40results about How to "Fully consider" patented technology

The invention discloses a comprehensive health status evaluation method for rotation machinery equipment based on influence of use and maintenance. The health status of the equipment is influenced by different factors, related influential factors are analyzed and arranged, and divided into technical status factors and non-technical status factors, and concepts of an inherent health degree and a comprehensive health degree are defined. The inherent health degree of the rotation machinery equipment is evaluated on the basis of WPD (Wavelet Packet Decomposition) and SOM (Self-Organizing Map) by utilizing degeneration state monitoring data of the equipment. A proportion degeneration model is established by considering influence of service age and condition; and on the basis of an evaluation result of the inherent health degree, influence of service age and condition is also taken into evaluation of the comprehensive health degree. A proportion health recovery model is established, and influence of maintenance is further taken into evaluation of the comprehensive health degree. Influence of the service age, condition and maintenance are comprehensively considered on the basis of the proportion degeneration model (PDM) and the proportion health recovery (PHR) model, and evolution rule of the comprehensive health degree is derived.

The invention belongs to the technical field of knowledge maps, and discloses a knowledge map information representation learning method, a system, equipment and terminal, and the knowledge map information representation learning method comprises the steps: carrying out the preprocessing according to a path constraint resource distribution method; calculating the reliability of all paths, and outputting the reliability to a training set and a test set; initializing the model and setting parameters; generating a triple according to an iterator, and randomly replacing head and tail entities; calculating a loss function of the triple according to the score function; calculating a loss function of an additional path according to the path reliability; performing parameter optimization by using an Adam method; and performing model verification by using entity prediction and relation prediction. According to the method, rich path information contained in the knowledge graph is considered, the modeling effect of entities and relationships is improved, the modeling of the relationships can be optimized by inputting vectors into a complex plane and using rotation to represent the vectors, and the method can be used for link prediction and recommendation systems.

The invention discloses a full-working condition performance prediction method for a compressor, and aims at providing a rapid and accurate full-working condition aerodynamic performance prediction method so as to increase the design and optimization efficiency of the compressor. In the method, a formula is established by taking parameters of a design point as the reference to predict the flow, the efficiency and the overall pressure ratio of an off-design working condition; in a flow prediction method, firstly, the flow of the design point is converted according to an empirical formula to flow corresponding to a peak efficiency point at different rotating speeds, and then, blocking flow and surging flow at respective rotating speeds are calculated; in an efficiency prediction method, firstly, the efficiency of the design point is converted according to the empirical formula to peak efficiency at different rotating speeds, and then, the efficiency at different rotating speeds is calculated according to an elliptic piecewise approximation method; and in a prediction method for the overall pressure ratio, work factors at different rotating speeds and different flow are calculated according to the thought of the equivalent width of an impeller exit, and the work factors are combined with current efficiency to obtain the overall pressure ratio. By applying the full-working condition performance prediction method to design and optimization of the compressor, the design cycle can be remarkably shortened, and the design cost is reduced.

The invention relates to a full-drive underwater vehicle track tracking control method based on an optimization algorithm, and belongs to the technical field of underwater vehicle track tracking control. The method comprises the steps of obtaining motion parameters of a vehicle, and designing a motion attitude constraint vector and a speed constraint vector of the vehicle; calculating a tracking error, and obtaining a kinematics controller and a dynamics controller according to the six-degree-of-freedom model of the vehicle; finally, obtaining the expected speed through the kinematics controller, and deriving the force and the moment in each degree of freedom through the dynamics controller; and carrying out the method until track tracking is completed. The redundancy problem of a full-drive vehicle in tracking a three-dimensional curve is solved, and meanwhile the attitude and speed constraint problem of the vehicle in the moving process is considered. An attitude and speed constraintconstruction optimization problem is a convex optimization problem, multiple reliable methods are provided for solving, and the solving speed can meet the real-time requirement; and the problem of speed saturation in operation of the full-drive vehicle is fully considered, and the practicability is high.

The invention relates to a mobile node parameter adaptive track prediction method. The influences of environmental factors on nodes under a dynamic sea condition are considered; the adaptability to a variable environment is fully considered specific to the requirement of a sea moving object on a positioning method; and the motion situations of beacon nodes are introduced into node motion track prediction. After a motion track is determined, a sampling region and a sample point weight are determined on the basis of an improved Monte Carlo method. Information about relative positions with one-hop and two-hop beacon nodes in the motion processes of unknown nodes is taken as a filter condition, so that the sampling rate, sampling speed and positioning accuracy are increased. The adaptive track prediction method can be established according to environmental changes. The motion tracks of the unknown nodes are predicted through effective utilization of the motion situations of sea area beacon nodes, and an improved Monte Carlo positioning method is put forward in combination with motion characteristics, so that the sea dynamic node positioning capability can be enhanced, and the sea search-rescue speed and success rate are increased.

The invention discloses a method and device for calculating an equivalent minable thickness ratio of a coal mine goaf for an overhead transmission line. The method comprises the following steps: calculating an equivalent thickness of each rock-soil layer above the gaof; accumulatively summing the equivalent thicknesses (shown in the specification) of all the layers of an overlying rock-soil layer so as to calculate a total equivalent thickness, corresponding to a standard medium, of the overlying rock-soil layer; calculating the equivalent minable thickness ratio of the goaf according to a mining thickness of a coal bed and the total equivalent thickness of the overlying rock-soil layer. Based on sufficient calculation theoretical basis and comprehensive consideration, a result is reliable; the influence degree of the thickness and the nature of the overlying rock-soil layer on surface deformation can be reasonably considered; the severity of actual surface deformation can be accurately reflected; evaluation of the dangerousness of the surface deformation of the goaf where the transmission line passes can be facilitated; determination of a reasonable planning, construction and operation technical scheme for the overhead transmission line of the coal mine goaf can be facilitated; the method has important guidance significance and reference value for guaranteeing the safety of the transmission line.

The invention discloses a trusted startup method for BMC firmware system security, belongs to the field of trusted startup, and is characterized in that trusted measurement is performed on a BMC without a trusted cryptographic module according to a file system, a bootstrap program and a kernel in sequence, and then trusted startup is performed on the BMC firmware system. The BMC processor is guided to measure and obtain an actual measurement reference value of the file system according to a trusted computing module preset in a nonvolatile storage area b and a factory file system standard reference value imported by a developer in advance by means of a repositionable function program arranged in the nonvolatile storage area a, if not, an alarm is given, and if yes, it is trustful; and verifying the bootstrap program and the kernel according to the same method, and once the bootstrap program and the kernel are credible, directly entering a starting stage of the BMC firmware. Based on the basic fact that the attack resistance of the kernel plug-in including a file system is weaker than that of a bootstrap program and a kernel, the potential safety hazard of system equipment caused by a method of starting while checking or checking after starting is overcome in advance.

The invention relates to a method for confirming the storage service life of a resin adhesive and a device and electronic equipment. The method comprises the following steps: by improving an Arrheniusmodel, establishing a secondary relationship of a logarithm of an acceleration service life of a resin adhesive and a temperature reciprocal so as to obtain a relationship of the acceleration servicelife and the temperature of the resin adhesive; calculating an actual storage service life of the resin adhesive at a normal storage temperature. By adopting the method, relatively high fit goodnessof service lives and temperatures can be achieved, and the storage service life of an epoxy resin adhesive is relatively accurate; a nonlinear relationship of temperatures and acceleration service lives can be widened, data fitting can be carried out through an improved model, the problem that the relationship of high secondary items of temperatures and service lives cannot be reproduced by usinga conventional Arrhenius method is solved, and service life estimation errors can be reduced; calculation can be updated at different temperatures, and compared with a conventional method, the methodis not only applicable to service life pre-estimation on the resin adhesive at a low temperature, and is also applicable to situations of high-temperature service life estimation.

The invention discloses a spinning forming method for a W-shaped metal sealing ring. The method comprises the following steps: S100, the height of an annular blank of the W-shaped metal sealing ring is calculated according to the axial section of the W-shaped metal sealing ring, and the annular blank with the height is prepared; S200, an annular waist groove part is machined in a spinning mode along the radial center of the annular blank prepared in the step S1, and the waist groove part is sunken in the direction where the axis of the annular blank is located; and S300, the parts, located on the two sides of the waist groove part, in the annular blank are subjected to spinning machining, and the W-shaped metal sealing ring is formed. The W-shaped metal sealing ring which is flat, complete and uniform in spinning can be obtained with the method; and a supporting ring is stuffed into the waist groove part of the annular blank, so that the strength of the edge of a second mold core is improved, and the technical problem that the annular blank is difficult to position is effectively solved.

The invention relates to a method for designing a stabilizer of an uncertain power system based on interval time lag influence, which comprises the following steps of: constructing a new augmentationvector and a multiple integral LyapunovKrasovskii functional, then introducing a double Wirtinger inequality to estimate a functional derivative on the basis of a single Wirtinger integral inequality,and adopting a convex combination method, so that a system robustness stability criterion with lower conservative property is obtained. On the basis, a memory-free and memory feedback controller of the system is designed, and a step linearization method is applied to obtain a stabilizer existence condition based on a strict linear matrix inequality. Finally, simulation analysis verifies that themethod provided by the invention effectively enlarges the stable operation region of the power system, and the designed controller has better control performance.

The invention provides a text emotion analysis method and device, electronic equipment and a non-transient storage medium, and relates to the technical field of artificial intelligence, and the methodcomprises the steps: obtaining a to-be-analyzed text and a context text; performing word segmentation processing on the context text and the to-be-analyzed text to obtain a first word segmentation set and a second word segmentation set; converting the first word segmentation set and the second word segmentation set into a first feature vector set and a second feature vector set respectively; multiplying a forgetting gate in the text emotion analysis model by the first feature vector set to obtain a first product; multiplying an input gate in the text emotion analysis model by the second feature vector set to obtain a second product; calculating the sum of the first product and the second product as the unit state of the to-be-analyzed text; and applying the unit state of the to-be-analyzed text to an output gate of the text emotion analysis model, and outputting an emotion identifier of the to-be-analyzed text. According to the technical scheme, the emotion analysis accuracy can be improved.

The invention discloses a chemical reaction conversion rate prediction method and system based on deep learning and a medium, and the method comprises the steps: selecting a reactant type A which has the greatest influence on the chemical reaction conversion rate from the types of reactants participating in a chemical reaction, carrying out word segmentation and feature extraction on reactants of the reactant type A and a chemical reaction formula R corresponding to the chemical reaction, and then solving deep characterization information Ta of the reactants of the reactant type A, deep characterization information Tr of the chemical reaction formula R corresponding to the chemical reaction and relation information Tm of the reactants and the reaction formulas through an attention mechanism; and finally, fusing the deep characterization information Ta of the reactant of the reactant type A, the deep characterization information Tr of the chemical reaction formula R corresponding to the chemical reaction and the relation information Tm of the reactant and the reaction formula by using a wide learning system, and predicting the conversion rate of the chemical reaction. The prediction precision of the chemical reaction conversion rate is greatly improved.