1447 results about "Online analysis" patented technology

A fluid contamination analyzer employs one or more MEMS-based sensors. The sensors are incorporated into probes or alternatively may be employed in an in-line analyzer residing in the fluid. The sensors, which can be selective to detect a distinct contaminant within the fluid, sense an impedance of the fluid, which is a function of its contamination and communicates the impedance to analysis circuitry.

Described herein are integrated systems for generating neutrons to perform a variety of tasks including: on-line analysis of bulk material and industrial process control (as shown in FIG. 1), security interrogation (as shown in FIG. 2), soil and environmental analysis, and medical diagnostic treatment. These systems are based on novel gas-target neutron generation which embodies the beneficial characteristics of replenishable fusible gas targets for very long lifetime, stability and continuous operation, combined with the advantageous features common to conventional accelerator neutron tubes including: on / off operation, hermetically sealed operation, and safe storage and transport. Innovative electron management techniques provide gas-target neutron production efficiencies that are comparable or surpass existing sources. The high-pressure high-resistance gaseous discharge is presented as a favorable gas-target neutron generator embodiment, combining ion source regions, accelerator regions, gas-target regions and electron management components within a single simple cost-effective device that is adaptable to various geometric configurations that provide specific neutron emission profiles for greater analysis capacity.

The invention discloses a behavior identification method based on a recurrent neural network and human skeleton movement sequences. The method comprises the following steps of normalizing node coordinates of extracted human skeleton posture sequences to eliminate influence of absolute space positions, where a human body is located, on an identification process; filtering the skeleton node coordinates through a simple smoothing filter to improve the signal to noise ratio; sending the smoothed data into the hierarchic bidirectional recurrent neural network for deep characteristic extraction and identification. Meanwhile, the invention provides a hierarchic unidirectional recurrent neural network model for coping with practical real-time online analysis requirements. The behavior identification method based on the recurrent neural network and the human skeleton movement sequences has the advantages of designing an end-to-end analyzing mode according to the structural characteristics and the motion relativity of human body, achieving high-precision identification and meanwhile avoiding complex computation, thereby being applicable to practical application. The behavior identification method based on the recurrent neural network and the human skeleton movement sequence is significant to the fields of intelligent video monitoring based on the depth camera technology, intelligent traffic management, smart city and the like.

The present disclosure describes an apparatus and methods for performing data analysis, in particular network analysis. Specifically it provides a framework and user interface whereby raw data may be imported into a data model with entities, attributes, and relationships between the entities and multiple data analysis algorithms may be pipelined into a larger data analysis model and applied to the data model. Offline and online data visualization and data exploration techniques, may be applied to the results of the data analysis enabling real-time and near real-time interactive online analysis. Extensibility models and market transaction models are also provided.

Certain example embodiments relate to using Complex Event Processing (CEP) techniques for statistical analysis of cache behavior and parameters, e.g., in connection with large, potentially heterogeneous data sets (e.g., “Big Data”). A dedicated stream mining operator registers a listener to a cache and receives notifications on cache operations. For selected element attributes, a first model estimates the probability density functions of the attribute values, delivering well-defined estimates of the attribute value distributions. A second model analyzes the time elements stay in the cache (“validity”). Validity is combined with the attribute value distribution. A meaningful analysis model (Cache Element Model) can be derived by combining additional summary statistics for the validity with the attribute value distribution, describing how long elements stay in the cache for attribute values of a specific region, and how the values are distributed. It may be used to inform administrative tasks such as, optimization of cache parameters.

The invention discloses a load balancing method based on program behaviour online analysis under a heterogeneous multi-core environment, which comprises the steps of: being compatible with a heterogeneous multi-core environment of the traditional scheduling domain model, dynamically monitoring task characteristics, calculating a logic CPU load, and balancing loads of program behaviour perception. The load balancing method is completely compatible with the traditional operating system scheduling strategy, is simple and efficient, and is suitable for popularization; and an algorithm is tested on an actual software and hardware platform.

The invention provides a lithium battery thermal runaway early warning and automatic control method, which is characterized by, to begin with, establishing a mathematic model for judging lithium battery thermal runaway development process by utilizing environmental data; then, collecting environmental data of a lithium battery in real time by utilizing a plurality of sensors, and carrying out on-line analysis on change of the collected multiple environmental data with reference to the established mathematic model to judge lithium battery thermal runaway occurrence risk or thermal runaway; and once thermal runaway causes fire, a fire control device is automatically and immediately started to control expansion of the thermal runaway, thereby reducing thermal runaway risk to the lowest degree, and preventing serious safety accidents of an electric automobile to the maximum degree.

The invention discloses an infrared cavity ring-down spectroscopy trace gas detection method based on quantum cascade laser; comprising the following steps: using a tunable quantum cascade laser as alight source, and selecting measuring waveband and wavelength scan step length aiming at spectrum line characteristic of the gas to be detected; respectively measuring the cavity ring-down time of each wavelength in the cavity with absorption or without absorption by cavity ring-down technique, and calculating the gas absorption coefficient of corresponding wavelength so as to obtain a relation curve that is an absorption spectrogram of the measured gas absorption coefficient and toned laser wavelength. The spectrogram is contrasted with spectrum line characteristic of corresponding gas in HITRAN database, thereby being capable of analyzing and determining weather the measured gas contains the predetermined gas component; the absolute concentration of the gas to be measured can be calculated and obtained and the absolute concentration of the gas to be measured can be measured through scaling measurement by using absorption peak wavelength of the absorption spectrum as the best detection wavelength and the relation among the gas absorption coefficient of the wavelength, the absorption cross section and concentration. The method has high measuring sensitivity and high property of resisting interference so that the fast and exact on-line analysis and detection of multiple trace gases are easily realized.

The invention provides a smart grid-oriented power quality monitoring system and a smart grid-oriented power quality monitoring method, which relate to the field of monitoring of power quality. The system comprises a distributed online / offline node detection module, a network communication module, a distributed database module and a comprehensive management module of the power quality monitoring system, wherein the distributed online / offline node detection module comprises a parallel analog-to-digital conversion module and a signal processing module so as to realize distributed detection of asmart grid. In the technical scheme provided by the invention, a plurality of analog-to-digital conversion chips are connected in parallel and an analog signal is sampled, so that high-accuracy sampling rate of signals is increased and the detection requirement on transient power quality signals is met; based on a programmable logic chip, online analysis and data compression are realized by a parallel signal processing algorithm; a distributed database is adopted, so that system reliability is enhanced and system upgrade is promoted; and a global positioning system (GPS) and a communication network module are adopted, so that a distributed network system is realized, and power quality monitoring of the smart gird is supported powerfully.

The invention discloses an intelligent ship-borne terminal device for inland waterway intelligent shipping information service. The ship-borne terminal device consists of a power supply module, a data collection module, a main control module, a communication module and a human-computer interaction module; and an online analysis processing technology, multiple sensing technologies (global positioning system (GPS), automatic identification system (AIS), wireless frequency identification devices (RFID), sensors and videos) and a communication technology are utilized by the invention to realize the automatic identification of a ship identity and the perception of a running status of the ship by aggregating, rebuilding and interacting polymorphic heterogeneous data under the sailing status of the inland waterway ship, so that solid guarantee can be provided for the ship data perception of an inland waterway intelligent shipping information service system, the realization of ship-ship interconnection, ship-bank interconnection and ship-cargo interconnection and for the safe sailing and high efficient transportation of inland waterway ships in China, and the rapid development of the inland waterway intelligent shipping information service (internet of ships) can be promoted.

The invention relates to a method for optimizing the cracking depth of an industrial ethane cracking furnace on line. A cracking furnace yield neural network multi-model is established by utilizing a mechanism model and practical production data as training samples and combining a cracking raw material clustering result, model input variables comprise raw material density, sum of raw material linear chain alkane contents, ratio of raw material N-alkane content and isoparaffin content, feed flow, gas and hydrocarbon ratio, coil outlet temperature (COT) and coil outlet pressure, and model output variables comprise ethane yield and propylene yield (or triene total yield). A belonged submodel is judged according to a practical measuring value of an oil product, and the cracking depth output by the submodel is corrected on line by a cracked gas online analyzing instrument; an optimal cracking depth value and the gas and hydrocarbon ratio are confirmed by utilizing an SQP method and taking maximal economic benefits as a target through the constraints of the cracking depth and the gas and hydrocarbon ratio, and the cracking depth value is continuously optimized back and forth nearby the current cracking depth value of the cracking furnace. The method is reasonable, reliable, simple and easy, is easy to transplant and has wide adaptability.

A method is described for providing rapid on-line analyses of chemical compositions such as chemical process streams, utilizing near-infrared (NIR) spectroscopy in combination with chemometrics. In the method, for each type of analysis to be conducted, a database is provided by analyzing a series of samples using standard laboratory analytical procedures, utilizing the results as reference values to establish quantitative calibration models from NIR spectroscopy using chemometric techniques and storing this information in a computer database. An NIR spectroscopic system is also provided comprising a transflectance or a transmittance probe coupled via fiber-optic cables to a stable white light source and a spectrograph. The probe is inserted into a test sample or chemical process stream to be analyzed, a stable white light of selected wavelength range is beamed to the probe and the spectra obtained on the spectrograph are recorded. Finally the spectra obtained are correlated to the reference data stored in the computer to obtain a rapid measurement of the analysis desired.

The invention provides a bad data detection and identification method based on the measurement of a PMU (Phasor Measurement Unit) and the measurement of an SCADA (Supervisory Control and Data Acquisition). The method comprises the following steps: obtaining a network computing module by performing network topology analysis, detecting and identifying bad data based on an incidence matrix representing network topology relation, and detecting and identifying the bad data based on dynamic partition. The bad data detection and identification method based on the measurement of the PMU and the measurement of the SCADA is high in practical level, can be widely applied to current provincial power grids and national power grid, can adapt to requirement on online analysis of future large power grids, can rapidly and accurately remove bad data in measured information, and can improve mode estimation accuracy.

The invention discloses a trace gas detection device and a trace gas detection method based on an intermediate infrared quantum cascade laser direct absorption spectrum method. A tunable quantum cascade laser serves as a light source, and concentration information of gas molecules to be measured is acquired by utilizing fundamental frequency fingerprint absorption characteristics of the gas molecules in an intermediate infrared wave band; the measured result is slightly influenced by light-intensity variation of the laser and has higher signal to noise ratio and certain anti-jamming capability by utilizing a direct absorption spectrum technology; and whether the measured gas contain expected gas components can be analyzed and determined by contrasting the measured spectrum with spectral line characteristics of corresponding gas in a HITRAN database, and concentration inversion is performed by utilizing spectral line parameters provided by the HITRAN database. The system is simple and compact in structure and convenient to use and maintain, has the characteristics of high measuring sensitivity, high accuracy and high response speed, can rapidly and accurately analyze and detect a plurality of trace gases and isotope ratios on line, and can be used for indicating and rapidly and accurately positioning intermediate infrared light spots.

The invention discloses a multispectral-based multipoint sampling multiparameter water quality on-line analytical system, comprising an optical system, a waterway system and a detection control system, wherein the optical system is used for scanning the ultraviolet-visible light transmitted spectrum, and fluorescence and Raman emission spectra and the like of a water sample to be detected by adopting a multi-wavelength laser, a pulsed xenon lamp and a charge coupled device (CCD) spectrum detector and converting the scanned spectra into digital signals; and based on multipoint sampling design, the waterway system is used for enabling quantified sewage and clear water to enter into a sampling device through controlling the on and off of a water pump and a solenoid valve so as to realize the collection of the spectroscopic data, moreover, the waterway system has a function of automatically cleaning a sewage pipeline system; and an industrial personal computer is adopted as a core processing unit of the detection control system. The whole system can automatically and continuously operate and is suitable for online analysis.

The invention discloses a proximate analyzing method for coal quality base on multivariate linear regression, The invention is characterized in that a set of samples with known proximate analysis index values is used, plasma spectrum data is obtained by detection of a coal quality on-line analysis system of LIBS (Laser-Induced Breakdown Spectroscopy), the proximate analysis of fire coal samples to be measured by a multivariate linear regression correlation of each proximate analysis index value are respectively established, the characteristic spectral line strength which has substantial contribution to proximate analysis index values is respectively introduced through the established multivariate linear regression correlation to obtain the proximate analysis results. According to the invention, the spectral line information of correlative elements which has substantial contribution to each proximate analysis index is comprehensively utilized, the process for analyzing the index by fire coal proximate analyzed by the LIBS can be simplified, and the speed and the accuracy of the quantitative analysis can be raised.

The present invention is a method and system for detecting an abnormal on-line analysis or laboratory measurement and for predicting an abnormal quality excursion due to an abnormal process condition.

The invention discloses an extraction method for brain-computer interface system imagination action EEG signal features, in particular to an EEG feature extraction method based on a wavelet transform and a BP neural network. The invention takes the energy change caused by imagination action thinking to be a feature distinguishing the imagination movements of a left hand and a right hand, respectively calculates the point-to-point average power of the entire samplings of the EEG signal obtained from C3 and C4 channels by the left hand and the right hand through the imagination (thereinafter called as C3 and C4 of the left hand and the right hand) within 0 to 9s according to the average power formula. A time window is arranged, a discrete dyadic wavelet transform is made to the data of a section provided with the window, an approximation signal a6 on a sixth size is selected to be taken as a signal feature; a BP neural network is used as a classifier to classify. The method of the invention adopting the wavelet transform and the BP neural network to extract the potential of the imagination movement helps to improve the signal / noise ratio and the identification correction rate of the potential of the imagination action; in addition, the wavelet transform is a linear transform, has a quick calculation speed, and is suitable for on-line analysis.

The invention belongs to the technical field of electric power system source-grid joint simulation and operation control, and discloses a grid-source joint simulation and a multistage dispatch closed-loop control system for grid-source joint simulation. The multistage dispatch closed-loop control system comprises a power source side simulation sub system, a power grid side simulation sub system, a protocol conversion module and a dispatch sub system, wherein the power source side simulation sub system is used for simulating work states of all units and adjusting the work states of simulation units according to a control command and adjusting parameters, the power grid side simulation sub system is used for generating power grid simulation data and transferring the control command and the adjusting parameters to the power source side simulation sub system, the protocol conversion module is used of achieving data conversion, and the dispatch sub system is used for generating the control command and sending the control command to the power grid side simulation sub system. The multistage dispatch closed-loop control system for grid-source joint simulation can be used for simulating joint simulation of large-scale wind power integration, the frequency changing condition of a power grid in the wind power changing process can be reflected more truthfully, and real-time data sources are provided for online analysis and study of an energy managing system, a wide area measuring system and distribution type state estimation.

The invention provides an on-line sugar concentration real-time detection system aimed at problems of low sampling speed of a small-scale biochemical reactor and lag of sugar concentration on-line detection. The system is mainly composed of an embedded module, a touch screen, a constant flow pump, an on-line sugar concentration analyzer, an off-line sugar concentration analyzer and the like. The touch screen is a man-machine interface and receives arrangement and operation of on-site personnel. The embedded module controls the flow rate of the constant flow pump and the action of the sugar concentration analyzers as a control unit of the system, collects the sugar concentration detection values of the on-line sugar concentration analyzer, performs on-line correction to the collected values, obtains accurate sugar concentration detection values in the biochemical reactor, and can amend model parameters according to the values of the off-line sugar concentration analyzer. The system integrates the information of the off-line analyzer and the on-line analyzer, combines the advantages of accuracy of off-line detection and real time of on-line detection, and is suitable for real-time detection of some small-scale biochemical reactors.

The invention relates to a cloud driving training system based on virtual reality and big data online analysis. A precise dynamic model, a road spectrum, a real training field and a driving environment 3D scene of a real vehicle are combined. The cloud driving training system provided by the invention has the advantages that a student performs vehicle driving simulated study by using a real vehicle operation and control device and a virtual reality helmet; the driving behavior data in the study process and the driving process scene video are uploaded to a system cloud side; after the big dataanalysis, the individualized evaluation and suggestion of the driving process can be formed. The system has the advantages that a customized three-dimensional virtual driving model consistent to the real driving field can be issued from the cloud end according to the user requirements and the system is used for training before driving exam or simulated training, driving experience and game in complicated environment; after the driving behavior data and the driving scene data in the driving process are synthesized, through big data analysis, a driver is guided to timely correct the driving behavior, so that the training according to the requirements can be realized; the driving training efficiency is effectively improved.

The invention discloses a device for analyzing gas phase chemical components of cigarette smoke on line, which is characterized in that: a smoke-transmitting quartz capillary is arranged between the sucking barrel of a smoking machine and an on-line analytical mass spectrometer; two openings are formed on the end faces of the sucking barrel; one opening is a smoke analysis sampling opening; the other opening is a smoke importing and exporting opening which is connected with a three-way pipe; the three-way pipe is communicated with a cigarette holder which can continuously switch and a pipeline vacuum extracting opening at the same time; a vacuum ultraviolet ionization area is formed in the on-line analytical mass spectrometer; one port of the smoke-transmitting quartz capillary is connected with the smoke sampling opening on the sucking barrel; and the other port of the smoke-transmitting quartz capillary passes through the cavity wall of the on-line analytical mass spectrometer and enters the vacuum ultraviolet ionization area. By using the device for analyzing the gas phase chemical components of the cigarette smoke on line, the influence of the smoke of a last toke on the analysis result of the gas phase components of the smoke of a next toke can be effectively eliminated in the process of sucking a cigarette toke by toke, and the gas phase components of a single toke of the cigarette smoke can be automatically and continuously analyzed on line.

Present invention discloses photons crystal optical fiber probe transducer based on nano particle surface enhancing Raman spectra belonging to laser Raman spectra detection technique. Combining photons crystal optical fiber PCF and SERS spectral technique to obtain PCF-SERS probe transducer having SERS activity, PCF-SERS probe covered with cycle arranged airport, the inner wall of central light guiding air core on PCF-SERS probe end having SERS activity nano metal granule. Said invention can be used in gas and liquid molecule detection with low background noise and high sensitivity, and making exciting light and SERS signal light existing steady mode field in PCF to realize very transmission loss, thereby suitable for on line analysis, real-time analysis, living body analysis, and in situ detecting etc.

The invention discloses a material defect infrared thermal imaging detection and targeted elimination method in laser metal forming. In laser metal forming, after layers with fixed interlayers are produced, a workbench is controlled by a computer to move in the horizontal direction at a constant speed, thus an infrared thermal imaging detection lens can move in the horizontal direction above the imaging plane and carries out non-contact scanning and photo-taking by utilizing the residual heat of metal parts, and then the infrared thermal imaging detection images are analyzed online to calculate the coordinate azimuth of the metal forming plane. The computer control laser beams to target-melt the detected defects so as to eliminate the defects; after laser re-melting, an infrared thermal imaging detector is used to re-examine the metal forming surface to confirm the defect elimination effect. The provided method solves the problems that the defects on micro materials cannot be detected online and eliminated, effectively improves the using performance and service safety of laser formed metal parts, and reduces the risk of fatigue breakage.

The invention relates to an online analysis meter and an online analytical method for operation performance of an elevator, belonging to the elevator technology field, the online analysis meter and the online analytical method are characterized in that: an upper computer is used for realizing the statistics and analysis of a signal, an embedded industrial controller serves as a main controller, on-site operation is performed by a touch screen, a lower computer is used for realizing the acquisition and processing of the signal and comprises a signal processing module, a signal collecting module, an A / D (Analog-to-Digital) conversion module, a three-axis acceleration sensor and a sound sensor, and the signal processing module is a main controller. By the analysis meter and the analytical method, the online analysis is performed to the operation performance of the elevator, the failure prediction and early warning of the elevator are realized based on an elevator three-axis acceleration and noise signals, a reliable quantified index is provided to analyze and evaluate the safety of the elevator, an effective technical method is provided for the operation quality measurement and risk assessment for the elevator, the online analysis meter adopts a dual-processor structure, thereby ensuring the acquisition and preprocessing of the signal in a high-speed and high-precision manner and having the mass storage capacity and flexible statistic analysis function.

The invention discloses a transformer online monitoring device. The device is used for carrying out real-time monitoring on an operation environment and a state of a transformer body. The monitoring device comprises an oil chromatogram online analysis apparatus, a transformer casing pipe online monitoring device, a temperature sensor, a transformer vibration sensor, a transformer partial discharge ultrasonic detection sensor and an upper computer. The upper computer is connected to the oil chromatogram online analysis apparatus, the transformer casing pipe online monitoring device, the temperature sensor, the transformer vibration sensor and the transformer partial discharge ultrasonic detection sensor through conductor wires respectively. By using the online monitoring device of the invention, based on multiple sensors, various parameters related to an operation environment and a state of a transformer are collected so as to carry out real-time monitoring and assessment on the operation state of the transformer; and the device adapts to the transformers with different voltage grades and possesses advantages that a data transmission speed is accurate, an interference is small and so on.

The invention discloses an intelligent shopping guide system and method of an electronic commerce website. The intelligent shopping guide system comprises an external data interface module, an online transaction processing module, an online analysis processing module and a complex event processing module, wherein the external data interface module is used for acquiring and preprocessing various kinds of required data in an external server / terminal in real time; the online transaction processing module is used for storing updated data acquired by the external data interface module in real time; the online analysis processing module is used for analyzing data in the online transaction processing module and updating a shopping guide policy; and the complex event processing module is used for implementing the updating of the shopping guide policy in real time and responding a shopping guide request in real time. The intelligent shopping guide system and method can be used for collecting and analyzing current data and other relevant data in real time and predicting current demands of a user by applying a data mining technology as well as recommending a proper product to the user on the basis of the prediction in a proper manner.

Certain example embodiments relate to using Complex Event Processing (CEP) techniques for statistical analysis of cache behavior and parameters, e.g., in connection with large, potentially heterogeneous data sets (e.g., “Big Data”). A dedicated stream mining operator registers a listener to a cache and receives notifications on cache operations. For selected element attributes, a first model estimates the probability density functions of the attribute values, delivering well-defined estimates of the attribute value distributions. A second model analyzes the time elements stay in the cache (“validity”). Validity is combined with the attribute value distribution. A meaningful analysis model (Cache Element Model) can be derived by combining additional summary statistics for the validity with the attribute value distribution, describing how long elements stay in the cache for attribute values of a specific region, and how the values are distributed. It may be used to inform administrative tasks such as, optimization of cache parameters.

The invention discloses a total organic carbon online analyzer for water, which mainly comprises an injection pump, a multi-ported valve, an oxygen diffusion pipe, a combustion furnace, a platinum catalyst, a condenser and a carbon dioxide gas detector (NDIR). The invention also relates to a method for analyzing the total organic carbon in the water by using the total organic carbon online analyzer for water. The total organic carbon online analyzer and the method can detect 0-2,000ppm water samples, and have the advantages of simple working principle, stability, reliability, low reagent consumption, no secondary pollution, simple and easy use, and wide application prospect in the water quality environment monitoring industry.

The invention discloses a fluid bed reactor sound-wave monitoring device and method, where the device includes receiving device, amplifying device, signal collecting device and signal processing device; the method includes the following steps: a, receiving sound signal transmitted in the fluid bed reactor; b, analyzing the sound signal, to select the parameters like frequency f, amplitude A, energy E, energy partition Pi in each frequency segment, etc; the practice proves that it has characters of sensitivity, safety and environmental protection, facility and shortcut, etc, can in time and accurately make on-line analysis on the information in the fluid bed (fluid situation, reaction situation, particle size distribution, flow pattern distribution, etc) during the producing practice, and can control production parameters by analyzing result.