70results about How to "Fix build issues" patented technology

The invention relates to a modeling method of a gas compressor capable of achieving graded regulation and control over the angles of adjustable vanes. The modeling method of the gas compressor capable of achieving graded regulation and control over the angles of the adjustable vanes is suitable for the gas compressor with two-grade adjustable vanes, wherein adjustable guide vanes serve as one grade, and adjustable static vanes serve as the other grade. The modeling method of the gas compressor capable of achieving graded regulation and control over the angles of the adjustable vanes comprises the steps that firstly, features of the gas compressor with the angle of the adjustable guide vanes and the angle of the adjustable static vanes controlled respectively are established; secondly, gas compressor model calculation is completed with the established features of the gas compressor. The modeling method of the gas compressor capable of achieving graded regulation and control over the angles of the adjustable vanes achieves the purpose of establishing a model of the gas compressor with the angle of the adjustable guide vanes and the angle of the adjustable static vanes of an inlet controlled respectively, or solves the problem that design and testing need to depend on a control system of an engine model.

The invention discloses a soft measuring method of product quality of an industrial fluidized bed gas-phase polyethylene device. The method comprises the following steps: selecting a plurality of key variables influencing product quality to set up a process detection variable set; applying the projection principle of multivariate statistics to establish a soft measuring model between product resin melt index and density and process detection variables; adopting a nonlinear partial least square method of embedded Taylor series approximation (used for carrying out process nonlinear characteristic representation) as core technology; and determining the number of optimal pivot elements through cross check technology. The soft measuring method avoids complex process mechanism analysis and has convenient site implementation and high precision of soft measuring; therefore, the method is particularly suitable for nonlinear industrial occasions with high dimension and abundant progress data similar to the industrial fluidized bed gas-phase polyethylene production device. Moreover, the soft measuring method can be used for real-time monitoring or production guidance to improve product quality, increase output and ensure smooth device operation, thereby bringing greater economic benefits.

The invention relates to oil geophysical prospecting and 3D complex geologic body reconstruction technique: constructing an equipotential field-based initial curve; optimizing cell quality of triangular grid of the initial curve and building a topological relation between grid cells, then converting all the other known information into various fuzzy control restriction information according to the requirements of input model of a disperse smooth interpolation algorithm, additionally, converting all control points into restriction information of fuzzy control points, inputting all restriction information into a discrete smooth interpolator, and then calculating coupling relation of these restrictions and the initial grid curve model, thus eliminating the interactive point offsetting process for curve model construction of a multivalued body , making it convenient to implement the curve model construction of a complex multivalued body and interactive curve editing method is flexible and convenient.

The invention discloses a method for searching a similar watershed based on a spatial dimension division theory. The method comprises the following steps: firstly, dividing a drainage basin into a plurality of orthogonal grid units based on DEM data to obtain an elevation in each grid unit, thereby obtaining an elevation grid Raster_Ele of the drainage basin, and calculating to obtain an elevationfractal dimension value Fra_Ele; secondly, calculating the gradient in each grid unit to obtain a gradient grid Raster_Slope of the drainage basin, and calculating to obtain a gradient fractional dimension value Fra_Slope; next, calculating the slope direction in each grid unit to obtain a slope direction grid Raster_Slope Dir of the drainage basin, and calculating to obtain a slope direction sub-dimension value Fra_Slope Dir; and finally, constructing a multi-dimensional feature space, generalizing a drainage basin into data points, labeling the data points in the multi-dimensional feature space, and classifying the data points, so that the drainage basin divided into one class is regarded as a similar drainage basin.

The invention discloses a functional magnetic resonance imaging brain connectivity map construction method based on collaborative clustering. Brain functional connectivity mapping is a key link in brain function and brain disease research. How to construct and validate brain functional connectivity mapping has become the focus and frontier of current brain science research. Recent studies show that there are still some shortcomings in the existing methods of constructing brain functional connectivity maps: the hypothesis-driven method based on model is not robust, the correctness of brain functional connectivity maps based on model independent method is difficult to verify, and the brain functional connectivity maps based on data-driven method are not precise enough. In order to overcome the shortcomings of the prior art, the present invention provides a novel and easy-to-verify method, which simultaneously identifies a functional sub-region of a specific brain structure and its connecting brain region by adopting a cooperative clustering algorithm, thereby realizing the construction of a refined brain functional connection map; at the same time, three approaches from different angles are adopted to verify the correctness of the brain functional connectivity map.

The invention discloses a robot system used for wall face environment perception. The robot system is composed of a wall climbing robot and a remote environment map information management platform. The wall climbing robot comprises a robot body, a power unit, a wall face information collection unit and a communication unit. The remote environment map information management platform comprises a data processing computer and management platform software. The power unit comprises a servo motor, a servo driver and a transmission structure. The wall face information collection unit comprises a visual sensor, a laser sensor, a wall face roughness sensor, a humidity sensor and a wall face inclination sensor. The communication unit comprises a 4G communication module, a WIFI communication module, avideo transmission module and a handheld remote controller. By means of the robot system, wall face environment information is collected, analyzed and processed, a wall face environment information map is generated, and therefore global environment information is provided for autonomous work of the wall climbing robot, people can conveniently conduct accurate work tasks remotely or the robot canconveniently conduct the accurate work tasks autonomously, and the application range is very wide.

The invention discloses an abrasive band grinding process simulation method. The method comprises the steps that an abrasive band contact wheel and workpiece simulation model is built; the simulationmodel is subjected to grid division; and part of abrasive particle units are deleted, and a multi-abrasive-particle random distribution model is generated. According to the abrasive band grinding process simulation method, the purpose of building the abrasive band grinding simplification model featuring multi-abrasive-particle random distribution is achieved creatively, accordingly, the problem that an existing grinding simulation method is insufficient in analysis precision can be relieved, and the abrasive band grinding machining process under a multi-abrasive-particle comprehensive effect can be accurately simulated.

The invention discloses a road smoothness predicting method based on a minimum variable coefficient assessment and inference model. According to the method, sample analysis and digging of vehicle-mounted GPS historical data are carried out, a variable coefficient assessment method and a technique for building a road traffic flow characteristic interference model in a sampling cycle are adopted, and road short-time smoothness and future smoothness trends are inferred through floating vehicle data analysis. According to the method, typical sample analysis based on a GPS is adopted, and a statistic cycle is obtained by means of a parameter optimization technique of a road smoothness analysis model, so that the method is supported by a strict mathematical model and has wide adaptability; road situation property types and corresponding rule base relations are quickly obtained by building the road traffic flow characteristic model, road smoothness trend prediction capacity is obtained based on knowledge inference, and statistic efficiency and the service level are greatly improved.

The invention provides a method and a device for establishing a power communication network model, wherein the method and the device relate to the technical field of a power communication system. The method comprises the steps of acquiring data of a network model structure and service distribution condition of the to-be-processed power communication network; determining a link capacity matrix and a service connection matrix, and determining a network service flow matrix according to the link capacity matrix and the service connection matrix; determining a service flow parameter of each power communication network node in each service type according to the link capacity matrix, the service connection matrix and the network service flow matrix; determining the determined value of importance of each power communication network node according to the service importance of each service type and the each service flow parameter; and correspondingly arranging each determined value of importance and each power communication network node in the network model structure of the to-be-processed power communication network, thereby forming the power communication network model in which each power communication network node has the determined value of importance.

The invention relates to a variance optimization histogram construction method and device based on Spark Streaming. The method comprises the steps that Spark Streaming is utilized to perform online sampling on streaming data; a variance optimization histogram is dynamically constructed according to online sampling data; and the variance optimization histogram is dynamically updated by use of newly added data, and the variance optimization histogram is dynamically constructed again according to the newly added data. Through the technical scheme, the high-precision approximate variance optimization histogram can be constructed by scanning data once within a limited memory space.

The invention relates to a process for preparing a heat-conducting polymer material by utilizing SLS to form a porous ceramic heat-conducting network, the method comprises the following steps: blending ceramic powder and powder; introducing the structure of a designed integrated filler into software, setting the technological parameters of the SLS, and printing and forming mixed powder; spraying an epoxy chloropropane solution on the obtained porous ceramic heat-conducting network and drying; placing the dried porous ceramic heat-conducting network in a muffle furnace, heating, and naturally cooling; filling the cooled porous ceramic heat conduction network into a thermosetting resin matrix, and using a prepreg-vacuum curing process to prepare the heat-conducting polymer material. The process for preparing the heat-conducting polymer material by utilizing the SLS to form the porous ceramic heat-conducting network is simple in process and high in flexibility, and the prepared heat-conducting polymer material has extremely high heat conductivity and ultrahigh strength, simultaneously has good toughness and rigidity, and has wide application prospect.

Aiming at the problem that the requirement of people for mining and recommending content associated websites cannot be met in the prior art, the invention provides a method for mining approximate websites and recommending the similar websites to users by learning example websites. The method comprises the following steps of: learning the example websites, mining other websites associated with thecontents of the example websites according to the theme contents of the websites, and recommending the other websites to the users. Website theme information is learned through the example websites, the example website system intelligently explores new websites associated with the theme contents of the example websites and recommends the new websites to the users, so the information level concerned or browsed by the users is broadened, the users can acquire other information associated with the browsed information more conveniently and quickly, information search time is saved, and informationsearch efficiency is improved. The method has a good promotion effect on information acquisition of the users, has the advantages of high interaction performance, high intelligent degree, high expandability, high recommendation speed, high mining precision and the like, and has huge utilization value and market application space.

The invention belongs to the technical field of reliability statistics. The invention discloses a reliability confidence lower limit construction method based on the Bayesian theory and linear fitting, and the method comprises the steps: calculating the confidence upper limit of the failure probability of each sample product life test data according to the Bayesian theory for each given sample product life test data, namely the failure time of each sample product; converting the Weibull distribution function into a linear function; and finally, constructing a confidence lower limit curve of the Weibull distribution reliability based on linear fitting. Through the steps, the construction problem of the lower confidence limit of the Weibull reliability is well solved. In each step of the method, a determination form of a corresponding mathematical expression is given, and the whole process is convenient to calculate, so that the method is very suitable for application in engineering practice.

The invention discloses a flow injection luminescent detection device, which comprises a base, a reference electrode, an auxiliary electrode and a working electrode. A detection cavity with an opening at the bottom is arranged inside the base, and the reference electrode and the auxiliary electrode are arranged along the base. Axially arranged in the base, one end of the reference electrode and the auxiliary electrode is suspended in the detection cavity, the other end of the reference electrode and the auxiliary electrode protrudes from the upper end surface of the base, and the working electrode is formed by Made of transparent material, the working electrode is fixed on the bottom wall of the base and is in contact with the detection chamber, the working electrode seals the bottom of the detection chamber, and two through holes are opened radially on the peripheral wall of the base, the The through hole communicates with the detection chamber. The invention solves the problem of constructing the bionano sensing interface in the flow injection chemiluminescence/electrochemiluminescence system, and realizes the highly selective and sensitive detection of biomolecules in the automatic flow injection chemiluminescence/electrochemiluminescence system.

The invention discloses a power transmission line defect risk modeling and prediction method based on a support vector machine, and the method comprises the steps: firstly enabling a power transmission line to be subdivided into a plurality of parts, and defining a defect risk value as an evaluation index of a line defect condition under the condition of considering the number of defects and the severity degree of the defects; secondly, screening out important factors influencing the defect risk value of each part through correlation coefficients, introducing a support vector machine machine learning method, and predicting the future defect risk value of the line by utilizing the advantage that the small sample learning problem can be effectively solved. The size of the defect risk prediction value reflects the defect condition of the power transmission line in the future, and an important reference can be provided for the work of related departments.

The invention discloses an industrial control system state mechanism construction method. The method starts from a clustering algorithm, adopts the most advanced BLOCK-DBSCAN algorithm, and improves both the speed and the accuracy. Moreover, a self-adaptive method for the clustering algorithm parameters of the DBSCAN is provided, the optimal matching parameters can be effectively and accurately found for the industrial control system, and the efficiency is greatly improved. Then a reward and penalty mechanism is utilized to re-classify clustering results, so that the problem that high-dimensional protocol information cannot be fully separated by a clustering algorithm is solved. Finally, the construction of the industrial control system state machine is achieved through the construction of the APTA tree, and the difficulty of the construction of the state machine is solved. According to the industrial control system state machine construction method, the construction problem of the industrial control system protocol state machine is solved, and a solid foundation is provided for intrusion detection of the industrial control system in the future.

The invention provides a method and system for constructing a semantic knowledge base in an environmental impact evaluation field, and the method comprises the steps: constructing a professional term knowledge base and a non-professional term knowledge base corresponding to an industry category according to the business demands and industry expert knowledge for each industry category, and for each non-professional term keyword in the non-professional term knowledge base, establishing a fuzzy extraction rule through a regular expression; constructing a quaternary relationship among industry categories, terminologies, rules and keywords, and generating a keyword-rule lexicon according to the quaternary relationship; selecting corresponding professional terms from the keyword-rule lexicon according to the industry category of a target environmental assessment file, and locating a target chapter of the target environmental assessment file and a table and text content corresponding to the target chapter; and extracting target chapters and keywords in forms and text contents corresponding to the target chapters according to rules in the keyword-rule lexicon, scoring the extraction result, and evaluating the normalization of the target environmental assessment file according to the scoring result.