2550 results about "Oxygen content" patented technology

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.

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 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 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 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.

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 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 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 relates to the technical field of titanium alloy metallurgical powder, in particular to a preparation method of titanium alloy metallurgical powder. Comprising the following steps that firstly, titanium alloy raw materials are smelted into melt, and the melt is guided into an electromagnetic centrifugal device under the protection of inert gas; 2, primary crushing is conducted on the melt through an electromagnetic centrifugal device, the rotating speed is larger than or equal to 25000rpm, and pre-crushed particles with the particle size being 100-200 microns are obtained; 3, the pre-crushed particles are conveyed to an ultrasonic-assisted gas atomization chamber, argon and helium mixed gas is introduced, 20-40 kHz high-frequency ultrasonic waves are applied, and atomization refining is carried out; 4, the atomized particles are cooled to form titanium alloy metallurgical powder; according to the method, 1 vol% of modified yttrium oxide particles are introduced into atomized gas of the ultrasonic-assisted gas atomization chamber, the oxygen content of the titanium alloy powder can be reduced to 600-800 ppm from conventional 1200-1500 ppm, the reduction amplitude is about 40-50%, oxygen embrittlement can be effectively avoided, and the ductility and high-temperature strength of the alloy are improved.

The invention relates to a purification method of penta (dimethylamino) tantalum, and relates to the technical field of purification of amino metal compounds. In a standard glove box with the oxygen content lower than 2 ppm and the water content lower than 0.01 ppm, taking a proper amount of sublimated crude product penta (dimethylamino) tantalum, putting the sublimated crude product penta (dimethylamino) tantalum into a dry and clean sample bottle, adding a solvent after water and oxygen removal to dissolve the penta (dimethylamino) tantalum, and filtering; and then cooling and crystallizing, slowly reducing the temperature until crystals are separated out, and slowly crystallizing to generate faint yellow micro-transparent crystals. After crystallization is completed, filtering is conducted again in a low-temperature state, and crystals are dried in vacuum. And after the mother liquor is desolventized to evaporate out the solvent, the recovered crude product penta (dimethylamino) tantalum can be sublimated and recycled again.

The invention discloses a super-large-scale silicon single crystal growth method based on a high-temperature superconducting magnetic control technology, and relates to the technical field of silicon single crystal growth, and the method comprises the following steps: setting and calibrating an initial magnetic field intensity, and combining a gradient graphite felt heat conductivity coefficient function to optimize temperature field uniformity; a dynamic magnetic field regulation and control mechanism is introduced in the melt stage, melt convection is inhibited through flow velocity-magnetic field joint control, and oxygen concentration monitoring is synchronized; a multi-physics coupling simulation and multi-objective optimization algorithm is adopted in the crystal growth stage, the magnetic field intensity, the heating power and the crystal pulling parameters are adjusted in real time, and the oxygen content and the growth rate are balanced; and the tail stress is relieved through a gradient field reduction technology, and finally, the low-defect and high-uniformity silicon single crystal is obtained. Melt flow and temperature field uniformity are accurately regulated and controlled through a high-temperature superconducting magnetic control technology, dynamic monitoring and a multi-target optimization algorithm are combined, the growth quality of silicon single crystals is remarkably improved, the defect rate and energy consumption are reduced, and meanwhile efficient and stable production of large-size crystals is achieved.

The invention provides a method for detecting oxygen content in copper / copper alloy, and belongs to the technical field of metal component analysis. According to the method for detecting the oxygen content in the copper / copper alloy, the mixed solution of nitric acid, hydrofluoric acid and water is used for cleaning the sample, nitric acid can perform corrosion cleaning on the sample, and when oxide or nitride which is difficult to dissolve by nitric acid exists on the surface of the sample, the oxygen content in the sample is detected by utilizing the characteristic of small molecular radius of hydrogen fluoride. The cleaning agent can rapidly penetrate through a compact metal oxide layer, reacts with metal oxide, destroys and dissolves the metal oxide layer, effectively cleans impurities such as oxide and nitride on the surface of a sample, and is beneficial to improving the accuracy of oxygen content testing. The fluxing agent and the sample are heated and melted together, so that the melting point of copper or copper alloy can be reduced, covalent bonds are destroyed, oxygen release is facilitated, and the detection accuracy is further improved; and the fluxing agent is used, so that the stability of low oxygen content detection is improved, and the detection of lower oxygen content is realized.

The invention discloses a method for step-by-step impurity removal in crude copper fire refining, and belongs to the technical field of metallurgical technologies. The method comprises the following steps: (1) removing As and Sb in an oxidation stage: heating and melting crude copper, blowing oxygen, and adding an impurity remover to remove As and Sb impurities in the crude copper; (2) removing Pb and Ni in an oxidation stage: after the impurity removal agent is added in the step (1) for reaction, adding a composite impurity removal agent, continuously blowing oxygen, stopping blowing oxygen until the oxygen content in the melt is 0.6-0.8% by mass, and slagging off to remove Pb and Ni impurities; and (3) deoxidation in a reduction stage: after slagging-off in the step (2), adjusting the temperature of the melt to a reduction temperature, adding high-sulfur pulverized coal in twice, and removing oxygen in the melt to complete impurity removal. According to the method, the impurity removal agent and the impurity removal process are optimized, and the impurity removal effect of the crude copper is remarkably improved through the synergistic effect.

The invention provides an argon flow and micro-positive pressure linkage control method for an electroslag furnace. The method comprises the steps that the oxygen content and micro-positive pressure signals in the furnace are collected; the future furnace condition is predicted through the deep belief network model; optimizing initial parameters of the fuzzy PID controller in an off-line manner by using a particle swarm algorithm; on the basis of the real-time signal and the prediction result, adaptively adjusting controller parameters on line; and finally, an argon flow and dust removal valve opening control instruction is output in a linkage mode. According to the method, future furnace conditions are predicted through the deep belief network model, the control advancement is realized, and the problem of large lag of the system is solved; offline parameter optimization is carried out on the fuzzy PID controller through a particle swarm algorithm, and excellent initial performance adapting to different working conditions is provided for the fuzzy PID controller; the parameters of the controller are adaptively adjusted through online fuzzy reasoning, so that the system has robustness for coping with a dynamic process; finally, accurate and stable linkage control of the oxygen content in the furnace and the micro-positive pressure is achieved through linkage calculation of the argon flow and a dust removal valve opening instruction.

The invention relates to the technical field of environment monitoring, in particular to a multifunctional air quality monitoring and early warning system, which comprises a monitoring and adjusting module, a monitoring and early warning module, a monitoring and early warning module, an early warning module and an early warning module, and is characterized in that the monitoring and adjusting module monitors pollutants and temperature and humidity information in air through various sensors and automatically adjusts sensor detection ranges according to air quality conditions; the intelligent early warning module is used for establishing a prediction model, pre-judging the deterioration trend of the indoor air quality in advance through the prediction model, and triggering trend early warning when monitoring that the deterioration risk is high; and the equipment linkage module is used for establishing an equipment linkage rule base and automatically matching an optimal equipment operation strategy according to the air quality data. Various high-precision sensors are integrated, multi-dimensional data of particulate matter, harmful gas, oxygen content and temperature and humidity in air can be comprehensively monitored, the indoor air quality condition is accurately reflected, an air purifier and fresh air system equipment are automatically allocated according to a data analysis result, and intelligent environment adjustment is achieved.

The invention discloses a local area inert gas protection auxiliary vacuum environment laser welding device and method, belongs to the technical field of laser welding, and aims to solve the problem that the laser welding quality of an existing easily-oxidized material is insufficient. A local area inert gas protection auxiliary vacuum environment laser welding device comprises a monitoring and feedback control system, a gas precise control system and a vacuum cavity, a gas nozzle, a workbench and a laser welding head are all arranged in the vacuum cavity, the laser welding head is located above the workbench, the gas nozzle is arranged on one side of the laser welding head, and the gas nozzle is arranged on the other side of the laser welding head. The vacuum pumping system is connected with the vacuum cavity, the laser welding head is connected with the laser welding machine, the gas precise control system controls the flow and the mixing proportion of inert gas jetted by the gas nozzle, and the monitoring and feedback control system monitors the temperature, the vacuum degree, the oxygen content and the plasma state of a welding area. And data are fed back to carry out closed-loop regulation control on various welding parameters. And the welding quality is greatly improved.

The invention provides a method for improving the high-temperature crack resistance of a cupronickel alloy based on addition of an alterant, which comprises the following steps: S1, heating a cupronickel alloy raw material until the cupronickel alloy raw material is completely molten; s2, scum in the metal solution is fished out; s3, adding a copper-magnesium alloy; s4, adding pure titanium, and fully melting and reacting the pure titanium through stirring; s5, scum in the metal solution is fished out; s6, casting after the furnace front analysis is qualified; s7, obtaining a cupronickel alloy round ingot or flat ingot; the copper-magnesium alloy is added as a deoxidizing agent, so that the oxygen content of a metal solution can be reduced, oxygen is prevented from reacting with alloy elements to generate inclusions, the purity of the alloy is improved, and the crack resistance of the alloy is enhanced; the fine and uniform grain structure can effectively improve the high-temperature plasticity of the cupronickel alloy, reduce grain boundary defects, improve the high-temperature crack resistance of the cupronickel alloy and avoid cracking under high-temperature forging or hot rolling.

The invention provides a silicon-based composite material, a preparation method thereof and a negative plate. The silicon-based composite material comprises silicon-based composite material particles, the silicon-based composite material particles comprise a porous substrate and silicon particles loaded in pores of the porous substrate, the silicon particles comprise at least one silicon nanoparticle and an oxygen-enriched layer at least partially coating the silicon nanoparticle, the oxygen-enriched layer is made of SiOx, x is more than 0 and less than or equal to 2, and x is more than 0 and less than or equal to 2. And the oxygen content in the oxygen-rich layer is in gradient change along the direction from the center to the surface of the silicon nanoparticle. According to the silicon-based composite material provided by the invention, the plurality of silicon particles taking the silicon nanoparticles as the core and the oxygen-enriched layer as the shell are loaded on the porous substrate, and the oxygen content in the oxygen-enriched layer is in gradient change, so that the conductivity of the silicon-based composite material is improved; moreover, the volume expansion of silicon in the lithium intercalation process can be relieved by utilizing the oxygen-enriched layer with the gradient change of the oxygen content, the expansion rate of the electrode is reduced, and the cycle performance of the battery is further improved.

The utility model provides a cooking utensil which comprises a body, a heating assembly and a fan assembly, the body is provided with a heat dissipation cavity and a cooking cavity, the heat dissipation cavity is communicated with the cooking cavity, the heating assembly and the fan assembly are connected with the body, the heating assembly is used for heating food materials in the cooking cavity, and at least one part of the fan assembly is located in the heat dissipation cavity. The other part of the fan assembly is located in the cooking cavity, and the fan assembly can blow air in the heat dissipation cavity into the cooking cavity. External fresh air can flow into the cooking cavity through the heat dissipation cavity, so that the cooking cavity can continuously introduce external air in the working process. Therefore, cooking parameters such as humidity and oxygen content in the cooking cavity are adjusted by means of the external air so as to meet the cooking requirements of specific food, and the technical defects that in the prior art, the cooking parameters such as humidity and oxygen content cannot be adjusted, the food cooking requirements cannot be met, and the quality of finished food is poor are overcome.

There is provided an oxygenation assembly submersible within a body of water. The oxygenation assembly includes a mass transfer vessel configured to receive water and promote dissolving of oxygen therewithin at least in part using pressure from the body of water. The vessel is elongate and may have a fixed diameter. The oxygenation assembly includes a bubble generator downstream of the vessel and which functions as a throttling device. The bubble generator is configured to dissipate pressure within the vessel in a manner that promotes breaking up of remaining undissolved gaseous bubbles. The oxygenation assembly may include an aeration system coupled to and in this example in line with the vessel. The aeration system disperses water of elevated dissolved oxygen content throughout a larger volume of water having a lower bulk dissolved oxygen concentration.