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43 results about "Pattern search algorithm" patented technology

Method for self-adjusting control parameters of speed ring of permanent magnet synchronous motor based on fractional orders

The invention discloses a method for self-adjusting control parameters of a speed ring of a permanent magnet synchronous motor based on fractional orders. An integer-order proportional integral (PI) controller in an alternating current servo system of the permanent magnet synchronous motor is replaced by a fractional-order PI controller, parameters of the fractional-order PI controller are automatically adjusted, and the alternating current servo system of the permanent magnet synchronous motor can be controlled. The method specifically comprises the following steps of: firstly, acquiring current and speed signals of the alternating current servo system; secondly, identifying a speed ring controlled object model of a permanent magnet synchronous motor servo system according to the acquired signals, and identifying the parameters of the model; and finally, optimally adjusting the control parameters, and thus obtaining optimal control parameters. According to the method, the original integer-order PI controller is replaced by the fractional-order PI controller, and the parameters of the controller are automatically adjusted; the parameters of the controller are optimized by using a pattern search algorithm; and the adjusted parameters of the controller are high in robust, high in anti-disturbance capacity and high in control accuracy.
Owner:HUAZHONG UNIV OF SCI & TECH

PDFF-based AC servo driver control parameter self-tuning method

The invention discloses a PDFF-based AC servo driver control parameter self-tuning method. Firstly, current and speed signals required for identifying an AC servo system model are acquired; secondly, according to the acquired signals, a speed loop controlled object model of a permanent magnet synchronous motor AC servo driving system is identified and parameters of the model are identified; and finally, according to the parameters and performance indexes of the model, searching optimization tuning is performed on control parameters of a servo driver so that the optimal control parameter is acquired. According to the self-tuning method, a PDFF controller is utilized to substitute a conventional PI controller on a speed loop of the servo driver and the parameters of the controller are automatically tuned. The model of the controlled object is identified by the self-tuning method by utilizing a recursion least square method. Then according to the feasible performance indexes, searching optimization is performed on the parameters of the controller by utilizing a mode searching algorithm, and the optimal control parameter is obtained so that the servo driving system can be great in anti-disturbance capability, control precision and robustness.
Owner:HUAZHONG UNIV OF SCI & TECH

A fault detection method for cage-type asynchronous motor rotor broken bars based on esprit and psa

The invention discloses a cage asynchronous motor rotor broken-bar fault detection method based on an electronic stability program rotation invariant technology (ESPRIT) and a pattern search algorithm (PSA). The method comprises the following steps of: performing a rotation invariant technology on a stator current instant signal acquired according to a certain frequency so as to obtain accurate frequency values, rough amplitude values and rough initial phase angles of a fundamental wave component and a side frequency component; estimating the accurate amplitude values and the accurate initial phase angles of the fundamental wave component and the side frequency component of the stator current instant signal by applying a pattern search algorithm, and thus obtaining a ratio, which is used as a fault characteristic, of the amplitude value of the current side frequency component to the amplitude value of the fundamental wave component; calculating a ratio of the ratio to a detection threshold value to determine a fault index; and finally determining whether a broken-bar fault exists or not according to the fault index. By the method, the asynchronous motor rotor broken-bar fault can be detected on line with high sensitivity and high reliability by using a small number of stator current signal sampling points; therefore, the influence caused by adverse factors such as load fluctuation, noise and the like can be overcome effectively; and the method is extremely applicable to low slip-ratio running situations of an asynchronous motor.
Owner:NORTH CHINA ELECTRIC POWER UNIV (BAODING)

Dangerous chemical gas leakage isoconcentration line mass center track tracing algorithm

The invention discloses a dangerous chemical gas leakage isoconcentration line mass center track tracing algorithm. The algorithm includes the following steps: acquiring dangerous chemical gas concentration data collected on site and calculating multiple sets of simultaneous isoconcentration line mass center data; conducting linear fitting on isoconcentration line mass center data sets in time sequence; acquiring gas leakage source position data according to a linear fitting result. First, the mass center of isoconcentration lines at each moment is obtained, and then the mass center of the isoconcentration lines in the time sequence is subjected to linear fitting by utilizing the linear moving track of the isoconcentration line mass center with the time. The location of a leakage source can be found quickly in the reverse wind direction of the fitted line to provide quick guidance for leakage emergency response, and the leakage accident expansion can be effectively controlled. The algorithm also provides a scientific theoretical basis for selection of initial population data and initial values for solving a genetic algorithm and a pattern search algorithm based on the optimized theoretical method, the iterative calculation time for the optimized theoretical method is shortened, and the calculation accuracy is improved.
Owner:CHINA ACAD OF SAFETY SCI & TECH

Large-spacing phased-array antenna grating lobe suppression method and suppression system

The invention provides a large-spacing phased-array antenna grating lobe suppression method. The method comprises the following steps: constraining the positions of array elements; constructing a fitness function and a fitness function optimization model; selecting and crossing: selecting a certain proportion of individuals before sorting as parents for generating a new generation of population; then performing crossover operation on the population of the generation to obtain a new generation of population; mutation: for each gene of each population, randomly generating a number r between [0,1], and if r is less than Pm, replacing r with a randomly generated parameter in a value domain, where Pm is a mutation probability; and optimal solution calculation: carrying out position optimization on the large-spacing planar array by utilizing a genetic algorithm, taking an optimization result as an initial solution of a mode search algorithm, and further optimizing to find an optimal solution under the current condition. The array obtained by constraining the positions of the array elements in the optimization process is easy to implement in engineering, the grating lobe suppression effect is good, and the grating lobe can be suppressed to-8dB or below under the condition that the minimum spacing of the array elements is 3 lambda.
Owner:HEFEI RHOSOON INTELLIGENT TECH CO LTD

Meta search method for gene tissue-specific sequence pattern and search result assessment method

InactiveCN102231178ASpecial data processing applicationsPattern search algorithmBioinformatics databases
The invention discloses a meta search method for a gene tissue-specific sequence pattern and a search result assessment method and belongs to the field of biological information science. The search method comprises the following steps: extracting promoter sequences of tissue-specific genes and housekeeping (HK) genes from a bioinformatics database as input initial data; carrying out local a search algorithm and an exhaustive search algorithm on the input initial data respectively; storing result tissue generated from the operation of the two search algorithms into a filter matrix; estimating the pattern probability by utilizing the data in the filter matrix; and merging the motifs. In the assessment method, Bayes factor analysis evaluation statistics are utilized to obtain the significance of the search result of the gene tissue-specific motifs. Compared with prior art, the methods provided by the invention have the advantages that the pattern search frame used in the invention integrates multiple algorithms, the principle of 'average result overcomes single choice' which prevails in bioinformatics is conformed, the robustness and creditability of results are improved, the creditability of search results is increased, and over estimation and low estimation of the pattern are avoided.
Owner:TIANJIN UNIV

Data processing method and device based on table function and computer storage medium

The invention relates to a data processing method and device based on a table function and a computer storage medium. The method comprises the following steps: performing classification characterization on cognitive contents based on a subject classification table to form different characterization categories and codes; adopting different calculation methods to carry out classification processing according to different representation categories and codes; constructing a data storage module according to the representation category and the coding and classification result; according to the representation category and the coding and classification calculation method, generating output results corresponding to different input information offline, and an input and output truth value mapping relation table based on a preset table function template; and querying in the input and output truth value mapping relation table by adopting a multi-stage mode search algorithm of a self-adaptive resonance network according to input information, and outputting a data processing result based on a mode similarity threshold calculation method. Content required by the user can be quickly and accurately searched, and the requirements of the user are met.
Owner:SHENZHEN Y& D ELECTRONICS CO LTD

Cage asynchronous motor rotor broken-bar fault detection method based on electronic stability program rotation invariant technology (ESPRIT) and pattern search algorithm (PSA)

The invention discloses a cage asynchronous motor rotor broken-bar fault detection method based on an electronic stability program rotation invariant technology (ESPRIT) and a pattern search algorithm (PSA). The method comprises the following steps of: performing a rotation invariant technology on a stator current instant signal acquired according to a certain frequency so as to obtain accurate frequency values, rough amplitude values and rough initial phase angles of a fundamental wave component and a side frequency component; estimating the accurate amplitude values and the accurate initial phase angles of the fundamental wave component and the side frequency component of the stator current instant signal by applying a pattern search algorithm, and thus obtaining a ratio, which is used as a fault characteristic, of the amplitude value of the current side frequency component to the amplitude value of the fundamental wave component; calculating a ratio of the ratio to a detection threshold value to determine a fault index; and finally determining whether a broken-bar fault exists or not according to the fault index. By the method, the asynchronous motor rotor broken-bar fault can be detected on line with high sensitivity and high reliability by using a small number of stator current signal sampling points; therefore, the influence caused by adverse factors such as load fluctuation, noise and the like can be overcome effectively; and the method is extremely applicable to low slip-ratio running situations of an asynchronous motor.
Owner:NORTH CHINA ELECTRIC POWER UNIV (BAODING)

Method for detecting broken bar fault of cage type asynchronous motor rotor based on multiple signal classification (MUSIC) and pattern search algorithm (PSA)

The invention discloses a method for detecting broken bar fault of a cage type asynchronous motor rotor based on multiple signal classification (MUSIC) and a pattern search algorithm (PSA). The method comprises the following steps of: firstly, applying a multiple signal classification technique to obtain frequency values of a fundamental component and a side frequency component of a stator current momentary signal which is acquired according to a certain frequency; secondly, estimating amplitude values and initial phase angles of the fundamental component and side frequency component of the stator current momentary signal by applying the PSA; thirdly, calculating the ratio of the amplitude value of the current side frequency component to that of the fundamental component and taking the ratio as a fault characteristic; fourthly, calculating the specific value of the ratio to a detection threshold value to determine a fault index; and finally, judging whether a rotor broken bar fault exists according to the fault index. By using the method, the broken bar fault of the asynchronous motor rotor can be detected in an on-line manner with high sensibility and high reliability by using few stator current signal sampling points, so the influence caused by adverse factors such as load fluctuation, noise and the like is effectively overcome, and the method is very suitable for the condition that an asynchronous motor runs at a low slip ratio.
Owner:NORTH CHINA ELECTRIC POWER UNIV (BAODING)

Photovoltaic system MPPT method based on leapfrog and pattern search neural network

The invention discloses a photovoltaic system MPPT (Maximum Power Point Tracking) method based on a leapfrog and pattern search neural network, which comprises the following steps of: (1) obtaining the temperature and irradiance of a photovoltaic module, and obtaining a maximum power point reference voltage by adopting a neural network; (2) enabling the controller to obtain an output quantity according to an error between the reference voltage and the measurement voltage of the photovoltaic module; (3) enabling an enhanced disturbance observer P& Q to obtain the control quantity of the chopper circuit according to the measured voltage, the measured current and the output quantity of the controller, so that the photovoltaic system stably works at the maximum power point along with the illumination change. According to the method, a hybrid recombination leapfrog and pattern search algorithm is adopted to optimize the maximum power point tracking based on the neural network in the photovoltaic system; the method has excellent performance in response speed and precision, and can provide the highest tracking efficiency and the fastest response time under the condition that the steady state and the irradiance are continuously changed, and the response time is 11 seconds.
Owner:HUAIYIN INSTITUTE OF TECHNOLOGY

Fifteen-phase asynchronous motor rotor broken bar number high-precision diagnosis method based on ESPRIT-PSA and LGBM

The invention relates to a Fifteen-phase asynchronous motor rotor broken bar number high-precision diagnosis method based on ESPRIT-PSA and LGBM. According to the method, for an instantaneous reactive power signal sampled in a short time (only 2 seconds), an accurate amplitude Aq of a characteristic component in the instantaneous reactive power signal is obtained by using an ESPRIT (Rotation Invariant Signal Parameter Estimation Technology) and a PSA (Pattern Search Algorithm); corresponding 71 characteristics such as voltage amplitude, current amplitude, average active power P and average reactive power Q are obtained; the method then includes determining Aq and the first five features, namely Aq, P and Q, a first phase voltage amplitude Um and a first phase current amplitude Im, in the 71 features according to an LGBM (Light Gradient Elevator) so as to form a data set, wherein the first five features include Aq, P and Q, and the first phase voltage amplitude Um and the first phase current amplitude Im; and then training and storing an LGBM model and carrying out high-precision diagnosis on the number of broken bars of the rotor (the training precision and the test precision are both 100%, and the five-fold cross validation accuracy is 99.38%).
Owner:NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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