1003 results about "Chemical process" patented technology

The invention discloses a big data-driven hydrogen fluoride purification risk entropy assessment and multi-parameter monitoring system, which relates to the technical field of chemical process monitoring, comprises a multi-mode heterogeneous sensor network, and realizes high-precision detection and three-dimensional monitoring by using a nanowire FET (Field Effect Transistor) and the like. The space-time tensor decomposition module extracts features and identifies a causal relationship; the risk entropy manifold learning module evaluates the risk; the self-adaptive twin network monitors the abnormity and simulates and disposes the abnormity; and a knowledge graph-reinforcement learning system decision making subsystem and a plurality of subsystems such as an optical monitoring subsystem and a multi-scale modeling subsystem are also provided, so that whole-process risk management and control are realized. The hydrogen fluoride purification monitoring level is greatly improved, the detection sensitivity and the anomaly detection accuracy are remarkably improved, risk early warning is more timely, decision response is accelerated, the production efficiency is improved, energy consumption is reduced, the system has self-repairing and self-power-supply capabilities, data are safe and traceable, reliable operation of the system is guaranteed, and economic losses and potential safety hazards are reduced.

The invention relates to the technical field of process parameter design, and discloses a silver electrolysis process parameter design method and system based on multi-objective optimization. The method comprises the following steps: performing differential time sequence parameter decomposition on operation data of the silver electrolysis process to obtain a sensitive parameter set and a reference parameter set; performing reweighted periodic feature extraction on the sensitive parameter set and the reference parameter set, and establishing a dynamic mathematical model of the silver electrolysis process parameters; based on the dynamic mathematical model of the silver electrolysis process parameters, physical and chemical process numerical simulation is conducted through COMSOLMultiphysics software, and a response curved surface model is obtained; and according to the response curved surface model, a process parameter combination evaluation value sequence is generated, silver electrolysis process parameter multi-objective optimization is carried out based on the process parameter combination evaluation value sequence, and a silver electrolysis process parameter optimization scheme is output. According to the application, multi-physical-field collaborative simulation of electrode reaction, ion transmission, heat conduction and the like is realized, and performance index responses under different process parameters are accurately predicted.

Devices and methods to mitigate the erroneous signal imparted by physical and / or chemical process incident upon analyte-selective electrochemical sensors that are non-analyte-related in origin are disclosed herein. A sensing system featuring at least one of an analyte-selective sensor and at least one of an analyte-invariant sensor.

The invention discloses a dynamic intelligent control method and system for improving the efficiency of a rectifying tower, particularly relates to the technical field of chemical process control, and is used for solving the technical defect that an operation variable is mismatched with a physical state due to the fact that an existing distributed control system cannot recognize a hidden degradation state of equipment. The method comprises the following steps: acquiring temperature gradient distribution of each tower plate of a rectifying tower, thermal load of a reboiler and tower top condensation load parameters in real time, calculating a mass transfer efficiency offset by combining the temperature gradient distribution to generate a scaling trend index, and synchronously calculating a local entropy yield based on the thermal load and the condensation load to generate a thermodynamic irreversibility index. When the double indexes exceed a preset threshold value, it is judged that a recessive degradation state is entered, then a backflow ratio correction coefficient is reversely derived through a dynamic correlation model, and the correction coefficient is input into a distributed control system to dynamically adjust backflow ratio operation parameters; the product purity is maintained, the tower plate scaling process is obviously delayed, and long-term efficient operation of the rectifying tower is guaranteed.

The invention discloses a chemical process fault diagnosis method and system, and relates to the technical field of chemical process fault diagnos.The scheme aims at the diagnosis bottleneck of catalyst inactivation type progressive faults, fine parameter offset is captured in real time through a dynamic reference model, weak signals are accumulated and amplified in combination with an attenuation weighting mechanism, and the fault diagnosis accuracy is improved. The problem that a traditional method is not sensitive to slow drifting, and consequently report omission is caused is solved, and a fault recognition window is remarkably advanced. The dynamic threshold value is updated in real time based on mobile statistics, and raw material fluctuation and sensor noise can be self-adapted; during working condition switching, the model is automatically reset and the threshold value is relaxed, so that false alarm triggered by parameter mutation is avoided, and the stability of production scheduling is guaranteed; the design that fault half-life period weight and moving window length are associated with an inactivation period is introduced, so that the model autonomously adapts to different catalyst characteristics.

The invention discloses a deep resource fluidized mining disturbance effect evaluation model under a multi-field coupling effect, and the method specifically comprises the following steps: constructing a multi-field coupling parameter system: collecting geologic body basic parameters, covering rock mass mechanical parameters, thermal physical parameters, fluid parameters and chemical parameters in deep three-high, high ground stress, high ground temperature and high karst water pressure environments, and establishing a multi-field coupling parameter system; the method comprises the following steps: establishing a dynamic parameter database, realizing real-time updating of parameters along with a mining process, establishing a heat-flow-force-chemical full-coupling mathematical model, introducing the influence of a rock plastic damage correction term quantification temperature on heat conduction efficiency, associating a dynamic mapping relation between mineral reaction and rock physical property parameters, and establishing a dynamic parameter database. Simplification errors of a traditional model on multi-field effects are thoroughly eliminated, chained interaction of temperature, fluid, stress and chemical processes in a deep three-high environment is accurately described, a model prediction result better fits an actual mining working condition, and prediction deviation is greatly reduced.

The invention discloses a chemical process fault diagnosis and detection method and system. Belongs to the field of mechanical equipment fault diagnosis, and comprises the following detection steps: de-noising collected data by using a de-noising diffusion probability model (DDPM), and reducing noise interference in signals, thereby providing a clearer data basis for subsequent fault diagnosis; then, a fault diagnosis model (AResNet-Linformer) is built, the AResNet model is used for carrying out feature extraction on the denoised signals, and then feature information is sent to a Linformer neural network model for fault diagnosis; in order to improve the accuracy of the model, an improved star-sparrow optimization algorithm is used to carry out parameter optimization on the established fault diagnosis model. According to the invention, faults in the chemical process can be effectively identified, fault types can be rapidly determined, and a powerful data basis is provided for prevention and maintenance work.

The invention provides a deep-sea mining plume diffusion in-situ monitoring system and a monitoring method thereof, the deep-sea mining plume diffusion in-situ monitoring system comprises a monitoring center node device and a portable monitoring node device, and mining plume diffusion in-situ monitoring can be carried out through a monitoring network. According to the method, in-situ monitoring of the plume of the sediment can be achieved, the method has important significance on mining environment influence evaluation, an in-situ means for effectively positioning three-dimensional space distribution of the plume is filled up, and the requirement for monitoring the deposition thickness of plume particles is met. The plume influence environment element change relation is constructed, and the blank of plume environment influence total element monitoring is filled. The establishment of the relationship between plume diffusion and environmental element change is beneficial to the quantitative evaluation of the mining environment influence. The system can monitor and analyze the physical and chemical process, biological diversity influence and the like of the surrounding environment of mining activities, observation data can provide effective real parameters for plume numerical simulation, data support can be provided for environmental parameter prediction and benthic organism class group influence prediction, and three-dimensional space distribution of plumes can be obtained.

The invention discloses a biomass-based reinforcing agent for paper and application of the biomass-based reinforcing agent. The reinforcing agent comprises a biomass-based material, the biomass-based material comprises a micron-sized structure and a nano-sized structure distributed on the micron-sized structure. The reinforcing agent prepared by the invention has abundant nanostructures, is beneficial to physical crosslinking such as entanglement and bridging of fibers in paper pulp, and improves the wet strength of paper; the preparation of the reinforcing agent is a simple physical process, and a complex synthesis chemical process for synthesizing a polymer in a traditional organic reinforcing agent is avoided; the reinforcing agent is prepared by a dissolution regeneration method, so that the energy consumption is low, the solvent can be recycled and reused, no chemicals are consumed, and the reinforcing agent is environment-friendly; the reinforcing agent prepared by the invention can achieve a satisfactory wet strength effect at a lower content.

The invention relates to the technical field of data processing, and discloses a chemical process control method and system based on 3D virtual simulation. The method comprises the steps that control element data are grouped and labeled according to dimensions, and a model data packet is formed through distributed storage; performing separation and parallel processing on the data packets, and obtaining a process parameter set through fusion; classifying and analyzing the parameter set to generate a control instruction; performing tracking verification adjustment on the instruction to generate a visual data stream; decomposing and analyzing the data stream to obtain equipment operation parameters; and analyzing, matching and optimizing the operation parameters to generate a control scheme. According to the invention, the internal structure and the operation state of the chemical equipment can be visually displayed, multi-angle observation and real-time control are supported, and safe and efficient chemical process control teaching and training are realized.

The embodiment of the invention provides a hydrochloric acid PH control device in a germanium oxide production process and a control method thereof, and belongs to the field of chemical process automatic control. The device comprises an acid liquor storage tank used for storing raw liquor hydrochloric acid and connected to an acid mixing tank through a raw acid feeding control valve; the acid mixing tank is used for mixing an acid solution with a diluent and is connected to the pH regulation reaction tank through a mixed acid feeding control valve; the alkali liquor storage tank is connected to the pH regulation reaction tank through an alkali liquor adding control valve; the pH regulation reaction tank is used for receiving the mixed acid liquor and the alkali liquor and regulating the pH value of a reaction system, and is provided with a pH sensor for detecting the pH value in real time; and the control unit is used for dynamically adjusting the opening degree of each valve by adopting an improved fuzzy self-adaptive PID control algorithm according to a detection result of the pH sensor so as to control the pH value to be within a target range. According to the scheme, the problems of overshoot and lag caused by traditional fixed parameter PID adjustment are solved, and therefore the stability of the pH value of the solution and the consistency of the technology in the germanium oxide production process are guaranteed.

The invention belongs to the technical field of chemical process intelligent control, and discloses an iron phosphate synthesis parameter self-adaptive control system based on an intelligent algorithm. The system is composed of a target quality sensing module, a reaction data acquisition and preprocessing module, a sensitive section identification module, a process boundary modeling module, a multi-strategy control model library module, a strategy evaluation and structure evolution module and a control execution and feedback module. According to the method, a multi-module cooperation mechanism including target scoring modeling, dynamic sensitive segment identification and reaction boundary modeling is constructed, so that whole-process online identification and segmented precise control of the crystal form, the particle size and the crystallinity of a product in the iron phosphate synthesis process are realized; compared with a traditional control system depending on experience setting and univariate feedback, the system has the advantages of being higher in state sensing depth, more accurate in crystal form conversion process recognition, finer in reaction stage regulation and control and the like, and the problems of crystal form deviation, particle size drift and inter-batch quality fluctuation are effectively solved.

A simulation system and method for hydrogen production by water electrolysis. The simulation system for hydrogen production by water electrolysis includes: a first simulation unit used for simulating a hydrogen production power system to obtain hydrogen production electrical parameters; a controller unit used for outputting a control instruction to control hydrogen production process parameters in a hydrogen production chemical system; a second simulation unit used for simulating the hydrogen production chemical system according to the hydrogen production electrical parameters and the control instruction so as to obtain a hydrogen production result; and a data interaction unit, the first simulation unit, the controller unit, and the second simulation unit being capable of performing data interaction by means of the data interaction unit. Joint simulation of complete chemical and electrical processes for hydrogen production by water electrolysis can be realized.

The invention relates to the technical field of computer application, and particularly discloses a chemical industry park safety risk assessment method based on an agent model. The method comprises the following steps: constructing a multi-agent collaborative perception framework, and fusing multi-source heterogeneous data of equipment, environment, materials and personnel to form a park panoramic view under a unified space-time reference; establishing an agent behavior model library embedded with the chemical process mechanism and the safety interlocking logic; an intelligent agent decision strategy is optimized through deep reinforcement learning, and multi-target training is carried out by taking a safety index as a reward function; executing dynamic risk deduction and accident chain simulation in a digital twin environment, and quantifying risk probability and consequences in combination with Monte Carlo sampling; and finally, a visual thermodynamic diagram and an interpretable risk assessment report are generated, weak links are identified, and intervention suggestions are provided. According to the technical scheme, dynamic, accurate and prospective evaluation of the safety risk of the chemical industry park can be realized, and the early warning timeliness and the evaluation reliability are remarkably improved.

The invention discloses a micro-fluidic chip, a sensing electrode and a sensor of wearable equipment, belongs to the technical field of electrochemical method testing, and solves the technical problem that an existing wearable sensor cannot improve the sensitivity and accuracy of sweat component detection. The micro-fluidic chip comprises a substrate layer, a channel layer and a chip cover layer which are attached in sequence, the substrate layer comprises a sweat inlet and a cavity, the channel layer comprises a sweat absorbing opening, a micro-channel, a detection area, a capillary pump, a stop valve and a ventilation opening which are communicated in sequence, the sweat inlet is communicated with the sweat absorbing opening, and the cavity is communicated with the detection area. The sensing electrode is of a four-layer structure, and a working electrode located on a working electrode layer is manufactured through a chemical process. In a sensor of the wearable equipment, a sensing electrode is embedded in a cavity of a micro-fluidic chip and is used for being in contact with sweat flowing into the cavity, so that the content of glucose, sodium ions and cortisol in the sweat is detected. The method is suitable for the technical field of wearable sweat detection and can be applied to research and development of wearable detection equipment.

The embodiment of the invention discloses an artificial intelligence simulation method and equipment for an atmospheric aerosol chemical process. The method comprises the following steps: acquiring three-dimensional initial concentrations and environmental factors of various aerosols and related gases from a non-static atmospheric numerical mode; wherein the environmental factors comprise temperature, pressure, air density and water vapor mixing ratio, and the plurality of aerosols comprise inorganic aerosols; according to the three-dimensional initial concentration and the environmental factors, adopting a pre-trained target model to predict and obtain predicted concentrations of the inorganic aerosol and the related gas after a specified step length; and the rest part iterates the environmental factors and other processes according to the predicted concentrations of the inorganic aerosol and the related gas, so that alternative calculation of an aerosol chemical process in a numerical mode is realized, and accurate simulation of the predicted concentrations of the inorganic aerosol and the related gas is realized. And therefore, the global high-fidelity simulation precision is realized, and the calculation efficiency is remarkably improved.

A system for online-coupled atmospheric chemical transport modeling and data assimilation is built using online coupling and secondary parallelization. In the prototype code of a nested air quality forecasting model system, a parallel data assimilation framework routine is introduced. The system includes observation modules, model modules, and assimilation modules. The observation module is responsible for flexible access and preprocessing of various component-type observation data. The model module handles the model integration of initial fields, involving calculations of physical and chemical processes. The assimilation module performs analysis assimilation of model state variables. This system meets the requirements for coordinated assimilation of multiple chemical component variables, simultaneous introduction and flexible combination of various types of observation data, and effective handling of non-linear and non-Gaussian distribution issues in chemical assimilation.

The invention relates to a chemical production anomaly detection method based on a space-time diagram variational encoder. The method comprises the following steps: selecting public chemical normal working condition data D; an anomaly monitoring model ST-GVAE is constructed, a loss function L (.) is constructed, D serves as input, an Adam optimizer is adopted to train ST-GVAE, model parameters are reversely updated through gradient descent, and trained ST-GVAE'is obtained; a to-be-detected target variable a is selected, normal working condition historical data corresponding to a are input into ST-GVAE ', and an anomaly detection score corresponding to a is obtained and serves as an anomaly detection threshold value of the target variable a; inputting the current chemical working condition data of a into ST-GVAE'to obtain an anomaly detection score corresponding to the current state of a, and if the score is greater than a threshold value, triggering an alarm; and then calculating a reconstruction deviation score B of each node in the PID, taking the node corresponding to the B greater than a deviation threshold as an abnormal node, and outputting the abnormal node. By using the method provided by the invention, the variable abnormal condition of the existing chemical process can be accurately detected and positioned.

The invention discloses a self-adaptive conductivity measurement method and system. The method comprises the following steps: 1) acquiring environment temperature and illumination intensity data in a set period in real time; 2) measuring the conductivity of the solution; 3) simulating physical and chemical processes in the solution by adopting a partial differential equation; and 4) calculating a conductivity compensation coefficient in combination with the differential equation model obtained in the step 3), and adjusting a conductivity measurement value in real time according to the conductivity compensation coefficient. According to the method, temperature and illumination change compensation is achieved through the partial differential equation model, measurement errors caused by environment change can be effectively eliminated, and therefore the accuracy and reliability of conductivity measurement in experiment and industrial application are improved.

The invention discloses a chemical process multi-parameter intelligent monitoring method based on deep learning, and the method comprises the following steps: collecting and preprocessing the data of a chemical production process, and obtaining a standardized input sequence; according to the chemical process flow diagram and the equipment topological relation, a standardized process structure matrix is obtained; inputting the standardized input sequence and the standardized process structure matrix into a constraint decoupling echo state network model, and outputting a hidden state sequence; performing multi-scale gating fusion on the hidden state sequence, and outputting a parameter prediction result; calculating a residual error based on a parameter prediction result and an actual observation value, and outputting an anomaly detection result and channel-level attribution information; triggering a self-adaptive correction process to form a monitoring model after self-adaptive correction; and outputting a parameter prediction result, an anomaly detection result and channel-level attribution information based on the monitoring model after adaptive correction. According to the invention, the constraint decoupling echo state network is adopted, and multi-parameter intelligent monitoring of the chemical process is realized.

The invention relates to the technical field of dynamic monitoring, in particular to a chemical production safety risk dynamic monitoring system based on the Internet of Things, and the system comprises a data collection module which receives pressure monitoring data, temperature fluctuation data and pipeline flow velocity data measured by a chemical plant sensor in real time, records the time of each data point, and transmits the data to a server; and sorting and organizing the data according to a time sequence. According to the method, by receiving and sorting the chemical plant sensor data and implementing comprehensive analysis of the multi-scale time window, the capture and analysis precision of key parameter fluctuation is remarkably improved, the scientificity of rapid identification and risk prediction of variable fluctuation in the chemical process is promoted, potential risks can be found in advance, and the risk prediction efficiency is improved. Therefore, production strategies are adjusted in real time, production safety is ensured, pre-judgment of future risks is optimized by analyzing long-term trends and periodic changes, the accuracy of risk assessment and the safety of operation are improved, the probability of accidents is reduced, and the safety of personnel and equipment is protected.

The invention discloses a fuel gas system management method and system based on data analysis, and belongs to the technical field of fuel gas system management.The fuel gas system management method comprises the steps that a wax deposition kinetic model and a deep neural network are combined, and a hybrid prediction model architecture is designed; the wax deposition kinetic model is used for describing physical and chemical processes of wax deposition and providing basic prediction capability; the deep neural network is used for capturing a non-linear relationship and a complex mode in the data and improving the accuracy and generalization ability of prediction; based on an improved particle swarm optimization algorithm (PSO-ADE), a self-adaptive pigging decision engine is designed; initializing the algorithm to generate an initial particle swarm; operating an algorithm, and evaluating and updating the particles according to a target function; through iterative optimization, an optimal pigging strategy is found; and feedback data is collected, and the algorithm is further adjusted and optimized, so that the accuracy and effectiveness of decision making are improved. The pipeline cleaning strategy of the oil pipeline can be optimized.

The invention provides an off-grid wind and light hydrogen production ammonia synthesis system operation control method and device, and relates to the technical field of renewable energy hydrogen production ammonia synthesis, and the method comprises the steps: building a system model of an off-grid wind and light hydrogen production ammonia system, the wind and light hydrogen production ammonia system satisfying a target function and a target constraint condition; wind-photovoltaic predicted output is obtained; calculating the fitness of each particle; respectively calculating hydrogen production power and ammonia synthesis power based on the hydrogen production flow and the ammonia yield; calculating the starting number of the electrolytic cells and calculating the abandoned electricity quantity; calculating energy storage output and energy storage capacity; calculating the fitness of each particle, comparing the fitness with a locally optimal solution and a globally optimal solution, and updating the locally optimal solution and the globally optimal solution according to a comparison result; and outputting the optimal solution set after the maximum number of iterations is reached. The real-time power balance of the wind-solar hydrogen production ammonia synthesis system can be met, the project profit maximization is realized, the utilization and consumption of renewable energy sources are improved, the electricity abandoning rate of new energy sources is reduced, and the green low-carbon transformation of the chemical process is facilitated.

The invention discloses a preheating treatment carbon dioxide adsorption system and an operation method thereof, and belongs to the technical field of energy storage and chemical process equipment. The problems of high heat consumption, low heat conductivity and slow heating of the adsorbent in the prior art are solved. The technical key points are as follows: the temperature of the system is slowly increased at the initial stage of heating, part of carbon dioxide is desorbed, the carbon dioxide is heated by high-temperature heat exchange equipment and then flows back to the tower body of the adsorption tower, and the heating process can be completed in idle time except energy storage-energy release due to the fact that the compressed gas energy storage system implements discontinuous energy storage-energy release. Good adsorption and desorption effects can be realized in a relatively low temperature range, so that the energy demand in the heating and cooling process is reduced, the overall energy consumption of the system is reduced, the heat exchange pressure of the heating system is relieved, and the demand on the heat exchange power of heating equipment is relieved; the gas pressure in the adsorption tower body is slightly increased, so that continuous and stable release and supply of carbon dioxide of an adsorption system are guaranteed, and the method has a good industrial application prospect.

The invention relates to a quality prediction method based on spatio-temporal dynamic graph convolution and mutual attention selection, and the method comprises the steps: collecting historical observation values of a target variable and a process variable in a chemical process, combining the historical observation values into a one-dimensional vector, carrying out the dimension rising processing of the time dimension of the one-dimensional vector, and carrying out the feature embedding and grouping processing, thereby obtaining a plurality of grouping features; respectively carrying out convolution operation on each grouping feature to obtain a corresponding time feature representation; obtaining a first time-space representation corresponding to the time feature representation based on the adaptive topological structure and a gating mechanism; aggregating each time feature representation through the attention weight to obtain an aggregated feature; carrying out average pooling and convolution operation on the aggregated features in the time dimension and the node feature dimension to obtain global features, time local features and node local features, and then obtaining second space-time representation; and performing residual connection on the second spatio-temporal representation and each first spatio-temporal representation, and outputting a predicted value of the target variable through a full connection layer.

The invention relates to the technical field of automation control, in particular to a high-quality phosphate chemical process automation system which comprises a resource demand prediction module, a concentration prediction adjustment module, a temperature real-time control module, a production data analysis module and a deviation correction module. According to the method, through material consumption prediction and concentration adjustment, in combination with temperature and flow control, accurate adjustment can be carried out in time, optimization of production efficiency and quality is guaranteed, errors caused by manual operation or system deviation in the production process are effectively avoided by analyzing deviation data and correcting deviation exceeding an allowable range, and the production quality is improved. The self-adaptive capacity of production is enhanced, product consistency and production stability are optimized, production parameters of all links can be adjusted in real time, it is ensured that the whole process is efficient and stable, resource use is optimized, energy consumption and material waste are reduced, and the production process better meets the requirements of green and sustainable development.

The invention relates to a venturi separator, which is characterized in that the venturi separator comprises a venturi tube and a liquid phase collecting tube surrounding at least one part of structure of the venturi tube, and the venturi tube comprises the following sections which are communicated in sequence: an optional equal-diameter section, a reducing section, a throat part and an expanding section, the venturi separator is provided with a gas phase inlet, a liquid phase inlet, a liquid phase outlet and a gas phase outlet, an opening is formed in the side wall or the tail end of the expanding section of the venturi tube, and the opening leads to the liquid phase collecting tube, so that a liquid phase leaves the venturi tube and enters the liquid phase collecting tube under the action of centrifugal force. The invention also relates to the use of such a Venturi separator in a chemical process.

The invention belongs to the technical field of electric poles, and provides a preparation method of a corrosion-resistant thin-wall concrete-filled steel tube electric pole and the electric pole. Corrosion-resistant elements such as copper, phosphorus, chromium and nickel are stored in an outer steel tube, an inner steel tube, a flange plate and a flange plate cover plate which are made of weather-resistant steel; and meanwhile, after sand blasting, the surface energy of the steel is increased, then water mist spraying and drying circulation treatment are conducted, the steel is promoted to form a stable rust layer on the surface of a base body, corrosive media in air are prevented from permeating into the base body, and chemical process anti-corrosion modes such as hot-dip galvanizing or coating brushing are replaced. The process difficulty is simplified, the generation of a rust layer is stabilized, the problem that the electric pole needs to be coated with an anti-corrosion coating regularly for anti-corrosion maintenance in the later period is solved, and the process difficulty and the anti-corrosion cost are reduced; meanwhile, the flange plate cover plate is arranged at the position of the middle hole of the flange plate, sealing of the inner wall of the inner steel pipe is achieved, and the anti-corrosion treatment and maintenance procedures of the inner wall of the inner steel pipe are avoided in the mode that air isolation is conducted on the inner wall of the inner steel pipe.

The invention discloses a distributed measurement method for fuel conversion rate and component content in a hydrocarbon fuel thermochemical process. The method comprises the following steps: pumping a target substance into a reaction tube, and heating to a target temperature required by thermal cracking; relevant parameters are monitored in real time; cooling in real time and collecting gas-phase and liquid-phase substances after thermal cracking of the target substance; analyzing the component distribution of the target substance after thermal cracking on line to obtain the component distribution of the target substance after thermal cracking at different temperatures; changing the pressure, and continuing the above steps to obtain component distribution of the target substance after thermal cracking under different pressures; based on component distribution of a target substance subjected to thermal cracking at different temperatures and different pressures, functions of the conversion rate and the component content of the target substance changing along with the temperature are obtained respectively, and distribution conditions of the conversion rate and the component content of the target substance along a reaction tube are obtained respectively. The invention further discloses a device adopting the method. According to the method and the device, the distributed fuel conversion rate and the content of each component are accurately measured.

The invention provides a coating material suitable for a quartz product and a preparation method of the coating material. The water-based coating material comprises a normal-temperature film-forming medium, a high-temperature film-forming medium, a ceramic functional additive and deionized water, the normal-temperature film-forming medium comprises a thickening binder, a dispersing agent, a defoaming agent and a flatting agent; the high-temperature film forming medium comprises low-melting-point glass powder and a high-temperature binder; the ceramic functional additive comprises silicon nitride, silicon carbide, aluminum oxide and zirconium oxide powder. The low-melting-point glass powder and the ceramic functional additive can improve the adhesive force, compactness and mechanical performance of the coating and adjust the expansion coefficient of the coating, and the room-temperature film forming medium can adjust the viscosity, fineness and the like of the coating material. And the binding force and compactness between the coating material and the quartz product can be ensured. The coating can effectively protect the quartz product, prevent erosion and stress damage of other physical or chemical processes to quartz, and prolong the service life of the quartz product.