upgrade brown grease to usable precursors for make beneficial products such as jet fuel. Other processes described herein include removal of carbon char from pyrolysis products like tires, plastics, rubbers, municipal solid waste, and oil or sewage sludge.

The application provides an intelligent optimization operation method for urban solid waste incineration process, and relates to the technical field of urban solid waste treatment and intelligent optimization. The method comprises the following steps: obtaining environmental data in the incinerator and concentration values of various incineration exhaust gases before a preset time length; iteratively optimizing the solution of the decision variable, so that the value of the target function obtained according to the solution of the decision variable is optimized in the direction of reduction; determining the solution of the target decision variable to obtain the set value of the oxygen content in flue gas and the hearth temperature in the current urban solid waste incineration process; the calculation step of the value of the target function comprises the following steps: inputting the solution of the decision variable, the environmental data in the current incinerator and the concentration values of various incineration exhaust gases before a preset time length into a pre-trained operation index model, outputting the predicted concentration values of various incineration exhaust gases, calculating the combustion efficiency and the concentration of flue gas pollutants, and obtaining the value of the target function. The combustion efficiency is improved while the emission of flue gas pollutants is reduced.

The method for sensing the temperature of urban solid waste incinerators based on a self-attention hybrid ensemble network belongs to the field of industrial process modeling and intelligent sensing. This method addresses the highly nonlinear, multi-condition variations, and complex physical-chemical reaction mechanisms in the MSWI process. Combining an ensemble learning framework and improved neural network structure, it introduces moving block bootstrap (MBB) sampling based on maximum likelihood estimation (MLE), a self-attention mechanism, and a hybrid ensemble strategy fusing AdaBoost and Bagging to achieve accurate modeling and dynamic prediction of the Fourier transform (FT). This results in good modeling accuracy, generalization ability, and engineering adaptability. Experimental verification under multiple benchmark problems and actual MSWI conditions demonstrates that the proposed FT sensing method exhibits superior performance in both prediction accuracy and robustness, possessing significant engineering application potential and widespread value.

This invention relates to the field of industrial control technology, and provides a multivariate intelligent control method and device for urban solid waste incineration processes. The method includes: acquiring the current state of urban solid waste incineration processes... m j Process variables at time and before m i Key process parameters at each moment; the preceding m j Process variables at time and before m i The key process parameters at a given time are input into a key process parameter prediction model to obtain the predicted values ​​of the key process parameters at the current time. The predicted values ​​of the key process parameters at the current time and the set values ​​of the key process parameters at the current time are input into an objective function to solve the objective function and obtain the change in the manipulated variable when the objective function is minimized. Based on the change in the manipulated variable, the manipulated variable is adjusted to control the key process parameters. This invention achieves stable, accurate, and rapid coordinated control of key process parameters such as furnace temperature and main steam flow.

The invention relates to the technical field of solid waste recycling, in particular to a method for preparing an aerated concrete wallboard from waste aerated concrete, vanadium-titanium slag and lithium slag. The low-carbon powder is prepared from building solid waste, steel solid waste, electric power industry solid waste, coal-based solid waste and urban solid waste, and replacement of Portland cement clinker is achieved; chemical solid wastes are used for replacing all calcium raw materials, namely quick lime; waste aerated concrete and inactivated ZSM-5 are used as high-silica raw materials to replace a silica raw material, namely river sand or fly ash, of a traditional autoclaved aerated concrete plate; solid waste in the nonferrous industry and solid waste in the chemical industry are used as retarders to replace gypsum in traditional raw materials; the pretreated bamboos are adopted as the bamboo reinforcements to replace a steel reinforcement framework, the utilization rate of industrial solid waste is effectively increased, the bamboo is used for replacing steel reinforcements in traditional aerated concrete slab production, the production cost of enterprises is remarkably reduced, and economic benefits and social and environmental benefits are remarkably improved.

The torrefaction unit 1 comprises at least one multiple hearth furnace 2 which is heated by a heat transfer fluid 16 comprising hot water taken from a water space 21 of a steam drum 11. The heat transfer fluid 16 is guided through a water circuit 20 to a heating system 19 of the at least one multiple hearth furnace 2. This means the multiple hearth furnace 2 is heated to a torrefaction temperature indirectly by the use of hot water as heat transfer fluid 16. This is environmentally advantageous. The torrefaction gas 3 created by the torrefaction of material comprising biomass such as municipal solid waste is preferably partially oxidized in a partial oxidation reactor 23 for creating syngas. Preferably, a part of the thermal energy of the syngas is used in an evaporator 9 and / or a superheater 13 to heat water and / or steam and / or to evaporate water. The evaporated water is preferably guided to a steam space 22 of the steam drum 11 and can, thus, be used to heat the heat transfer fluid 16. The partial oxidation reactor 23 and the temperature of the heat transfer fluid 16 can be controlled independently allowing to one single partial oxidation reactor 23 for at least two multiple hearth furnaces 2.

A system of waste management includes a steam gasification unit to convert municipal solid waste to a syngas. A molten carbonate fuel cell (MCFC) unit receives the syngas at an anode and an industrial exhaust gas at a cathode to generate electrical energy and separate a first carbon dioxide gas. An oxygen combustion unit receives remaining syngas from the anode and combusts the remaining syngas with oxygen to generate a heated gas stream. A steam Rankine cycle unit captures a first thermal energy from the heated gas stream. A carbon capture unit separates water and a second carbon dioxide gas from a resulting cooled gas stream. An electrolysis unit uses the electrical energy from the MCFC unit to split water into the oxygen gas for the oxygen combustion unit and a second hydrogen gas for the anode.

Provided is an artificial intelligence (AI) evaluation platform for municipal solid waste incineration (MSWI). The AI evaluation platform for municipal solid waste incineration includes: An AI-driven modeling system of multimodal data is connected to an AI optimization system for cloud-side safety isolation and a synchronous publishing system of multimodal historical data, the synchronous publishing system of multimodal historical data is connected to an AI control system for edge-side safety isolation, and the AI control system for edge-side safety isolation is connected to an AI control system of an end-side multiple-input multiple-output loop and the AI optimization system for cloud-side safety isolation. This application resolves, in conventional technologies, a problem that “AI+MSWI” digital industry clusters cannot implement safety collaboration on a cloud side, an edge side, and an end side, and a problem that MSWI plants are difficult to maintain stable optimization conditions for a long period of time.

The application discloses a kind of urban solid waste treatment devices, it is related to solid waste treatment technical field, the urban solid waste treatment device of this kind includes: strip mechanism, strip mechanism is used to twist cut into strip with plastic piece;Compaction box and compaction mechanism, compaction mechanism includes center compression column, side pressing plate, first compaction drive component and second compaction drive component, the output end of first compaction drive component is transmission connection with center compression column, the output end of second compaction drive component is transmission connection with side pressing plate, let slot is opened in side pressing plate, under the drive of second compaction drive component, side pressing plate is slidably fitted with center compression column by let slot;When compaction mechanism carries out compaction operation to plastic piece, center compression column is located in compaction box, side pressing plate carries out compaction operation to the plastic piece of first compaction area;Side pressing plate moves to initial position, center compression column carries out compaction operation to the plastic piece of second compaction area;The device realizes the regional compaction of plastic block.

The invention provides an urban solid waste incineration process multi-controlled variable prediction method and system based on multi-modal depth feature fusion, and the method comprises the steps: collecting a flame image sequence and a process data sequence, and carrying out the preprocessing of a flame image, and obtaining a standard image set; respectively extracting channel features of the standard image set by using eight deep neural networks, and screening the channel features to obtain a flame image depth feature set; performing feature selection and depth feature extraction on the process data sequence to obtain a process data depth feature set; fusing the flame image depth feature set and the process data depth feature set to obtain a final fusion feature; and inputting the final fusion feature into a multi-controlled variable prediction network for prediction to obtain a multi-controlled variable prediction result. The method can effectively extract and integrate the flame image depth features and the important features of the process data, and achieves the precise prediction of multiple controlled variables in the urban solid waste incineration process, so as to improve the operation efficiency and the environmental protection effect.

This application provides a remote sensing method, apparatus, and processing equipment for urban solid waste extraction based on an improved YOLO V11 model. By making corresponding adaptive optimizations based on the YOLO V11 model, it can effectively solve the contradiction between efficiency and accuracy in solid waste identification of traditional methods, significantly improve the processing capability for large-area and large-scale remote sensing images, meet the high-efficiency and accurate high-quality application requirements in urban solid waste remote sensing monitoring, and thus provide good data support for urban solid waste treatment.

The present technology integrates multiple technologies to substantially reduce the economic and environmental cost of managing municipal solid waste (MSW) and the biomass growth in forests or rangelands. The technology employs rotary kiln gasification of MSW to generate steam, renewable electrical energy, and an inorganic sintered ash suitable for a variety of uses. Net electrical power from the power plant is used to operate a pyrolysis system or a hydrothermal liquefaction unit that converts wood biomass to liquid hydrocarbon fuels. A carbon capture and utilization system uses CO2 recovered from the power plant exhaust stack to generate a variety of fuels and / or specialty chemicals. Steam from the power plant is used to make activated carbon from the char residue from pyrolysis. Revenue from the technology includes gate fees for MSW diverted from landfill, renewable electrical power to the grid, a variety of liquid hydrocarbon fuels and activated carbon.

The application provides a kind of urban solid waste incineration process multi-objective integrated random configuration network furnace temperature prediction method, relating to urban solid waste incineration process furnace temperature intelligent prediction technical field, the method is to the urban solid waste incineration process data is pretreated, by self-service sampling strategy, obtain S training data set;Using random configuration network algorithm, base model construction is carried out, and the base model corresponding to each training data set is obtained;Using global negative correlation integration strategy based, S base model integrated model is trained in parallel, and the learning ability of integrated model to multi-region furnace temperature is realized by introducing group sparse regularization technology, and the trained integrated model is obtained;Using the trained integrated model, the urban solid waste incineration process data is analyzed, and the furnace temperature prediction result is obtained, to complete the prediction of furnace temperature.The application solves the problem of low accuracy and stability of the existing furnace temperature prediction method.

A kind of urban solid waste collection and transportation method for classification processing, comprising: collecting picture information of solid waste, and obtaining a plurality of sub-picture information after preprocessing;Obtain the spectral feature data in each sub-picture information;Spectral feature data is input into the convolutional neural network module trained in advance, and the first feature vector corresponding to each solid waste in sub-picture information is calculated;According to the first feature vector corresponding to each solid waste, based on the trained graph neural network, the node feature matrix is calculated;According to node feature matrix, the second classification result corresponding to each solid waste is output.The present application creatively introduces graph neural network on the basis of convolutional neural network, and the feature information of all solid wastes in the same batch is associated, the feature defects of single solid waste are strengthened, and then the category of each solid waste can be more accurately judged.

A recycling and waste management method is disclosed that receives municipal solid waste (MSW) having a high organic content to form a supercritical water oxidation (SCWO)-based self-sustaining hydrothermal mineralization (HTM) process to receive supercritical steam and carbon dioxide having power generation potential and then form calcium carbonate suitable for use in concrete production. Hydrothermal mineralization (HTM) provides for rapid elimination of organic waste while producing emission-free and thermally stable cementitious additives for acting as carbon sinks. Hydrothermal mineralization (HTM) provides a fast handling approach for organic waste, a green power source, and a final product that can be combined with traditional and alternative cement production to reduce cement production carbon footprint.

The invention provides a pavement base material based on sludge and construction waste as well as a preparation method and application of the pavement base material. The pavement base material comprises a basic component and an additive component, the basic component comprises 45-55% of regenerated coarse aggregate, 20-35% of regenerated fine aggregate, 15-25% of sludge, 4-6% of cement and 1-4% of water; the regenerated coarse aggregate and the regenerated fine aggregate are both derived from construction waste; the external doping component comprises quick lime, sodium hydroxide and zinc ricinoleate, the mass percentage of the quick lime to the sludge is 4-8%, the mass percentage of the sodium hydroxide to the sludge is 0.1-0.2%, and the mass percentage of the zinc ricinoleate to the sludge is 0.2-0.5%. According to the invention, high-valued utilization of urban solid wastes such as the sludge and the construction wastes can be promoted, and the pavement base material with higher performance is obtained based on the sludge and the construction wastes.

This invention belongs to the field of waste plastic recycling and carbon nanomaterial preparation technology, specifically relating to a method for the high-value co-production of nitrogen-containing waste plastics. The method uses volatiles released by the controlled thermal decomposition of nitrogen-containing waste plastics as carbon and nitrogen sources. Chemical vapor deposition is performed on the surface of a nickel-molybdenum (Ni-Mo) nano-alloy catalyst synthesized by a one-step precipitation method to grow nitrogen-doped carbon nanotubes in situ. Simultaneously, light aromatics and hydrogen-rich fuel gas are co-produced through graded treatment of the gas phase products. This method directionally fixes the endogenous nitrogen from the nitrogen-containing waste plastics into the carbon nanotube lattice, converting the remainder into N2, effectively suppressing the release of NH3, HCN, and NO. x This invention reduces the generation of harmful nitrogen-containing byproducts, significantly increases the degree of graphitization, and inhibits the formation of amorphous carbon. The method of this invention can be adapted to the complex mixed waste plastic system containing nitrogen that is widely present in actual urban solid waste, and realizes the efficient, clean and high-value utilization of all its components, with broad prospects for industrial application.

The application provides a kind of data-driven urban solid waste incineration process multi-objective optimization control method, first, the MSWI process whole process model facing pollutant emission is established, including furnace temperature, boiler steam flow and flue gas oxygen content controlled object model and CO, CO2 and NOx pollutant emission index model, then, using single neuron adaptive PID establishes the multi-input multi-output loop controller facing key controlled variable, realizes the stable control to combustion process, finally, combined with the knowledge of field experts, the adaptive solution of key controlled variable optimization set value based on multi-objective particle swarm optimization algorithm is realized.The data-driven urban solid waste incineration process multi-objective optimization control method provided by the application can realize the multi-objective optimization control of urban solid waste incineration process, guide the existing running factory, reduce the pollutant emission concentration and improve the combustion efficiency.

A refinement process to reclaim aggregates derived from municipal solid waste incineration (MSWI) bottom ash is tailored for use in the asphalt and cement industries. Initial size reduction achieves market-specific gradation to liberate fused particles, followed by magnetic separation for the recovery of ferrous and non-ferrous metals. The aggregate material undergoes density separation to remove organic contaminants and heavy metal-bearing particles across size-specific fractions. Finally, a targeted wash cycle using neutral pH water reduces the chloride concentrations of the final aggregate product. This multi-stage process produces a reclaimed aggregate with controlled absorption, loss on ignition, and contaminant levels, enabling its safe and effective use in encapsulated construction applications.

The present invention relates to a method for converting CO2 to CO, comprising the steps of: a) exposing a process gas comprising CO2 to a plasma source, whereby a plasma of said process gas comprising CO and O species is generated; b) contacting the plasma of said process gas comprising CO and O species with solid carbon, whereby a gas mixture comprising CO and CO2 is obtained; c) and quenching the gas mixture, whereby a product gas comprising CO and CO2 is obtained; wherein the solid carbon comprises pyrolytic carbon obtained by pyrolysis of i) plastic waste, preferably end-of-life tires (ELT) waste, mixed plastic waste (MPW), automotive-shredder-residue (ASR), plastic solid waste (PSW), present in municipal solid waste (MSW), electronic waste (E-waste) or mixtures thereof; ii) at least one kind of hydrocarbons; or iii) mixtures of i) and ii); and a process for preparing solid carbon, for converting CO2 to CO in a plasma process comprising the steps: A) pyrolyzing components i), ii) or iii) mentioned above, whereby pyrolytic carbon in form of primary particles is obtained; B) optionally further processing the pyrolytic carbon in form of primary particles obtained in step A); C) optionally mixing the pyrolytic carbon obtained in step A) or optionally obtained in step B) with at least one binder; and a reducing agent for a method for converting CO2 to CO by a plasma process comprising solid carbon, preferably in form of particles, being pyrolytic carbon obtained by pyrolysis of components i), ii) or iii) mentioned above.