61 results about "Homotopy analysis method" patented technology

A motion analysis device includes two posture angle sensors attached to a measurement object at locations distant from each other, a data acquisition section, a posture angle correction section, and a deformation amount calculation section. The data acquisition section acquires data of a first posture angle and a second posture angle respectively detected by the posture angle sensors. The posture angle correction section corrects a difference between the first posture angle and the second posture angle after starting a motion of the measurement object in accordance with a difference between the first posture angle and the second posture angle before starting the motion of the measurement object. The deformation amount calculation section calculates a deformation amount of the measurement object based on a difference between the first posture angle and the second posture angle corrected by the posture angle correction section.

A motion analysis method includes calculating a change in an amount of inertia of a region attached with an inertial sensor during a swing using an output of the inertial sensor, and identifying a maximum value of the amount of inertia during the swing to compare the maximum value and the amount of inertia at an impact with each other. A deceleration timing during the swing of the region (the grip of the sporting equipment) attached with the inertial sensor is identified, and the quality of the swing can be evaluated.

The invention relates to a lower-bound limit analysis method of bearing capacity considering rock translation and rotation effects at the same time, and belongs to the technical field of rock slope stability analysis. According to the method, a rigid block unit is scattered as a geometry system of a rigid rock and a structural plane, the normal force, shearing force and bending moment of the structural plane are used as unknown quantities, a static permission stress field satisfying an equilibrium equation considering the translation and rotation effects of the rigid block unit, structural plane shear yield conditions, structural plane tensile yield conditions, structural plane rotational yield conditions and static boundary conditions is constructed, an overload coefficient is used as a target function, and a lower-bound linear mathematic programming model is built; the linear mathematic programming model is solved by means of an interior point algorithm, a strength reserve coefficient is solved by means of an iterative method at the same time, and the lower-bound solution and corresponding yield area of the overload coefficient or the strength reserve coefficient of the jointed rock slope are acquired. The method has the advantages that the concept is clear and the computational accuracy is high, and the method can be applicable to bearing capacity analysis of translational or rotational failure of the jointed rock slope.

The invention relates to an upper-bound limit analysis method of ultimate bearing capacity of rock slope considering rock translation and rotation effects at the same time, and belongs to the technical field of rock slope bearing capacity analysis. According to the method, based on a plastic upper-bound limit analysis theory, by means of multiple freedom degree rigid block unit discrete jointed rock slope, the translational speed and rotational speed of the rigid block unit centroid are used as unknown quantities, the translation and rotation mechanical effects of rocks are considered at the same time, the overload coefficient of the slope is used as a target function, and plastic flowing conditions satisfying shear failure, tensile failure and rotational failure of a structural plane are constructed; then combined with a virtual work principle and speed boundary conditions, a linear mathematic programming model for working out the ultimate bearing capacity of the jointed rock slope is built, the linear mathematic programming model is solved by means of a simplex method, a strength reserve coefficient is solved by means of an iterative method at the same time, and finally the upper-bound solution and corresponding failure mechanism of the ultimate bearing capacity of the jointed rock slope are acquired. The method has the advantages that the concept is clear and the computational accuracy is high.

The invention aims to provide a data buried point analysis method, equipment and system. The method comprises the following steps: determining a changed configuration content according to newly acquired configuration version information, and carrying out buried point definition and format definition of a delivery log on the basis of events on a page; verifying an acquired delivery log according tothe defined format of the delivery log, and obtaining a verified delivery log; parsing the changed configuration content and the verified delivery log so as to extract a session context identifier, and aggregating the session context identifier according to a preset aggregation rule to get an aggregation result; and determining an exception object based on the session context identifier and the aggregation result. Therefore, the tedious processes of data cleaning and statistical analysis at the later stage are greatly reduced, and the working efficiency is improved; and besides, intelligent and more automatic statistical analysis and accurate user behavior tracking are realized, and real-time visual playback can be carried out on user behaviors, thereby improving user experience.

The invention discloses an intelligent Internet of Things platform, which is characterized in that a protocol analysis engine performs protocol analysis on data uploaded by Internet of Things equipment of various protocols of an access platform, the protocol analysis comprises general protocol analysis and self-defined protocol analysis, and the general protocol analysis is performed according toan analysis method of a general protocol; the self-defined protocol analysis comprises the following steps: setting a protocol analysis self-learning model, and automatically generating a protocol analysis method according to an acquired self-defined protocol; the rule engine realizes separation of service logic and service rules and performs unified centralized management on the service rules; the storage engine performs classified storage on the data analyzed by the protocol analysis engine; the message transmission engine is used for transmitting and sending messages among the components ofthe platform; the log analysis system constructs a set of centralized log system; the automatic monitoring alarm system is constructed by the automatic monitoring alarm system. According to the invention, accessed hardware equipment can be managed in a unified manner, a data transmission protocol is identified, and sensors are controlled in a unified manner based on a protocol analysis engine.

The invention discloses a small interference oscillatory stability decomposed model analysis method for an electric power system. Decomposition calculation is carried out on mode analysis of common calculation residual error Ri so as to realize a model analysis calculation result with clear physical significance. The small interference oscillatory stability decomposed model analysis method comprises the steps of: firstly, measuring stable data and static data of the electric power system; and then respectively calculating a channel factor, a reconstruction factor and a participation factor toobtain model analysis of the residual error R1 for decomposing a calculation result, wherein based on the decomposed calculation result, the internal principle of influencing the damping by a controller is clearly disclosed so as to realize the adjustment of an additional damping controller and further effectively inhibit the low-frequency oscillation of the electric power system. The small interference oscillatory stability decomposed model analysis method can clearly detailedly give that how an appointed controller or device influences the electromechanical oscillation model of the appointed electric power system, thereby providing guidance with clear physical significance for the small interference stability analysis and the control design.

The invention discloses an improved modal analysis method of power distribution network harmonic resonance. The improved modal analysis method comprises the following steps that: a resonant frequency is determined through using a spectrum analysis method; the eigenvalue matrix of a node admittance matrix under the resonant frequency is obtained; the eigenvalues of the node admittance matrix are sequenced according to an ascending order, and the locations of the eigenvalues are recorded; and the first m minimum eigenvalues are selected as the feasible solutions of critical modes under the resonant frequency, critical right eigenvectors corresponding to each feasible solution are determined, the maximum right eigenvalues and the positions thereof of the critical right eigenvector feasible solutions can be obtained, and the positions are the feasible solutions of a highest excitation node. The improved modal analysis method of the invention has the advantages of high computational efficiency and accurate positioning of the highest excitation node, and the like, and is more suitable for the harmonic resonance analysis of a power distribution network.

The invention discloses a loess landslide type and sliding mode analysis method based on the insar multi-dimensional deformation information. The method comprises the following steps: 1, acquiring a filtered insar differential interference diagram through data acquired by t SAR sensors; 2, carrying out phase unwrapping on the filtered insar differential interference diagram, geocoding and samplingto the same coordinate grid and spatial resolution; 3, unwrapping an interference pattern under a geographic coordinate system, calculating a multi-dimensional surface deformation rate and acquiringa multi-dimensional surface deformation time sequence; 4, based on the multi-dimensional surface deformation rate and the multi-dimensional deformation time sequence, carrying out the landslide deformation mechanism analysis and determining the type and the sliding mode of the landslide through combining remote sensing images with a topographic map. According to the method, the insar technology isadopted for loess landslide type and sliding mode analysis, wherein only SAR images, remote sensing images and the topographic map of a research area are required. Therefore, the method is high in efficiency and accuracy. The workload of the outdoor operation is greatly reduced. The method is suitable for the landslide research in the dangerous area, and provides an important technical support for the landslide disaster prevention and reduction of the loess landslide.

The invention relates to a control analysis method for inverters in a grid-connected test power supply, and belongs to the technical field of electronic power. The control analysis method for the inverters in the grid-connected test power supply comprises the following steps that (1) the topological structure of the inverters in the grid-connected test power supply is determined; (2) the model of an inversion circuit is constructed; (3) the control strategy of the inversion circuit is determined; (4) quasi PR control analysis is performed; (5) the transfer function of a quasi PR controller is discretized, modeling of the discretized PR controller is performed through Simulink and then various control parameters of the inverters are calculated; and (6) a 30KW hardware-in-the-loop grid-connected test power supply dual-core control experiment platform is established based on dSPACE and the correctness of the control model is verified. According to the method, PR control is adopted, and the specific frequency can be accurately tracked by PR control in comparison with PI control so that the gain of the frequency is increased and the steady state error of PI control is eliminated.

The invention discloses a target sentiment analysis method and system based on an attention gated convolutional network, and the method comprises the steps: step 1, inputting a given context word vector and a corresponding target word vector, and enabling the given context word vector and the corresponding target word vector to serve as inputs for training; step 2, performing multi-head attentionmechanism interaction by utilizing the context words and the context sensing target words; step 3, enabling the sentiment feature vectors cintra and tinter generated by two channels to respectively pass through a gating convolution mechanism to generate a context word representation ai and a context word representation ui with context perception target word representations; step 4, pooling the emotion feature oi, and selecting the most representative feature; step 5, performing full connection on the pooled feature word vectors, and then performing classification through a Softmax classifier;and step 6, training and updating the attention gated convolutional network model by minimizing the cross entropy loss function. The accuracy can be effectively improved, the convergence time can be shortened, and the practicability is higher.

The invention discloses a standardized automatic analysis method for a neonatal brain function, which comprises the following seven continuous standard steps: S1, neonatal medical history data are acquired; S2, signal connection and signal quality are confirmed; S3, upper and lower boundaries of an amplitude integrated electroencephalogram are determined, background pattern classification is carried out, and burst inhibition detection is carried out; S4, a sleep awakening cycle is recognized; S5, suspicious areas in the electroencephalogram are recognized; S6, the symmetry of the amplitude integrated electroencephalogram is evaluated; and S7, the long-term trend of the amplitude integrated electroencephalogram is described. By adopting seven continuous steps, standardized integration is carried out on the neonatal brain function analysis methods, automatic analysis is realized at the same time, the output result provides reliable medical data for doctors, and the efficiency and the accuracy are improved.

The invention relates to an emotion analysis method and system. The method comprises: using hidden layer outputs of the context embedding matrix and the target word embedding matrix as calculation parameters; and calculating attention mechanism coefficients of the context and the target word based on an attention mechanism, and performing weighted summation on the context vector and the target word vector according to the attention mechanism coefficients to obtain a new context vector and a new target word vector. Compared with the prior art, the influence coefficient between the target word and the context is calculated by using the attention mechanism, the importance of different words in the target word is distinguished, and the accurate analysis of the emotion of the target word is realized.

The invention relates to a Chinese semantic structure and finely segmented word bank combination based emotional analysis method. The emotional analysis method comprises: 1) inputting a to-be-tested text at least consisting of a statement into a computer system; 2) performing word segmentation processing on each statement of the to-be-tested text and marking emotional words and other words in each statement; 3) performing matching on the to-be-tested text subjected to word segmentation processing to obtain a semantic mode of each semantic unit; and 4) correspondingly converting the semantic mode of each semantic unit of the to-be-tested text to an emotional value, and performing accumulation on the emotional values of all the semantic units in the text to obtain an emotional value of the to-be-tested text. According to the method, the emotional words, connective words, transitional words and the like are segmented from a non-structured text; according to actual arrangement of the words, sentence patterns are matched to obtain the emotional values of the semantic units; and the emotional value of a sentence is comprehensively calculated according to the emotional values of the semantic units to achieve the purpose of quantizing the emotional value of a financial news comment sentence.

The invention relates to a chromatographic analysis method. According to the chromatographic analysis method, a gas chromatograph and a sampling device are used, wherein the sampling device is used for providing fluid to be detected to the gas chromatograph; the gas chromatograph comprises a first chromatographic column, a second chromatographic column, a damping column and an FID detector; the sampling device comprises a ten-way valve and a six-way valve; the six-way valve can be selected to be in a state I and a state II; the ten-way valve can be selected to be in a first state and a second state; and the chromatographic analysis method comprises the steps of sample gas quantification, detection and back flushing. The chromatographic analysis method has the advantages that the dosage of carrier gas is saved, the accuracy of the sample gas separation is improved, the accuracy of the sample gas detection is improved, the life of the chromatographic columns is prolonged, and two different substances of the same sample gas can be measured at the same time, so that the working efficiency is greatly improved.

The invention discloses an emotion analysis method based on regional CNN-LSTM. The method comprises the following steps of building a regional CNN-LSTM model; constructing word vectors of words in a text, and representing the text by a sequence of the word vectors; performing regional module decomposition according to sentences in the text or phrases in the sentences; taking regional modules afterthe decomposition in the previous step as input primitives of a CNN, and taking results obtained after text word vector matrixes of regions are subjected to a convolution layer and a maximum poolinglayer as input vectors of an LSTM layer; inputting information of the regional modules obtained in the previous step into the LSTM layer according to an occurrence sequence of the regional modules inthe text, so as to obtain a text vector of the whole text; and inputting the text vector obtained in the previous step into a linear decoder, and carrying out prediction of an emotion value Valence and an excitation value Arousal so as to obtain a VA emotion value result.

An adult gait extraction and anomaly analysis method based on Kinect mainly comprises the following steps of: (1) collecting adult traveling videos, and solving and obtaining adult traveling gait space-time parameters based on foot end track analysis and lower limb inverse kinematics; (2) performing deduction based on the lower limb inverse kinematics to calculate Z-Y-X Euler angles and step lengths of hip joints, knee joints and ankle joints of an adult; (3) calculating the maximum value, the minimum value, the mean value and the variance of each joint angle in each set of data to obtain datacomprising the joint angles, the step lengths and the gait time parameters; and (4) employing a K-S single simple to inspect and obtain distribution conditions of the parameters, and combining the Pauta criterion to obtain the normal ranges of the parameters. On the basis of collection of adult gait parameters, small samples are analyzed based on the related knowledge of the probability and mathematical statistics to obtain the normal ranges of the parameters and provide reference for doctors' clinical analysis.

The invention provides an equipment efficiency evaluation result rapid analysis method based on a meta-model. theThe meta-model technology is introduced into the weapon equipment combat effectivenessevaluation modeling and evaluation result analysis process; T; the method depends on an attack-defense confrontation simulation deduction system. Analyzing and assessing task requirements, constructing an efficiency assessment index system, designing a simulation experiment according to input and output indexes of the assessment index system, obtaining a training and testing sample data set of theefficiency assessment meta-model, and fitting sample data by adopting a BP neural network model improved by a particle swarm algorithm to obtain a simplified meta-model of the efficiency assessment problem meeting the precision requirement; A; and an extended fast Fourier transform global sensitivity analysis algorithm is used to evaluate the analysis efficiency problems and sort the analysis efficiency problems from large to small. The method is suitable for digital modeling of the efficiency evaluation problem, rapid analysis of the sensitivity of the efficiency evaluation index and miningof the key battle technical index influencing the battle efficiency of the equipment.

The invention discloses an image omics analysis method fusing traditional features and depth featuresThe method comprises the following steps: firstly, extracting the traditional features of a regionof interest, such as first-order features, shape features and texture features; secondly, performing feature selection on the extracted original feature set to remove redundant features; secondly, extracting depth features through a convolutional neural network model; and finally, the traditional features and the depth features are fused to realize classification of different groups. Compared withsingle use of traditional features or depth features, the method has the advantage that a better classification effect is obtained.

The invention discloses a shallow-buried shield tunnel ground uplift limit analysis method considering local failure of excavation face, belonging to the shield construction technical field. Theoretical model research is mainly based on the assumption of overall instability of excavation face, but the passive failure of excavation face caused by excessive supporting force has a gradual evolution process from local failure to overall instability. The phenomenon of local passive instability and failure of excavated face has been found in the existing numerical simulations. At present, the globalpassive instability hypothesis is limited to analyze the local passive failure mode, and the research on the development and instability mechanism of local passive failure is less. The method assumesthe failure mode of soil mass and presents a theoretical model. According to the theoretical model, the theoretical formula is deduced. A numerical 3D model is established to calculate the local instability ratio Eta and the ultimate supporting force sigma T, and the results are compared with the theoretical model. The limit support pressure obtained by the local instability model provided by theinvention is smaller, and is closer to the result obtained by numerical simulation.

The invention discloses a three-phase decoupling load flow calculation method for a weakly meshed distribution network based on a sequence component method, comprising the following steps of: (1) carrying out three-phase load flow modeling on the weakly meshed distribution network based on the sequence component method and realizing three-sequence decoupling; and (2) building a three-phase decoupling load flow calculation method for the weakly meshed distribution network based on the step (1), wherein the three-phase decoupling load flow calculation method for the weakly meshed distribution network is a loop analysis method based on roads. Thereof, the algorithm keeps the advantages of a forward-backward sweeping method facing to branches; the convergence of the algorithm is not affected by the loop and the loop has better algorithm. Simultaneously, after adopting the three-sequence decoupling, the node number of the system load flow calculation is reduced; the load flow calculation quantity is reduced; and the calculation efficiency is improved. Finally, the accuracy and better convergence of the method provided by the invention are tested through 6-busbar and 33-busbar tests; the stronger loop processing ability is also tested; and the number of iterations is reduced along with the increased closed loop.

The invention discloses a worm homologous analysis method and device. The method comprises the following steps of: extracting static features and dynamic features in a worm sample, wherein the dynamic features comprise network behavior features and an application programming interface API calling sequence; preprocessing the static features by utilizing the network behavior features to obtain a worm feature set; constructing a sensitive behavior feature library according to the API calling sequence; processing the worm feature set by utilizing a first homologous analysis algorithm so as to output a first probability distribution matrix; processing the API calling sequence and the sensitive behavior feature library by utilizing a second homologous analysis algorithm so as to output a second probability distribution matrix; carrying out weight adjustment on the first probability distribution matrix and the second probability distribution matrix to obtain a third probability distribution matrix; and obtaining a homologous analysis result according to the third probability distribution matrix. According to the method and device disclosed by the invention, the efficiency and correctness of the worm homologous analysis are improved.

The invention discloses an emotion analysis method based on structuring features. The emotion analysis method includes the steps of collecting Twitter text data; building a Twitter text database; collecting existing emotion polarity value dictionaries; manually establishing related auxiliary dictionaries; preprocessing the Twitter text database; defining an emotion score influence factor, extracting language features of information, and updating the value of the emotion score influence factor every time one language feature is extracted; calculating the emotion polarity values of the Twitter text data through the emotion polarity value dictionaries and the emotion score influence factor. According to the emotion analysis method based on the structuring features, it is avoided that in supervision methods, a large amount of marked data is required to train a classifier, and analysis and generalization are difficult; the CPU processing requirement, the internal storage requirement and the overhead for calculating training time are reduced.

The invention discloses a modal analysis method based on finite element modeling of an airborne active phased-array antenna. The method comprises the following steps: 1) according to structural parameters of the airborne active phased-array antenna, determining a geometric model file, and inputting parameters of the geometric model file into Ansys; 2) setting antenna material attribute data in the Ansys file; 3) setting unit type and size of a geometric model of the antenna; 4) automatically dispersing the geometric model of the antenna into multiple units, and dividing finite elements by adopting Ansys free grids; 5) giving constraint conditions of a finite element model of the antenna and determining a modal order to be extended of the finite element model; 6) computing natural frequency of each order of the finite element model of the antenna, and drawing mode of vibration and displacement cloud picture of each order of the finite element model of the antenna; 7) constructing an APDL (Ansys Parameter Design Language) macro document; and 8) directly generating the finite element model of the antenna. According to the method, a large amount of data cannot be required, and the method has the advantages of short modal analysis time, low cost and simple operation.

The present invention relates to an automated system of measuring and assessing an individual's improvement in motion (for example, a patient's recovery) through exercise performance. In an embodiment of the system of the present invention, two approaches for monitoring movement are introduced for quantifying an individual's performance. Both approaches consider the control population as their reference and consider the difference, or what is referred to in this application as the distance, between the individual's data and the control population as the measure of performance.

The invention discloses physiological electric signal entropy analysis method based on de-trending terms. The method can determine trend term components corresponding to different frequencies according to a one-to-one numerical relationship between cut-off frequencies and characteristic value parameters of trend terms, which is an advantage that wavelet analysis and ensemble empirical mode decomposition methods do not have. Secondly, trend terms of different components are superposed on the HRV signals under the circadian rhythm of a healthy person in the standard database to enable the HRV signals to present a single or mixed trend to a certain extent, then he trend terms of the HRV signals are eliminated by using a smooth prior method, and finally entropy values under different trends before and after detrending are respectively calculated by using approximate entropy and fuzzy entropy. The two entropy analysis methods can identify two groups of samples under different trend interferences, so that the two entropies have the advantage of trend or noise existing in processing signals, and another important way is opened up for nonlinear signal processing and characteristic value selection.

The invention provides a method for analyzing path cost of mobile self-organized network, comprising: step 1: a communication source node gets the multiplicative cost parameter, the additive cost parameter and the income of this time of communication when beginning the communication; step 2: the route which gets the most income surplus in the multi-jump route which can reach the destination node in the route list is calculated out as the data transmission rout in this time of communion; step 3: the multiplicative cost and the additive cost in the real transmission process is calculated, the route cost information is feed back to the communication source node to refresh the cost parameter in the route list. The invention has the advantages that the communication link of the mobile self-organized network has higher stability and the route cost has less consumption. Under different communication income, the invention can provide more appropriate route for data transmission, which simplifies the route choosing of the mobile self-organized network.

The present invention discloses a Givens iteration based Prony analysis method for low frequency oscillation, and the analysis method adopts an iterative method to reduce the number of orders of a signal model, and improve numerical stability of calculating a characteristic equation coefficient to solve an equation set. The method comprises the following steps: reading measurement data after filtering; using a singular value decomposition method to calculate the actual number of orders of the signal model; using a Givens iterative method to calculate the characteristic equation coefficient; calculating frequency and an attenuation factor; and calculating amplitude and an initial phase. According to the method disclosed by the present invention, by using a Givens iterative Prony method to analyze low frequency oscillation, the number of orders of the signal model maybe the actual number of orders of the signal model during extended Prony analysis, so that the singular of a coefficient matrix for using the characteristic equation coefficient to solve the equation set is effectively avoided, and the numerical calculation stability is improved; and under conditions of the number of orders of the signal model is the actual number of orders of the signal model, the method disclosed by the present invention has a higher calculated result of low frequency oscillation information than the result calculated by using the conventional Prony method.

The invention relates to welding process quality on-line monitoring analysis equipment and a monitoring analysis method thereof. The welding process quality on-line monitoring analysis equipment comprises a current sensor, a voltage sensor, a baroceptor, a temperature sensor, a gas flow sensor and a detector, wherein the detector is in communication connection with a key, a display and an interface; the interface is in communication connection with the current sensor, the voltage sensor, the baroceptor, the temperature sensor and the gas flow sensor; and the detector records data and output data of the current sensor, the voltage sensor, the baroceptor, the temperature sensor and the gas flow sensor. The monitoring analysis method is characterized in that self-learning is carried out; a limit line is generated; a welding gun begins to weld; the data acquired by the current sensor, the voltage sensor, the baroceptor, the temperature sensor and the gas flow sensor are transmitted to the detector; the detector transmits the data to a PC (Personal Computer); and the detector generates a report form. According to the invention, the detector is used to process the sensor data, and timely finds the problems in a welding process, so that the problems can be solved timely, and the welding quality can be improved; the current sensor, the voltage sensor, the baroceptor, the temperature sensor and the gas flow sensor can be mounted in the conventional welding system conveniently, so that the equipment modification cost is reduced; and the detector can freely filter the data and export different production forms, so that paperless production is realized.

Provided is an action analysis device (10), comprising an acquisition unit (11) which acquires sounds, and an analysis unit (12) which analyzes the frequency of the acquired sounds per predetermined time interval. The analysis unit (12) compares frequency distributions of frequency components within each frequency distribution which is a frequency analysis result, said frequency components corresponding to work sounds which are emitted in a predetermined task which a subject perform, and thereby generates information which denotes a change in time required for the predetermined task of the subject over elapsed time.