2013 results about "Energy conservation" patented technology

The invention provides a reusable rocket landing stage starting height prediction method, a guidance system and a processor, and aims to dynamically and accurately determine the ignition time of an engine by constructing a real-time online starting height prediction model based on an energy conservation principle and combining multiple safety thresholds (including an allowable starting height upper limit and a standby starting height lower limit) so as to predict the starting height of the rocket in a landing stage. And the safety and fuel optimality in the whole flight envelope are ensured, so that the reliability, accuracy and economical efficiency of the reusable rocket landing are remarkably improved. The problems that in the prior art, engine starting height prediction precision and robustness are insufficient, online adaptation to uncertainty of a complex flight environment cannot be achieved, and safety margin consideration is insufficient are solved, and potential safety risks are thoroughly eliminated.

The invention provides a multi-parameter cold source intelligent control system and method based on big data, and the system comprises a data collection and control module which is used for collecting related parameters of a cold source system; the comprehensive energy consumption standardization module is used for converting the energy consumption parameters into unified standardized energy consumption indexes; the comfort degree algorithm construction module is used for generating a dynamic comfort degree index; the association rule mining module is used for mining a multi-dimensional association rule from historical data; the intelligent decision module is used for generating an optimal control strategy based on the index, the index and the association rule; according to the embodiment of the invention, based on a multi-parameter fusion cold source intelligent control technology of deep reinforcement learning and an improved FP-Growth algorithm, through deep mining and intelligent decision making of multi-source data, the optimal control strategy is converted into equipment regulation and control parameters, and the equipment regulation and control parameters are obtained. And high efficiency and energy conservation of the cold source system and accurate regulation and control of indoor environment comfort are realized.

The invention provides an intelligent electric meter calibration method and device, computer equipment and a storage medium, and the method comprises the steps: constructing a single meter-transformer area double-layer data system through a special transformer collection terminal, and collecting transformer area total intelligent electric meter data, user meter temperature and humidity, an electric energy observation value, transformer area line impedance and load unbalance degree data; constructing an energy conservation optimization function according to the user meter electric energy observation value and the total meter electric energy by combining the deviation with the observation value; determining line loss data according to total meter current and user temperature and humidity, determining power supply stability through total meter voltage, and determining optimization function constraint conditions according to corresponding data; and solving an optimal user table software compensation coefficient and a transformer area line loss correction coefficient by a generalized genetic algorithm, updating a humidity-error correlation coefficient and a line loss reference value by a feedback performance attenuation model to determine an adjusted single table calibration error range, and performing single table calibration by combining the user table temperature and humidity and an electric energy observation value. By adopting the scheme, the accuracy, the reliability and the environmental adaptability of the calibration of the intelligent electric meter are improved.

The invention relates to the technical field of refrigeration house energy-saving control and digital twinning, in particular to a refrigeration house fan energy-saving operation method and system, and the method achieves the whole-field temperature deduction of a sensor-free area by constructing a CFD reference model and simulating and predicting the three-dimensional transient airflow and temperature distribution in a refrigeration house. Model parameters are calibrated through measured data, and the order of the model is reduced by adopting intrinsic orthogonal decomposition and Galerkin projection, so that the calculation amount is remarkably reduced, and online optimization is supported. And in combination with a data assimilation algorithm, the prediction result of the reduced-order model is continuously corrected, and the adaptability to environment change and system aging is improved. The optimization control stage takes minimization of the total energy consumption of a fan as a target, solves an optimal fan control sequence under the hard constraint that the whole-field temperature does not exceed the cargo safety upper limit and does not exceed the cargo safety lower limit, and adopts a rolling time domain mode for execution to realize collaborative optimization of safety and energy conservation.

The invention belongs to the technical field of electronic equipment thermal management, and discloses an electronic equipment thermal field rapid prediction method for multi-physical field strong coupling. According to the method, a layered heat source intensity distribution model is constructed, a grid mapping relation topological graph technology and a boundary node energy conservation compensation mechanism are developed, a multi-time scale coupling transfer function is designed, and a dynamic adjustment strategy based on phase deviation analysis is introduced. According to the method, the non-uniform heat source distribution and thermal diffusion dynamic characteristics under the high-frequency condition are accurately captured, the energy consistency of multi-physical field coupling is ensured, the thermal field prediction precision is improved, particularly, the method has outstanding advantages in the aspect of phase and amplitude prediction of transient thermal response, and meanwhile calculation resource consumption is greatly reduced.

The invention discloses a temperature and humidity cooperative control method for an air source heat pump drying room, and relates to the technical field of energy conservation, environmental protection and intelligent manufacturing. The method comprises the following steps: acquiring gas heat state parameters and material and environment characteristic parameters in an air source heat pump drying room, and constructing a multi-source state vector; calculating a dynamic response coefficient group and a material evaporation influence coefficient based on continuous sampling data, and establishing a cross response model; a control compensation signal is generated and corrected according to the disturbance estimator, and the comprehensive control quantity is input into an execution module of the air source heat pump system; a dynamic response coefficient group and a lag correction parameter are updated through a periodic feedback data set, and dynamic coordination between temperature and humidity variables is achieved; the response stability of temperature and humidity control can be maintained under the condition that the material moisture content, the stacking density and the external environment condition change, system oscillation and energy consumption deviation are reduced, and the energy efficiency level of the air source heat pump drying process and the product drying uniformity are improved.

The invention discloses a public building cold load short-time prediction method fusing physical information, and the method comprises the steps: collecting and preprocessing the historical cooling capacity, indoor environment, outdoor weather and equipment operation state data of a public building at a fixed time interval, and obtaining multi-dimensional input features; respectively establishing a workday sub-model and a holiday sub-model according to workday and holiday scene division; the workday sub-model and the holiday sub-model jointly form a cold load prediction model, the workday sub-model adopts a long short-term memory (LSTM) network, and the holiday sub-model adopts a light gradient elevator (Light GBM); a physical constraint loss function based on building energy balance and heat conduction residual error is introduced in the training process, and the physical constraint loss is fused into a total loss function according to a weighting coefficient so as to constrain that the output of each sub-model accords with the law of energy conservation and thermal inertia; monitoring the prediction error MAPE in real time and performing online calibration; and outputting a short-time cold load prediction result.

The invention discloses a low-carbon transformation method, system and device for a building air conditioning system. The objective of the invention is to solve the problems of static model, single target, one-sided evaluation and non-standardized process in the existing reconstruction technology. According to the method, building multi-dimensional data are collected; constructing a building energy consumption prediction physical simulation model coupled with a user behavior prediction model based on machine learning to dynamically reflect a real operation condition; a multi-dimensional objective function is defined, and a Pareto optimal transformation scheme set is generated; constructing an evaluation model based on an analytic hierarchy process and a fuzzy comprehensive evaluation method, and calculating a comprehensive evaluation value of each scheme; and selecting an optimal scheme according to the comprehensive evaluation value, and generating a detailed implementation report. The method can scientifically and efficiently determine the global optimal transformation strategy considering energy conservation, carbon reduction, comfort and economy, and significantly improves the scientificity and comprehensive benefits of building transformation decision.

The invention discloses an artificial intelligence home management system, which relates to the technical field of smart home and comprises a data acquisition module, a behavior analysis module, an environment sensing module, a cooperative control module and an energy consumption optimization module. According to the artificial intelligence home management system provided by the invention, through multi-source data fusion and cross-equipment collaborative decision, the intelligent management level of a home scene is remarkably improved, user behavior data can be deeply analyzed, a dynamic behavior model can be constructed, and a user habit mode can be accurately identified and predicted, so that the initiative and adaptability of equipment control are realized, and the user experience is improved. The system comprehensively senses environmental parameters, constructs an environmental state map, provides accurate environmental background information for a cooperative control strategy, ensures the accuracy of an equipment control strategy, combines equipment operation data with a user behavior scene, generates an energy consumption optimization scheme, ensures the comfort of a user, realizes high efficiency and energy conservation, and improves the user experience. And user privacy leakage is effectively prevented, and potential faults are early warned.

The invention discloses a property energy consumption abnormity monitoring method and system based on big data analysis, and relates to the technical field of energy consumption abnormity management. According to the property energy consumption abnormity monitoring method based on big data analysis, in a specified energy consumption monitoring time period, an energy consumption power group of a specified property service area is firstly obtained, and the energy consumption power group is compared with an energy consumption prediction interval to screen energy consumption abnormity; according to the comparison result, energy consumption abnormal data in the abnormal energy consumption time period are repeatedly checked, transient normal fluctuation caused by normal working condition switching of equipment or sudden change of the external environment is eliminated, and repeated checking comprises peak value abnormal detection and recheck verification; and finally, after repeated inspection is completed, association verification is carried out in combination with the abnormal energy consumption feature set. According to the method, a scientific basis is provided for property energy consumption management, accurate positioning of energy consumption abnormal points is facilitated, the problem of abnormal identification misjudgment caused by transient change in energy consumption monitoring in the prior art is effectively solved, and energy conservation, consumption reduction and cost optimization are realized.

The invention relates to the technical field of water conservancy irrigation control, and particularly discloses an energy-saving and environment-friendly water conservancy irrigation system informatization control method which comprises the following steps: S1, acquiring key environment parameters influencing irrigation operation in real time through a wind power detector deployed near a sprinkling irrigation opening, synchronously acquiring a reference working state and a target area of the sprinkling irrigation port; s2, abstracting natural wind into a computable wind vector by establishing a spatial reference coordinate system, and constructing a water drop kinematics model based on a physical law; with the aim of achieving accurate falling of water drops to a target area, model reverse solution is carried out, and the spray irrigation opening angle and the water pressure compensation amount needed for counteracting the wind power influence are accurately calculated; and S3, according to the solved compensation amount, the initial working parameters of the sprinkling irrigation opening are adjusted in real time, so that water drop drifting and evaporation caused by wind power are effectively inhibited, the water resource utilization rate is remarkably increased, and the purposes of energy conservation and environmental protection are achieved.

The invention discloses an LED (Light Emitting Diode) energy-saving street lamp system self-adaptive to an ambient light effect and an illumination adjusting method thereof, and belongs to the technical field of novel illumination control and green energy conservation. The system comprises a light environment sensing module, a traffic flow monitoring module, an LED driving power supply and an electroluminescent illumination module composed of a plurality of light emitting diodes. The main control module is configured to execute active lighting effect decoupling logic, namely, when the electroluminescent lighting module keeps steady-state lighting, the driving power supply is controlled to inject a micro-disturbance modulation signal which cannot be perceived by human vision into output current, and illuminance response data of the light environment perception module are synchronously collected; the road surface reflectivity coupling coefficient is obtained in real time by calculating the change ratio of the response data to the modulation signal, then the reflected light component excited by the street lamp itself is accurately removed from the total illumination value, and the pure environment background illumination is decoupled. The problems of misoperation and energy waste caused by self-luminous interference of a traditional light-operated street lamp are solved.

The invention discloses a control method for steam condensate waste heat recovery and waste water heating, a control device for steam condensate waste heat recovery and waste water heating, control equipment and a computer readable storage medium. The thermal load and the logarithmic average temperature difference are calculated based on the energy conservation principle, and the needed heat exchange area is calculated through a logarithmic average temperature difference method. A flow combination scheme of the plate heat exchanger is determined according to the heat exchange area and the flow parameters, a steam condensate side adopts a single flow, and a waste water side adopts asymmetric configuration of double flows or multiple flows so as to adapt to the flow difference of the two sides. In addition, a real-time monitoring mechanism is further established, when the total heat transfer coefficient is decreased by more than 10%, a cleaning program is automatically triggered, continuous and stable operation of the system is guaranteed, and efficient utilization of waste heat resources is achieved.

The invention discloses a mechanism for detecting the content of cyanide in solid waste, and belongs to the technical field of cyanide detection.The mechanism comprises a supporting bottom plate and a cylinder installed on the upper surface of the supporting bottom plate, a shaft rod of a stirring assembly is arranged at the inner bottom end of the cylinder in a bearing penetrating mode, and a servo motor is further installed on the supporting bottom plate through a motor support; the lower end of a shaft rod on the stirring assembly is connected with the shaft end of a servo motor through a first belt transmission structure, a feeding hopper is arranged on the barrel, a reciprocating telescopic mechanism is further arranged on the barrel, and a discharging door is further arranged on the barrel. When the cyanide gas detection device is used, gas can be extruded to a detection part of the detection assembly, so that cyanide gas can be in full contact with the detection assembly, the accuracy of a detection result is improved, in addition, in the process of detecting the cyanide content, the cyanide gas can be conveyed to the treatment tank to be treated, and the detection efficiency is improved. Therefore, the energy consumption of the detection mechanism is reduced, and energy conservation and emission reduction are facilitated.

The invention relates to a wind power plant active wake flow control method and device based on machine-field cooperation. The method is characterized in that a field control layer and a machine control layer are cooperatively operated; calculating the real-time wind speed of each fan in the wind power plant based on a Gaussian rotation-energy conservation wake flow superposition model describing the asymmetric characteristics of the wake flow and the multi-wake flow interactive superposition of the whole wind power plant; in the field control layer control, the optimal yaw angle under different wind condition combinations is obtained by taking the maximization of the total output power of the wind power plant as a target; in the control of the machine control layer, yaw angle tracking errors and the fatigue load of a yaw bearing are considered, model prediction control is applied within a continuous time range, and the yaw angle of each fan is dynamically adjusted according to the optimal yaw angle provided by the field control layer. Compared with the prior art, the method has the advantages that the generating capacity is remarkably improved and the fatigue load is reduced in a randomly fluctuating wind field environment, and the method has remarkable applicability in a large offshore wind plant.

The invention relates to the technical field of electric energy metering of a low-voltage power distribution system, and provides an EM algorithm-based district metering device misalignment identification method and system. The method comprises the following steps: establishing a theoretical misalignment value model of each outgoing line in different metering misalignment states, and determining a mapping relation between the different misalignment states and actual electric quantity data; the method comprises the following steps: constructing theoretical deviation values of each outgoing line metering device in different misalignment states on the basis of a transformer area incoming and outgoing line electric energy data and energy conservation relationship, estimating an initial attribution probability of a line state in combination with an index normalization mapping method, and obtaining a posterior attribution probability of each outgoing line line through Gaussian mixture distribution modeling under dynamic prior guidance; and based on the posterior affiliation probability of each outgoing line, constructing an objective function of joint observation value fitting quality, time continuity and misalignment amplitude balance, solving the objective function, and quantifying the electric quantity misalignment proportion of each outgoing line at each moment so as to judge classification and identification of misalignment behaviors.

The invention discloses a vector evaluation gradient multi-objective optimization algorithm for data center cooling system decision making. The overall thought comprises the steps that multi-source sensor data related to a cooling system is obtained according to data center machine room operation logic; performing corresponding preprocessing on data acquired by the sensor to obtain an overall sample; designing a vector evaluation gradient multi-objective optimization algorithm oriented to a data center cooling system decision; the optimization algorithm comprises the definition of a multi-objective optimization problem, uniformly distributed initial populations, population division based on vector evaluation and gradient updating. The optimal decision of the air supply amount and the air supply temperature of the cooling equipment in the cooling system is mainly obtained through an optimization algorithm, and optimal decision parameters are sent to the cooling equipment so as to achieve optimal control over the cooling equipment of the data center. The algorithm provided by the invention ensures that the decision strategy of the cooling equipment can be reasonably and quickly given, so that the appropriate temperature of the machine room and the energy conservation of the cooling equipment are simultaneously realized to meet the requirement of efficient operation of the data center. The energy consumption of the data center can be reduced, and the method is of great significance in promoting green and sustainable development of the data center.

The invention relates to the technical field of industrial lighting control, in particular to a dynamic optimization regulation and control method and system for an industrial intelligent lighting lamp based on multi-mode environment perception and computer equipment. An environment feature matrix and a lamp portrait matrix are constructed by deploying a sensor network integrating illumination intensity, thermal distribution and production process light demand labels and combining lamps embedded with unique two-dimensional code labels and digital portraits of the lamps. A 0-1 continuous value priority matrix is generated based on cooperation of a multi-layer perceptron and FLC, and a control threshold is dynamically adjusted in combination with QoS parameters of an edge gateway. Under the abnormal working condition, a two-dimensional code maintenance work order is triggered, an adjacent lamp is activated to compensate illumination, meanwhile, a safety redundancy coefficient is fed back through a compensation effect, a dynamic demand model is driven to be iteratively upgraded, and a self-evolution system of'perception-decision-regulation-optimization 'is formed. According to the scheme, the environmental adaptability, the energy efficiency utilization rate and the operation and maintenance intelligent level of the industrial lighting system are remarkably improved, and real-time response and low-carbon energy conservation are both considered.

The invention relates to the technical field of industrial automation control and dynamic simulation, and discloses a centralized control console and 3D model linkage virtual-real simulation system, which comprises a control signal sampling interface, a load response modulation unit, a dynamic model evolution unit and a virtual-real closed-loop feedback unit, the load response modulation unit performs energy consumption weight accumulation on all the virtual controlled objects in transient action to generate a global time scaling factor so as to correct an inertia time constant of the system in real time; the dynamic model evolution unit introduces a hard limiting boundary by using an amplitude limiting link and calculates a process variable; the virtual-real closed-loop feedback unit extracts a control deviation signal and drives a physical instrument to generate a nonlinear damping action, and by establishing a global load modulation model based on energy constraint, a discrete control system spontaneously emerges a nonlinear hysteresis characteristic conforming to physical energy conservation under the low calculation power condition without complex fluid network solution.

The invention discloses a green ecological energy-saving irrigation roof system and a using method thereof, and relates to the technical field of building roofs. A green ecological energy-saving irrigation roof system comprises a root blocking waterproof layer, a blind ditch structure layer, a non-woven fabric filter layer, a planting layer and a vegetation layer which are arranged on a roof from bottom to top, a rainwater collecting device is arranged in the blind ditch structure layer, an irrigation device is arranged on the planting layer, the rainwater collecting device is communicated with a water storage tank, and the water storage tank is communicated with the irrigation device through a water suction pump; a soil humidity sensor is arranged in the planting layer, the soil humidity sensor and the water suction pump are both connected with the controller, and the solar power supply device is used for supplying power to the water suction pump, the soil humidity sensor and the controller. The solar power supply device is arranged on the roof and used for supplying power to electric equipment in the whole roof system, power supply depending on mains supply is avoided, near-zero-energy-consumption operation is achieved, the building capacity and energy consumption self-balance requirements are met, and the purposes of environment friendliness and energy conservation are achieved.

The invention provides a water plant energy conservation and carbon reduction optimization method and system based on full-process carbon emission accounting, and belongs to the technical field of energy conservation and emission reduction. The method comprises the following steps: constructing a mountain city water plant whole-process carbon emission accounting model; obtaining energy consumption data and carbon emission factors of each link based on a mountain city water plant whole-process carbon emission accounting model; according to the energy consumption data and the carbon emission factor of each link, calculating the carbon emission of each link and the contribution degree of the carbon emission to the total carbon emission of the water plant; and on the basis of the carbon emission and contribution degree of each link, evaluating water plant whole-process energy-saving and carbon-reducing potential data, and determining an energy-saving and carbon-reducing optimization strategy according to the water plant whole-process energy-saving and carbon-reducing potential data. Therefore, by adopting a water plant energy-saving and carbon-reducing optimization scheme based on full-process carbon emission accounting, the carbon emission of each link of the water plant can be accurately accounting, and a targeted energy-saving and carbon-reducing optimization strategy is proposed in combination with special geographical conditions of a mountain city, so that high-efficiency energy conservation and low-carbon emission of water plant operation are realized.

The invention discloses a carbon emission flow analysis method for carbon emission evaluation in multiple application scenes, belongs to the technical field of power system carbon emission modeling and evaluation, constructs a connection relationship among nodes, branches and a power supply in a power system, and collects output data and type information of a power generation power supply and a power flow result in multiple operation conditions. The method comprises the following steps: calculating carbon emission of a power generation node, distributing the carbon emission to a load node according to a power flow path, identifying a carbon emission source of the load node by adopting a power tracking method, and calculating carbon emission intensity and a carbon potential index; a transmission structure of carbon emission in a power grid is defined, step-by-step distribution and flow direction tracking of the carbon emission are realized, and the defect that a carbon emission path is unobservable in the prior art is overcome; the identification precision of the carbon emission composition is improved, and a basis is provided for the priority division of energy-saving and emission-reducing measures; a carbon emission path mapping matrix and a transition probability matrix are constructed, dynamic identification of path changes is realized, and discovery of key paths and nodes is facilitated.

The invention discloses a security unmanned aerial vehicle system based on STM32, and relates to the technical field of security unmanned aerial vehicles. The strategic value of the unmanned aerial vehicle in the public safety field is verified, the technical iteration and application deepening of the unmanned aerial vehicle can continuously promote the modernization of social governance, and the novel 7 * 24-hour all-weather security unmanned aerial vehicle system is provided for solving the problems that an existing unmanned aerial vehicle is poor in endurance, single in application scene, low in working efficiency and the like. The problem of endurance is solved by adopting a new technology and a new thought, and the system has the advantages of low cost, low power consumption, high efficiency, energy conservation, environmental protection and the like; the YOLOv5 algorithm and the ArcFace algorithm can form complementation in function, complete more complex tasks together, and realize more efficient and accurate face recognition and pedestrian analysis; the Hungary tracking algorithm and the Kalman filter are combined and used, so that multi-target tracking can be effectively realized, and the tracking accuracy and reliability are improved.

The invention belongs to the technical field of electricity markets and low-carbon clearing, and discloses a novel subject participated electricity spot market day-ahead two-stage clearing method under electricity-carbon coupling. The method comprises the following steps: firstly, designing a two-stage clearing mechanism comprising preliminary clearing and multi-target robust optimization; secondly, a unit carbon quota accounting and transaction cost model and a multi-energy power generator model considering marginal cost and carbon emission are constructed based on regional power grid carbon emission factors; then the above models are fused, a non-parameterized uncertain set is adopted to describe new energy fluctuation, a day-ahead two-stage clearing model based on a min-max-min three-layer robust optimization framework is constructed, and the model fuses stepped quotation and dynamic carbon emission factors; finally, the model is converted into a mixed integer linear programming problem, and Camp is adopted; and solving by a CG algorithm. According to the method, the comprehensive clearing cost can be effectively reduced, energy conservation and carbon reduction are promoted, meanwhile, the robustness of the clearing plan to deal with extreme scenes is improved, and the system operation safety is guaranteed.

This invention discloses a cutting device for plastic woven bags, comprising a frame, a drive mechanism, a conveying mechanism, and a cutting mechanism. The conveying mechanism includes a base, a conveying roller, and a pressing roller. The conveying roller includes a front roller and a rear roller. The base is fixedly mounted on the frame. The pressing roller, the front roller, and the rear roller are arranged sequentially above the base along the conveying direction of the plastic woven bag and are rotatably connected to the frame. The pressing roller, the front roller, and the rear roller are each driven to rotate by the drive mechanism mounted in the frame. The cutting mechanism is mounted on the frame between the front roller and the rear roller, and is located directly above the base. Using the cutting device of this invention, a thermal cutting method is employed, which not only provides a good cutting effect but also facilitates subsequent processes, effectively reduces processing costs, and avoids the emission of pungent odors during the cutting stage, achieving energy conservation and environmental protection. It has high processing efficiency, a simple overall structure, and is easy to operate, making it suitable for widespread application.

The invention provides an intelligent collaborative regulation and control method and system for photo-thermal equipment, which give consideration to comfort, health and energy conservation. The method comprises the following steps: acquiring operation state parameters and first outdoor meteorological data of a field to be regulated and controlled; establishing a target function taking the minimum comprehensive energy consumption of the to-be-regulated place as a target, and constraining the target function by adopting a plurality of constraint conditions to obtain an optimization target; taking the operation state parameters of each device at the current moment as one individual to generate a population and taking the first outdoor meteorological data as initial input, and performing iterative optimization on each individual in the population under the limitation of an optimization target by utilizing a pre-trained prediction model and combining a particle swarm optimization algorithm, an optimal regulation and control strategy integrating the light environment, the thermal environment and the comprehensive energy consumption is obtained; and controlling the operation state of each corresponding device in the to-be-regulated place according to the optimal regulation strategy. According to the invention, comfortable, healthy and energy-saving intelligent regulation and control can be considered, and efficient construction and intelligent operation and maintenance of a low-carbon and healthy environment of a building are realized.

The invention discloses a loading lap joint device for cold chain transportation and sorting and a using method thereof, and relates to the technical field of cold chain transportation, the loading lap joint device comprises a drawing cold storage module, a cold storage module, a cold storage module, a cold storage module, a cold storage module, a cold storage module and a cold storage module, the drawing cold storage module is slidably mounted on a sliding groove in the bottom of a cold chain vehicle compartment, and a cold storage cavity is formed in the drawing cold storage module; the linkage defrosting mechanism comprises a frame type defrosting scraping plate arranged above the drawing cold storage module, a frost collecting groove is formed in the side edge of the cold storage cavity, and scraped frost water is guided into the frost collecting groove through the defrosting scraping plate; the lap joint interface module is arranged at the front end of the drawing cold storage module and comprises a conveying plate and a temperature adjusting air curtain which are movably hinged, and the temperature adjusting air curtain communicates with the cold storage cavity and the frost collecting groove through an air duct and releases cold air; the control unit is used for monitoring the temperature in the compartment and the platform position and adjusting the air speed of the air curtain to control the cold air circulation amount. The system not only can automatically remove the frost layer in the carriage and effectively reduce the environment temperature during loading, but also can be flexibly butted with a sorting line, so that energy conservation, high efficiency and temperature control guarantee of a cold chain loading link are realized.

The invention discloses a multi-mode-based self-adaptive air conditioner control method and device and a related medium, and the method comprises the steps that user parameters in a multi-source sensor are collected, and a multi-mode original data set is obtained; performing feature extraction on the multi-modal original data set to obtain a multi-modal fusion feature set; performing parametric fitting by using the multi-modal fusion feature set to construct an individual comfort mapping model; the individual comfort mapping model is controlled and solved, and an air conditioner operation parameter set is obtained; dynamic parameter correction processing is conducted on the air conditioner operation parameter set, and an optimized instruction set is obtained; and performing energy-saving adjustment on the individual comfort mapping model based on the optimization instruction set, and outputting energy-saving control parameters. According to the method, the individual comfort mapping model is controlled and solved, then dynamic parameter correction processing and corresponding energy-saving adjustment are carried out, and finally the energy-saving control parameters are output, so that the individual adaptability of the air conditioner operation parameters is improved, and meanwhile, the energy efficiency is optimized.

The invention provides a deep learning-based ultrasonic-assisted CMT welding process parameter optimization method, which comprises the following steps of: acquiring process parameters, ultrasonic parameters, multi-modal sensing data and result quality labels, and constructing a fusion data set containing numerical simulation and actual measurement samples; and introducing physical consistency constraints of energy conservation, mass conservation and temperature-solid phase fraction evolution into a learning target, and establishing a micro-proxy model comprising a spatial-temporal feature encoder, a layer channel adjacency graph network and a physical consistency output head, so as to realize end-to-end prediction from process / ultrasonic parameters and sensing data to multiple quality indexes. According to the uncertainty of the agent model and the distance between the candidate point and the Pareto frontier, the problems that in the prior art, multi-target / multi-constraint / cross-material migration and online disturbance self-adaption are difficult to solve, and the test cost is difficult to systematically reduce under the small sample condition are solved.

The invention discloses a VOCs emission dynamic prediction and energy-saving control system for catalytic combustion equipment in a casting workshop and a medium, the system comprises a high-frequency VOCs concentration monitoring unit which adopts TDLAS and FTIR spectrum analyzers and obtains high-precision concentration data through a data fusion algorithm, and a secondary differential signal of the TDLAS analyzer is independently extracted as a key feature; the data preprocessing and feature engineering module is used for processing multi-source data; the dynamic emission prediction module is internally provided with an attention mechanism time sequence convolutional network ATCN model, and realizes the ultra-early prediction of the emission concentration by fusing the secondary differential signal and historical data; the multi-objective optimization control module adopts a model predictive control MPC framework, the lowest comprehensive operation cost is taken as an objective, a dynamic virtual carbon penalty coefficient beta can be dynamically adjusted according to a workshop production plan, an advanced control instruction is generated through rolling optimization, and the equipment power and the fan frequency are adjusted; according to the method, ultra-early prediction, prospective control, energy conservation and consumption reduction of VOCs treatment are realized.