106results about How to "The results of the analysis are comprehensive" patented technology

The invention provides an identification method of transient state power-angle stable key transmission cross-section corresponding to an expected fault, belonging to the field of electric power systemdispatching automation. Based on a transient state power-angle stable quantitative analysis theory and method, namely extended equal-area criterion (EEAC), the method identifies the key transmissioncross-section corresponding to the expected fault to provide decision support for the electric power system dispatching operation and control. The method comprises the following steps: carrying out atime domain simulation in an expected fault scene based on the operation state, model and parameters of an electric fence; identifying a generator critical group with stable transient state power-angle by EEAC based on simulation track and calculating the participation factor of the generator; calculating the sensitivity to the cross-section components power change caused by the output of each generator in the generator critical group by a power flow sensitivity analysis method; and taking the sum of products of the participation factor in each generator of the generator critical group and corresponding sensitivity of the cross-section component as a judging indicator of the transient state stable key transmission cross-section corresponding to the fault.

The invention relates to a wearable human achilles tendon information collection and monitoring system. The wearable human achilles tendon information collection and monitoring system comprises a foot cover, a human achilles tendon information collector, a human physiological parameter collector, a micro vibrator, a data collection and control device, a user manual device, a mobile terminal and an open type cloud processing platform, all the collectors are arranged on the foot cover and each preferably adopts a corresponding soft textile sensor, relative achilles tendon signals and/or physiological parameters obtained through the collectors are subjected to primary process through the mobile terminal and sent to the cloud processing platform, analysis and process are conducted through a data analysis and feature extraction algorithm, a final report containing an analysis result is automatically generated, when a person has discomfort symptoms, the user can manually record the discomfort degree through the user manual device, changes of all indexes at this moment are compared through a timer axis, and a damage alarming waveform graph is set. According to the wearable human achilles tendon information collection and monitoring system, the analysis result is more comprehensive, detailed and accurate, and the wearable human achilles tendon information collection and monitoring system can be used by subjects extremely conveniently.

The invention discloses an automatic method for analyzing constitution and diversity of a bacterial community of a 16SrRNA gene. The automatic method comprises the following steps: in 16SrRNA sequencing data analysis process, by taking original sequencing sequence data as input, calling a standard analysis tool (such as Mothur and QIIME) of the industry, and performing visualization on data finally, thereby obtaining analysis results which are easy to analyze. The automatic method includes popular main analysis items at present, meanwhile analysis contents can be modularized, relatively rich and deep data mining analysis methods can be available, different analysis module contents can be combined according to different demands, and process procedures can be relatively reasonably arranged; and in addition, analysis errors caused by different sequencing depths can be eliminated, and the analysis results can be relatively comprehensive, accurate and reliable.

The invention discloses an accelerated degradation testing method for a nitrile rubber O-shaped sealing ring based on step stress, which includes the concrete steps: firstly, preliminarily testing the nitrile rubber O-shaped sealing ring; secondly, determining an accelerated simulation model and the stress level of a formal test; thirdly, testing step-stress accelerated degradation of the nitrilerubber O-shaped sealing ring; fourthly, arranging degradation data; and fifthly, building an accelerated degradation model for predicting the reliable life of the sealing ring. By means of applying the step stress, testing cost and testing time can be greatly reduced, and an example verification failure mechanism is unchanged. Evaluation of the degradation data is based on a plurality of degradation paths of a plurality of test specimens, errors caused by difference among the specimens can be greatly reduced, and the reliability of evaluation results is higher than that of aging life prediction.

The invention provides a liquid detection diagnosis system. The liquid detection diagnosis system comprises testing equipment and mobile equipment, wherein the testing equipment is used for carrying out detection and obtaining detection data, and is further used for converting the detection data into a two-dimension code; the mobile equipment is used for obtaining the two-dimension code, decoding the two-dimension code to obtain the detection data and displaying the detection data. According to the liquid detection diagnosis system, the utilization convenience and the privacy are improved. Preferably, the mobile equipment is used for transmitting the detection data to a cloud server; the capabilities of processing and analyzing the data by the cloud server are great and the efficiency is high; more analysis results can be provided and can be rapidly fed back to a user.

The invention discloses a voice analyzing method and system and a voice collecting front-end device that are applied to the field of communication technology. The method of the invention comprises: the data packet of a UDP odd port is obtained in the collected voice data packet and a RTCP data packet is obtained by judging the version number and the message type of the data packet of the UDP odd port; the RTCP data packet is decoded to obtain a voice link damage index and an SSRC mark; a voice link corresponding to the RTCP data packet is confirmed by utilizing the port of the RTCP data packet and the SSRC mark; the voice link damage index is utilized to analyze the corresponding voice link. The invention provides a voice analyzing system and a voice collecting front-end device. When the invention carries out high flow voice data analyzing, the analyzing process is simple, fast and accurate.

The invention provides an overall design phase safety analysis method for an advanced reactor. The method comprises the following step: in step S1, advantages and shortcomings of design are identified via a qualitative safety characteristic inspection tool and advices are given accordingly; in step S2, physical phenomena in a specific situation and importance degree rankings thereof are evaluated via phenomenon identification and a ranking table; in step S3, via a defense function tree form analysis system, challenges faced by safety objects and safety functions are evaluated; in step S4, according to execution results of steps S1-S3, whether safety measures and system design are reasonable is confirmed, and preliminary design is completed. The method disclosed in the invention is based on safety regulations, defense in depth and basic safety functions; opinions of experts in different fields are considered according to an information base of system design, accident analysis, experiment data and code analysis; comprehensive transverse and longitudinal analysis results can be quickly obtained on anything from systems to parts or even in-depth partial layers according to research demand and purposes.

The invention discloses a method for evaluating resilience of an electric power system under a disaster, comprising the following steps: 1) determining a type of the disaster and occurrence property;2) obtaining types of easily damaged elements under the disaster and related fault probabilities; 3) acquiring a running state of easily damaged equipment in a disaster environment by utilizing Monte-Carlo simulation; 4) carrying out system minimum load shedding calculation based on direct current optimal power flow; and 5) carrying out index calculation and system resistivity analysis. An expected running state and strong degree of the electric power system under various natural disasters and a man-made disaster can be rapidly calculated by utilizing the method disclosed by the invention, a calculating process gives consideration to types and characteristics of the disasters at the same time, and resilience enhancement limiting factors of the system under the disaster can be analyzed, sothat the method disclosed by the invention can be used for providing a reference and a suggestion for disaster prevention planning and construction of the electric power system.

The invention discloses a fault analysis detection method for cable accessories. The method includes the steps of collecting a partial discharge signal generated when a cable accessory malfunctions; carrying out filtering and frequency division for the partial discharge signal; performing conversion analysis through HHT transformation; extracting a partial discharge fault characteristic signal on the basis of an analysis result, and establishing a partial discharge fault characteristic database; identifying data information of the partial discharge fault characteristic database, and establishing a corresponding relation between a fault characteristic and a fault type and degree; and obtaining a fault identification result. The method is capable of detecting whether partial discharge of a cable accessory occurs, and also determining and identifying the fault defect type and degree through analysis of acquired signals. An analysis result provided by the method is comprehensive in data and is improved. High systematicness is exhibited, the cable accessory fault analysis detection efficiency is increased, faults can be quickly removed, and losses caused by the faults are minimized.

The invention discloses a traffic congestion situation analysis system. The traffic congestion situation analysis system includes the following components of: a data acquisition module which is used for acquiring and storing traffic information data in real time; a first analysis module which obtains the traffic information data acquired by the data acquisition module and selects corresponding evaluation indexes according to whether the data are deficient, and calculates real-time evaluation values based on real-time traffic information data, and compares the real-time evaluation values with corresponding evaluation threshold values so as to analyze traffic congestion situations in real time; a second analysis module which obtains all traffic information data which are stored in a set period from the data acquisition module, and establishes a Gauss mixture distribution model of all the traffic information data, and solves estimation values of related parameters of each sub Gauss distribution model, and analyzes traffic flow congestion states corresponding to each sub Gauss distribution model according to the estimation values. According to the traffic congestion situation analysis system of the invention, traffic information data which are acquired in a real-time manner and in a non-real-time manner are analyzed, and therefore, the traffic congestion situation analysis system is advantageous in few analysis variables, low cost and greater practicability.

The invention provides a BNSobol method for sensitivity analysis on the precision of a Helicopter fire control system. The method comprises the steps of performing global sensitivity analysis of the influence of error sources on the precision of the fire control system by combining a Bayesian network and a Sobol index; establishing the Bayesian network according to priori knowledge; learning related parameters in the network through Bayesian estimation to obtain a probability that the precision of the fire control system reaches a specified level under the condition of taking different values for the error sources; and finally processing a probability result by utilizing Sobol method variance decomposition to obtain sensitivity coefficients of the error sources. The invention proposes a new sensitivity analysis mechanism combining the Bayesian network and the Sobol index method, thereby providing reference and theoretical support for performing the sensitivity analysis on the precision of the Helicopter fire control system under the condition of insufficient sample quantity, and providing an uncertain quick quantitative analysis concept for other large-sized complicated systems.

The invention provides a data analysis method and apparatus. The data analysis method comprises the steps of collecting multi-channel original public sentiment events; according to a set data cleansing rule, cleansing the multi-channel original public sentiment events to generate to-be-clustered information; performing classification polymerization processing on the to-be-clustered information to generate a public sentiment event analysis result; generating the public sentiment event analysis result into graph data; and showing the graph data according to requirement of a user. By adoption of the data analysis method and apparatus disclosed by the invention, the polymerization efficiency of effective public sentiment events is greatly improved, and the problem of more abundant information and single analysis channel in the conventional public sentiment event analysis method is solved; in addition, the invention also provides a public sentiment event service for realizing all-around showing of the development process and trend of the public sentiment events to form a complete public sentiment event propagation path, so that a more accurate and more all-around public sentiment event analysis result is provided for the user; and therefore, social situation can be mastered in time, hidden dangers can be found, hidden risks can be recognized, and forceful data support is provided.

The invention discloses an analysis method and system for college employment data. A data collection unit obtains employment post information, obtains the specialized course setting information of a college and obtains user input information; the employment post information is classified to obtain the employment post data of each industry; and the employment post data is subjected to data analysisto obtain an employment post guidance analysis result. By use of the analysis method and system, an employment guidance scheme can be automatically formed, a matching degree between the employment post information and personal skills can be accurate, and effective employment guidance work is provided for students and employers to realize the college to carry out relevant teaching reform; and theunceasing update of technical development and employability skills can be effectively catered, and an employment analysis system is more intelligent.

The invention discloses a precise determination method of extreme working conditions of external heat flow of an orbit of a remote sensor in a whole life cycle, and belongs to the technical field of precise heat control of spatial optical remote sensors. The method specifically includes: 1), selecting parts, which are on a satellite and block the external heat flow of a light entrance of the remote sensor, and parts which are inside the remote sensor and in radiation heat exchange with an optical lens, ignoring radiation, heat capacity and heat conductivity of the back of the optical lens, andestablishing a finite-element heat model of the remote sensor; (2), adopting heat analysis software to calculate temperature of all finite-element nodes of the finite-element heat model of the remotesensor in the whole life cycle according to the preset orbit, and extracting temperature of each finite-element node of the optical lens of the remote sensor in the whole life cycle therefrom; and (3), calculating external heat flow absorbed by each finite-element node of the optical lens of the remote sensor in the whole life cycle according to temperature of the optical lens of the remote sensor in the whole life cycle, and selecting extremum values of the external heat flow to determine the extreme working conditions of the external heat flow of the orbit of the remote sensor in the wholelife cycle. According to the method, calculation is comprehensive, efficiency is high, and precision is high.

The invention relates to the technical field of water supply and drainage engineering, river regulation, environmental science and engineering and environmental protection, and provides a new urban river water quality standard analysis method which can objectively reflect each influence factor of river water quality. Therefore, the technical scheme adopted by the invention is as follows: a currenturban river water quality standard-reaching analysis method based on orthogonal analysis comprises the following steps: analyzing natural background characteristics of a region where the current urban river water quality standard-reaching analysis method is; constructing and calibrating a riverway hydrodynamic water quality coupling model; carrying out single-factor riverway water quality standard analysis of different influence factors; performing multi-factor river water quality standard analysis based on orthogonal analysis; and optimizing an orthogonal analysis result by active water volume checking and engineering cost analysis, and finally determining boundary conditions and engineering scale of river channel water quality reaching the standard. The method is mainly applied to drainage engineering and river regulation occasions.

The embodiment of the invention provides a finance analysis management system and method based on big data. The system includes: a finance statement acquisition module, wherein the finance statement acquisition module is used for obtaining an original form of a plurality of financial statements of a target enterprise; a finance item extraction module, wherein the finance item extraction module isused for extracting a predetermined type financial item and a corresponding financial amount from the original form of the plurality of financial statements; a finance vector generation module, wherein the finance vector generation module is used for generating a financial vector; a finance vector identification module, wherein the finance vector identification module is used for matching the finance vector with a pre-trained finance vector identification model; a finance type output module, wherein the finance type output module is used for outputting a financial type corresponding to the target enterprise after determining the type of the finance vector. According to the finance analysis management system, the financial indexes in the financial statements can be comprehensively extractedand the comprehensive analysis on the basis of the machine learning can be performed, the regularity characteristics of the analysis objects in the financial information can be fully mined, and the analysis result is more comprehensive, meanwhile, the manpower cost is saved.

The invention discloses a system for implementing multidimensional processing on failure mode and effect analysis (FMEA) data, and a processing method of the system. According to the method, when a subsystem in a real-time processing system continuously makes response to a request of a network user, and simultaneously, a multidimensional data analysis operation procedure is finished by the subsystem. The method comprises the following steps of: (1) setting an analysis dimension storage unit for setting a method comprising multidimensional data analysis and an equation; (2) responding the request of the user by an FMEA application system, acquiring ineffective data information and product data information which are required to be extracted during calculation of the data, and transmitting a result to an FMEA data multidimensional processing subsystem; (3) summing up the data transmitted by the user through the multidimensional data processing subsystem in the FMEA data multidimensional processing subsystem, wherein a summed result comprises the ineffective data information and the product information which are required by multidimensional data analysis; (4) extracting the information required by the step (1) from a database; (5) calculating an analyzed data result according to the equation set in the step (1); and (6) displaying the result on a client in forms of a three-dimensional diagram and a report. For a high-level risk priority coefficient failure mode, a system supplies a reference solution to the user.

The invention discloses an aircraft fire control system precision sensitivity analysis method based on a neural network. The method comprises the steps: introducing a local sensitivity algorithm and a global sensitivity algorithm into the index sensitivity analysis of an aircraft fire control system, and comprehensively employing an entropy method and a Sobol method according to the organic combination of different precision indexes, thereby achieving the precision sensitivity analysis of the aircraft fire control system. The analysis precision of the sensitivity coefficient of the precision index of the aircraft fire control system is improved. According to the method, the BP neural network is added in the aircraft fire control system and is trained, the precision index of the aircraft fire control system and the final killing probability are fitted, and required sample data are expanded quickly and effectively. Through a precision optimization distribution algorithm, optimization distribution of precision indexes of the aircraft fire control system is realized. According to the method, the problem of analysis and evaluation of multi-precision indexes in the aircraft fire control system under the condition of insufficient data samples can be well solved, experimental data can be quickly expanded based on learning and analysis of the neural network, and it is guaranteed that the aircraft fire control system reaches the specified killing rate.

The invention provides a method for monitoring meteorological drought. The method comprises the steps: acquiring environmental remote sensing data of a region to be monitored; determining the comprehensive drought condition index of each image source point in the region to be monitored based on the acquired environmental remote sensing data and the environmental conditions of the region to be monitored.

The invention provides a mesh combination method for acquiring sneak circuits in power electronic converters. Circuit topography of a power electronic converter is regarded as being composed of a plurality of independent meshes, the meshes are subjected to combination operation to obtain all sub-circuits in the converter, the sub-circuits invalid are eliminated according to the basic principle of circuit and the operating principle of power electronic converters, the sub-circuits remaining are in valid operating modes, the valid operating modes are combined to obtain all operating modes according to on and off rules of switch elements in the converter, and the sub-circuit in the mode different from the normal operating nodes is regarded as a sneak circuit, and accordingly the potential circuit in the power electronic converter is obtained. The method has the advantages that the analysis process of sneak circuit is simplified, analysis results are more complete, and no sneak circuit is missed; the method is applicable to the search of sneak circuits in various power electronic converters.

The invention discloses a spatial expansion method and system for a construction land. The method comprises the steps of: performing multi-factor evaluation on a target area according to different types of evaluation factors to obtain an expandable first land area; when the first land area is smaller than the required land area, repeatedly adjusting one or more evaluation factors, performing multi-factor evaluation on the target area according to the adjusted evaluation factors to obtain an expandable second land area, and when the second land area is greater than the required land area, performing superimposed calculation on the first land area and the second land area to obtain expandable land position and area. By adopting the method and the system, the land position and area serving as the construction land can be reversed according to the construction land requirement, so that the available construction land is not limited to the existing available land, and the expandable range of the construction land is enlarged.

The invention provides a human coronavirus nucleic acid multiplex detection kit. Specifically, the nucleic acid RNA of seven coronaviruses, namely human coronaviruses OC43, 229E, HKU1 and NL63, middle east respiratory syndrome coronavirus (MERS-CoV), severe acute respiratory syndrome coronavirus (SARS-CoV) and acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is simultaneously detected by a multiplex rRT-PCR method, and human coronavirus nucleic acids from multiple sample sources can be rapidly detected and analyzed.

The embodiment of the invention provides an overlapping coverage analysis method and a device, and the method comprises the steps: obtaining MR data of all serving cells in a region according to a CGIlist, and forming an MR data set; for any serving cell, counting the number of first MR data and second MR data in an MR data set and the number of overlapping coverage neighbor cell pairs formed bytaking the serving cell as an interference neighbor cell so as to calculate the interference contribution degree of the serving cell to the overlapping coverage of the region; and sorting the interference contribution degrees of all the serving cells to obtain a sorting list of the interference contribution degrees. The method of the invention meets daily optimization work requirements, and has the advantages of high accuracy, strong globality, high work efficiency and economic saving compared with conventional analysis based on sweep frequency data.

The invention provides an analysis method of a mixed DNA map, and belongs to the technical field of forensic genetics and forensic physical evidence. The method comprises the following steps: reading first-generation DNA STR map data and related parameters generated by capillary electrophoresis; generating a candidate genotype set of each gene locus by using the map data and the related parameters; determining a sampling interval of prior distribution of the preset sample parameters by using the atlas data and the related parameters; according to the determined sampling interval of the prior distribution of the preset sample parameters, sampling the candidate genotype set and the posterior distribution of the sample parameters by using an MCMC algorithm; and performing statistics on preset related indexes by using the candidate genotype set obtained by sampling and the posterior distribution of the sample parameters, and performing mixed DNA atlas analysis to obtain various analysis results. According to the method, first-generation DNA STR atlas data can be analyzed, atlas analysis is more objective, meanwhile, all input gene loci are split, and the splitting accuracy is high.