19results about How to "Short runtime" patented technology

The invention belongs to the technical field of micro-grids, and particularly relates to a distributed micro-grid system and a dispatching control method thereof.The micro-grid system comprises a wind power generation device, a photovoltaic power generation device, a hydroelectric power generation device, a tidal energy power generation device and a diesel engine power generation device; the energy storage equipment comprises a storage battery energy storage device, a super capacitor energy storage device, a flywheel energy storage device and a water electrolysis hydrogen production and fuel cell energy storage device; the water electrolysis hydrogen production and fuel cell energy storage device comprises a water electrolysis device, a hydrogen storage tank and a fuel cell; the water electrolysis device is connected with the alternating current bus through an electrolysis control switch and conveys prepared hydrogen to the hydrogen storage tank for storage, and the hydrogen storage tank is connected to the fuel cell through a hydrogen control valve. A micro-grid energy optimization scheduling problem is described as a Markov decision process, and a WGAIL-based energy optimization scheduling solving algorithm is adopted, so that the stability of a training process is improved, a better strategy can be obtained, and the energy optimization scheduling of the micro-grid can be realized.

The invention discloses a target relative pose resolving method based on monocular vision depth estimation, which comprises the following steps: firstly, calibrating an internal reference matrix of a monocular camera, shooting a target image for preprocessing and target detection, and extracting pixel coordinates of at least two feature points; the method comprises the following steps: firstly, acquiring the depth of a feature point through a monocular distance measurement algorithm based on a pinhole imaging model and a similarity principle, acquiring attitude data of a flight control system, carrying out air communication, and finally calculating the relative pose between aircrafts by combining a projection transformation relationship between 2D-3D point pairs established based on a camera mathematical model. According to the method, the relative pose between the aircrafts can be solved only by adopting the monocular camera to process the single-frame image and the at least two feature points, the problems that a traditional monocular vision positioning algorithm is high in complexity and long in consumed time are solved, the detection requirement for the feature points is reduced, meanwhile, the depth of the feature points is directly measured through a monocular distance measurement algorithm, and the accuracy of the relative pose between the aircrafts is improved. And the calculation complexity is further reduced.

This invention discloses a rendering optimization method, program product, and storage medium based on frame interpolation and super-resolution. The method includes: acquiring an optimized super-resolution rendering frame at time t as a first rendering frame, and acquiring a low-resolution rendering frame at time t+1 in the frame display sequence as a second rendering frame; reprojecting the first rendering frame and the upsampled second rendering frame to an intermediate frame time and correcting them together to obtain corrected data for a high-resolution intermediate frame; reprojecting the features of the first and second rendering frames to the intermediate frame time and combining them with the features of the corrected data for the high-resolution intermediate frame to reconstruct a super-resolution intermediate rendering frame; reprojecting the first rendering frame to the time of the second rendering frame and correcting it together with the upsampled second rendering frame to obtain corrected data for the second rendering frame; extracting features from the corrected data for the second rendering frame; and reconstructing the super-resolution rendering frame at time t+1 based on the features of the corrected data for the second rendering frame and the features of the second rendering frame. This invention has a short running time and good rendering effect.

The invention provides a method and a kit for detecting blood concentration of compound sulfamethoxazole and metabolite thereof. According to the method, a methanol precipitator is combined with Oasis PRiME HLB reversed-phase solid-phase extraction, the centrifugal process of plasma treatment is reduced, traditional activation and balance steps are omitted, time is saved, meanwhile, the method is more environmentally friendly, and the extraction recovery rate of a to-be-detected substance can be improved; gradient elution is replaced by isocratic elution, the balance returning time is avoided, the overall operation time is shorter, the separation application is not influenced, the operation time is only 6 minutes, all the to-be-measured substances can be accurately and simultaneously measured only by 1 microliter, and the peak appearance time is 2 minutes. According to the invention, trimethoprim, sulfamethoxazole and metabolites thereof sulfamethoxazole-N-acetyl and 4-nitro sulfamethoxazole in human plasma can be monitored at the same time by using a treatment method and a computer method.

The invention provides a method for detecting video mosaics based on a proportional gradient algorithm, which aims to solve the problem that the video image mosaics are difficult to detect quickly and accurately, and comprises the following steps of: firstly, preprocessing an image, converting the image into a grey-scale map, and carrying out early-stage denoising work on the image to obtain a preprocessed image; calculating a proportional gradient through a proportional gradient algorithm, and extracting edge information of the image; further, traversing the image, detecting the feature region of the mosaic, and realizing mosaic region positioning; and finally, according to the characteristic that pixel point values in the mosaics are uniform, through setting a threshold value, further distinguishing the detected mosaic areas, and displaying the detected finally obtained mosaic areas, the algorithm can accurately and timely detect mosaic faults occurring in the video image playing process, and provide high-quality video programs for users.

The present invention belongs to the technical field of drug intermediate analysis and detection, and provides an analysis and detection method for a hydrochloric acid cefuroxime intermediate cefuroxime precursor acid. The mobile phase of the analysis and detection method of the present invention is mainly composed of methanol and water, and tetrapentyl ammonium bromide and sodium dihydrogen phosphate are added, which can not only improve the solution stability of cefuroxime precursor acid, but also ensure the accuracy of the analysis and detection method results; and, the peak type, tailing factor, separation degree and theoretical plate number of the main component are significantly improved; and, impurity A, impurity B, impurity C and impurity D all have higher response values ​​and separation effects, and more unknown impurity peaks can be separated and detected. At the same time, the operation process of the analysis and detection method of the present invention is simple and convenient, the running time is short (within 30min), and it is suitable for rapid detection of industrial production; and the equipment requirements are not high, and the brand of the chromatographic column is not limited.

The invention relates to the technical field of m-nitro-trifluoromethyl benzene detection, and discloses a method for determining chromatographic purity of m-nitro-trifluoromethyl benzene and by-products by GC (gas chromatography), which comprises the following steps: dissolving a substance to be detected by acetonitrile to obtain a solution to be detected with the concentration of the substance to be detected being 20-100mg / mL, and performing GC determination on the solution to be detected to obtain the chromatographic purity of the m-nitro-trifluoromethyl benzene and the by-products of the m-nitro-trifluoromethyl benzene and the by-products of the m-nitro-trifluoromethyl benzene. The content of each substance in the to-be-detected substance is obtained; during GC determination, dimethyl polysiloxane is used as a capillary chromatographic column of a stationary phase; n2 is used as carrier gas, H2 is used as fuel gas, and air is used as combustion-supporting gas; the method can be used for simultaneously detecting the raw material trifluorotoluene and the by-products o-nitro trifluoromethyl benzene and 1-nitro-4-trifluoromethyl benzene, and has the advantages of good separation degree, convenience in operation, short running time and accurate detection result.

The invention discloses a fault diagnosis and self-healing closed-loop method for thermal power equipment, which solves the problems of high arrangement cost, complex diagnosis rule and low fault recovery efficiency of a fault case knowledge base in the prior art, and comprises the following steps: carrying out fault case arrangement based on a large language model to form the fault case knowledge base; parameter anomaly detection is carried out in the equipment operation process, text description is carried out on early warning information, and early warning text information is generated; performing fault diagnosis on the early warning text information based on a large language model, and generating self-healing operation recommendation; and according to the self-healing operation recommendation, performing self-healing through a dependency inversion closed loop based on an optimized DAG scheduling algorithm. According to the method, the arrangement cost of the fault case knowledge base and the fault diagnosis complexity are reduced, and the fault recovery efficiency is improved.

This invention discloses a method and system for binocular image super-resolution reconstruction based on cross-scale disparity prior, comprising: S1: acquiring the original left feature map and the original right feature map corresponding to the low-resolution left and right binocular images; S2: using a binocular attention module to perform cross-view interaction on the original left feature map and the original right feature map respectively, to obtain the interacted left feature map and the interacted right feature map; S3: inputting the interacted left feature map and the interacted right feature map into the cross-scale disparity attention module, and fusing them to obtain an aggregated feature map; S4: inputting the aggregated feature map into a cascaded dynamic upsampling reconstruction network to obtain the reconstructed super-resolution binocular image. This invention can fully utilize disparity information and obtain more realistic and higher-quality super-resolution images in a shorter running time.

The application discloses a kind of control moment gyro high-speed bearing sliding state monitoring method based on transfer learning, belong to rolling bearing fault diagnosis technical field, comprising the following steps: S1, builds control moment gyro high-speed bearing sliding test bench, obtains motor current experimental data and bearing sliding data;S2, obtains motor current simulation data;S3, extracts current feature;S4, current feature is classified;S5, based on the current feature after classification, bearing sliding prediction model is constructed and trained, and motor current experimental data and motor current simulation data are input to the bearing sliding prediction model after training, and the classification result of bearing skidding is generated.The application has the advantages of high prediction accuracy and shorter running time in bearing sliding state prediction task based on simulation data training.

The present invention belongs to the field of drug analysis technology, and is specifically related to a content detection method of a fluocinolone hydroquinone retinoic acid cream and its use for measuring the drug release amount in the in vitro release test of fluocinolone hydroquinone retinoic acid cream. The content detection method described in the present invention is to adopt high performance liquid chromatography, with phosphate buffer solution as mobile phase A and methanol as mobile phase B, and gradient elution is performed on the chromatographic column of octadecylsilane bonded silica gel, and the content of three active ingredients of fluocinolone, hydroquinone and retinoic acid can be detected simultaneously, and the running time is short and operability is strong. In addition, the content detection method provided by the present invention can be applied to the detection of drug content in the fluocinolone hydroquinone retinoic acid cream test solution obtained by sampling with physiological saline 50% ethanol as the receiving medium, selecting a specific artificial membrane, and using an in vitro release device to measure the cumulative release of drugs in the in vitro release test of fluocinolone hydroquinone retinoic acid cream.

The invention discloses an underwater acoustic OFDM (Orthogonal Frequency Division Multiplexing) system carrier synchronization algorithm based on gradient estimation combined with optimal solution search, and belongs to the technical field of underwater acoustic communication. The method specifically comprises the following steps: step 1, in an underwater acoustic OFDM communication system, synchronizing underwater acoustic OFDM carriers by adopting a time domain method; and step 2, in one OFDM frame, carrying out frequency offset estimation on the first OFDM symbol by adopting a carrier synchronization algorithm based on optimal solution search. And step 3, starting from the second OFDM symbol, estimating a frequency offset value by adopting a carrier synchronization algorithm based on gradient descent, and taking a frequency offset estimation result of the first OFDM symbol as an initial value of iteration. According to the method, finer residual carrier frequency offset compensation can be carried out through pilot symbols, an Adam method is adopted to improve an underwater acoustic system carrier synchronization algorithm of a step length, the complexity is reduced while the precision is improved, and reliable and effective underwater acoustic OFDM communication is realized.

The invention discloses a multi-feature extraction signal modulation identification method based on a miniaturized radio frequency instrument, and belongs to the technical field of information. The invention provides an electromagnetic signal multi-feature fusion feature quantity construction and modulation identification method and scheme which can be deployed on a resource-limited miniaturized portable radio frequency instrument. Comprising the following steps: extracting multi-feature parameters; constructing characteristic quantity parameters; designing a classifier through a modulation recognition algorithm; and through modulation identification test and analysis, identification of a signal modulation mode is completed. The method has the advantages of low algorithm complexity, rich feature representation, small operation resource demand and simple engineering implementation; the method has the advantages of low calculation complexity, short operation time, high recognition speed, high recognition accuracy and the like, can help a user to quickly determine the modulation type of a signal, and improves the new environment exploration efficiency and spectrum monitoring and detection.

The invention belongs to the technical field of optimal control of a pressure delay osmotic energy-photovoltaic-solid oxide fuel cell and wind energy hybrid energy system, and particularly relates to an optimal control method for a hydrogen-electricity coupling system based on improved giant armadillo optimization. Based on a giant armadio optimization algorithm and a triangular topology aggregation optimizer, a key parameter, namely a random solution, is introduced in an exploration stage, an optimal solution is removed, the influence of a current solution on position updating is reduced, the convergence speed and the global search capability of the algorithm are improved, the solving quality is greatly improved, and the algorithm is more effective than a classical GAO algorithm, and has a wide application prospect. The real-time tracking and accuracy based on the IGAO algorithm are improved, and when the MPPT control problem is solved, the method has higher calculation accuracy and shorter operation time, can be used for a pressure delay osmotic energy-photovoltaic-solid oxide fuel cell and wind energy hybrid energy system to obtain higher power generation, and is beneficial to the development of the energy field.

The present application relates to a 2D-3D medical image registration method, device, computer equipment and storage medium. The method includes: obtaining a preoperative CT image and an intraoperative X-ray image of a target bone block, inputting the preoperative CT image and the intraoperative X-ray image into a regression network based on deep learning, and roughly estimating the initial spatial pose of the target bone block through the regression network; adjusting the projection of the preoperative CT image based on the initial spatial pose to generate a DRR image; inputting the DRR image, the intraoperative X-ray image and the preoperative CT image into a pre-trained corresponding point relationship estimation network, estimating the feature point correspondence between the DRR image and the Xray image through the corresponding point relationship estimation network, optimizing the initial spatial pose of the target bone block according to the feature point correspondence, and obtaining the optimized spatial pose. The present application does not require manual annotation of a large amount of data, greatly reduces the radiation damage caused by repeated perspectives, and can achieve relatively efficient and accurate registration.

This invention discloses a bearing fault diagnosis method based on XGBoost and feature combination, comprising the following steps: S1, data preprocessing; S2, constructing a BO-XGBoost and feature combination model: S21, using the BO algorithm to find the optimal hyperparameter combination; S22, substituting the optimal hyperparameter combination into the XGBoost algorithm to form a BO-XGBoost model; S23, constructing a sealing gas flow characteristic line graph model; S4, training the BO-XGBoost model; S5, inputting the data to be predicted into the BO-XGBoost prediction model and the sealing gas flow characteristic line graph model respectively. When both models output warnings, the combined model will output a fault alarm. This invention uses the BO-XGBoost algorithm and sealing gas flow characteristic combination to diagnose centrifugal compressor bearing faults, which can improve the accuracy of judgment and achieve effective early warning of bearing faults.

The invention discloses a low-resistance grounding system high-resistance fault detection method based on a sampling value vector included angle, and belongs to the field of power system relay protection. The method is characterized by comprising the following steps: step a, collecting zero-sequence current in a line; b, judging whether the zero-sequence current break variable exceeds a preset threshold value or not; c, three-phase voltage and zero-sequence current of the outlet side of each line are collected; step d, carrying out data interception on the three-phase voltage and the zero-sequence current; e, calculating a vector included angle between the three-phase voltage and the zero-sequence current; f, whether the vector included angle is smaller than a preset vector included angle threshold value or not is judged; and g, judging a fault phase and a fault section. According to the low-resistance grounding system high-resistance fault detection method based on the sampling value vector included angle, high-resistance grounding fault detection is achieved through the relation between the three-phase voltage after the fault and the zero-sequence current sampling value vector included angle, the problem that a traditional protection method depends on zero-sequence voltage is solved, and the transition resistance resistance capacity is improved.

The present invention discloses an FPGA task scheduling optimization method and system using DQN, defines a non-uniformly distributed FPGA on-chip reconfigurable resource model, models CLB, BRAM and DSP resources, uses the modeling results as the placement chip carrier of the online task to characterize the online task, uses the optional modeling results of the online task as the target chip, uses the fixed-length data defined by the online task and the target chip as the input data of the DQN network, uses the reward function of DQN as the feedback of the neural network, and updates it with the DQN update value function; uses DQN and the optimal longest fit algorithm to jointly train the DQN network; finds a suitable target chip and the optimal placement result in each scheduling event, inputs the online task and the target chip into the trained DQN network, selects the target chip with the highest reward value as the running chip of the corresponding task, and realizes task scheduling optimization. The present invention improves the scalability of the model by fixed-length input.

The application discloses a contour extraction method based on an adaptive ellipse edge detection and fast fitting algorithm, obtains an image region where an ellipse is located, and gives a search center, a search direction, a search frame position and size and a search space, and in the search space, from the search center to the search space boundary, according to the search direction, the whole search path of the search frame in the form of a ray is determined; all pixel values in the search frame are obtained; the gray values of all pixel points in the search frame are obtained; the obtained pixel values are clustered into two categories by using K-Means clustering; the ellipse is fitted by using a least square method; the point set far from the ellipse boundary is removed, and the point set close to the ellipse boundary, that is, the best inner point set, is left, so that the least square ellipse fitting is completed; and the last point set fitting result is drawn by using key coefficients of an ellipse equation obtained by the least square algorithm. The application can accurately find the positions of strong edges and weak edges of the ellipse, can autonomously screen inner points and can accurately fit the ellipse equation.