576results about How to "Short calculation time" patented technology

A method for controlling an arc welding equipment (21) used in a welding operation and adjustable by varying at least one welding parameter value, comprising the steps of determining said at least one welding parameter while using a theoretical model (24) of the welding process associated with the welding operation, and controlling the operation of the welding equipment and the welding process associated therewith by using said at least one welding parameter for adjusting the welding equipment and a device comprising an arc welding equipment (21) used in a welding operation and adjustable by varying at least one welding parameter and an arrangement (22) for controlling the operation of the arc welding equipment, said control arrangement including a means (23) adapted to determine the value of said at least one welding parameter while using a theoretical model (24) of the welding process, and a member (25) adapted to control the operation of the welding equipment and the welding process associated therewith by using said at least one welding parameter value for adjusting the welding equipment.

A workpiece pick-up apparatus including: a hand for gripping a workpiece; a robot for bringing the hand into a desired gripping position or posture; a sensor for performing three-dimensional measurement of the workpiece to obtain workpiece measurement data; a storage medium for accumulating at least hand profile data; an information processing unit for calculating the gripping position or posture based on data from the sensor and data from the storage medium; and a control unit for controlling the robot based on the gripping position or posture calculated by the information processing unit. The information processing unit includes an optimum gripping candidate creating section for directly deriving the gripping position or posture based on the workpiece measurement data and the hand profile data.

The invention provides an infrared images method for detecting targets at sea, which relates to a method for detecting the targets at sea. The invention aims to provide the method for detecting the targets at sea, which not only can well inhibit sea clutters to obtain reasonable image segmentations, but also can extract out the fractal characteristics at a high speed to remove false targets so as to achieve effective detections. The method comprises the following steps: performing preprocessing on the obtained infrared images; performing self-adapting iteration threshold segmentation; detecting whether the part of a sea-sky line has a region of interest (ROI); extracting the ROI at the background part of the sea-sky line; extracting the ROI at the background part of a non-sea-sky line; and combining the regions of interest to obtain an image of interest to be further processed, and extracting the fractal characteristics of each ROI to perform target detections. The method can quickly and effectively segment out the regions of interest in the infrared images, and not only reduces the amount of calculation to extract out the fractal characteristics at a higher speed because the extracted regions of interest is far smaller than the original images, but also can remove the false targets appearing in the threshold segmentation through the fractal characteristics.

The invention discloses a physical prediction method for wind power station power based on a computational fluid mechanics model. The physical prediction method comprises the following steps: establishing a computational fluid mechanics model; performing discretization on wind conditions of a wind power station, and taking the discretized wind as boundary conditions for conditions numerical simulation of the computational fluid to obtain space flow filed distribution of the wind power station at the discretized wind conditions; establishing data base of hub height, wind speed, wind direction and generated power of wind generation sets under the discretized wind conditions; and taking numerical weather prediction parameters as input data, and utilizing the data base to figure out the wind speeds and the wind directions of the wind generation sets so as to figure out the generated powers of the wind generation sets, and accordingly obtain predicted value of the wind power station power. According to the invention, the physical prediction method is applicable to multiple wind power stations, has small calculated amount in the power prediction stage and has short calculation time.

A variable-length key cryptosystem is provided, in which the amount of parameters for generating a key to be shared is small, security is high, and calculation cost is small.

The length of a plain text inputted from a data input part 10 is detected by a data string length detection processing part 20. A variable-length key generation processing part 30 generates an encryption key with a required arbitrary length, using an initial character string and a conversion rule, based on the length of a plain text. A conversion character string generation processing part 32 generates a converted character string from an initial character string by applying a conversion rule of increasing the length of a character string. Conversion is conducted until the length of a plain text is reached. An encryption key is not used twice. Therefore, an unused conversion character string is searched for, and a stream code processing part 40 generates an encrypted text by using a generated encrypted string. A receiver system 200 generates a converted character string from an initial character string by the same conversion, based on the length of an encrypted text, thereby obtaining the same encryption key.

Transmitting and receiving compensation coefficients of each antenna element relative to a calibration antenna element are obtained in the pre-calibration of a smart antenna. After the antenna array is installed, in transmitting calibration, amplitude and phase response of each transmitting link is computed according to the calibration signals received by the calibration link and, together with the transmitting compensation coefficient obtained in the pre-calibration, the compensation coefficient of each transmitting link is computed to compensate the downlink data of a base station. In receiving calibration, the amplitude and phase response of each receiving link is computed based on the signals received by the receiving links and, together with the receiving compensation coefficient obtained in pre-calibration, the compensation coefficient of each receiving link is computed to compensate the uplink data of the base station. The calibration signal of each antenna element is generated by a periodic cycling shift of a basic calibration sequence.

The invention relates to a method for optimizing an orbital transfer strategy of a geostationary orbit satellite, which comprises the following steps of: 1, determining orbital transfer times, orbital transfer circle times and the controlled variable of each-time orbital transfer; and 2, determining time and a thrust direction in each-time orbital transfer. The process of launching the geostationary orbit satellite at present generally comprises the following steps of: launching the satellite into a highly elliptic transfer orbit with an inclination angle by using a carrier rocket; performing apogee/perigee orbital transfer for several times by using a self-contained liquid engine of the satellite, and transferring to a geosynchronous orbit; and correcting and rounding the inclination angle of the orbit to realize a geostationary orbit. For the satellite, operation for changing the transfer orbit into the geostationary orbit by performing apogee/perigee orbital transfer for several times is complex, so too many orbital transfer times is not suitable, and orbital transfer complexity and risk are prevented from being increased; in addition, factors such as the capacity of the liquid engine of the satellite, arc segment loss in an orbital transfer period, and the like are considered, so too few orbital transfer times is not suitable.

The invention provides an automatic vertical parking system and a parking method based on multi-stage planning and machine learning. The image is collected by a ring-view camera, and an ultrasonic sensor detects obstacle information to judge the position, heading information and the validity information of the storage location relative to the storage location. The automatic parking process is initiated when a suitable size and no vehicle-occupied space is identified. The automatic parking system plans the parking route according to the current self-parking posture and the information of the garage. If necessary, the automatic parking system uses multiple R-S curve is adjusted from the parking position to the proper position, and then the secondary helix parking trajectory is generated according to the learning network. The steering wheel, throttle and brake pedal are controlled electronically for parking and garage entry. The invention utilizes the secondary helix training set and thelearning network to improve the efficiency of the parking process and the adaptability to the path deviation, and combines R-S curve for multi-stage planning, to achieve a very small range of parkingplanning high success rate, a wider range of application, more reliable parking process.

The present invention is in the field of manufacturing, processing and design, and also packaging. Nesting is the process of placing objects together with minimal spaces between them. The invention is described below in two forms. The first form, set forth in Part I below, is directed to methods and systems for nesting of two dimensional (2D) objects in a target plane. The second form, set forth in Part II below, is directed to methods and systems for nesting three dimensional (3D) objects in a target volume. The specific details of the preferred embodiments are set forth in those respective parts.

The invention discloses a micro-grid short-term load forecasting method based on the EMD-KELM-EKF, and belongs to the technical field of intelligent power grids. The method includes the steps of firstly, preprocessing micro-grid history load data, enabling the preprocessed micro-grid history load data to serve as a training sample, and extracting the load attribute of the training sample; secondly, determining a combined forecasting model based on the EMD-KELM-EKF and parameter initial values of the combined forecasting model; thirdly, optimally selecting parameters of the combined forecasting model through a particle swarm optimization algorithm; fourthly, substituting a test sample into the combined forecasting model based on the EMD-KELM-EKF with determined parameters to obtain a forecasting result. The method is clear in physical concept and thought, and provides the theoretical foundation for micro-grid short-term load forecasting, and calculation is easy and convenient; according to the method, by means of the implementation pattern of combining offline parameter optimization with online forecasting, the forecasting result is good in stability, and optimal dispatching can be easily conducted on micro-grids.

The invention provides a bus arrival time estimation method and device. The method includes dividing each bus running line into a plurality of running portions, and establishing corresponded artificial neural network models respectively; training the running portions to acquire corresponded parameter values of the corresponded artificial neural network models; determining all target running portions between the current bus position and a target station, acquiring current values of the current influence factors corresponding to each target running portion, inputting the corresponded artificial neural network models, acquiring output values of the artificial neural network models corresponded to the target running portions, and acquiring times for the bus arriving the target station according to the output values. The device comprises a dividing module, a model establishing module, a first artificial neural network model processing module, a current state processing module, a second artificial neural network model processing module and a calculating module. By the aid of the method and device, the bus arrival time can be calculated more accurately.

The invention discloses an online calibrating method of a ship-based rotary strapdown inertial navigation system. The method comprises the following steps: establishing an inertial component output error model and an inertial navigation system error equation, and researching the calibration of inertial component parameter errors and determining the quantity of state and the quantity of measuration; determining the position and weight of a cubature point according to dimension of the quantity of state, deducing a state equation and a one-step state prediction and state prediction covariance matrix related to the cubature point, and introducing a multiple time-varying fading factor modified state prediction covariance matrix; and deducing a measuring equation related to the cubature point and the fading factors, a self-correlated covariance matrix, a cross-correlated covariance matrix, a gain matrix, a state estimated value and a state error covariance estimated value, and designing a strong tracking volume Kalman filtering method with strong tracking performance and strong robustness. The method disclosed by the invention estimates the inertial component parameter errors by a filtering algorithm and carries out online calibration and compensates the inertial component parameter errors, so that the navigation precision is effectively improved. The method has strong parameter-varying robustness.

The invention discloses an improved particle filter track-before-detection method for weak target detection. In the method, The method is characterized in that: particles are divided into three types of sets of death, new birth and continuing survival according to the state of a target existence variable, and the state of particles in different sets are separately operated; the particles in the death set are not defined or operated; the particles in the new birth set acquire a new state according to prior distribution sampling; and the particles in the continuing survival set are regenerated according to gaussian distribution and acquire a new state according to a target motion model. By the method, the amount of operation is reduced, the diversity of the particles is improved, and the phenomenon of sampling exhaustion is effectively avoided. The method has the characteristics of short calculation time, high robustness, stable and reliable detection performance and high tracking precision.

The invention provides a method for Bayes compressed sensing signal recovery based on a self-adaptive measurement matrix and relates to the field of the information and communication technology. The method aims at solving the problem that an existing compressed sensing signal recovery method is low in accuracy. Based on the design of the self-adaptive measurement matrix in compressed sensing and combined with the Bayes compressed sensing algorithm, a design scheme of the compressed sensing method is obtained. The method is characterized in that the designed measurement matrix can be generated in a self-adaptive mode according to different signals, the purposes of determinacy and storage of the matrix are both achieved, and combined with the Bayes compressed sensing recovery algorithm of a relevant vector machine, the priority of a layered structure is introduced. The design scheme passes simulation verification, it is confirmed that the good signal recovery effect can be obtained, and the error range of recovered signals can be evaluated. The method is suitable for wireless signal transmission occasions in the information and communication technology.

The invention discloses a regional comprehensive energy system reliability evaluation method considering heat load dynamic characteristics. The regional comprehensive energy system reliability evaluation method comprises the following steps that according to a selected regional comprehensive energy system, data of electricity, natural gas and regional heating system data, energy concentrator data,failure rate of various components, electricity, gas and heatload shedding price data, a hierarchical decoupling optimal convergence judgment threshold value, a reliability index convergence judgmentthreshold value, the maximum number of sampling and the building interior design temperature are input; running states of all components are selected to conduct system state analysis; power flow optimization calculation is conducted to the selected system state to obtain load shedding amount of electricity, gas and heat load shedding amount in the system state; the reliability index is calculated, wherein the reliability index comprises expected load reduction and expected load reduction frequency of the electricity, gas and heat; a reliability index convergence criterion is calculated; the number of quasi-sequential sampling is judged; and the electricity/gas/heat area comprehensive energy system reliability index is output. Electricity/gas/heat area comprehensive energy system reliability can be more accurately evaluated.

The invention discloses a bus behind-schedule recovering method based on arrival time predication with a time window. The method provides a behind-schedule recovering concept on the basis of arrival time predication of a bus. The specific method comprises the following steps of: firstly, predicating arrival time of the bus by using Kalman filtering; secondly, taking a predication result as the basis and giving out a dispatching time judging time window; and finally, providing the behind-schedule recovering concept and introducing a time deviation coefficient; taking a corresponding speed of a critical time deviation coefficient and a maximum allowable speed as restrictions to establish a behind-schedule recovering model, so as to provide a referred speed of road segment driving to a bus driver and a dispatching center to avoid possible behind-schedule or recover normal operation as soon as possible.

The invention provides a noise source identification method adopting vibration speed measurement and a partial near-field acoustical holography method.. The method comprises the following steps of: measuring the vibration speed of a normal mass point on a finite aperture measurement surface H positioned at a near field; performing zero-padding expansion on the vibration speed; calculating a transmission matrix between the measurement surface and a sound source surface; and finally calculating so as to obtain sound pressure on the sound source surface S and the vibration speed of the normal mass point. The vibration speed of the normal mass point is used as an input value for sound field reconstruction, so that sound field information with relatively high precision can be acquired. Compared with the conventional iterative partial near-field acoustical holography method, the method adopting the partial near-field acoustical holography method has the advantages of being simple in calculation operation, short in calculation time, high in calculation efficiency and the like and is used for identifying and positioning a noise source and reconstructing a sound field.

A method for the processing of images in interventional radioscopy to produce a sequence of de-noised images in which elongated objects of guiding instrumentation equipment are preserved and enhanced. The method of the invention uses a tool for indicating the confidence to be placed in a given pixel as regards its belonging to a piece of guidance equipment. This tool is used to create a combination algorithm capable of re-injecting the pixels having a low contrast-to-noise ratio into the de-noised image. This combination algorithm enables the enhancement solely of the pixels of the guidance equipment with a high confidence value so as not to produce artifacts with the enhancement of false positives.

There is provided a similarity calculation device for calculating an index for judging technical similarity between technical document groups consisting of technical documents. The similarity calculation device includes: technical document group input means (365) for inputting a first technical document group and a second technical document group to be compared; technical information input means (371) for inputting technical information; cluster analysis means (380) for searching technical documents contained in the first technical document group and the second technical document group and including the technical information which has been input and decomposing the searched technical documents into a cluster for each technical information; similarity calculation means (380) for calculating the ratio of the number of mixed clusters including the technical documents of both of the first technical document group and the second technical document group against the total number of clusters obtained as the cluster decomposition; and output means (365) for outputting the similarity calculated.

The invention discloses a method for analyzing loop closing risks based on an interconnection switch in a power distribution network. The method comprises the steps that firstly, the voltage difference of the two sides of the interconnection switch is acquired, a power transmission network CIM model and a power distribution network CIM are spliced to form a loop closing path, and the loop impedance of the loop closing path is calculated; secondly, the loop closing steady-state current and the maximum impact current are worked out according to the voltage difference of the two sides of the interconnection loop and the loop impedance of the loop closing path; lastly, safety verifying is carried out on all devices on the loop through the loop closing impact current and the loop closing steady-state current, and whether loop closing can be carried out or not is judged. The method does not depend on the telemeasuring data of the power transmission network, the computing time is short, the computing result accuracy is high, the convergence problem does not exist, the change of the power transmission network can be followed in real time, the power transmission network loop closing risks under the most situations can be solved, the power outage caused by the loop closing failure is avoided, and the high social benefits and economic benefits are achieved.

To intraoperatively generate an updated volume data set in which a image information of biological tissue is volume data set representing reconstructed from a series of n 2D biological tissue x-ray projections, one version, in intraoperatively acquired m 2D biological tissue x-ray projections the biological tissue 2D contour is segmented and this is back-projected in the reconstructed volume data set. In another version, in the volume data set the biological tissue 3D contour is segmented and this is projected in intraoperatively acquired m biological tissue 2D x-ray projections. The 3D contour is visually repositioned by projection in the m 2D x-ray projections in the volume data set, until its projection is substantially congruent with the biological tissue image information in the respective 2D x-ray projections. In both versions, a volume data set updated around the intraoperatively determined biological tissue 3D contour is generated.

The invention is suitable for the spectral imaging technical field, and provides a coded aperture spectral imaging system which comprises a preposition imaging system, a digital micro-mirror, a collimation system, a reflection raster, a microlens array and a detector. The microlens array comprises a plurality of microlenses; the filtering bands of the filtering layer on each microlens are different; the preposition imaging system images an object to be measured on the digital micro-mirror; the image after coded modulation is incident on the reflection raster through the collimation system to perform light splitting; a space spectrum mixing image is obtained after light splitting; a plurality of images are obtained through the microlens array with a filtering function; the detector simultaneously receives the plurality of images, and performs fusion decoding on the plurality of images to obtain the spectral information of the object to be measured. The coded aperture spectral imaging system can maintain system single rapid measurement, and meanwhile substantially improve system spatial resolution.

The invention relates to the field of noise, in particular to a sound field separation and reconstruction method applicable to sound field separation and reconstruction of large sound sources. The sound field separation and reconstruction method comprises the following steps of: acquiring sound pressure and normal particle vibration velocity on a measuring surface; performing zero filling extension on the measuring surface positioned between two sound sources; acquiring transfer matrixes between the extended measuring surface and surfaces of the two sound sources, namely sound source faces; building a transitive relation between the sound pressure and the normal particle vibration velocity on the measuring surface; and acquiring the sound pressure and the normal particle vibration velocity of the first sound source face and the sound pressure and the normal particle vibration velocity of the second sound source face. A sound field is separated and reconstructed by using the single-measurement-surface and local near-field acoustical holography method. The sound field separation and reconstruction method has the characteristics of simplicity, short calculation time and high calculation efficiency, and can be widely applied to the measurement of near-field acoustical holography, the measurement of material reflecting coefficients, the separation of scattering sound fields and the like of large-size sound-source sound fields.