72results about How to "Solid theoretical foundation" patented technology

The invention relates to a compression method of the mass energy consumption information in an intelligent building, which comprises the following steps that: (1) the data on the monitoring end in the building are collected, and each record of the recording points of the collected data is one triple group (the tagid, the time and the data); (2) when the tense attribute value of some recording point is changed, the corresponding new data are stored into the first stage of buffering, then the next task is directly carried out, and the new data are stored into files through a background data storage thread; (3) the second stage of buffering is established; (4) a historical data compression region is arranged, and the data in a buffering region are transferred to a disk file after being compressed in the compression region; (5) the data files are organized by adopting the form of a file queue, and the next file in the file queue is started after the file is fully stored; and (6) the compressed data are stored into a storer and supplied to the required client to call after the compression is finished.

The invention discloses a milling flutter recognition method based on variation modal decomposition and energy entropy, and belongs to the technical field of machine tool machining flutter recognition. The milling flutter recognition method comprises the following steps of S1, establishing a VMD mathematical model; S2, establishing a mathematical model of the energy entropy; S3, conducting three sets of milling machining experiments representing three cutting states, including stable cutting, a weak flutter and a severe flutter, and obtaining three sets of milling force signals through a dynamometer; S4, conducting FFT analysis on the three sets of milling force signals, and proving that the three sets of milling force signals represent the states of stable cutting, the weak flutter and the severe flutter respectively; S5, determining the number K of optimal modals of VMD decomposition and a penalty factor alpha through a VMD parameter automatic selection method based on a kurtosis value; S6, solving instantaneous frequencies of multiple IMF, and determining a milling flutter characteristic frequency band; S7, adopting a hammering experiment to obtain the modal of a knife; S8, extracting a flutter characteristic vector of each IMF based on the energy entropy. According to the milling flutter recognition method based on the variation modal decomposition and the energy entropy, the VDM decomposition effect is improved, and automatic flutter recognition is achieved.

The invention discloses a fatigue lifetime measuring method for anisotropic material structural parts and belongs to the field of service lifetime analysis and measurement for engine turbine blades. The objective of the invention is to overcome the problem of fatigue life measurement in different crystal orientations for anisotropic materials and structural parts thereof. According to the principles of the fatigue lifetime measuring method, a load condition in a load coordinate system is converted into a load condition in a material coordinate system through coordinate transformation; and based on mechanisms of fracture of the anisotropic materials, a novel form of Hill equivalent strain is provided, and a local strain method in a uniaxial form is expanded to conditions of complex strain. A load at any orientation can be uniformly allowed to be equivalent to a specific crystal orientation to obtain an equivalent load by the fatigue lifetime measuring method. A fatigue lifetime measuring model is built according to material parameters and the equivalent load in the orientation. The fatigue lifetime measuring method is advantageous in that: the fatigue lifetime of the anisotropic materials and the structural parts thereof at any orientation can be accurately measured by only using the material parameters and the equivalent load in the specific crystal orientation, and measurement precision is high.

The invention discloses a characterization method of material fatigue, creep, and fatigue-creep interaction service life, and belongs to the field of service life prediction of aero-engine critical materials. The characterization method is used for solving service life characterization and prediction problems of materials under low cycle fatigue, creep, and fatigue-creep interaction conditions. According to the principles, a power function form service life prediction method non-linear behavior characterization capacity is established via fatigue-creep interaction, low cycle fatigue, and creeptests of materials at different holding time, and obtaining of effective holding time and normalization dimensionless service life via normalization calculation method. The characterization method iscapable of realizing accurate characterization of service life of materials under low cycle fatigue and fatigue-creep interaction conditions, and especially, consideration and accurate prediction ofcreep service life can be realized. The advantages of the characterization method are that consideration of both physical mechanisms and model implementation convenience is realized, and material lowcycle fatigue, creep, and fatigue-creep interaction service life characterization and prediction problems are solved effectively.

The invention provides a method for getting expert system knowledge based on a support vector machine. A rule extracting process based on the support vector machine comprises data preprocessing, clustering of support vectors, extracting and simplifying of a super-rectangular rule, and sample identifying based on the rule. The method has the advantages that after the feature extracting and the rule simplifying are carried out, the extracted rule is more concise and is easier to explain; when a clustering and distributing matrix is calculated, only the support vectors are clustered and identified, so the calculation amount is greatly reduced; the rule extracting method is advanced, and the diagnosing and identifying rate is higher; the support vector machine is an emerging classifying technique for data mining, and has a solid theoretical foundation and a favorable generalizing performance; and the method can be used for effectively getting the rule of the expert system knowledge, and the bottleneck of dynamic getting of the expert system knowledge is broken through.

The invention relates to the field of slope stability calculation methods, in particular to a striping method capable of accurately calculating an inter-striping force inclination angle and a slope stability safety coefficient. A striping method for calculating an inter-striping force inclination angle and a slope stability safety coefficient comprises the following steps: S1, calculation parameters are determined according to slope survey data, S2, a sliding body of a slope is divided into a plurality of vertical stripes, S3, the inclination angle of inter-striping acting force is calculated,and S4, the slope stability safety coefficient is calculated through a semi-accurate striping method or an accurate striping method. The invention discloses a striping method capable of accurately calculating an inter-striping force inclination angle and a slope stability safety coefficient. The bottleneck that the existing slitting method depends on the assumed direction or position of the inter-slitting force to solve the statically indeterminate problem is broken through; based on the Mohr-Coulomb criterion, the function relationship between the ratio of the shearing force to the normal force between the strips and the sliding surface inclination angle, the shearing strength parameter, the strip physical property parameter and the load is theoretically deduced, so that the statically indeterminate strip division problem obtains a statically determinate solution.

The invention provides an urban traffic health indicator system evaluation method based on the complex network theory. The method mainly comprises the following steps: A: establishing a reliability indicator R of an urban traffic network; B: establishing a brittleness indicator B of the urban traffic network; C: establishing an elasticity indicator S of the urban traffic network; based on obtainedactual urban traffic operation data, importing seepage analysis to calculate the size of a functional sub-group of the urban traffic network under a given threshold, and establishing the reliabilityindicator R of the urban traffic network; mining a key road in the urban traffic network, analyzing a road set collapsing the functional sub-group of the urban traffic network to a certain proportion,and establishing the brittleness indicator B of the urban traffic network; and finally, establishing the elasticity indicator S of the urban traffic network through a whole process of generation-evolution-dissipation. The establishment of the urban traffic health indicator system can provide a support for the assessment of the actual operation state of the urban traffic, the development of targeted traffic management measures, and the improvement of the urban traffic health.

The invention discloses an irrigation and drainage method for improving a soda alkali-saline paddy field in a field steeping period, and relates to a method for improving a soda alkali-saline paddy field. The method aims at solving the problems that when a soda alkali-saline paddy field is improved in the prior art, the alkali-saline removing effect is poor, and the rice yield of the soda alkali-saline paddy field is low. The method comprises the steps that 1, the soda alkali-saline paddy field is selected; 2, the land is leveled, and desulphurization gypsum is added according to the soil alkalisation degree; 3, manual irrigation and field steeping are carried out for the first time; 4, water raking and slurry mixing are carried out for the first time, stabilization is carried out for 24 h, and level drainage is carried out for the first time; 5, after first-time level drainage is finished, manual irrigation and field steeping are carried out for the second time; 6, after second-time manual irrigation and field steeping, water raking and slurry mixing are carried out for the second time, stabilization is carried out for 24 h, level drainage is carried out for the second time, and then the irrigation and drainage for improving the soda alkali-saline paddy field in the field steeping period are completed. According to irrigation and drainage method for improving the soda alkali-saline paddy field in the field steeping period, the alkali-saline removing effect is thorough, the rice yield is improved by 36-63%, and the irrigation and drainage method is used for improving the soda alkali-saline paddy field.

A combination preparation for remedying the gastroesophageal reflux disease (GERD) and the functional dyspepsia is characterized in that the prescription of the combination preparation consists of a proton pump depressor and a gastrointestinal power drug of itopride; the proton pump depressor is selected from one of a Pantoprazole, a Omeprazole, a Esomeprazole, a Lansoprazole, a Rabeprazole, a Tenatoprazole and a Leminorazole, wherein the Pantoprazole is preferential, and at the same time the neutral form of the basic salt of the proton pump depressor is also included, such as Na^plus, Mg^2plus, Ca^2plus, K^plus or Li ^plus salt and a pure optical stereoisomer of the proton pump depressor or an active metabolite of the proton pump depressor; the gastrointestinal power drug is the itopride and a ramification of the itopride or one of the medicinal salts of the itopride; in the combination preparation, the weight ratio of the Pantoprazole and the itopride is 2 to 5 to 2 to 7. The invention has important affect for remedying the gastroesophageal reflux disease and the functional dyspepsia, and the preparation method of the invention is simple and convenient; the cost is low; the invention is fit for being orally taken by the patient; the invention has good conformance performance, high curative effect, low recrudescence rate and little adverse reaction.

The invention provides a computing method for neighboring underground pipeline additional load caused by ground in-out type shield construction. In order to solve the problem of the magnitude of the neighboring underground pipeline additional load caused by the special working condition, and provide a formula foundation for site construction and theoretical research in future, according to the computing method, a brand-new soil body additional stress computational formula caused by front additional thrust, shield shell friction force, additional grouting pressure and soil body loss is provided by taking into account an included angle beta (namely tunnel buried depth change) of a shield axis and a horizontal plane; when the additional stress of a pipeline is computed, a plurality of points on the same cross section are taken to compute corresponding additional stress values respectively, then the additional stress values are averaged to obtain the additional stress of the pipeline on the cross section, and finally the projection of a pipeline arc is multiplied at the position of the axis horizontal plane to obtain the additional load of the pipeline.

The invention relates to a predication method for spray-stopping stratum pressure of an oil well. The method is characterized by including the following contents: 1) establishing a typical flow oil well production system node analysis model; 2) calculating oil and water two-phase relative permeability Krw, Kro and a zero dimension fluid collection index JDL, and obtaining an oil and water two-phase relative permeability curve and a zero dimension fluid collection index curve; 3) on the basis of a fluid collection index PI0 when a water content of an oil well is 0 and the zero dimension fluid collection index curve, calculating different water contents of nodes in the well and inflow curves in different stratum pressure conditions; 4) on the basis of the minimal output pressure PDSCmin needed by crude oil in the mouth of the well, calculating outflow curves of the nodes in the well in different water content conditions; and 5) on the basis of the inflow curves and the outflow curves of the nodes in the well, determining a critical spray-stopping state of the oil well, and calculating the critical spray-stopping stratum pressure Pc of the oil well.

The invention discloses an MRTD (Minimum Resolvable Temperature Difference)-based gas infrared imaging detection system performance evaluation method, belonging to the field of gas detection technologies. The method comprises the steps of: firstly, determining a calculation analytic expression of the radiant exitance difference of a target and the background; then according to the analytic expression, respectively deducing and calculating the radiant exitance difference of the target and the background by using MRTD (Minimum Resolvable Temperature Difference) and MRGC (Multi Row Graphite Core) testing devices and methods; secondarily, enabling the radiant exitance differences of the two conditions to be equal, and calculating the gas transmittance; finally, resolving a performance evaluation parameter MRGC value of a gas infrared imaging system through the gas transmittance. The calculating method not only fully combines the gas infrared absorption characteristic imaging factor to realize the temperature resolving power of the system and the comprehensive evaluation of the space resolving ability, but also avoids the building and laboratory operation processes of a complicated testing system, and is firm in theoretical basis, thus having extremely strong application and popularization values.

The invention discloses an automatic driving automobile driving behavior reliability index evaluation method, and the method comprises the following steps: planning an automatic driving automobile driving path according to an automatic driving function testing rule of an automatic driving automobile; according to unreliable driving behaviors generated in the driving process of the automatic driving automobile, obtaining driving behavior data of the automatic driving automobile from a starting point to a terminal point in the driving path of the automatic driving automobile; calculating a reliability index value according to the driving behavior data, wherein the reliability index value comprises a first-level index and a second-level index; and calculating the reliability of the driving behavior of the autonomous vehicle according to the calculated reliability index value and a preset corresponding weight. According to the method, the reliability of software and hardware of the automatic driving automobile does not need to be analyzed, the reliability evaluation result of the automatic driving automobile can be obtained only by calculating and analyzing the driving behavior data ofthe automatic driving automobile, the reliability analysis efficiency of the automatic driving automobile is improved, and the reliability of the whole automatic driving automobile is guided and improved.

The invention discloses a method for determining inherent chemical components of a traditional Chinese medicinal material. The method comprises the following steps: a. determining a dipole moment by Fourier transform infrared spectroscopy (FTIR) when molecules vibrate in an amorphous component of the traditional Chinese medicinal material; b. determining a crystal component of the traditional Chinese medicinal material by powder x-ray diffraction (PXRD); c. determining elements and content of the traditional Chinese medicinal material by x-ray fluorescence (XRF); and d. characterizing the inherent chemical components of the traditional Chinese medicinal material. The method can overcome the one-sidedness caused by separate application of the existing analysis techniques, simplify a plurality of inconvenience such as complicate pretreatment of samples and the like, can help conveniently and rapidly determine and characterize all inherent chemical components of the tested traditional Chinese medicinal material. The method is also suitable for determining and characterizing all inherent chemical components of the traditional Chinese medicinal materials which are planted according to good agricultural practices (GAP) and can be made into powdered samples, and identifying whether the medicinal material is genuine or fake. The method can help avoid the disadvantages of analytical one-sidedness and non-objectivity caused by a single method used previously, thus the inherent chemical components of the traditional Chinese medicinal material which are determined and characterized by the method have more complete, thorough and objective characteristics. Meanwhile, the method has the advantages of simple sample preparation, fast determination speed, good reproducibility and the like.

The invention provides a plant oil classifying method based on combination of a GC-MS technology and a PSO-SVM algorithm. The method comprises the following steps: using the GC-MS technology to obtain the qualitative and quantified results of fatty acids in six different kinds of plant oils and establish the fatty acid fingerprint database of the plant oils; adopting the POS optimal parameter-based SVM classification algorithm to classify samples and establish a PSO-SVM model; and substituting data to the PSO-SVM model, and determining the class of the samples according to a calculation result. The classifying method has the advantages of simple pretreatment operation, high sensitivity and high accuracy.

The invention relates to a device for distinguishing ureters and blood vessels. The device comprises a handle and a clamping body arranged at the front end of the handle, the clamping body comprises clamping handles and a clamping head, the upper part and the lower part of the outer side of the clamping head are respectively provided with the clamping handles, the inner side of the clamping head is provided with arc-shaped rubber pads which fit the clamping head in a up-down corresponding manner, and detection units are correspondingly arranged in the rubber pads respectively; a display screenand a switch are arranged on the handle, and a power supply and a processing unit are arranged in the handle. The invention also relates to a method for distinguishing ureters and blood vessels. Themethod comprises the following steps: a tube to be tested is clamped; a single-chip microcomputer controls a first light source to sequentially emit incident light, a first photoelectric detector detects the light intensity of reflected light, and a second photoelectric detector detects the light intensity of transmitted light; the obtained light intensity is converted into a digital signal and sent to the single-chip microcomputer; and the single-chip microcomputer analyzes and processes the light intensity, judges that the tube to be tested is a blood vessel or a ureter, and performs calibration. The invention realizes accurate discrimination of blood vessels and ureters in a human body.

The invention discloses a text classification method based on CNN and Bi-GRU, and the method comprises the following steps: 1, carrying out the convolutional neural network modeling of text data, andobtaining a first text feature expression containing local implicit information; 2, performing Bi-GRU neural network modeling on the text data to obtain a second text feature expression containing sequence information of the whole sentence in two directions; and 3, performing feature fusion on the two text feature expressions obtained in the step 1 and the step 2, and performing classification byusing an LSSVM classifier. According to the method, not only are sentence local features and context semantic information captured, but also more diversified and richer feature expressions of the textare obtained by fusing two different text feature expressions, and the classification accuracy is further improved.

The invention discloses an artificial influence weather operation effect evaluation method, which utilizes a statistical test method to provide an operation effect evaluation method for artificial influence weather operation by integrating different influence factors on the basis of objective observation data and strict reliability analysis, and has a solid theoretical basis. According to the method, a regional historical regression analysis method is adopted for testing the efficacy and accuracy which are higher than those of a sequence test method and a non-paired rank sum test method, and the result has higher credibility by applying significance test for many times; according to the method, the Monte Carlo simulation random test is used for analyzing the influence of the natural change rate on the statistical result, so that the evaluation of the operation effect is more objective; according to the method, the specific influence of the artificial influence weather is quantitatively analyzed through the entropy weight method and the first-level fuzzy comprehensive evaluation method, so that the artificial influence weather effect is visualized, and the practicability and readability of the result are improved.

The invention discloses a method for obtaining the J resistance curve of a ductile material by an I type crack elastoplasticity theoretical equation. The method comprises the following steps: performing tensile or bending test on an I type through crack sample to obtain the P-h curve of the sample, substituting the P-h curve into the elastoplasticity theoretical equation to obtain the real-time crack length and J integral of the sample corresponding to any loading point, and performing crack propagation correction on the J integral result by an incremental technology to obtain the J resistancecurve of the material. The method avoids an error caused by the approximate solution of the plastic factor eta p during the calculation of the J integral by using traditional test methods, and is convenient to carry out the fracture toughness test of the ductile material at a high temperature, under irradiation or in other special environments.

The invention discloses a model generation method and system, a semantic recognition method and system, equipment and a storage medium. The model generation method comprises the following steps: obtaining historical data; performing word segmentation and labeling on each piece of historical data to obtain a corresponding first historical sequence; performing character-level feature extraction on each first historical sequence by adopting a CNN to obtain a second historical sequence; performing word-level feature extraction on each second historical sequence by adopting LSTM to obtain a third historical sequence; and performing model training on the third historical sequence by adopting a conditional random field learning algorithm to determine parameters of the conditional random field model. According to the model generation method and system, the semantic recognition method and system, equipment and the storage medium provided by the invention, compared with the traditional thought of template matching, the training thought of fusing the traditional conditional random field CRF and deep learning is more flexible and covers more users, and the user experience and click conversionrate of voice related services can be improved.

The invention relates to a static state optimization method for a DC power grid line transmission power. The method comprises steps that 1, a DC power grid rack model is established; 2, a network equalization optimization principle for the DC power grid line transmission power is determined; 3, a static state optimization mathematics model for the DC power grid transmission power is established; and 4, an optimization mathematics model is solved. Through the method, power transmission requirements between each power source and a load can be distributed to each transmission line and a converter station, the transmission power can realize optimal distribution along DC lines, power static state distribution optimization in the whole DC power grid scope is realized, various power source, power grid and user requirements can be satisfied, and DC power grid advantages can be realized.