3720 results about "Oxygen content" patented technology

The invention discloses an old people tumble alarm system and method based on multiple sensors, and relates to the technical field of intelligent monitoring, and the system collects the body data of old people through an intelligent bracelet and a sensor group, transmits the body data to a cloud platform through a wireless network, carries out the processing, and generates a state data group. The acceleration modulus length, the angular velocity modulus length, the gait cycle and the posture angle of the old people are calculated, so that the motion state and the falling risk are accurately judged, a falling risk assessment coefficient is calculated based on the data, old people falling assessment is performed according to the falling risk assessment coefficient and a preset falling risk threshold value, and an alarm is triggered and a guardian is notified when the risk exceeds the standard. The heart rate variability index and the blood oxygen content are analyzed, a comprehensive health index is obtained through calculation, possible body injury after falling is evaluated, and injury alarm information is generated. The system can accurately monitor the health state of the old people in real time, timely send out early warning and alarm information, and provide comprehensive fall prevention and health monitoring guarantee.

The invention relates to the technical field of mine ventilation control, in particular to a mine fan ventilation control method and system based on digital twinning. The method comprises the following steps: carrying out data preprocessing on acquired mine monitoring data; performing feature extraction on the preprocessed mine monitoring data; utilizing a random forest algorithm to predict the relationship between the data characteristics and the fan air volume; a digital twinborn model is used for resolving the relation between the data characteristics and the fan air volume, and a fan ventilation control strategy is obtained; and generating a PLC control instruction based on the fan ventilation control strategy. And through multi-source data fusion and deep analysis, the real-time ventilation requirement of the mine can be accurately grasped. Based on random forest algorithm prediction and digital twinborn model calculation, dynamic and accurate adjustment of the air volume of the draught fan is achieved, it is ensured that the concentration of harmful gas in all underground areas is maintained within a safety threshold value, the oxygen content is sufficient, an ideal environment is created for personnel operation and equipment operation, and the safety and reliability of a ventilation system are remarkably improved.

The invention relates to the technical field of dark green tea processing, in particular to a fermentation monitoring method in the dark green tea processing process. The method comprises the following steps: acquiring temperature sequences and oxygen contents of different monitoring positions of a fermentation box in a dark tea processing process; determining a corresponding fluctuation index according to the length corresponding to each sub-sequence section of each monitoring position and the fitting error of each data in the sub-sequence section; the temperature anomaly degree is obtained by combining the difference between the fluctuation indexes of the corresponding sub-sequence segments of each monitoring position and other monitoring positions and the temperature difference; integrating the temperature anomaly degree, the temperature change degree, the oxygen content change degree and the relative distance of the corresponding subsequence segments of each monitoring position and other monitoring positions to obtain contribution factors; and updating the temperature of the current moment based on the time interval between all the sub-sequence segments of all the monitoring positions and the current moment and the contribution factor. According to the invention, the accuracy and credibility of the temperature monitoring result in the dark tea processing process are improved.

According to the combustion optimization method and device based on machine learning and the electronic equipment, the real-time operation data of the to-be-optimized system is input into the trained multi-target prediction model for data prediction processing, and the multi-target prediction result is obtained; the trained multi-target prediction model is a model which is established based on a graph neural network and is used for predicting performance indexes of the to-be-optimized system; according to a multi-target preset result and the real-time operation data, through the trained combustion optimization model, oxygen amount and air door opening adjustment processing is carried out on the to-be-optimized system, and the to-be-optimized system after combustion optimization is obtained; the trained combustion optimization model is a model which is constructed based on a distributed reinforcement learning algorithm and is used for carrying out combustion optimization on the to-be-optimized system by dynamically adjusting the oxygen content and the air door opening degree of the to-be-optimized system. Compared with the prior art, the embodiment of the invention can respond to the requirement of state change in real time in the combustion optimization process, improve the optimization effect and reduce the operation complexity.

The invention relates to the technical field of tin-containing copper alloy manufacturing, in particular to a method, system and equipment for detecting the oxygen content of copper alloy melts.The method comprises the steps that resistivity data of the copper alloy melts.The temperature data of the copper alloy melts.The resistivity data of the copper alloy melts.The temperature data of the copper alloy melts.The resistivity data of the copper alloy meltsare acquired in real time; the resistivity data are corrected based on the temperature data, and standardized resistivity irrelevant to the temperature is obtained; a correlation model of the resistivity and the oxygen content is established according to the linear influence relation of oxygen impurities in the copper alloy melt on the resistivity, a real-time oxygen content value is output based on the standardized resistivity, and an oxygen content fluctuation trend is generated; and according to the real-time oxygen content value and the oxygen content fluctuation trend, the oxygen content tolerance threshold value of the copper alloy melt is dynamically adjusted based on the oxygen sensitivity requirements of different alloying stages. By means of the method, the problems that in a traditional oxygen content detection method, due to the fact that temperature distribution is uneven, alloy element interaction and solidification behaviors are not systematically modeled, the detection precision is low, and microstructure control fails are effectively solved.

The invention discloses a method for preparing a high-performance injection-molded titanium alloy product by adding an oxygen absorbent, which comprises the following steps of: 1, ball-milling titanium alloy spherical powder and YB6 powder to obtain mixed powder; 2, the mixed powder and a binder are subjected to banburying and granulation, and granular injection molding titanium alloy product feed is obtained; thirdly, the feed is injected into a mold, and an injection-molded titanium alloy product green body is obtained; 4, performing catalytic degreasing on the green body to obtain a degreased blank; and fifthly, the degreased blank is subjected to thermal degreasing and sintering, and the injection molding titanium alloy product is obtained. YB6 is adopted as an oxygen absorbent, the oxygen content in a matrix of the injection-molded titanium alloy product is reduced, meanwhile, TiB and Y2O3 reinforced phases are generated in situ, synchronous improvement of strength and plasticity is effectively achieved, the high-performance injection-molded titanium alloy product is obtained, and the obtained injection-molded titanium alloy product is low in oxygen content, high in density, excellent in mechanical property and good in mechanical property. And the development of the titanium and titanium alloy injection molding industry can be promoted.

The invention relates to the technical field of automobiles, and provides a vehicle intelligent oxygen cabin system, a control method of the vehicle intelligent oxygen cabin system and a vehicle. The vehicle intelligent oxygen cabin system comprises a dispersed oxygen outlet used for releasing oxygen into a vehicle cabin of a target vehicle; the snorting oxygen outlet is used for providing snorting oxygen; the oxygen concentration sensor is used for detecting the oxygen content in the cabin of the target vehicle in real time; the altitude positioning device is used for detecting the altitude of the target vehicle in real time; and the controller is in communication connection with the dispersion oxygen outlet, the snorting oxygen outlet, the oxygen concentration sensor and the altitude positioning device, and is used for controlling opening or closing of the dispersion oxygen outlet and the snorting oxygen outlet according to the oxygen content and the altitude. According to the vehicle intelligent oxygen cabin system provided by the embodiment of the invention, the driving experience of a driver and passengers is effectively improved, and the applicability and safety of the vehicle are guaranteed.

The invention discloses an intelligent control method for water treatment aeration. The intelligent control method comprises the following steps: S1, setting a preset condition; s2, measuring water quality data, wherein the data comprises chemical oxygen demand (COD), ammonia nitrogen amount, water temperature and water flow velocity; s3, an intelligent aeration algorithm is set, the intelligent aeration algorithm comprises an air inflow calculation model, the air supply amount of a fan and the opening degree of a valve are adjusted according to the result of the air inflow calculation model, and therefore the dissolved oxygen content, namely the DO value, is adjusted; s4, performing operation calculation according to the current water quality data through an intelligent aeration algorithm to obtain a suggested air volume of the intelligent aeration algorithm; intelligent aeration algorithm model training is carried out by collecting data of a fan, a regulating valve, dissolved oxygen, ammonia nitrogen and the like, dynamic response can be carried out on a training result biochemical pool aeration link according to the inlet water quality and water quantity of a sewage treatment plant and the water quality and water quantity of a water outlet of the sewage treatment plant, and stable process indexes are achieved through aeration according to needs.

The invention discloses a denitration system inlet nitric oxide disturbance and super-emission control method and system, and the method comprises the steps: adjusting the operation oxygen amount and the over fire air ratio in real time based on the measured values of the carbon monoxide concentration and the nitric oxide concentration of the denitration system inlet; based on denitration system operation data, combining actual sampling delay time to carry out sample data alignment and construct a training sample set; constructing a prediction model based on the training sample set, obtaining a nitrogen oxide concentration prediction value of the inlet of the denitration system through the prediction model, and updating the prediction model in real time; based on the difference between the average value of the outlet nitrogen oxide concentration of each partition and a set value and the difference between the concentration value of the nitrogen oxide at the outlet of the denitration system and the set value, and by combining the predicted value of the nitrogen oxide concentration at the inlet of the denitration system, treatment measures after the nitrogen oxide concentration super-emission are set in a segmented mode. The control performance of the denitration system can be improved, the ammonia spraying amount is reduced, the ammonia escape concentration is reduced, and the system automation input rate is increased.

The invention discloses a refined ammonia injection control system for a coal-fired power plant, and relates to the technical field of ammonia injection control systems for power plants. The real-time monitoring module is used for monitoring NOx concentration, oxygen content and temperature parameters in flue gas in real time and transmitting data to the central processing unit; and the prediction model construction module is used for constructing an NOx generation prediction model by utilizing a machine learning algorithm according to the historical data and the real-time monitoring data. Through the real-time monitoring module, the system can continuously track key parameters such as NOx concentration, oxygen content and temperature in flue gas; the control decision is ensured to be based on the latest environmental condition, so that the response speed and accuracy of the ammonia spraying system are improved; the NOx generation prediction model constructed by using a machine learning algorithm not only considers historical data, but also integrates real-time monitoring data, so that the model can accurately predict the NOx concentration change trend in a period of time in the future; and the system can predict and adapt to the future emission condition.

The invention relates to the technical field of tobacco curing, in particular to a nitrogen preparation and storage oxygen content automatic control system which comprises a purity and pressure joint control module, a humidity regulation and optimization module, an oxygen content dynamic regulation and control module, a moisture response regulation module and a multi-parameter coupling linkage module. According to the system, intelligent dynamic adjustment is achieved through multi-parameter real-time collection and linkage feedback, synchronous judgment and optimal adjustment path formation between the nitrogen outlet purity and the pressure of each compression section, and matching of the airflow temperature, the wet film area and the nitrogen humidity, it is guaranteed that humidification is uniform and controllable in combination with automatic comparison of the outlet humidity and the storage target standard, and the system is suitable for large-scale popularization and application. The nitrogen injection flow rate and the outlet humidity directly participate in the active response process of oxygen content change, self-adaptive balance of the storage oxygen environment is achieved, moisture monitoring penetrates through the surface layer and the interior, temperature setting and the wet film area are finely adjusted along with the moisture state, and the nitrogen humidity state is finely matched with the tobacco leaf requirement.

The invention relates to an intelligent breeding method for crayfish offspring seeds in a winter fallow field, and belongs to the technical field of aquaculture. In order to solve the problems of dissolved oxygen management lag, high ammonia nitrogen accumulation risk and overlarge energy consumption caused by low utilization rate of winter fallow fields and dependence of water quality regulation and control on artificial experience in the prior art, the method comprises the following steps: deploying a water quality dynamic monitoring system based on the Internet of Things to collect data of water temperature, dissolved oxygen, pH value, ammonia nitrogen and nitrite in real time; the power and the water level of the oxygenation equipment are dynamically adjusted after analysis of the edge calculation module; graded regulation and control are achieved by combining a three-level response mechanism, when the dissolved oxygen content is lower than 6 mg / L or the pH value is abnormal, the power of the nanometer oxygenation device is started to 50%, and when the dissolved oxygen content continuously deteriorates, the irrigation system is linked to inject the water body with the temperature being adjusted in advance. According to the method, through intelligent multi-parameter cooperative control and ecological bait design, the resource utilization rate of the winter fallow field is increased, the survival rate of the young crayfish is increased to 85% or above, and the method is suitable for large-scale and green efficient breeding of the young crayfish in a rice-shrimp rotation mode.

The invention relates to the technical field of gas purification, in particular to a novel start-up method for a PSA (Pressure Swing Adsorption) hydrogen extraction device, which comprises the following steps: on the basis of the working environment of the PSA hydrogen extraction device, checking before start-up is carried out, nitrogen replacement is carried out, the oxygen content of a hydrogen extraction system is controlled within a preset range, and the pressure of the hydrogen extraction system is reduced to normal pressure; the difference between the current environment data and the standard environment data is analyzed, the valve opening degree and the adsorption pressure are adjusted, the equipment operation parameters are optimized to meet the current environment conditions, and an environment parameter adjusting instruction is obtained. By collecting and analyzing the current environmental data, dynamically adjusting the adsorption pressure and the valve opening and connecting the gas quality monitor to collect and analyze the hydrogen purity in real time, the concentration change of impure substances can be found in time, the adsorption time is optimized according to the data, and it is ensured that the hydrogen purity continuously reaches the high standard; and through continuous monitoring and quality verification of the hydrogen purity of the product, the consistency and reliability of the hydrogen product are guaranteed.

The invention relates to the technical field of control, and discloses an oxygen supply dynamic regulation and control method, system and device for a plateau district and computer equipment, and the method comprises the steps: carrying out the first-stage oxygen supply for an indoor room through a first oxygen supply operation corresponding to a first oxygen supply flow under the condition that there is no person in the indoor room; after the indoor real-time oxygen content reaches the target oxygen volume fraction, if people move in the indoor room and the indoor room is in a ventilation state, second-stage oxygen supply is carried out on the indoor room through second oxygen supply operation corresponding to second oxygen supply flow, so that the indoor real-time oxygen content is kept stable at the target oxygen volume fraction; and the second oxygen supply flow is corrected by using the number of indoor people, the indoor activity type and the indoor real-time carbon dioxide content which are monitored in real time, and the difference value between the indoor real-time oxygen content and the target oxygen volume fraction is kept within the target threshold value range. Finally, the oxygen supply regulation and control method for dynamically controlling the indoor oxygen supply flow of the plateau area based on the environment parameter data monitored in real time is achieved.

The invention discloses an aquaculture intelligent oxygenation device based on a neural network, which adopts a low-energy-consumption and high-efficiency technology to remarkably improve the dissolved oxygen content of a water body and promote the healthy growth of aquatic animals such as shrimps, crabs and fish schools. The device is suitable for small, medium and large culture pond environments, and the frequency of an air blower is adjusted through an intelligent control system to adaptively adjust the water dissolved oxygen level. The system integrates the fuzzy neural network model with strong self-learning ability, and can predict the dissolved oxygen amount according to the real-time data collected by the water quality monitoring module, thereby realizing accurate environment control. In addition, due to the modular design of the device, installation and maintenance are more convenient, and the technical threshold of farmers is greatly lowered. The device is also integrated with a water quality monitoring and communication module, supports real-time environment monitoring and data remote transmission, and realizes remote monitoring and management functions. The highly integrated intelligent solution provides powerful technical support for modernized and intelligent aquaculture.

The invention discloses a dynamic monitoring method for a dolphin behavior for dolphin protection, and the method comprises the steps: arranging a dolphin hydrophone collection device, a dolphin water surface video shooting device and a water environment monitoring device in a dolphin protection water area; the method comprises the following steps of: acquiring audio data sent by a cowfish to acquire five environmental metadata including water temperature, air temperature, dissolved oxygen content, average water level measured value of a water area of a protection area and fishing amount of fish and shrimp in the water body, and marking data according to a cowfish behavior image shot by a cowfish water surface image shooting device during audio acquisition of the cowfish and according to a cowfish behavior attention category; and training and deploying the audio fusion identification model of the cowfish, so that the behaviors of the cowfish can be identified more accurately. According to the method and the system, the behavior condition of the cowfish in the protection area under the time window can be judged by acquiring the easily acquired cowfish audio data in combination with the environment, so that the cowfish community condition in the protection area can be dynamically monitored, and the cowfish can be better protected.

The invention relates to the technical field of biomass energy conversion, in particular to a gradient catalytic biomass tar cracking reactor and a control method thereof.The gradient catalytic biomass tar cracking reactor comprises a multilevel component characterization module, a functional group reaction activity evaluation module, a multi-scale reaction network coupling module, an oxygen content gradient regulation module, a self-adaptive product directional regulation module and the like; the system is used for finely representing tar components, improving complicated composition understanding and processing capability, calculating a functional group reaction activity index, constructing a three-level reaction network, optimizing reaction path selectivity, and generating an oxygen content gradient index and a catalyst distribution scheme, so that gradient reduction of oxygen content and oriented conversion of products in a reactor are realized; the multi-section fixed bed reactor is designed, different catalysts are filled in each reaction area, the reaction requirements are met, the system intelligently regulates and controls reaction operation parameters, the biomass tar cracking efficiency and the product directionality are remarkably improved, and innovation and breakthrough are brought to the technical field of biomass energy conversion.

The invention relates to the technical field of fire monitoring and alarming, in particular to an intelligent household fire automatic alarming and escape guidance system, which comprises a time-sensitive escape window evaluation module, a time-sensitive escape window evaluation module, an escape window evaluation module and an escape guidance module, wherein the time-sensitive escape window evaluation module is based on fire source temperature, smoke concentration, humidity and oxygen content collected by a fire detection sensor network in combination with a fire source position; the severity of a current fire and the influence of the current fire on an escape window are evaluated in real time, and preliminary escape time early warning is provided; the fire spreading trend prediction module is used for predicting a fire spreading path based on fire detection sensor network data and a machine learning algorithm and generating a dynamic risk map; and the self-adaptive escape path optimization module is used for generating a plurality of escape paths with different priorities, optimizing the paths in real time according to the fire change, and ensuring that the escape paths are always in a low-risk area. According to the invention, it is ensured that family members can obtain timely alarm and action guidance in an escape time window, and the escape success rate is improved.

A laser additive manufacturing system and method for a magnesium-based composite material. The system comprises a laser adjuster (1), a laser (2), a forming cover (3), an oxygen content adjuster (4), an inert gas cylinder (5), a powder feeder (6), a substrate (7) and a wire feeder (8), wherein the laser adjuster is used for controlling laser processing parameters of the laser; the laser is connected to a laser processing head (10) by means of an optical fiber (9); the oxygen content adjuster is in communication with the forming cover, so as to control the oxygen content of a processing environment in the forming cover; the inert gas cylinder and the powder feeder both pass through the forming cover to be connected to the laser processing head; the substrate is located inside the forming cover; the wire feeder is connected to a wire feeding head (12) by means of a wire feeding tube (11); the wire feeding head passes through the forming cover to perform laser additive manufacturing for a magnesium-based composite material, together with the laser processing head; and a real-time cooling sleeve (13) is also mounted on the wire feeding tube. Also provided are a method for preparing a magnesium-based composite material using the laser additive manufacturing system for the magnesium-based composite material, and a prepared magnesium-based composite material. By means of the manufacturing system and method, the additive processing of wires and powder is realized, and a magnesium-based composite material with a good mechanical property is prepared.

The invention provides a method for solving signal drift of an oxygen sensor in a high-temperature and high-pressure environment, which comprises the following steps: collecting acid-base gas concentration data and zirconium oxide material surface state information in the high-temperature and high-pressure environment, and classifying erosion sensitivity degrees by adopting a support vector machine algorithm to obtain an initial response characteristic deviation value; a neural network model is adopted to process the determined potential signal drift trend and oxygen content detection historical data, a simulation response characteristic curve is generated, and a quantitative mapping relation of the pH value change to erosion sensitivity is obtained; refining the correlation between the determined long-term monitoring reliability index and the pH value change by adopting a neural network model, generating a dynamic response characteristic prediction sequence, and obtaining a signal drift suppression threshold set; and through fusion of the obtained signal drift suppression threshold set and the oxygen content detection real-time signal, if it is judged that erosion sensitivity is aggravated in a prediction sequence, a compensation model is activated to update and circulate, and optimized sensor stable output is obtained.

The invention relates to the technical field of new energy, and discloses an independent energy supply system suitable for a high-altitude area and a control method thereof, electric power is generated through photovoltaic power generation, part of the electric power is stored in a storage battery, and the residual electric power is used for electrolyzing water to prepare hydrogen and oxygen, and the hydrogen and the oxygen are respectively stored. The oxygen content in the air is increased by mixing the oxygen, the oxygen and the hydrogen jointly enter the fuel cell for chemical reaction, and stable electric power and hot water are output. In order to ensure the stability of the system, a low-temperature air source heat pump is configured to serve as standby heat supply equipment, and accurate adjustment and storage of electric power are achieved through cooperative work of a load tracking module and an efficient storage battery. According to the system, photovoltaic power generation, hydrogen energy storage and fuel cell technologies are combined, continuous and reliable power and heat combined supply can be achieved in high-altitude areas lack of power grid support, and an efficient and environment-friendly solution is provided for energy supply in remote areas.

The invention discloses a preparation method of high-rhenium and low-oxygen spherical tungsten-rhenium alloy powder, which comprises the following steps: proportioning tungsten powder and rhenium powder, adding into a ball mill for ball milling and mixing to obtain uniform composite powder slurry; the composite powder slurry is fed into a spray dryer to be subjected to spray granulation to form sphere-like alloy powder; and the spheroidized powder is subjected to plasma spheroidizing treatment to form the spherical tungsten-rhenium alloy powder. According to the preparation method disclosed by the invention, the tungsten-rhenium suspension slurry with uniformly dispersed components is prepared, and then granulation and spheroidization are carried out, so that the uniform state of the suspension is successfully solidified, oxygen can be reduced, impurities can be removed, and the spherical alloy powder with relatively large granularity and unlimited rhenium adding amount is prepared. The technical route flow is short, the process controllability is high, pilot scale production can be achieved, and the prepared tungsten-rhenium alloy spherical powder is high in density, sphericity degree and uniformity and low in oxygen content.

The invention discloses an intelligent fault diagnosis and early warning method for an electrical automatic composting process system, and relates to the technical field of intelligent monitoring. Sensor data in a composting process is collected, high-frequency noise is removed by adopting sliding window filtering, and a timestamp is synchronized to align multi-dimensional signals; based on a hidden Markov model, dividing composting stages of temperature rise / high temperature / decomposition period, and extracting time domain and frequency domain features for different working conditions; and an online K-means + + algorithm is adopted to initialize a clustering center. According to the method, multi-dimensional sensor data such as temperature, humidity and oxygen content in the composting process are collected in real time, the online K-means + + algorithm and the density peak value clustering technology are utilized to dynamically adapt to the time-varying characteristics of composting parameters, outliers caused by sensor drift or dust interference are effectively filtered, the sensitivity of a model to noise data is remarkably reduced, and the method has the advantages of being high in reliability and high in reliability. It is ensured that the composting system can still operate stably under complex working conditions, and the risk of fermentation interruption or material decay caused by parameter abnormity is reduced.

The invention belongs to the technical field of metal additive manufacturing, and relates to a preparation method of a large-size thin-wall structure based on magnetic field regulation and control of laser directional energy deposition. According to the method, the part forming area is filled with the protective gas, the oxygen content of the forming area is 100 ppm or below, and oxidation and inclusion pollution of alloy in the forming process are avoided. By starting the electromagnetic field generator, a stable uniform magnetic field is formed in a part forming area, the metallurgical behavior of a molten pool is regulated and controlled through the thermal damping effect and the thermal electromagnetic convection effect generated by the magnetic field in the molten pool, and optimization of the grain structure is achieved. A laser cladding head is started, powder metal materials are conveyed to the position of a molten pool through powder carrying gas, and the powder metal materials are molten through laser to form a stable molten pool; and a laser cladding head is controlled to scan in a uniform magnetic field area according to a set track to carry out circulating deposition, and light stopping is carried out every time deposition of one layer is completed, so that heat of a deposition layer is released, and heat accumulation is reduced until part forming is completed.

The invention relates to the technical field of TMBP preparation, in particular to a TMBP reaction device and a TMBP synthesis method. The reaction device comprises a closed tank body, a heating mechanism is arranged in the tank body, the tank body is divided into a gas phase area and a liquid phase area from top to bottom, a hollow rotating shaft is arranged in the center of the tank body, the top of the hollow rotating shaft is connected with a motor, a gas inlet mechanism is arranged in the hollow rotating shaft, gas inlet holes communicated with the gas phase area are formed in the upper portion of the side wall, and a gas distribution mechanism is arranged below the side wall. The gas distribution mechanism comprises a plurality of hollow and horizontally-arranged spiral blades which are communicated with the hollow rotating shaft in a sealed mode, the outer side wall is provided with a gas outlet pipe perpendicular to the normal of the outer side wall, and the gas outlet pipe is provided with a one-way nozzle. The device is compact in overall structure, small in occupied area and good in stirring effect, oxygen in a gas phase region can be dispersed into a liquid phase region, the gas distribution mechanism has gas distribution and stirring effects at the same time, the oxygen content and dispersion uniformity in a liquid phase are greatly improved, the reaction efficiency is improved, and the reaction time is shortened.

The invention relates to a vehicle control method and device, a controller, a medium, a product and a vehicle, and the method comprises the steps: determining the oxygen generation parameters of an oxygen generation device of a target vehicle based on the vehicle data of the target vehicle and / or the in-vehicle personnel on the target vehicle; on the basis of the oxygen generation parameters, the oxygen generation device is controlled to adjust the oxygen content in the target vehicle, and the time for adjusting the vehicle environment in the vehicle can be shortened.

The invention relates to the technical field of smelting process parameter optimization, and discloses a data-driven multi-furnace continuous smelting intelligent regulation and control system and method, and the system comprises a data collection module, a machine learning module and an intelligent control module; the method comprises the following steps: acquiring operation component data of temperature, oxygen content and gas components in the oxygen-enriched side-blowing and top-blowing furnace; constructing a continuous smelting simulation model, inputting the real-time operation component data into the continuous smelting simulation model for analogue simulation, and adjusting process parameters according to the feedback of an analogue simulation result; according to the dynamic change rate in the learning production process, process parameters are adjusted in real time; a fuzzy rule base is defined to intelligently control multiple-input-multiple-output equipment, and a control strategy is dynamically adjusted through fuzzy reasoning. According to the invention, fine control in the smelting process is realized, the production efficiency is improved, the smelting time is shortened, the dependence on operators is reduced, and the labor intensity and the labor cost are reduced.

The invention provides an online detection and compensation method for local decarburization of a high-strength spring steel band, which comprises the following steps: arranging an oxygen content sensor in a continuous annealing furnace to monitor oxygen concentration in real time, and marking a potential decarburization risk section; scanning the risk section steel strip by adopting infrared thermal imaging, and generating a carbon distribution map to position a decarburization area; pulse laser heating is conducted on the decarburization area, and methane-argon mixed gas is introduced to achieve in-situ carburization; and finally, local thermal stress is eliminated through high-frequency induction heating. According to the method, decarburization risk dynamic early warning, defect accurate positioning, local efficient carbon supplementation and stress homogenization control are achieved, and the surface quality and fatigue performance of the steel strip are remarkably improved.

The invention discloses a modeling method and device for a soft measurement model of the flue gas oxygen content of a gas turbine, and the modeling method comprises the following steps: obtaining multi-source operation data of the gas turbine, including a gas turbine combustion chamber pressure pulsation original signal, an operation parameter and an environment parameter; carrying out time-frequency domain feature extraction on the pressure pulsation original signal to obtain a time domain statistical feature and a frequency domain spectrum feature, fusing the time domain statistical feature and the frequency domain spectrum feature with the operation parameters and the environment parameters, and then screening key input variables through variable importance analysis; constructing a cascade hybrid model based on the screened key input variables; and jointly optimizing model parameters of a time sequence feature learning layer, a static feature mapping layer and a dynamic fusion layer in the hybrid model through a gradient descent method until the model converges, and generating a soft measurement model capable of outputting an effective flue gas oxygen content predicted value.

The invention discloses an anaerobic microorganism fermentation device, and relates to the technical field of anaerobic microorganism fermentation, the anaerobic microorganism fermentation device comprises a fermentation assembly, the outer surface of the fermentation assembly is provided with a detection assembly; when the air purifier is used, aerobic gas is discharged through the gas outlet pipe and the diffusion pipe, the oxygen content is detected by the oxygen sensor, and when it is detected that the discharged aerobic gas is discharged, the gas enters the air purifier through the connecting pipe and the fixing pipe under the action of the flow guide plate to be subjected to air purification treatment. When oxygen-free gas is detected, the PLC can control the gas injection valve to be closed, a first electric one-way valve and a forward and reverse motor are started, the forward and reverse motor drives a rotating rod, a sealing plate and a sealing ring to rotate anticlockwise, a connecting pipe is blocked, and a flow guide plate guides the oxygen-free gas into a recycling pipe. The oxygen-free gas enters the fermentation tank again through the conveying pipe, the annular pipe, the gas inlet pipe and the gas injection pipe, waste of the oxygen-free gas is reduced, and the use efficiency is improved.