396results about How to "The identification result is accurate" patented technology

The invention discloses a power lithium battery model parameter identifying and dump energy estimating method. The method includes the steps of firstly, establishing a state space equation of a two-order impedance-capacitance model of a lithium battery; secondly, establishing a regression model of the relation of an end voltage and open circuit voltage and a current; thirdly, conducting parameteridentifying based on an iterative learning recursive least-squares method on the regression model; fourthly, conducting identifying based on the iterative learning recursive least-squares method on experimental data meeting the discharge current conditions in the parameter identifying process in the third step to obtain prediction errors, and conducting converging through the prediction errors toobtain a nonlinear function in parameters of the state space equation and a parameter set; fifthly, verifying the battery model precision formed by the nonlinear function and the parameter set obtained in the fourth step; sixthly, collecting current and voltage data, and estimating the dump energy through expanded Kalman filtering. The model parameter identifying precision is high, the dump energyestimation value error is small, and good application prospects are achieved.

The invention provides a grid voltage stabilization on-line monitoring method based on voltage stability local indexes, comprising the following steps: calculating single power consumption transmission equivalence system parameters of a monitored node according to grid topology structure parameters and relevant node voltage current phasor in adjacent areas of the monitored node; using the single power consumption transmission equivalence system parameters to identify the influence of a system outside the area on the monitored node to obtain a single power consumption transmission equivalence system expanded by the monitored node; calculating voltage stability local indexes of the monitored node according to the expanded single power consumption transmission equivalence system parameters; judging whether the monitored node is a weak node according to the node voltage stability local indexes; and if so, performing voltage stability warning. The identified initial value is the calculatedsingle power consumption transmission equivalence system parameter. The invention can solve the problem of misjudgment of index values generated by incorrect identified parameters when the continuousexcitation condition is not satisfied; the method has fine index value performance, can judge the weak node correctly, and realize on-line monitoring of the grid voltage stability.

The invention discloses a liquid chromatography-mass spectrometry screening method of unknown toxic substances in blood. The liquid chromatography-mass spectrometry screening method comprises the following steps: taking a blood sample to be detected, adding acetonitrile precipitated protein, oscillating, centrifuging, taking a supernatant, filtering by using a 0.22-micron microporous organic filter membrane, then performing LC-MS/MS analysis, and judging whether the blood sample to be detected contains toxic substance components or not according to an analysis result; the used instrument is an ultraLC 100-XL-4000Q TRAP liquid chromatograph/mass spectrometer or an Agilent 1100 liquid chromatography-AB 3200 QTRAP triple serial quadrupole mass spectrometer from an AB company. By the liquid chromatography-mass spectrometry screening method, detection methods of different types of toxic substances are established, detection is fast and accurate, the detection limits of common toxic substances are given, high-sensitivity and effective detection of all target objects are guaranteed, a scientific data support is provided for a negative detection result, and thus a strong scientific basis is provided for relevant clinical diagnosis and rescue as well as criminal investigation and litigation.

The invention discloses a method for online identification of a low-frequency oscillation mode of an electric power system based on random response signals. The method comprises the following steps of: firstly, reading a section of angular speed signals of different power generators when the electric power system runs normally; then performing mean removal processing on the read signals to obtain zero-mean random response signals; processing the zero-mean random response signals by using a natural excitation technology to obtain free oscillation signals; and finally, performing mode identification on the obtained free oscillation signals by adopting a PRCE method to obtain a frequency, a damping ratio and an oscillation mode state of the low-frequency oscillation mode. The method disclosed by the invention can identify the low-frequency oscillation mode of the electric power system in a wider time range, is better in identification precision, speed and noise immunity, and is more capable of identifying an oscillation mode state, thereby providing a brand-new way and method for low-frequency oscillation analysis of the electric power system.

The invention provides a method for detecting a Chinese patent drug containing at least two of white paeony root, ginseng, salvia miltiorrhiza, sweet wormwood, liquorice and angelica sinensis, comprising the steps as follows: preparing a sample solution and a comparison product drug solution, adopting acetonitrile and water as mobile phases, and performing high performance liquid chromatography (HPLC) measurement, wherein the detection wavelength is 201-290nm; and detecting whether a corresponding chromatographic peak exists at a position, which has the same reservation time with the chromatograph of a comparison drug, in the chromatography of a sample. Compared with the traditional thin-layer chromatography identification method, the detection method in the invention has the advantages that the mode of processing a sample containing various drugs in a liquid phase chromatograph is changed, the mixed peak in the liquid phase chromatography except the components to be detected in the Chinese patent drug is successfully eliminated, and results are more accurate and stable.

In soft measurement technology frame, the easy-to-measure reliable pressure difference fluctuation signal is adopted as auxiliary variable in detecting flow pattern of two phase flow as the main variable. The acquired pressure difference signal is wavelet analyzed, corresponding characteristic values are extracted, and the characteristic values are used in fuzzy identification of the flow pattern of two phase gas/liquid flow in horizontal pipe. The key soft measurement model is established by means of combining the wavelet analysis technology and fuzzy pattern identifying technology. Then, one flow pattern identifying system for two phase gas/liquid flow is established, and the system consists of test pipeline, pressure sampling hole, pressure sampling pipe, pressure difference sensor, amplifier, data acquiring card, microcomputer and printer. The detected pressure difference signal is processed in the system for pattern identification of two phase gas/liquid flow.

The invention belongs to the field of analysis of traditional Chinese medicinal materials, and particularly discloses an HPLC (High performance liquid chromatography) method for distinguishing different cultivars of uncaria. All chromatographic peaks are separated effectively when the uncaria traditional Chinese medicinal materials are subjected to HPLC detection by optimizing each experimental parameter; the phenomena of mutual interference of the chromatographic peaks, trailing and the like are reduced; mutual interference of the chromatographic peaks of different ingredients in different cultivars of uncaria in HPLC detection is basically avoided, so as to provide basis for authenticating different cultivars of uncaria and constructing a uncaria HPLC fingerprint spectrum.

The invention discloses a road accident dark spot identification system based on a system safety index distribution method. The system comprises a history accident data recording unit, a system safety index recording unit, a dark spot identification unit and a dark spot identification result output unit. The system safety index method comprehensively takes consideration of history accident data correlative in space positions on a target road, calculation is simple, only system safety indexes on a road segment node need to be calculated, road segment units are needless to be divided, the occasion that in a traditional dark spot identification method, the road segment units must be divided first is eliminated, meanwhile the space correlation of the history accident data is taken into consideration, and results are precise.

The invention discloses a method for simply and clearly detecting and finding recovered oil processed from kitchen waste oil through an instrument by adding a tracer in the used kitchen waste oil for clearly marking the kitchen waste oil. Therefore, the kitchen waste oil after recovery can still be simply and clearly detected even through the treatment, such as dilution, high temperature, deodorization, bleaching, deacidification and the like, and a way that people re-eat the kitchen waste oil is further cut off. The method disclosed by the invention has the advantages of high sensitivity in identification, simple identification method, accurate identification result, low using cost and no impacts on reasonable re-utilization of the kitchen waste oil, and is easy to popularize and use.

The invention belongs to the field of crop disease resistance identification and especially a method for rapidly identifying the black shank resistance of tobaccos. The method for rapidly identifying the black shank resistance of the tobaccos is capable of effectively overcoming the defects of exiting identification, and comprises the following steps: step 1, culturing tobacco black shank bacteria; step 2, taking tobacco seeds to be tested and sterilizing the surface; and step 3, performing germination rate and morbidity statistics and performing disease resistance evaluation. The method is capable of saving manpower and material resources and also greatly reducing the identification time; the resistance level to the black shank is not limited by the growth seasons; besides, the method is simple in identification operation steps and relatively low in test room requirement conditions; according to the method, the purpose of rapidly identifying the black shank resistance of the tobaccos at low cost and high flux is achieved; the method is suitable for identifying the black shank resistance of a large batch of germplasm materials in tobacco breeding study; and as a result, the anti-disease germplasm resource screening, the resistance hereditary character study and the anti-disease variety breeding and popularization/application can be accelerated.

The invention belongs to the field of ship parameter identification and particularly relates to a ship parameter identification method, which can be used for estimating unknown parameters in a ship time domain state space model, based on particle filtering. According to the ship parameter identification method, a force and a moment are applied to a ship by using executing mechanisms such as a propeller, a rudder and the like of the ship, so that the ship takes special exercise; displacement and attitude angle information of the ship at each discrete sampling moment is measured under geodesic coordinates by using a measuring system, and is an output observation value of the ship; a ship parameter estimation value at each moment is obtained by identifying the ship by using a ship parameter estimation device according to a state estimation value and the output observation value of the ship; and state values, namely an angular speed value and a linear speed value of the ship under the geodesic coordinates, of the ship are estimated by using a particle filter according to stress information at each moment and a parameter value which is identified at the previous moment. According to the ship parameter identification method based on particle filtering provided by the invention, observed data does not need to be processed in batches and a lot of iteration does not need to be carried out, and the filtering precision is very high; and the calculation is simple and the execution efficiency is high.

The invention discloses a motor mechanical parameter identification method and system based on a high-order sliding-mode observer. The method comprises the following steps of operating a motor under two working conditions of the same acceleration and different rotating speeds, obtaining output signals of the high-order sliding-mode observer, and then calculating a friction coefficient estimation value; eliminating the influence of a friction coefficient error, obtaining output signals of the high-order sliding-mode observer when the motor is operated in two working conditions of different acceleration, and then calculating a torque inertia estimation value; and eliminating the influences of the friction coefficient error and a torque inertia error, obtaining an output signal of the high-order sliding-mode observer when the motor is operated in a working condition, and calculating a load torque estimation value. According to the method, the mechanical parameter identification is realized, the accuracy of a mechanical parameter identification result is improved, and the application value of the mechanical parameter identification is improved.

The invention relates to a method for identifying fidelity of paintings and calligraphy works, and the method is characterized in that a plurality of small areas on a painting are selected as identification areas, image characteristics of the works to be identified for identification in each identification area are compared with the corresponding image characteristics in each identification area of a pre-stored correspondent genuine to be used as an evidence for judging the fidelity of the works. For convenience in operation, a rapid recognition template is preferably adopted to determine and recognize the identification areas of the works, the rapid recognition template is a flat plate with a plurality of recognition holes on the surface, each recognition hole is an isometric through hole which is vertical to the surface, the rapid recognition template covers the genuine according to a selected coverage position, and an appropriate small area selected on the painting exposed after the coverage is selected as the identification area. The method can simply and rapidly identify the fidelity of the paintings and calligraphy works.

The invention discloses a method for identifying hybrid germplasm of actinidia based on genome heterozygosity, relating to the technical fields of plant genetic resources and biology. The method comprises the following steps: (1) performing low-depth genome sequencing on a sample; (2) comparing reference genomes of sequencing data and mining single-base mutation sites; (3) calculating the heterozygosity of genome level of the sample based on the single-base mutation sites; (4) constructing a basic species heterozygosity distribution rule database of a main ancestor of the actinidia; and (5) performing heterozygosity comparison on a to-be-detected sample and the database so as to identify the hybrid germplasm. Compared with the traditional molecular marker technology, the method disclosed by the invention has the advantages that the identification accuracy is greatly improved; and meanwhile, compared with the traditional morphological identification method, the method disclosed by the invention is high-efficiency and rapid, and the identification time and cost can be saved. The method disclosed by the invention has wide applicability on different sequencing platforms, and comprehensive evaluation and application of the germplasm resources of actinidia can be formed.

The invention discloses a microbial identification and analysis system and device based on second-generation high-throughput sequencing, and the system comprises a task management module which is usedfor building a task list, managing an identification and analysis task in the task list, uploading to-be-identified and analyzed data to a server, and carrying out the identification and analysis ofthe to-be-identified and analyzed data through the server; a report management module used for generating an identification and analysis report according to the identification and analysis result andcompleting the auditing and approving process of the identification and analysis report according to an auditing and approving instruction of a user; and a report statistics module used for performingreport statistics on the identification analysis report or the identification analysis sample according to the four dimensions of the strain, the microorganism type, the strain source and the identification analysis report statistics. According to the invention, strain or strain identification can be carried out at a molecular level, and the identification result is more accurate and the throughput is high; besides conventional bacteria and fungi, mould and actinomycetes can be identified; meanwhile, mixed bacteria or bacteria difficult to culture can be identified; and the whole genome sequencing data can be subjected to traceability analysis.

The invention relates to a method and a PCR (polymerase chain reaction) primer for identifying dendrobium officinale. The method includes identifying the dendrobium officinale on the basis of mononucleotide difference sites of chloroplast ACCD gene sequences of the dendrobium officinale and other herba dendrobii of dendrobium by the aid of Tetra-primer ARMS-PCR processes. The PCR primer for identifying the dendrobium officinale comprises specific inner primers for identifying the dendrobium officinale and the other herba dendrobii of the dendrobium and a pair of specific outer primers. The method is simple, and the dendrobium officinale can be detected by the aid of one-step PCR and conventional electrophoretic techniques; identification results are accurate, mismatched basic groups are introduced when the primers are designed, accordingly, the specificity of PCR amplification reaction can be greatly enhanced, and false negative results can be prevented owing to positive control of outer primer strips; further, the method is sensitive, and the dendrobium officinale can be completely identified only by a few samples.

The invention discloses a high-throughput STR typing system capable of identifying complex consanguinity and a kit thereof, and relates to the technical field of nucleic acid detection in vitro. The high-throughput STR typing system capable of identifying complex consanguinity comprises PCR primers used for amplifying 60, 118 or 179 linked autosomal STR loci; and the kit comprises a PCR primer composition, an Index connector sequence, an IGT-EM707 polymerase mixture, an amplification buffer enhancer NB, a YF buffer solution B, a database setting-up reagent and the like. The high-throughput STRtyping system capable of identifying complex consanguinity and the kit thereof provided by the invention are capable of realizing single-tube amplification of 60, 118 or 179 linked autosomal STR loci; and moreover, the STR typing system and the kit thereof are good in balance, high in sensitivity, good in specificity, and accurate in typing result. Thus, the high-throughput STR typing system capable of identifying complex consanguinity and the kit thereof can be used for identifying complex relationships of different consanguinity at the same level.

The invention discloses a surface heat flow identification three-dimensional effect correction method based on a neural network. The correction method comprises the following steps: mounting a plurality of temperature sensors on the inner wall surface of an area around a stationary point heat flow; utilizing temperature data of each internal temperature measuring point; obtaining a heat flow on acorresponding heating surface point through a one-dimensional heat flow identification method; and then introducing an artificial neural network algorithm, carrying out normalization processing on theidentified heat flow corresponding to each measuring point in the previous step to serve as an input sequence of the neural network, and carrying out training in the neural network to obtain an output anti-normalization result to serve as a heat flow identification value of a region of interest. According to the correction method provided by the invention, the time complexity of three-dimensionalidentification is avoided, meanwhile, the good noise resistance of the sequential function method and the strong nonlinearity of the neural network are combined, a traditional model can be greatly simplified, the identification precision of the stationary point heat flow is improved, and the real-time performance of on-line identification is ensured.