145results about How to "Meet analysis needs" patented technology

The invention discloses a network traffic statistics implement method supporting multi-dimensional aggregation classification. The network traffic statistics implement method adopts a multi-level storage manner and a data format, is flexible to use, high in expandability, and low in storage occupation space, and can meet different application requirements. An original message is stored in a database, and original traffic is stored in a binary file, so that the requirements of storage and integrity of a large amount of data are met; a traffic linked list is stored in an internal storage, so that the data accessing speed of a user is improved, and multi-granularity traffic statistical analysis is supported. As a third-order HASH aggregation traffic linked list matrix is introduced, the traffic inquire and access speed is improved, and the user is helped to find query information quickly and rapidly. The network traffic statistics implement method is a multi-dimensional traffic aggregation classification algorithm, can be used for dynamic traffic analysis according to various divided time periods of an application, and also supports business traffic aggregation analysis based on the variation of groups organized by various applications of original-target addresses, so that multi-dimensional traffic aggregation classification statistical analysis of flexible combinations of five key words is realized.

The invention relates to an evaluation model for evaluating the operation risk of the electrical network on the basis of a Bayesian network modeling method, and belongs to the technical field of scheduling automation of the power system. The method comprises that (1) a Bayesian formula based network model is established; and (2) the risk early-warning evaluation index and model are calculated. The evaluation model has the advantages that the electrical network risk early-warning evaluation model is based on the Bayesian network, the Bayesian network model has unique bidirectional inference technology, the operation risk of the electrical network is evaluated, influence of components on the operation risk of the electric network can be analyzed, weak links of the system are obtained, requirements for risk early-warning evaluation and analysis in practical electrical network service are met, and basis is provided for improvement of the system.

The invention discloses a method for identifying and predicting a bus passenger flow influence factor based on geographically and temporally weighted regression (GTWR). The method comprises steps of: extracting a traffic zone hour bus passenger flow and calculating built environment density; 2, constructing a space-time three-dimensional coordinate system according to the time of a passenger flow observation point and latitude and longitude to calculate space-time distance, and reckoning a spatial regression weight matrix according to a Gaussian function and the distance; 3, calculating a relation between a passenger flow volume and land utilization under different space-time conditions based on the GTWR; and 4, obtaining a change of a relevant parameter to a coefficient according to the calculation to perform visualization processing in time and space, and analyzing an inherent law. The method takes account of the influence of a time factor on the bus passenger flow and the built environment relation, can deeply excavate an internal relation between the passenger flow and the land utilization, accurately predicts the bus passenger flow, and provides the scientific theoretical guidance for the bus line planning and operation management.

The invention relates to an automatic sampling distinguishing chemiluminescent multi-component immunological detection system and an analysis method of the same. An incubation system of the detection system consists of a test tube (1), a stir bar (2), magnetic beads (3) and a constant temperature magnetic stirring apparatus (11); a multi-channel sampling system consists of sampling channels (4), a magnet (12) and a glass tube (13); a solution conveying system consists of a peristaltic pump (14), a connecting pipe (10), a multifunctional syringe valve (15) and a multiposition valve (16); a signal acquisition system consists of a detection channel (9), a plane mirror (17) and a multiplier phototube (18); and the method is to fix various capture antibodies on the functionalized surfaces of the magnetic beads to perform specific reactions with an object to be detected and a tracing antibody so as to form a sandwiched complex, introduce chemiluminescent substrate liquid into the sandwiched complex after collecting and washing off excessive enzyme labeled antibodies by using the magnet, and inject the chemiluminescent substrate liquid into detection channels sequentially to perform detection. The method has the characteristics of simplicity, quickness, good reproducibility, high flexibility, low cost, and the like, and can be applied to the fields of clinical diagnosis, environmental monitoring, food security, and the like.

The invention discloses a realizing method for a long-distance electrocardiogram monitoring system with automatic analyzing and real-time information sharing functions. The method comprises the steps that 1, automatic dynamic electrocardiogram analyzing equipment collects electrocardiogram signals and motion sensor signals and analyzes the signals in real time; 2, the automatic dynamic electrocardiogram analyzing equipment transmits analysis results in a wireless mode through a low-power-consumption Bluetooth communication module; 3, a user monitoring terminal receives data, processes the data locally in real time and the transmits the data to a long-distance monitoring terminal; 4, information received by the long-distance monitoring terminal is transmitted to a long-distance index real-time analysis processing and early warning module, and processed results are submitted to an information sharing module; 5, the information sharing module enables received information to be shared in real time according to the preset share range and the sharing mechanism. The method has the advantages that data wirelessly transmitted are reduced to the maximum degree, human intervention is reduced, high automation degree analysis is achieved, and the real-time prediction and early warning ability of severe events is improved.

The invention discloses a transient impact type high-speed wind tunnel low supersonic velocity flow field testing method and spray pipe devices thereof, which belong to the technical field of wind tunnel tests. In the prior art, an ideal low supersonic velocity flow field cannot be realized, and test requirements cannot be met. The transient impact type high-speed wind tunnel low supersonic velocity flow field testing method utilizes the newly designed M1.3, M1.35 and M1.4 spray pipe devices combined with an aperture wall test section to establish a low supersonic velocity flow field in a transient impact wind tunnel, and adopts a Mach number control method to obtain ideal flow field control quality; through the analysis of the axial Mach number distribution of the test section at different expansion angles, the method determines that the smaller the expansion angle of the test section at low supersonic speed, the better the uniformity of the flow field, and the expansion angle of 0 degree is selected as a tunnel body condition; the nozzle devices are combined with the aperture wall test section, and a test section expansion angle and flow field control mode is used to obtain a qualified flow field that meets the requirements of the national military standard; the ideal low supersonic velocity flow field and the test requirements are achieved; and a hardware basis is provided for realizing the ideal low supersonic velocity flow field and meeting test requirements by adopting spray pipe aerodynamic profiles of the M1.3, M1.35 and M1.4.

The invention discloses a sperm morphology analysis method based on a deep neural network model, and the method comprises the steps: recognizing and positioning sperms in a microscopic image through asperm image positioning module, extracting a sperm image, finally analyzing the image of each sperm through a sperm morphology analysis module, and completing the classification. According to the invention, the influence of interference factors on detection results can be greatly weakened, and the reliability of sperm morphology analysis results is improved. Feature information which cannot be obtained by a traditional measurement method in sperm pictures can be captured, so that the accuracy of sperm morphology analysis is improved. The sperm morphology analysis requirements of different sperm classification targets can be met.

The invention relates to a method and system for implementing a data sandbox based on mongoDB. The method comprises the steps that a server receives a data sandbox creation application sent by a user side; the server creates an independent data sandbox on the mongoDB according to the application; the server stores the data sandbox and manages operation resource quotas; the server leads data warehouse data or external data into the data sandbox and performs data processing in a data sandbox environment; and after the data processing, the server leads processed data out of the data sandbox, destroys the data sandbox and recycles system resources. An elastic data operating environment is provided for users, and the request on local installation and transaction database management is omitted; through an isolated environment, data risks caused by misoperation by users are effectively avoided, the conditions that a data warehouse is retarded due to a centralized mode are reduced, environmental availability is improved, and efficient data access is achieved while the overhead of the data warehouse is reduced.

The invention discloses a distributed type A / B test method for a personalized recommendation system. The method comprises the steps of performing module or intersystem distribution on data, and adding module or system identification on the data; performing inter-flow re-distribution on the data in the module or the system, and adding corresponding flow identification on the data during re-distribution; and collecting user behavior point data by a client end, integrating with the data having the module or system identification and the flow identification, and uploading to a server. The distribution strategy disclosed by the invention supports multi-dimension and multi-method distribution realization; the data flow is subjected to multi-dimension and multi-method feedback data tracking, so that multi-dimension and multi-method distinguished statistics can be carried out conveniently; flow information is recorded in the distribution process, namely, a dimension use method in the flow is recorded at the same time, namely corresponding data tracking; and therefore, each detailed processing leaves identification on the data, so that high subsequent handlability is achieved, and analysis requirements of different levels can be satisfied.

The invention relates to a method for storing massive industrial equipment monitoring data by means of a non-relation database, and belongs to the technical field of computer database management. At first, a plurality of unstructured data management systems form a non-relation database cluster of a distributed structure, the massive industrial equipment monitoring data are read from a relation database, the read monitoring data are stored into multiple client machines in a form with text files are separated by commas, a non-relation database storage mode is constructed, and the text files separated by commas and on the client machines are led into the non-relation database cluster. According to the method, the massive equipment monitoring data can be effectively stored, rapid data inquiring and analyzing are supported, enterprises can inquire and analyze the massive monitoring data, information having commercial value in the monitoring data is excavated, and finally the purpose of providing references for designing, manufacturing, marketing, using, maintaining and other aspects of industrial production is realized.

The invention relates to an SVG standard customizable graphic symbol based power system graphic display method. A power system image is displayed through an SVG graphic element, wherein the SVG element comprises the following attributes: an SVG file header; defs, used for storing a graphic symbol definition; a graphic symbol, used for describing a display mode of a power system object image; graphic element conversion, comprising translation, scaling and rotation; a layer number, used for reflecting a sequence of adding graphic elements into a scene, wherein a currently loaded graphic element covers a previously loaded graphic element; and a group number, used for grouping the graphic elements. According to the method, a power graphic symbol can be flexibly drawn, so that the workload and cost of independent development are reduced, the development efficiency is improved, and the development cycle is shortened.

The present invention discloses a new use of nanometer gold and graphene oxide, wherein the new use is specifically an application in ELISA detection signal amplification. The present invention further discloses an ELISA detection method, which comprises: (1) adding an analyte capable of specifically binding with coating antigen to an enzyme label plate loaded with the coating antigen; (2) adding a nanometer gold marker to the enzyme label plate, wherein the nanometer gold marker is a substance obtained by concurrently binding nanometer gold, a protection A (capable of specifically binding with the analyte) and a protein B (incapable of binding with the analyte); and (3) adding a graphene oxide marker to the enzyme label plate, wherein the graphene oxide marker is a substance obtained by binding graphene oxide and a protein C (concurrently binding with the protein A and the protein B). According to the present invention, the nanometer gold and the graphene oxide are concurrently introduced into the conventional ELISA method, such that the double signal amplification is achieved, the detected protein signal is amplified by more than 10 times, and the cost is substantially reduced.

The invention relates to a methacrylate polymer solid phase micro extraction fiber and a preparation method thereof, in particular to a solid phase micro extraction. A fiber is provided with a stainless steel substrate which is a stainless steel wire, and one end of the stainless steel wire is provided with a methacrylate polymer coating. The preparation steps of the invention are that: one end of the stainless steel wire is cleaned with water and dried after being ultrasonically cleaned by an acetone solvent and an ethanol solvent; trimethylolpropane trimethacrylate, toluol and azodiisobutyronitrile are added to the methacrylate in sequence, then ultrasonic blending process and nitrogen flushing and deoxygenizing process are conducted, and then a prepolymerization blended solution is obtained; the prepolymerization blended solution is injected to a glass point sampling capillary by a microliter syringe, then the stainless steel wire is vertically inserted into the central part of the point sampling tube, and the two ends of the point sampling tube are sealed by rubber, then the point sampling tube is placed into an oven for polymerizing and cross linked at a certain temperature. After a polymer solution is solidified at the surface of the fiber, the point sampling tube is soaked in a hydrofluoric acid solution for a certain period, then the glass tube wall is removed, and then the solid phase micro extraction fiber is obtained.

The invention relates to a biomarker combination for molecular typing and / or prognosis prediction of the muscle-invasive bladder cancer, and a screening method and application thereof. The biomarker combination comprises the following genes: FGF10, TP53INP1, DDR2, MYC, CDC73, IGF1, PLA2G1B, SKI, FN1, EGFR, PPARG, PDGFRA, PDGFD, GAS6, PDGFC, FNTB and CCNB1. Through non-negative matrix factorizationclustering analysis based on transcription data of the biomarker combination, the muscle-invasive bladder cancer can be classified to respectively correspond to different expression characteristic spectrums. The classification corresponds to significantly different overall survival statuses, thus being used for survival prognosis assessment. The transcription data analysis method adopted has theadvantages that the number of biomarker combinations is small, the analysis steps are simple, the requirements of large sample analysis are met, the requirements for the calculation ability are low, and the method is applicable to standardized transcription data; the transcription data can be a transcriptomic data sub set or a set of genetic transcription data for individual detection.

The invention belongs to the technical field of molecular marker-assisted breeding, and discloses a molecular marker detection method based on a next-generation sequencing technology. Amplicons of allsingle plants at important agronomic trait-related loci are obtained at a time through multiple PCR by using designed specific primers of the multiple loci and a PCR reaction system and an analysis process according to the principle of amplicon sequencing, primers containing different tag sequences are used to carry out one-time amplification on the amplicons, the amplicons of all the plants areexpanded. With the different tag sequences, the amplicons undergo next-generation sequencing, and sequencing results are analyzed to obtain the genotypes of all the single plants at a time. A high-throughput detection system constructed in the invention is used to quickly and accurately detect the disease-resistant quality-related genes which are widely used in existing breeding practices.

The invention discloses a scientific literature key content potential association mining method based on a graph neural network, and the method comprises the following steps: S1, obtaining scientificliterature data related to a certain specific event, and carrying out the data cleaning and preprocessing; s2, extracting a literature content keyword by utilizing a TF-IDF method; s3, constructing aword co-occurrence network for the extracted keywords and references to which the keywords belong by taking sentences as units; s4, learning vector representation of the keywords by using a graph convolutional neural network; and S5, obtaining the relevancy between different keywords by utilizing a similarity calculation function, and mining the potential incidence relation of the different keywords. According to the method, modeling is carried out on the keyword relationship extracted from the article content, and the potential association of the main keywords of the literature is mined by utilizing the graph convolutional neural network technology, so that the analysis requirement on the scientific literature content is met, and the correlation of the scientific literature in different fields is analyzed; and an effective method is provided for systematic analysis of scientific literatures.

The invention relates to the field of electric power system simulation, in particular to a visual modeling method for the simulation data of a power distribution network cyber-physical system. The method comprises the following steps that: (1) determining an analysis target; (2) selecting an analysis angle; (3) constructing a data analysis and calculation model; (4) configuring an analysis resultdatabase; (5) constructing and configuring an analysis topic diagram; and (6) carrying out the visual displaying of analysis result data. By use of the method, the analysis modeling problem of a greatquantity of historical simulation data of the power distribution network cyber-physical system and the visual displaying problem of the analysis result are solved, the simulation data analysis of complex research contents, including the state evolution properties of the power distribution network cyber-physical system, the dynamic interaction influence of an information system and a physical power grid and the like under the function of multiple correlation events and the information system under a situation that the cascading failure of the power distribution network cyber-physical system isin the presence is realized, and therefore, complex and diversified simulation data analysis requirements under a power distribution network cyber-physical system environment can be met.

The invention relates to a device used for quickly extracting chemical constituents from plants and a method thereof, which belongs to the field of chemical analysis technology. An extracting device comprises a cylinder, a plunger rod, a filtering screen plate and a faucet, the plunger rod is arranged on the internal upper end of the cylinder, the filtering screen plate is arranged on the internal lower end of the cylinder, the faucet is arranged on the external lower end of the cylinder. Different extracting solvents can be chosen according to the properties of the chemical constituents of the plants, in the condition of the rotating speed of 14,000 to 22,000r / min, high-speed agitation can be carried on for 0.5 to 2min, then the faucet is opened, external pressure is added for filtering, and filter residue is stirred with the solvents for reextraction. The device of the invention gathers the extracting samples and the filtering into a device can reduce the loss of samples in the transferring and extracting processed, at the same time, through adding external pressure for filtering, filtering speed can be improved, so the extracting process is only 10 to 20 minutes, thus achieving the good extracting effect, simple and fast operation and the hign practicality.

The invention provides a data analysis method and system. The method comprises the steps of obtaining a to-be-analyzed data table which is selected by a user and corresponds to a data processing chain; determining a data processing component in the data processing chain; wherein the data processing chain comprises at least one data processing component selected by a user; determining an executionsequence of the data processing components specified by the user for the data processing chain; and performing data processing on the to-be-analyzed data table according to the execution sequence of the data processing components and the data processing mode of the data processing components to obtain a processing result of the data processing chain. The data processing assembly in the data processing chain can be flexibly configured according to user requirements; the data processing flow changes along with different processing components selected by a user or different execution sequences ofthe data processing components specified by the user, so that the problem that the data processing flow is fixed and single is solved, the analysis requirements of industrial data in more applicationfields can be met, and the universality is higher.

Embodiments of the invention disclose an optimal scale selection method and device, and a computer readable storage medium. The method comprises the steps of generating the segmentation result graphsunder different scale parameters based on an input remote sensing image; selecting a training sample from the generated segmentation result graphs, training the training sample to obtain a multi-scaleclassification model, then carrying out multi-scale classification on the remote sensing image to be classified, and generating the classification result graphs under different scale parameters; selecting a plurality of target classification result graphs from the classification result graphs, and respectively calculating the classification precision associated with each target classification result graph; and carrying out optimal scale selection after classification precision statistics. By implementing the invention, the multi-scale classification result is used for precision evaluation, the optimal scale is selected according to the precision evaluation statistical result, the applicability is wider, the analysis requirements under more scenes can be met, the conversion from the optimal segmentation scale to the optimal classification scale is achieved, and the defects that the efficiency is low and the effect is poor when the analysis scale is selected at the segmentation stage are overcome.

The invention relates to the technical field of data marts and data warehouses, in particular to a data modeling method for data marts and data warehouses, which comprises the following steps: a stepof building a bus architecture: extracting main data of a service system for automatic integration, obtaining a public consistency dimension, and building a standard bus interface; a data processing step: classifying the business data tables, and automatically screening a data extraction mode to extract the business data tables according to a classification result; and a model integration step: combining the business data tables through the inverse three normal forms, splitting the business data tables to form a fact table and a plurality of dimension tables, and constructing a dimension modelwhich takes the fact table as a main part according to the fact table and the plurality of dimension tables. By the adoption of the scheme, the technical problems that in the prior art, due to the fact that all independent data markets are independently constructed by all users or departments, data architectures of the independent data markets are independent of one another and cannot be reused,data islands are easily caused, and meanwhile standardization, consistency and accuracy of enterprise data cannot be guaranteed can be solved.

The invention provides a multi-loop control parameter identification method and system for a grid-connected inverter. The multi-loop control parameter identification method comprises the following steps of acquiring a circuit element parameter group W; determining a plurality of groups of steady-state operation point parameter groups O and impedance value sequences under a plurality of groups of steady-state operation points based on the conventional operation condition range of the grid-connected inverter; and performing control parameter fitting on the parameter group, the impedance numerical value sequence and the circuit element parameter group under each group of steady-state operation points based on an impedance / admittance model of the inverter to obtain control group parameters; fitting precision of different loop control parameters is improved by adopting a frequency band-by-frequency band fitting mode, influences of different steady-state operation points on impedance characteristics of the inverter and influences of phase-locked control and direct-current bus voltage control frequency band superposition are considered, and applicability of parameter fitting is improved;a problem of accurate modeling caused by black / gray box control of an actual grid-connected inverter is solved; and the obtained amplitude-frequency curve and phase-frequency curve of the broadband impedance of the steady-state operation point meet the analysis requirements on the characteristic mechanism of the device.

The invention discloses a non-dispersive infrared light gas detection system adopting an electric pulse infrared light modulation method, so as to reduce power consumption at the part where infrared light is modulated, and stability is improved; an internal coating method is adopted in structural design of a gas chamber, so that infrared light diffusion and external disturbance are reduced further, and gas detection accuracy is improved; a calibrating circuit is used for signal processing, so that different collected gas can be detected accurately through calibration; a programmable logic device is adopted to calibrate different environmental factors in air through software collection, the functions of data teletransmission, abnormity warning and the like are achieved through FPGA treatment, thereby improving module detection precision, timeliness and stability and reducing system cost simultaneously. The non-dispersive gas detection system disclosed by the invention has the advantages that the system is small in volume and low in power consumption, continuity and timeliness of gas detection can be achieved, and the detection precision is improved greatly.

The invention is a kind synchronous recording system for experience animal behavior and electrophysiology signal, which belongs to nerve biology experience device. The recording system includes a video gathering card, a camera, an aD sampling board, an electrophysiology signal amplifier, micro electrode, a computer which stores the video and electrophysiology signal gathering procedure in the memory. The invention stores the video and electrophysiology data through programming correspondent procedure, it corresponds the electrophysiology signal and the animal behavior and maintain the synchronization in the playback process. The gathering of video and the electrophysiology signal are integrated together. It provides several kinds of video compressing methods; it has multi-channel, multi-frequency electrophysiology data sampling rate and video sampling rate of 1-30 frames / second; provides video finding mode step-by-step; it can output the synchronization of electrophysiology data and the animal behavior in a high accurate time range.

The invention discloses a miniature snapshot spectrometer. The spectrometer comprises an angle filter, a spectrum selection layer, a photosensitive surface and a reading circuit which are sequentially arranged from top to bottom. According to the invention, a wide-spectrum-angle filtering function is realized by using the high-aspect-ratio diaphragm array, and a micro-nano structure or band gap and refractive index adjustable thin film is constructed to realize specific spectrum transmission in the same plane. The light-sensitive surface is used for converting transmitted light of different spectrum selection layers into light current signals, and the light current signals collected by the light-sensitive surface are processed and output through a reading circuit or an external processing circuit. According to the invention, an ultra-small-size snapshot spectrograph can be realized, so that high-precision and large-spectral-range spectral analysis is realized, and the device can be suitable for various wavebands, so that different spectral analysis requirements are met.

The invention discloses a method for analyzing influences, caused by beaded-shaped karst, on pile foundation stressed deformation. The method comprises the following steps: A, selecting finite element numerical value simulation software; B, establishing an axisymmetric two-dimensional geometric model according to on-site geological researches; C, carrying out grid division, selecting a constitutive model, and setting boundary conditions and material parameters; D, additionally arranging a contact unit between a pile foundation and a stratum; E, killing a pile foundation material unit, and simulating a stress state and settlement deformation of the stratum under the effect of gravity; F, activating the pile foundation material unit and simulating pile foundation construction; G, applying pile foundation top load and simulating the effect of external load; H, discounting an elastic modulus of fillings in a karst cave, and simulating a secondary consolidation settlement process of the soft fillings in the karst cave after disturbance; and I, obtaining stressed deformation results of the stratum and the pile foundation through a post-processing program. The method disclosed in the invention is feasible, simple and convenient to operate and efficient in calculation, has the effect of satisfying the design and construction of pile foundations in karst areas, and has great importance for the design and construction of building pile foundations in the karst areas.

The invention relates to a method and a device for detecting gas and discloses a device and a method for detecting and analyzing impurities in corrosive gas. In the device, the impurities in the corrosive gas is separated and detected by switching a valve to change the flow direction of the gas. The device has the advantages of simple structure, simple and rapid analysis process, on-line detection and good impurity component separation effect, and can meet the analytic requirements on the corrosive gases of different impurities.

The invention discloses a method for preparing a sample for low-carbon steel EBSD analysis. The method includes the steps that 1, a test specimen is intercepted, wherein the face to be tested of the intercepted test specimen is grinded flat by a grinding machine; 2, the test specimen is burnished, wherein 400# silicon carbide waterproof abrasive paper, 800# silicon carbide waterproof abrasive paper and 1200# silicon carbide waterproof abrasive paper are used in sequence for burnishing the test specimen; 3, the test specimen is washed, wherein the test specimen is washed by absolute ethyl alcohol and dried by cold air; 4, argon-ion beams conduct polishing, wherein the high-energy argon-ion beams are adopted to bombard the face to be tested of the test specimen for 40-120 minutes to conduct polishing, and the sample for the low-carbon steel EBSD analysis is obtained. According to the method, mechanical polishing or electrolytic polishing is not needed, a destressing corrosive liquid is not needed, and in the whole sample preparation process, the usage of acid chemical agents is avoided, so that the method is safe and environmentally friendly. By the adoption of the method, the obtained sample for the low-carbon steel EBSD analysis is extremely high in desorption rate, the sample calibration rate reaches 92-99%, and the sample meets the EBSD analysis requirements.

The invention discloses a link data access method and device, a storage medium, a processor and an electronic device. The method comprises the following steps: acquiring business log data of multipleservice nodes, wherein log records corresponding to different types of business actions are recorded in the business log data; analyzing into a plurality of business events of different types according to the log record; forming a service link by the plurality of service events of different types based on a link template, and storing the service link into a first preset storage space, wherein thefirst preset storage space is a tree structure pre-established by the link template according to a service flow, and the first preset storage space is a distributed graph type database; obtaining a query index; and performing access operation on the data content in the service link according to the query index. The technical problem that an effective link data access mode cannot be provided for complex and massive link data storage and analysis requirements in the prior art is solved.

The invention discloses a handheld FC bus tester which comprises a data capturing module, a data sending module, a statistics module, a human-computer interface and a control module, wherein the data capturing module captures data, stores the data into a storage unit, and has data filtering and data triggering functions; the data sending module sends the data to tested equipment by an optical interface; the statistics module carries out statistics on the data captured by the data capturing module and the data sent by the data sending module, obtains short-term statistic values and accumulated statistic values, and carries out data interaction with the control module; the human-computer interface receives input control information and displays a testing result; and the control module controls coordinative operation of the data capturing module, the data sending module, the statistics module, a protocol parsing module and the human-computer interface. The handheld FC bus tester disclosed by the invention solves the problems of low integration, inconvenience for carrying, high price and the like of an existing testing instrument, so that the handheld FC bus tester not only meets requirements for FC protocol analysis and testing, but also is simple, easy to use and convenient to carry.