159results about How to "Reduce analysis error" patented technology

The invention discloses a PM2.5 particulate mass sampler with four sampling channels: in the first sampling channel, the sampling head includes a PM2.5 cutter, a diffused solution container, Teflon filter membrane and nylon filter membrane; the sampling head in the second sampling channel includes a PM2.5 cutter and Teflon filter membrane; the sampling head in the third sampling channel includes PM2.5 cutter and two-layer quartz membrane; the sampling head in the forth sampling channel includes PM2.5 cutter and polycarbonate membrane.

The invention relates to a method for measuring gas component concentration in an inverse calculation mode based on a differential optical absorption spectrum. In the method for measuring the gas component concentration in the inverse calculation mode based on the differential optical absorption spectrum, a mathematic model is established and solved by a least square method, the contents of various pollutants in flue gas can be recorded in real time, and the gas which comprises unknown components can be determined. Meanwhile, the invention provides a solution scheme aiming at main factors which influence the precision of differential optical absorption spectroscopy (DOAS), analysis errors due to spectral line shift can be effectively reduced, and the precision problem of the gas component concentration measurement in which absorption spectral lines are superposed is solved.

The invention provides a WiFi technology based behavior analysis method and system. The method includes: arranging a lot of WiFi signal acquisition equipment in a target area; letting the WiFi signal acquisition equipment respectively acquire WiFi signals emitted by WiFi terminals carried by a plurality of target objects in the target area; demodulating and analyzing the acquired WiFi signals to obtain the WiFi information corresponding to the target objects in the target area, with each target object corresponding to at least one piece of WiFi information; according to the signal strength of the WiFi signals, extracting the WiFi information corresponding to a target object entering the target area within a preset period of time; and calculating the number of unique identification information that is non-repetitive in the extracted WiFi information and has corresponding time information in the preset period of time to serve as the number of target objects appearing in the target area, and generating the behavior statistical form of the target object according to the statistical result.

The invention which relates to a process or continuously and rapidly determining components in desulfurization gypsum belongs to the field of chemical detection. The process adopts iodometry, a back titration method with sodium hydroxide and a gravimetric method with barium sulfate in sequence to determine. The process of the invention has the advantages of reasonable design of test steps, easy and laborsaving operation, low cost, less pollution, high accuracy and less test workload.

The invention discloses a large-scale photovoltaic power station and distribution grid harmonic wave cross-impact analysis model building method and belongs to the technical field of new energy power generation and transmission. The large-scale photovoltaic power station and distribution grid harmonic wave cross-impact analysis model building method is mainly used for analyzing harmonic wave interaction influence of a large-scale photovoltaic power station and a distribution grid. The large-scale photovoltaic power station adopts a power electronic device as a grid-connection interface and can fill a large amount of harmonic wave into a power grid inevitably, and by means of specificity of a photovoltaic inverter, the generated harmonic wave has the advantages of being wide in broadband, high in frequency and capable of generating series-parallel connection resonance with distributed capacitors of the power grid. A large-scale photovoltaic power station and distribution grid harmonic wave cross-impact analysis model is formed by a photovoltaic harmonic analysis model and a distribution grid equivalent circuit, the photovoltaic harmonic analysis model is used for analyzing power station harmonic wave output characteristics, and the distribution grid equivalent circuit is used for representing the distribution grid which the power grid is connected in. The large-scale photovoltaic power station and distribution grid harmonic wave cross-impact analysis model can provide a theoretical basis for issues of photovoltaic power station and distribution grid planning, harmonic wave estimation, estimation of photovoltaic power station accepting capability of the distribution grid, photovoltaic grid connection regulation formulation and the like.

The invention discloses a method for determining effective stress coefficients of a rock. The method comprises the steps of preparing a rock test sample and measuring and recording the size of the rock sample; loading the rock sample into a pressure chamber of a triaxial servometer, loading confining pressure to a predetermined value, keeping the confining pressure, constantly loading bias, loading the bias to a set value, unloading, keeping the bias and the confining pressure constant and loading pore water pressure; repeating the previous step and loading the bias until the rock sample is destroyed; drawing a relation curve of bias increments and axial / circumferential strain increment under different confining pressure and carrying out data fitting on the curve to obtain an effective elastic modulus E1 and poisson ratio v31 related to bias grades; and calculating an axial effective stress coefficient and a circumferential effective stress coefficient of the rock sample through a formula. The effective stress coefficients obtained through the method are accurate and reliable, and can be applied to numerical calculation of seepage and stress coupling in practical engineering, the calculation accuracy is greatly improved and the analysis error is reduced.

The invention belongs to the field of power plant safety control systems, and particularly relates to a multi-dimensional data anomaly detection method and device based on XGBoost. The method is characterized by comprising a first step of data acquisition and cleaning, a second step of performing standardization processing on cleaned data, and unifying dimensions between data of different dimensions; step 3, feature extraction and dimension reduction; step 4, exception detection model training: training the dimension reduction data by using an XGBoost method, and establishing a prediction model of equipment exception; and step 5, abnormity on-line detection is carried out, and if a given threshold value is exceeded, it is determined that abnormity occurs. The method is suitable for processing and predicting important abnormal events of equipment, the thought and technology of ensemble learning are fully utilized, important features in multi-dimensional data information detected by an equipment sensor are effectively utilized, and then online abnormal detection based on real-time measuring point data of a power plant is achieved. The method is large in collected data volume, small in analysis error and high in early warning result accuracy.

The invention belongs to the new material alloy element analysis technology, and relates to an analysis method for determining titanium, vanadium, tungsten, manganese and silicon in a K25 chromium-base high temperature alloy. The analysis steps comprise: weighing a sample; preparing a sample solution; preparing a calibration solution; measuring concentrations of titanium, vanadium, tungsten, manganese and silicon in the sample solution; and calculating the measurement result to obtain contents of titanium, vanadium, tungsten, manganese and silicon. According to the present invention, the ICP-AES method for determining contents of titanium, vanadium, tungsten, manganese and silicon in the K25 chromium-base high temperature alloy is provided, wherein the method has characteristics of high analysis sensitivity, simple operation, short analysis period, high efficiency and wide application prospect, can meet engineering application of the high temperature alloy, can meet requirements of scientific research and production on material quality control, and further has characteristics of product scrap rate reduction, development saving and production cost saving.

The invention discloses a method for determination of the polychlorotrifluoroethylene (PCTFE) content in a polymer-bonded explosive (PBX) by near infrared spectroscopy. The method includes the steps of: preparing and collecting 260 PBX samples, taking 180 samples of them as a calibration set for establishing a calibration model, taking the remaining 80 samples as a validation set for model validation, and acquiring the near infrared spectrum data of all the samples; using a standard method to determine the PCTFE content in the samples; subjecting the spectrum data of the validation set samples in the wave bands of 6102.0cm<-1>-5697.0cm<-1> and 4680.2cm<-1>-4242.9cm<-1> to a first order derivative treatment, correlating the treated spectrum data with the PCTFE content by a partial least squares method, and establishing the calibration model by cross validation; employing the calibration model to predetermine the PCTFE content of the validation set samples, and selecting an optimal model according to a minimum root mean squared error of prediction (RMSEP) of the validation set; and acquiring the near infrared spectrum data of the samples to be determined, and making use of the optimal model to obtain the PCTFE content directly. Being suitable for determination of the PCTFE content in a PBX explosive, the method has the characteristics of convenient operation, and rapid and accurate analysis.

The invention discloses a method for analyzing arsenic content in a glass refining agent, which comprises the following steps: processing samples by a potassium permanganate preoxidation-hydrofluoric acid wet digestion method to obtain a sample digestion solution; measuring the content of arsenic in the digestion solution by an inductance coupling plasma atomic emission spectrometry. By using potassium permanganate as a pre-oxidizing agent to carry out routine wet acid digestion on glass refining agent samples, the method can effectively avoid volatilizable loss of low-valent arsenic components in the preliminary processing of the samples, therefore, a routine inductance coupling plasma atomic emission spectrometer can be used to directly measure the content of the effective content-arsenic in the glass refining agent without allocating a hydride generator or an atomic fluorescence spectrometer. The method has the advantages of high operability, high analysis speed, high accuracy and favorable sensitivity and repetitiveness.

The invention relates to a plantar pressure analysis method. The method comprises the following steps of: obtaining plantar pressure data and preprocessing the plantar pressure data to obtain plantar pressure indexes (a plantar pressure maximum value, a plantar pressure average value, a plantar pressure variance, a plantar pressure standard deviation, a pressure intensity and the like); further processing a plantar pressure round edge in the preprocessed plantar pressure data to obtain a smooth plantar image satisfying a predetermined requirement; and partitioning the smooth plantar pressure image to obtain foot indexes (a foot contact area, a foot gravity center, an arch length, a foot length and a foot width), and analyzing a standing posture, strephenopodia and strephexopodia indexes and arch indexes of a testee. Through the plantar pressure analysis method, the plantar pressure distribution condition can be comprehensively analyzed, the further analysis for the plantar pressure data is realized, the analysis result is optimized, the analysis error is decreased and various plantar pressure indexes are obtained correctly.

The invention discloses a power failure risk computing method for an electric power system containing double-fed wind power plant. The power failure risk computing method comprises the steps of pre-establishing multiple models, wherein a simulation process comprises the steps of determining the initial working condition of a system, and setting an initial fault; determining whether a short circuit fault or line broken fault occurs or not, if the short circuit fault occurs, processing according to an off-network model of a wind turbine generator, and then performing island-division searching; determining a frequency fall-off and recovery condition of an electrical island according to a frequency stabilization model, and enabling the electrical island to restore to a power balancing state; carrying out alternating current power flow calculation on the system and determining whether the system is converged or not, if not, solving a power flow convergence boundary, and analyzing voltage weak points; switching loads for the voltage weak points; next, determining whether the system is restored to be stable or not, if not, determining that the current wind power plant system is subjected to global voltage collapse, cutting all loads; and if the system is restored to be stable, determining whether a tangent line exists or not, if so, returning to perform the island-division searching step, and or otherwise, finishing the simulation process. By adoption of the power failure risk computing method, the load reducing amount required by the system for system recovery can be reduced to the minimum, and cascading failure analysis error is lowered.

The invention provides an integrated micro-fluidic chip used for fluorescence detection of an enzyme catalysis product. The chip is mainly composed of two layers of micro-channel network; as shown in a figure 1, the lower-layer micro-channel network is composed of roundabout broken line channels and used as a concentration gradient generation unit; as shown in a figure 2, the upper-layer micro-channel network in the chip is composed of branch channels symmetrically increasing layer by layer, connected with six columns of broken line channels and six expansion channels and used as an equivalent distribution unit, a fluorescence derivative reaction unit and a fluorescence detection window; and the upper-layer micro-channel network is communicated with the lower-layer micro-channel network. The micro-fluidic chip integrates an automatic concentration gradient generation function, an equivalent distribution function, an enzyme area immobilizing function, an enzymic catalytic reaction product separating function, a product fluorescence derivatization function and a fluorescence detection function into one, can be used on a standard ELIASA for acquisition of analysis data and provides a solution for related analysis in fields like the industry, agriculture, medicine and environmental science.

The present invention belongs to the field of power plant security control systems, and particularly relates to an LSTM-based gas turbine online detection method and apparatus. The method is characterized in comprising the following steps: data collection; normalization processing; feature extraction; LSTM abnormality detection model training; and online abnormality detection: inputting to-be-detected data to a trained detection model, to obtain a model prediction value, calculating a difference between the prediction value and a sensor measured value to obtain an absolute value, and if the absolute value exceeds a given threshold, determining that abnormality occurs. The method is suitable for processing and predicting important events with a relative long interval and delay in a time series, and is suitable for analysis and fitting of the time series. A deep learning concept and technology is fully utilized to automatically select and extract hidden characteristics in data information detected by a device sensor, so as to implement online abnormality detection based on gas turbine real-time measuring point data. The LSTM-based gas turbine online detection method is large in collected data quantity, small in analysis error, and high in early warning result accuracy rate.

The present invention discloses an convergence RLC circuit model-based method for analyzing subsynchronous resonance in a power system. The method comprises the following steps of: establishing a power plant model and a series compensated transmission line system model so as to acquire a non-linear differential equation model of each subsystem; generating a state equation model according to a parameter under a particular working condition and the non-linear differential equation model; generating an algebraic equation model according to the Laplace transform and the state equation model; acquiring a final equivalent resistance model so as to acquire a series resonance point; aggregating the final equivalent resistance model into an equivalent second order RLC electric circuit model according to the series resonance point; and quantifying SSR analysis. According to the analysis method provided by an embodiment of the present invention, the final equivalent resistance model is aggregated into the equivalent second order RLC electric circuit model, so that the SSR analysis is quantified, thus implementing the accurate quantification evaluation of SSR, reducing analysis errors and improving analysis accuracy.

The invention relates to a grinding ball sensor used for monitoring internal medium motion status of a ball milling machine. The grinding ball sensor includes an inertial sensor circuit board, a spherical bearing body, a battery and a wireless charging receiver. The inertial sensor circuit board, the battery and the wireless charging receiver are arranged in the spherical bearing body. The battery is used for supplying power to the inertial sensor circuit board. The inertial sensor circuit board includes a six-shaft inertial sensor, a temperature sensor, a wireless transmission module, an embedded CPU, a flash memory and a power supply management module, wherein the six-shaft inertial sensor and the temperature sensor send the acquired data to the embedded CPU respectively. The embedded CPU stores the received data in the flash memory. After data acquisition is finished, the embedded CPU reads the content of the flash memory and sends the read content to a host computer through the wireless transmission module in a wireless transmitting manner. The wireless charging receiver charges the battery in a wireless manner. The spherical bearing body comprises a ball cover and a ball base.

The invention relates to proton exchanging film fuel cell membrane electrode platinum loading analysis, concretely to a measuring method for proton exchanging film fuel cell membrane electrode platinum loading. The method includes steps: 1) accurately measuring size and quality of a MEA sample, heating the MEA sample to adequately incinerate carbon in the MEA sample, after cooling, adding thick sulfuric acid and thick nitric acid to the sample, and heating solution to completely dissolve platinum; 2) adding water to scale to prepare measured sample solution; 3) measuring platinum content in the solution by inductance coupling plasma atom emission spectroscopy method, calculating membrane electrode platinum loading in MEA sample. The invention obtains measured sample by an MEA direct treatment method, uses an ICP-AES analysis method which has high sensitivity, high accuracy, fast process, simple operation and good feasibility to measure platinum content, and estimates MEA which is key material of PEMFC.

The invention discloses a method and a system for determining sulfide content in water body. The method for determining the sulfide content in the water body comprises the following steps: sampling the sulfide-containing water body, collecting the hydrogen sulfide gas through a chemical reaction; performing spectrum detection on the collected hydrogen sulfide gas, obtaining a hydrogen sulfide gas absorbance spectrum feedback optical signal; transiting the obtained hydrogen sulfide gas spectrum absorbance optical signal to a data signal; analyzing the hydrogen sulfide gas absorbance spectrum feedback data signal, drafting a work curve by taking the concentration of a standard sample as abscissa and taking the absorbance of the standard sample as ordinate, and calculating the sulfide content by determining the absorbance of the sample to be measured. By employing the system for determining the sulfide content in the water body, detection process is simple and fast, the detection result is accurate and reliable, the detection cost is low, analysis operation is simplified, analysis speed is increased, and analysis error is reduced.

The invention relates to a sampling bottle for measuring soil release gaseous mercury. The sampling bottle comprises a bottle body and a rubber plug matched with the bottle body, wherein a sampling pipe, an air inlet pipe and an inert gas inlet pipe are arranged on the rubber plug; the sampling pipe, the air inlet pipe and the inert gas inlet pipe are respectively communicated with the interior of the bottle body and are used for connecting gas inside and outside the bottle body; and airbag is arranged at one end of the air inlet pipe inserted into the bottle body. According to the sampling bottle, when the same amount of soil sample is tested, a large amount of gas samples can be collected, and the analytic error is reduced; sampling is directly performed at the sampling pipe orifice, and gas loss is avoided; and moreover, due to the airbag, the phenomenon that the actual sample gas amount is reduced due to the reduction of air pressure in the bottle body is avoided because the outside air enters the airbag to balance the air pressure in the bottle during sampling.

The invention relates to a gas chromatography detection system and method for online analysis of trace He, H2 and impurity components in Ne. The system comprises a ten-way valve I (1), a quantification tube I (5-1), a quantification tube II (5-2), a first predissociation chromatographic column (6-1), a six-way valve I (2), a first dissociation chromatographic column (7-1), a six-way valve II (3), a second dissociation chromatographic column (7-2) and a plasma emission detector (8); a second valve way comprises a ten-way valve II (4), a quantification tube III (5-3), a second predissociation chromatographic column (6-2), a third dissociation chromatographic column (7-3), a heat conduction detector (9) and matched pipelines. With the adoption of the system and the method, content of the trace He and H2 components and O2, N2, CH4 and CO impurity components in Ne as well as content of H2, O2, N2, CH4 and CO impurity components in He can be accurately analyzed online, the gas analysis process is simplified, and gas analysis errors are reduced.

The invention provides a steam turbine axial vibration data collecting and processing method. According to the invention, multiple channels of original vibration signals are collected synchronously ata high speed and pre-treatment and software resampling are performed on the signals. Real time feature extraction is performed according to analysis requirements and feature values are standardized and then remotely transmitted in an encrypted manner. Two software resampling treatments including equal-angle software resampling and equal-time software resampling are performed on different analysisunits of each channel separately. shaft centre orbit analysis is performed on equal-angle sampling data, so that analysis errors are reduced. When performing frequency spectrum calculation, the vibration frequency spectrum of the steam turbine when rotating for each cycle is calculated separately and then the values are added up and averaged, so that errors caused by adopting identical sampling rate in multiple cycles are reduced. In a data transmission process, only the feature values required by data analysis are sent, so that transmission of the original vibration data is avoided and requirements on network bandwidth are reduced substantially.

The invention discloses a rotation machinery torsional vibration signal collection analysis method, comprising steps of installing a marking device at a rotation shaft measurement cross section of a device to be tested, installing a matching detection device, removing low frequency interference in an outputted pulse signal, converting the pulse signal to a standard TTL pulse signal, utilizing a high frequency counter to perform signal collection to obtain a series counting value, using an obtained series counting value to solve a series transient angular speed value, solving the series uniform angle collection transient torsional angle speed value, solving a series equal-time-interval sampling transient torsional angle speed value, solving the real torsional angle speed signal, performing integral transformation on a real torsional angle speed signal after the trend item is eliminated to obtain a torsional vibration angular displacement signal. The invention maximally improves the accuracy and reliability of rotation machinery torsional vibration signal analysis and has high reliability and high measurement accuracy.

The invention discloses a method of obtaining characteristic parameters of an aerobic composting microstructure. The method provided by the invention comprises the following steps: (1) respectively blending and sampling a composting body in an aerobic composting process at more than two time points; (2) vacuum freeze drying the obtained sample to obtain a granular sample to be measured with particle diameter smaller than 2mm; (3) detecting the median particle diameter D50 of the granular sample to be measured, and drawing a change trend chart; (4) detecting the shape factors of the granular sample to be measured, and drawing a change trend chart; (5) obtaining the average porosity of a composting micro-unit, and drawing a change trend chart; and (6) determining the thickness of an aerobic layer, and drawing a change trend chart. The method provided by the invention can be used for effectively solving the realistic problem of creation and characterization difficulty of the microstructure in the existing aerobic composting numerical simulation and mechanism research processes, and facilitating the energy saving and emission reduction in the composting process, improving the reaction mechanism research and enhancing scientific and practical engineering technology and equipment research and development.

The invention discloses a statement similarity analysis method and device and computer equipment, relates to the technical field of computers, and can solve the problems that when statement similarityis calculated, an analysis result is large in error and not accurate enough. The method comprises the steps of determining a received text statement and any basic statement stored in a knowledge baseas target statements with the similarity to be analyzed; configuring a target weight corresponding to each word in the target statement according to the correlation between the words; constructing atarget sentence vector of the target statements based on the target weight; analyzing interaction comparison information between the target sentence vectors corresponding to the two target sentences respectively; and based on the interaction comparison information, determining statement similarity between the two target statements. The invention is suitable for analyzing the similarity between thesentences.

The embodiment of the invention discloses a log analysis method and device for a server system and the server system. The method includes the steps that management-level logs or OS-level logs in the server system are captured; the management-level logs or the OS-level logs are screened according to set key words, and warning information is output; classified statistics is conducted on problems inthe management-level logs or the OS-level logs, and a log analysis report is generated. By adopting the technical scheme of the embodiment, logs of various modules can be automatically analyzed, manual intervention is not needed, manpower is saved, and efficiency is improved; besides, analysis errors caused by artificial statistics mistakes can be reduced.

The invention provides a method for rapidly detecting naphthalene component concentration in coal tar, relating to a detection method of coal tar components, which comprises the following steps: dissolving refined naphthalene and dimethylbenzene to prepare a naphthalene standard solution, and analyzing the naphthalene standard solution records with a gas chromatography to calculate a peak area of the naphthalene; dissolving the coal tar and the dimethylbenzene by heating to 50-80 DEG C to prepare a sample solution, injecting the sample solution into a quartz capillary column, and controlling the parameter record results, such as time, temperature and the like to obtain the peak area of the naphthalene in the sample solution; and comparing and calculating the peak area of the naphthalene in the naphthalene standard solution and the measured peak area of the naphthalene in the sample solution, thus obtaining the naphthalene component concentration in the coal tar components. The invention has the following advantages: utilizing the dissolution method instead of a traditional extraction method; saving detection time by 50%, and saving consumptive materials by 60% due to low dimethylbenzene cost; and reducing analysis error, with more than 99.8% of accuracy and more than 99.5% of precision.

The invention relates to a method for determining the content of magnesia in phosphorus ore, which comprises the steps of: when the content of the magnesia in the phosphorus ore is determined, directly placing filter paper together with a precipitate into a beaker after solution forms the precipitate and is filtered, dissolving the precipitate in 20mL of solution of hot hydrochloric acid, then performing subsequent titration step and blank experiment to calculate the content of the magnesia in the phosphorus ore, but not adopting hot hydrochloric acid and hot water to wash the precipitate on the filter paper. The method can effectively reduce analytical error and improve analysis precision.

The invention discloses a rapid analysis method for sodium hydroxide and ammonia content in sodium cyanide reaction solution and its liquid products, which uses excess formaldehyde and ammonia to react to generate hexamethylenetetramine, and then divides into two groups of titration with hydrochloric acid, Obtain two sets of values ​​of ammonia-containing acid consumption and ammonia-removing acid consumption, and then calculate the content of sodium hydroxide and ammonia in the sample through data measurement, thereby effectively reducing the interference of free ammonia on the analysis of sodium hydroxide content, and quickly and accurately analyzing cyanide. Sodium hydroxide content and ammonia content in sodium chloride reaction liquid and its liquid products. The method of the invention is fast and effective, has obvious mutations in analysis and titration, accurate and reliable measured values, simple and convenient operation and easy mastery.

The invention discloses a method for detecting fat-soluble vitamins in a blood sample and belongs to the technical field of vitamin detection. The method includes the pretreatment of the blood samplewith a simple liquid-liquid extraction method, and the quantitative analysis with an internal standard curve method with the relative retention time of five fat-soluble vitamins and detected quantitative ion-pair information by using the methods of chromatographic separation and mass spectrometry detection. The technical indicators such as a recovery rate, a detection limit and precision of the method of the invention meet the requirements, the operation is simple, the error is small, the analysis time is short, the reproducibility is good, the requirements of clinical sample detection are met, and the method is easy to promote and popularize.

The invention relates to a sampling device for exhaust particles of an engine. The sampling device is characterized in that a lower cover is arranged inside a casing pipe of a base and can move up and down; an upper cover and the lower cover are automatically compacted by springs; and filter paper installing plates are arranged between the upper cover and the lower cover. When the springs are compressed, the upper cover, the filter paper installing plates and the lower cover are sealed; exhausts of the engine inflow, the exhaust particles are filtered by filter paper, and the exhausts outflowthrough the lower cover and the casing pipe of the base; the multiple filter paper installing plates are arranged on the same turntable; the turntable can rotate around a fixing shaft parallel to themiddle axes of the upper cover and the lower cover; when a certain amount of particles are collected, the springs are compressed again so as to lead the upper cover, the filter paper installing plates and the lower cover from being separated; the turntable is rotated so that the installing plates, in which clean filter paper is placed, are rotated between the upper cover and the lower cover; and after the springs are loosened, the filter paper sealing is realized again for carrying particle sampling. The sampling device has the characteristics of having simple structure, being convenient to operate and being capable of realizing the online connection and replacement of the filter paper.