91 results about "Product analysis" patented technology

The invention relates to the technical field of green product analysis, and discloses a green product full life cycle analysis system based on big data. The system comprises a data acquisition module, a preprocessing module, an environmental impact assessment module, a resource consumption optimization module, an association modeling and result generation module and a visual interaction module. The system collects data of all stages of a full life cycle and related element data of environment, resources, carbon emission and the like, after preprocessing of abnormal value elimination, entropy weight method weighting and the like, environment influence is dynamically evaluated through a fuzzy membership function, resource consumption is subjected to multi-objective optimization by utilizing a genetic algorithm, and the resource utilization rate is improved. A key stage is determined by means of grey relational degree, an analysis result is generated in combination with a multi-target decision model, and finally the analysis result is visually presented in the form of a three-dimensional map and a dynamic thermodynamic diagram. The system realizes efficient analysis and comprehensive evaluation of full-life-cycle data of green products, and provides scientific support for product environment performance optimization and decision making.

The invention provides a neutron dose evaluation method and system based on mobile phone neutron activation product analysis, and the method comprises the steps: constructing an equivalent medium model for replacing a real mobile phone, and carrying out the neutron energy spectrum solving through the mobile phone activation product. The neutron energy spectrum can be reconstructed on site in daily scenes without professional equipment, such as villages, streets and shopping malls, so that the uncertainty of individual dose is reduced to a level equivalent to that of a laboratory spectrometer, the dependence on a multi-ball spectrometer, a TOF spectrometer and professionals is thoroughly eliminated, rapid and accurate measurement of the neutron energy spectrum and large-scale population dose evaluation are realized, and the accuracy of the neutron energy spectrum is improved. And a basis is provided for delimiting the influence range of the nuclear event, judging the event level of the nuclear event and formulating a hierarchical medical rescue scheme.

The invention relates to the technical field of market analysis, in particular to a brand positioning optimization method based on big data, and the method comprises the steps: collecting multi-channel brand performance data, calculating a mean value, extracting a co-occurrence relation between emotion words and labels in comments, judging an emotion and image matching structure, and analyzing competing product label frequency difference and cognitive overlap. And identifying a user portrait and emotion offset, and merging expression gaps to generate an optimization suggestion scheme. According to the method, differentiated collection and unified coding are performed on multi-channel indexes, a brand expression structure capable of cross comparison is constructed, data definition is improved, comment words and brand labels form a co-occurrence matrix, an emotional expression structure under the value dimension is extracted, competitive product analysis locates a cognitive blank on the basis of label difference and coverage degree, and the competitive product analysis accuracy is improved. The emotion deviation value and the label acceptability are introduced as dynamic parameters by user division, and finally a fusion label missing and emotion space is output, expression reconstruction and crowd adaptation are completed, and dynamic linkage and positioning updating of a brand structure are realized.

The invention discloses an agricultural product quality safety full-chain tracing system based on multi-node cooperation, and relates to the technical field of agricultural product analysis. Comprising a history acquisition module, a map construction module, an analysis node module, an analysis uplink module, an analysis management and control module, a query display module and a comprehensive rectification module, wherein the history acquisition module is used for acquiring full-chain data of various fruits in recent 3-5 years and preprocessing the acquired data; the map construction module is used for carrying out feature extraction and correlation analysis on the preprocessed full-chain data of various fruits; according to the technical key points, technologies of knowledge graph, block chain link-by-link chaining, unique fruit coding, nodal quality evaluation and consumer feedback rectification are comprehensively used, so that full-process tracing is realized, data in each link is ensured to be real and traceable, production, logistics, supervision and consumer multi-node collaborative participation are promoted, and the system is suitable for large-scale popularization and application. The method provides support for follow-up exception cooperative processing and system iteration, and has a good use prospect.

The invention relates to the technical field of big data and is applied to the fields of finance and medical health. The invention discloses a visual data integration method and device, computer equipment and a storage medium. The method comprises the following steps: determining entities, attributes and relationships based on business requirements, and forming document metadata; on the basis of the document metadata, generating an interface prototype according to user demand research and competitive product analysis results; generating a graphic component for operating the interface prototype and realizing a dragging function to obtain a data model; and storing the data model in a selected storage medium, and recording version information for a terminal to backtrack and compare historical version information. By implementing the method provided by the invention, the development efficiency can be remarkably improved, and meanwhile, the consistency of data and the expansibility of the system are ensured, so that non-professional developers can also efficiently participate in the development and maintenance of the application program, the technical threshold is greatly reduced, and complex business requirements are met.

The present invention discloses a smart marketing management method and system based on AI artificial intelligence. The smart marketing management system includes a data collection and preprocessing module, a market dynamics prediction module, a competitive product analysis module, an advertising strategy generation module, and a strategy execution and feedback module. The smart marketing management system collects relevant data on marketing advertisements in the market, collects market dynamics data, monitors and updates the advertising strategies and market performance of competitive products in real time, and automatically adjusts advertising delivery strategies through AI artificial intelligence technology based on competitive product analysis results and real-time advertising effect data. Through the introduction of AI technology, market and competitive product data can be analyzed in real time, advertising strategies can be automatically adjusted, advertising content and delivery channels can be optimized, and advertising budgets and time frequencies can be dynamically adjusted. This system is not only highly intelligent and automated in advertising decision-making, but also achieves a reasonable allocation of marketing resources through multi-dimensional optimization strategies, significantly improving the overall effectiveness of advertising and the rate of return on investment.

The invention provides an equipment control method based on sludge anaerobic fermentation product analysis, and relates to the technical field of sludge treatment.The method comprises the steps that initial feature information of current sludge before fermentation is obtained, and the initial feature information comprises the moisture content, volatile solids and / or the carbon-nitrogen ratio; acquiring the actual content of a fermentation product at a first time node according to preset key time nodes in the anaerobic fermentation process; inputting the sludge initial feature information into a preset machine learning model to obtain the predicted content of the fermentation product corresponding to the first time node; calculating a content difference value between the actual content and the predicted content of the product, and when the content difference value exceeds a preset threshold value, inputting the content difference value into a preset parameter adjustment model to obtain a corresponding parameter adjustment quantity; and adjusting the current fermentation parameters according to the parameter adjusting quantity. The problem that in the prior art, the fermentation state is difficult to monitor according to product information of sludge with different characteristics in the fermentation process, and consequently the parameter control precision of fermentation equipment is low is solved.

This invention relates to the field of detection technology and provides a liquid chromatograph for product analysis. The open-top box has a shock-absorbing support at its bottom, on which the liquid chromatograph body is mounted. An exhaust pipe is connected to the liquid chromatograph body, with one end extending outside the open-top box and connected to a condensing mechanism. The condensing mechanism is connected to the open-top box. A cylindrical body is connected to one side of the open-top box via a second fixing plate, and a housing is fixedly connected to one side of the cylindrical body. The bottom of the housing is connected to the cylindrical body via a connecting pipe, and a filtration mechanism is connected to the housing. The bottom of the cylindrical body is connected to the liquid inlet of the liquid chromatograph body via a flexible hose. This invention filters out debris from the extract using several filter screens. The filtered extract is then introduced into the cylindrical body through the connecting pipe and passes through several filter screens to filter out debris from the test solution, preventing debris from clogging the internal pipes of the liquid chromatograph body.

The invention discloses an electrocatalyst high-throughput screening platform for an electrocatalytic reaction system and a method thereof. According to the platform, a flowing electrolytic tank and a high-flux pipetting workstation are taken as cores, and gas chromatography (GC) and nuclear magnetic resonance (NMR) rapid product analysis are integrated. The platform adopts an aluminum alloy gantry type four-axis (XYZ1Z2) moving mechanism to realize space positioning of clamping and pipetting; the high-flux pipetting workstation is provided with a gun head storage module, a reagent bottle storage module, a rotary bottle cap module and an electrocatalyst preparation module, so that accurate liquid proportioning and electrocatalyst preparation are realized; a flowing electrolytic tank and the like are arranged in the electrochemical test workstation, so that continuous flowing electrolysis, automatic sample loading and electrolyte circulation are realized; the GC / NMR module is used for rapidly detecting a product on line. The platform realizes whole-process unmanned and repeatable catalyst preparation and high-throughput screening through a unified control circuit and an upper computer. The electrocatalytic reaction system is a carbon dioxide reduction reaction system.

The invention provides a trimming die shearing fault analysis early warning method and device based on product analysis, and relates to the technical field of fault early warning, and the method comprises the steps: continuously collecting shearing product features outputted by a trimming die, and generating a product feature time sequence; carrying out product abnormal modal positioning; when the abnormal modality of the product is instantaneous abnormity or no abnormity, performing qualified characteristic fluctuation rule analysis, and generating qualified characteristic fluctuation rule information; performing product feature one-way trend verification to generate a one-way trend verification result; and generating first reminding information for fault early warning. The technical problems that in the prior art, due to the fact that quality fluctuation analysis of qualified products is lacked, shearing fault early warning is not timely, and production quality is affected can be solved, potential fault early warning is carried out through qualified characteristic fluctuation rule analysis and one-way trend verification under the condition of instantaneous abnormity or no abnormity, and the production quality is improved. The technical effects that the timeliness of shearing fault early warning is guaranteed, and then the production quality is guaranteed are achieved.

The application discloses a product analysis method and system based on a life cycle-system level data chain model, realizes transparent recording and tracing of product life cycle data through a decentralized data storage platform of a block chain, applies smart contract technology, accurately cooperates global and local decisions, and breaks the collaboration bottleneck of a traditional manufacturing system. Meanwhile, the problem of small sample data imbalance is solved by using a distributed sharing mechanism of the block chain, and the data credibility and the overall availability of the system are improved. On the basis of the decentralized data storage platform, a product life cycle and system level double digital main line block chain data model is established, an intelligent manufacturing data analysis and knowledge learning model is established in a method domain, the block chain is combined with edge computing, data processing is more efficient and intelligent, the intelligent level of the manufacturing system is further improved, and a comprehensive, efficient and intelligent solution is provided for digital transformation.

The invention relates to the technical field of battery manufacturing, in particular to a QMS defective product analysis and tracing method based on the battery manufacturing industry, which comprises the following steps of: according to battery product performance requirements and safety standards, quantifying a defective product rate target, defining a standard of deviation between the purity of a positive electrode material and the capacity of a battery cell, and obtaining coating thickness deviation and welding strength parameters; equipment operation state information input by an operator and a raw material batch number provided by a supplier are fused, acquisition parameters are compared with a preset standard in real time, data exceeding a threshold value are marked, and a multi-dimensional quality feature data set is established. According to the invention, multiple dimensions of quality planning, quality control, defective product analysis, tracing, quality improvement and the like are integrated, and a set of systematized and standardized QMS defective product analysis and tracing method in the battery manufacturing industry is formed. A supplier management and control system is established by formulating clear targets and standards in the quality planning stage, and defective products are prevented from being generated from the source.

The invention provides a method for determining the form of a silver mineral, and belongs to the technical field of process mineralogy. The method comprises the following steps of silver ore sample preparation, first-time automatic mineralogy analysis, layer-by-layer stripping and repeated analysis, substance composition measurement and coefficient calculation, comprehensive morphological parameter calculation and morphological statistics. According to the method, through a strategy of combining'surface layer-by-layer analysis-three-dimensional parameter reconstruction 'and'process product analysis-distribution behavior analysis', accurate quantification of two-dimensional / three-dimensional forms (such as length-width ratio, thickness and complexity) of the silver minerals is realized, and the process mineralogy characteristics of different types of silver minerals are disclosed synchronously; comprehensive and accurate data support is provided for silver ore crushing particle size optimization, sorting process selection and process evaluation, and the defects that a traditional method is single in form information and insufficient in correlation with process behaviors are overcome.

The invention discloses a vehicle product analysis decision method, device and equipment. The method comprises the following steps: calling a pre-constructed knowledge search tool based on a pre-constructed large model for vehicle product analysis and decision, searching first vehicle use scene information, first vehicle product project information and first vehicle product constraint information associated with the vehicle product demand analysis data from a pre-constructed vehicle knowledge base; based on the first vehicle product constraint information, determining a plurality of vehicle product decision factors matched with the vehicle product demand analysis data, calling a pre-constructed constraint and risk assessment tool, and based on the plurality of vehicle product decision factors, determining a vehicle product risk assessment result; and generating a vehicle product analysis decision result corresponding to the vehicle product demand analysis data based on the first vehicle use scene information, the first vehicle product project information and the vehicle product risk assessment result. Therefore, the accuracy of vehicle product analysis decision can be improved.

The invention discloses a precise pyrolysis regulation and control and product analysis system and method for urban biomass solid waste, and relates to the technical field of solid waste treatment. Comprising a material characteristic prediction module which is used for carrying out pyrolysis behavior characteristic prediction through a machine learning prediction model after preprocessing urban biomass solid wastes, and obtaining a corresponding pyrolysis behavior characteristic report; the process pyrolysis regulation and control module is used for constructing a feature target vector according to the pyrolysis behavior feature report and a user product quality target, acquiring a corresponding candidate process track through a deep learning prediction model, and adjusting the candidate process track in real time according to product quality data in a pyrolysis reaction treatment process; and the product collection module is used for collecting and analyzing products obtained after the pyrolytic reaction is carried out according to the candidate process tracks. According to the method, the problem of unstable product quality caused by raw material fluctuation in a traditional method can be solved, and the reliability of pyrolysis behavior prediction is improved.

The application discloses an experimental platform for microwave plasma assisted metal and water reaction, which comprises a combustion adjusting system, a fuel comprehensive supply system, a microwave plasma generating system, a diagnosis system and a comprehensive control system; wherein the combustion adjusting system comprises a premixing chamber and a combustion chamber which are sequentially communicated from bottom to top, a rectifier and an igniter are arranged in the premixing chamber, and the rectifier is used for controlling the uniformity of mixed gas; the combustion chamber comprises a microwave combustion assisting zone, an observation and diagnosis zone and a product analysis zone which are sequentially distributed from bottom to top, a back pressure valve is arranged at the top of the product analysis zone, and the back pressure valve is used for regulating and controlling the reaction pressure in the combustion chamber. The application constructs a stable and accurate comprehensive experimental platform, can better observe and study the influence of microwave on the combustion of metal and water reaction and analyze specific influencing factors, and powerfully promotes the research on judging the combustion dominant mechanism and the like.

The invention belongs to the technical field of mineral product analysis, and discloses a mineral product component detection device and method.The mineral product component detection device comprises a mounting ring, and the rear end of the outer wall of the mounting ring is fixedly connected with a fixing plate; a sampling assembly for sampling and drilling a rock core, a crushing assembly for crushing an ore rock sample and a detection mechanism for detecting the sample are distributed on the front side of the outer surface of the mounting ring in an annular array manner by taking the circle center of the mounting ring as an axis; and a driving assembly used for driving the sampling assembly, the crushing assembly and the detection mechanism to work is mounted at the rear end of the outer surface of the mounting ring, and the driving assembly comprises a motor. Through the driving assembly, a single motor drives the multiple assemblies to work cooperatively, power input is provided by a single driving source while the multiple assemblies achieve different effects, and it is ensured that depth detection can be conducted on the rock core.

The application discloses an electrocatalyst high-throughput screening platform for an electrocatalytic reaction system and a method thereof. The platform takes a flow electrolytic cell and a high-throughput pipetting workstation as cores, and integrates gas chromatography (GC) and nuclear magnetic resonance (NMR) rapid product analysis. The platform adopts an aluminum alloy gantry four-axis (XYZ1Z2) moving mechanism to realize spatial positioning of clamping and pipetting. The high-throughput pipetting workstation provides a gun head storage module, a reagent bottle storage module, a rotating bottle cap module and an electrocatalyst preparation module to realize accurate liquid proportioning and electrocatalyst preparation. The electrochemical test workstation is internally provided with a flow electrolytic cell and the like to realize continuous flow electrolysis, automatic sampling and electrolyte circulation. The GC / NMR module realizes online rapid detection of products. The platform realizes unattended, repeatable catalyst preparation and high-throughput screening of the whole process through unified control of a circuit and an upper computer. The electrocatalytic reaction system is a carbon dioxide reduction reaction system.

The application relates to the technical field of data management, and discloses a multi-source Beidou space-time big data whole life cycle integrated management method, which comprises the following steps: collecting Beidou space-time big data of different sources, and processing the Beidou space-time big data according to a whole life cycle to form a processing flow of a plurality of theme products; obtaining nodes corresponding to each link of each theme product and generating a theme product analysis graph structure; quantifying the public weight of each node; obtaining an initial unique factor of each data attribute of each node; obtaining a plurality of comparison data attributes of each data attribute; quantifying the correlation degree change degree of the data attribute and each comparison data attribute thereof; obtaining a final unique factor of each data attribute of each theme product; and adjusting and distributing storage of a plurality of source data of each data attribute. The application aims to solve the problem that the data attribute correlation is not considered in the whole life cycle integration process of multi-source Beidou space-time big data, and the storage influences the calling efficiency.

The application belongs to the technical field of e-commerce competitive product analysis, more particularly to a product traffic analysis and competitive product identification method based on ASIN and keywords, in the present application, by introducing a predetermined time window mechanism, the similarity change trend of each target ASIN and high overlap competitive product in each time window is repeatedly calculated, and the similarity threshold of the continuous window is combined to filter out stable competitive products and temporary competitive products; and in the present application, ASIN is taken as a node, and competitive similarity is taken as an edge to construct a traffic competition network, a Louvain community discovery algorithm is used for clustering to obtain a potential competitive product pool, and then the traffic overlap degree of the ASIN in the competitive product pool and the target ASIN is calculated, only the high overlap degree competitive product higher than a predetermined threshold is reserved, the weakly related ASIN with low traffic overlap is effectively eliminated, and the problem of competitive group redundancy is solved.

The invention relates to the technical field of tourism product analysis, in particular to an elderly tourism product and experience behavior analysis management system based on big data. The user terminal obtains feedback content which is input by a user and aims at the tourism product, and then sends the feedback content to the server; the feedback content is processed to obtain text sentences corresponding to the feedback content, and the text sentences are tourism product judgment character evaluation content of the user and are subjected to sentence segmentation processing; the server carries out word recognition on the text sentences on the basis of a tourism item word bank and an emotion judgment word bank and generates an emotion score value corresponding to the feedback content, the emotion score value can reflect the evaluation degree of the user on the tourism product, the feedback content is displayed through the management terminal, and the user experience is improved. And according to the corresponding product numbers and the corresponding emotion score values, management personnel can perform targeted analysis and optimization on the tourism products according to the feedback content and the corresponding emotion score values.

The invention discloses a commodity recommendation method and device oriented to a sea culling scene, and a medium, belongs to the technical field of electronic commerce, and is used for solving the technical problems that data acquisition is difficult, commodity recommendation is not accurate enough, and an effective data feedback mechanism is lacked in an existing sea culling market. The method comprises the steps of performing data acquisition processing on a plurality of sea culling platforms by simulating a user access behavior to obtain initial commodity data; according to a preset classification rule, performing data classification marking on the initial commodity data, and obtaining and storing marked commodity data; performing data analysis on the marked commodity data under related sales cycle factors, price cycle factors and regional popularity factors to obtain comprehensive commodity analysis data; and carrying out training output of a related neural network model on a potential recommendation relationship between the user and the commodity by integrating a priority recommendation rule corresponding to the commodity analysis data to obtain a personalized recommendation strategy.

The present invention relates to the technical field of chemical reaction equipment, and provides a laboratory continuous reaction apparatus, which comprises a reaction kettle, an overflow discharge pipe arranged on the upper side of the reaction kettle, and a sampling channel penetrating through the upper side wall of the overflow discharge pipe, a sampling tube is arranged at the lower part of the sampling bottle, a sealing plug is arranged in the sampling bottle in a sliding manner, the sampling bottle is arranged in a lifting manner, and after the sampling bottle descends, the sampling tube penetrates through the sampling channel, enters the overflow discharging tube and is used for extending into liquid in the overflow discharging tube; the lifting rod is arranged above the sampling channel in a lifting mode, the lower end of the lifting rod is detachably connected with the sealing plug, and the lifting rod is used for driving the sealing plug to slide upwards in the sampling bottle and extracting a sample from the overflow discharging pipe. According to the technical scheme, the problem of inaccurate sampling is solved, and the product analysis accuracy can be improved.

This invention provides a method for cleaning ultra-deepwater long-distance gas-liquid mixed transport subsea pipelines, belonging to the field of marine oil and gas engineering and flow safety assurance technology. The method includes the following steps: accurate data analysis and operational condition simulation; calculation of the minimum ethylene glycol injection volume required for each stage; prediction of the maximum slug flow rate and its impact on the platform separator and trap; determination of the specific duration, gas volume control range, and gas source switching node for each cleaning stage based on the simulation results, while developing an emergency plan; sequential execution of the four stages: production gas carrying liquid stage, recirculating gas purging and carrying liquid stage, recirculating gas cleaning stage, and production gas cleaning stage; and depressurization via a balancing valve, removal of the cleaning tool, and product analysis. This invention achieves controllable risks, reduced time, and minimized production loss in pipeline cleaning operations through a multi-stage gas source switching strategy, integrated real-time online simulation and early warning technology, and optimized slug flow control and ball launch / receiver procedures.

The utility model discloses an IR defective product analysis auxiliary device of MLCC, including bottom plate, the electrically conductive vessel fixed mounting is in the top of bottom plate, and the electrically conductive vessel is used for storing electrolytic solution, and clamping subassembly sets up in the electrically conductive vessel, and the detection piece is set up in the inside of electrically conductive vessel through clamping subassembly, and power module installs in the top of bottom plate, and power module is used for providing power supply to the detection piece electroplating, and installation casing sets up in the electrically conductive vessel, and elastic member fixed mounting is in the top of installation casing, and the bottom of elastic member and detection piece extrusion are inlaid. The utility model discloses the cooperation use mode of electrically conductive vessel, clamping subassembly and power module, and the inside storage of electrically conductive vessel has the electroplating solution, and the short circuit layer corresponding Ni electrode of detection piece occurs replacement reaction constantly after electrification, and Ni electrode is dissolved constantly, thereby leading to the color of this layer and other positions produce differentiation, and the position of short circuit layer is fast and definite, thereby improving the efficiency of MLCC defective product analysis.

The application provides a trimming die shearing fault analysis early warning method and device based on product analysis, relates to the technical field of fault early warning, and comprises the following steps: continuously collecting shearing product features output by a trimming die, and generating product feature time sequences; performing product abnormal mode positioning; when the product abnormal mode is instantaneous abnormality or no abnormality, performing qualified feature fluctuation rule analysis, and generating qualified feature fluctuation rule information; performing product feature one-way trend verification, and generating one-way trend verification results; and generating first reminding information to perform fault early warning. Through the application, the technical problem that shearing fault early warning is not timely and production quality is affected due to the lack of qualified product quality fluctuation analysis in the prior art can be solved. In the case of instantaneous abnormality or no abnormality, potential fault early warning is performed through qualified feature fluctuation rule analysis and one-way trend verification, so that the timeliness of shearing fault early warning is ensured, and the technical effect of ensuring production quality is achieved.

The present application relates to the field of financial technology artificial intelligence, and in particular to a method for intelligently unifying asset management product valuation tables based on NLP, which pre-processes original valuation table data, extracts full-text information of underlying accounting subject codes as input for an NLP model, trains a bert classification model, and thereby establishes a corresponding relationship between the original valuation table accounting subject system and the standard accounting subject system, for completing the cleaning of the valuation table. The method can be embedded in asset management product analysis software, thereby greatly reducing the workload of valuation table data analysis and improving data accuracy.

The invention discloses an automatic competitive product analysis method and terminal, and the method comprises the steps: collecting first competitive product information of a first target product, carrying out the feature identification of the first competitive product information, and constructing a training data set; training according to the first target product and the corresponding training data set to obtain a competitive product feature analysis model; and inputting data of a second target product into the competitive product feature analysis model to obtain a competitive product having the highest matching degree with the second target product and a feature identifier of the competitive product, and generating an improvement scheme of the second target product according to the competitive product and the feature identifier of the competitive product. The competitive product information is automatically collected through the competitive product feature analysis model, the competitive products are subjected to feature recognition, and the competitive products with the highest matching degree with the target product and the feature identifiers of the competitive products are obtained, so that the improvement scheme of the target product is generated, and the competitive product analysis efficiency and accuracy are improved.

The invention discloses a hardwood pyrolysis gas product analysis method and system. The method comprises the following steps: S1, carrying out a thermogravimetric-infrared spectroscopy instrument experiment on a typical hardwood material, collecting and processing data, and determining peak temperatures of three components (hemicellulose, cellulose and lignin) according to a K-K method; s2, determining a specific pyrolysis temperature range of each component by using a double-Gaussian function; s3, dividing temperature regions of the pyrolysis gas product of each component, including an overlapping region and a non-overlapping region, and performing curve area integration on each region; and S4, calculating the corresponding gas yield in each component, performing data separation, and comparing and observing the corresponding relation of hemicellulose, cellulose and lignin gas products. According to the method, the limitation of the prior art on general analysis of biomass pyrolysis is broken through, accurate tracking and quantification of release behaviors of the three main component gases are realized, and key data support is provided for optimizing a pyrolysis process.