65 results about "Product analysis" patented technology

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 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 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 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 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 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 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.

The invention discloses a detection device for chemical oil product analysis, and belongs to the technical field of oil product detection, the detection device comprises an analysis detector, the analysis detector is provided with a display screen for operation, the analysis detector is internally provided with a detection cavity, a light shielding plate is slidably connected between the detection cavity and the analysis detector, and the light shielding plate is slidably connected with the analysis detector. According to the detection device for chemical oil product analysis, the driving assembly is arranged to work to vertically move the pushing rod, the pushing rod can push the piston when vertically moving, and the piston can slide in the sample measuring cylinder when being pushed; when the piston slides, an oil product in the sample measuring cylinder can be pushed into the sample vessel, and as the volume of the oil product in the sample measuring cylinder is slightly greater than that of the interior of the sample vessel, the oil product can fully spread the placing cavity when entering the sample vessel, so that the oil product can fully spread the placing cavity conveniently, the operation is convenient, and the detection accuracy is improved.

We provide the system. [Solution] A speech recognition means that receives voice input and converts the voice data into text data, A product analysis means that analyzes the aforementioned text data and identifies potential purchasable products, A payment processing means that executes an electronic payment procedure based on the product selected from the aforementioned candidate products, A delivery instruction means for instructing the delivery arrangements for the selected product, A system that includes this.

The utility model discloses a centrifuge for oil product moisture analysis, and relates to the technical field of oil product analysis, the centrifuge comprises a support, a separation mechanism is arranged in the support, and a fixing mechanism is arranged in the support. When the rotating shaft rotates, a connecting block is driven to rotate, when the connecting block rotates, a disc is driven to rotate circumferentially, then a second rotating shaft is driven to rotate circumferentially, when the disc rotates circumferentially, the second rotating shaft is driven to move, and therefore a gear is driven to move; when a gear moves, the gear is in a self-rotation state, then a rotating shaft II is driven to rotate, so that a disc is driven to rotate, when the disc rotates, a tank body II is driven to rotate, so that a container is driven to rotate, the container can be in a revolution state and a self-rotation state at the same time through the mechanism, and the oil-water separation efficiency can be improved; and the separation stability is ensured.

The invention discloses a quantitative detection method for beta-caryophyllene in high-matrix complexity fermentation liquor, and belongs to the field of biological fermentation product analysis. Comprising the following steps: performing low-temperature high-speed centrifugation to remove fermentation broth precipitates, and preparing beta-caryophyllene series standard solutions from blank fermentation broth; diluting the to-be-detected liquid and the standard liquid with ultrapure water, saturating with NaCl, adding alpha-terpilenol-d3 internal standard, carrying out anhydrous ether ice-bath ultrasonic extraction, dehydrating an organic phase, and then carrying out GC-MS (Gas Chromatography-Mass Spectrometer) detection; drawing a plotting curve according to the peak area ratio and the standard solution content ratio, and calculating the content of the to-be-detected solution. The method is anti-interference, accurate and reliable, and is suitable for detecting trace beta-caryophyllene in the fermentation liquor.

The application discloses a kind of ship main engine lubricating oil product analysis monitoring methods, for monitoring and guaranteeing ship main engine lubricating oil quality;Based on offline detection and online detection, the oil quality sensitive parameters of the lubricating oil of multiple main engines of ship are collected and the corresponding dielectric constant, form the relationship curve of oil quality sensitive parameters and dielectric constant based on the cumulative sailing time of ship main engine, can determine the alarm threshold of dielectric constant according to ship age, when its reaches the alarm threshold of the above dielectric constant, alarm, with comprehensiveness, economy and timeliness, the timeliness and accuracy of ship safety monitoring are improved.

The application provides a method for determining silver mineral morphology, and belongs to the technical field of process mineralogy. The method comprises the following steps: silver ore sample preparation, first automatic mineralogical analysis, layer-by-layer stripping and repeated analysis, material composition determination and coefficient calculation, comprehensive morphology parameter calculation, and morphology statistics. Through the strategy of combining "surface layer-by-layer analysis-three-dimensional parameter reconstruction" and "process product analysis-distribution behavior analysis", the application not only realizes accurate quantification of two-dimensional / three-dimensional morphology (such as length-width ratio, thickness and complexity) of silver minerals, but also synchronously reveals the process mineralogical characteristics of different types of silver minerals, thereby providing comprehensive and accurate data support for the optimization of the crushing particle size of silver ore, the selection of the separation process and the evaluation of the process, and overcoming the shortcomings of single morphology information and insufficient correlation with process behavior in the traditional method.

The invention discloses a big data processing and analysis system for a data medium platform, and belongs to the technical field of data analysis. Data acquisition is performed according to each data source to obtain enterprise data; storing and processing the enterprise data; obtaining product information of each user product, setting a product service scheme according to the product information, configuring an intelligent service model according to the product service scheme, identifying a learning data range corresponding to the intelligent service model, collecting learning optimization data according to the learning data range, and performing optimization adjustment on the intelligent service model according to the learning optimization data; performing product service analysis according to the intelligent service model and the product service scheme to obtain a product analysis result; the situation of data islands formed due to the fact that data are dispersed in different systems and platforms in the enterprise operation process is effectively broken through, efficient circulation and sharing of mass structured and unstructured data are achieved, and the potential value of the data is fully released.

The invention discloses a vehicle index data processing method and related equipment, and the method can obtain a target index value corresponding to a target index score of a vehicle, and the target index score represents the visual effect of an index item, so that the subjective use experience of the vehicle can be quantitatively represented, and the user experience is improved. The target index value is a value possessed by the index project in engineering technology, so that by executing the vehicle index data processing method in the embodiment, the target index score obtained by means of vehicle competing product analysis, customer demand collection and the like can be used as an overall target and is converted into a specific technical parameter such as the target index value, and the target index value is obtained. Therefore, targets and directions of technicians in the processes of design and development, production and manufacturing, later maintenance and the like of the vehicle can be defined, the efficiency of the processes can be improved, and satisfactory vehicle products can be obtained. The invention is widely applied to the technical field of automobiles.

The application relates to an electronic product analysis method and device, computer equipment and a storage medium. The electronic product is simulated and analyzed to obtain fault information and each level of the electronic product. Then, a fault transmission model is constructed according to the fault information and each level. Based on the fault transmission model, fault influence analysis and fault tree analysis are performed on the electronic product to obtain an electronic product reliability analysis result. Based on the fault transmission model, a correlation matrix is constructed, and a testability analysis result of the electronic product is obtained according to the correlation matrix. The fault transmission model constructed by the fault information and each level can realize collaborative modeling and analysis of the reliability and correlation of the electronic product, and improve the design analysis efficiency and result accuracy of the reliability and testability of the electronic product.

The invention belongs to the technical field of information processing, and provides a semantic fusion and deep extraction-based structured content generation method and system, which is characterized in that a global context text is constructed by integrating multi-source heterogeneous information of materials uploaded by a user, network search and image analysis; a deep cognitive large model supporting long text processing is used for cross-source cross validation, conflict resolution and correlation analysis, high-precision information fusion and structured extraction are achieved in combination with systematic Prompt engineering, and finally high-value structured product analysis data are generated and automatically archived. According to the method, the limitation of shallow processing in the prior art is broken through, simple data quality filtering is improved to deep semantic understanding and fusion of multi-source heterogeneous information, AI can process single information, cross validation, conflict resolution and correlation analysis of cross-source information can be carried out, multi-modal data dimension reduction integration and deep knowledge recreation are achieved, and the method has the advantages of being high in practicability and easy to popularize. And the content creation and decision analysis efficiency is obviously improved.