132results about How to "Reduce computing load" patented technology

The invention relates to the technical field of multi-beam sounding calibration, and discloses a multi-beam sounding online real-time calibration method. The method comprises the following steps: acquiring original water depth data and corresponding sensor attitude data in real time; generating a data quality evaluation result containing a data credibility index and a data abnormal distribution feature based on the original water depth data; triggering a dynamic calibration mechanism containing a calibration period adaptive adjustment strategy and a calibration parameter optimization rule according to the data credibility index; optimizing the target calibration rule parameters in combination with the sensor attitude data to generate an optimized calibration parameter set, and correcting the original water depth data in real time by using the parameter set to generate primary calibration data; and performing topographic feature consistency check on the primary calibration data, if the primary calibration data does not pass the topographic feature consistency check, starting a re-calibration process containing a rule base updating mechanism and a parameter iteration mechanism, and analyzing a deviation trend based on historical calibration records to generate a system error prediction model.

The invention discloses a multi-modal sensor abstract description and packaging method and system based on software definition. Firstly, a unified sensor abstract description model based on software definition is introduced, so that hardware independence is realized, and the differences of a bottom-layer multi-mode sensor in the aspects of interfaces, protocols and data formats can be effectively shielded; secondly, abstract packaging of data is achieved through an autonomous information processing module, and high-bandwidth and high-redundancy original data is converted into low-bandwidth and high-value structured information; in addition, by means of automatic registration, discovery, scheduling and control mechanisms of the sensor management control module on sensor resources, the system realizes a real plug-and-play function. According to the invention, by deploying the autonomous information processing modules at various sensor nodes, the original sensing data is preprocessed, and standardized data packaging with semantic consistency is output, so that the operation load of the central controller is reduced, and the information processing efficiency and the system response capability are also improved.

The invention relates to the field of fruit tree disease and insect pest detection, in particular to a fruit tree disease and insect pest detection method and system based on machine vision, and the method comprises the steps: obtaining an image metabolome feature matrix and a preliminary difference pixel based on a preprocessed multispectral image of an original machine vision image obtained by a camera, carrying out the topological skeleton extraction, and carrying out the dimension fusion; outputting a core focus feature set; each discrete feature is used as a network node, a mutual information value between any two discrete features is calculated, and a focus area is obtained; and based on a lesion region containing lesion boundary coordinates, area and morphological parameters, extracting the ROI of the lesion region from the multispectral image, and carrying out disease and pest identification matching to obtain a detection result. According to the method, the essential attributes of the lesion are comprehensively captured by fusing the multi-dimensional features of the spectrum, the texture, the space coordinates and the morphological topology, a multi-dimensional fusion feature system is formed, and the problems that similar pest and disease damage forms are difficult to distinguish, and early lesion features are weak and difficult to recognize are effectively solved.

The invention discloses an urban multi-unmanned aerial vehicle cooperative route planning method based on deep reinforcement learning, and the method comprises the steps: building a flight environment model based on urban three-dimensional point cloud data, and achieving the efficient obstacle query through an R-Tree index; for multiple unmanned aerial vehicles, acquiring distance information of surrounding obstacles by adopting a ray-based environment sensing mode, and constructing a state space containing a current unmanned aerial vehicle state, a target relative position, relative positions of other unmanned aerial vehicles and the distance information of the surrounding obstacles; outputting continuous flight control actions through a deep reinforcement learning strategy of parameter sharing; a multi-target reward function is designed, and the multiple unmanned aerial vehicles are guided to achieve safe and efficient collaborative route planning; in the execution stage, each unmanned aerial vehicle makes an independent decision only by depending on the shared strategy network and local observation information of the unmanned aerial vehicle, and distributed cooperative flight is realized. According to the method, the complexity of a traditional method for environment perception and decision calculation is effectively reduced, and the method is suitable for a multi-unmanned aerial vehicle planning task in a complex urban airspace.

The invention relates to the technical field of virtual geographic scene visualization, and discloses a virtual geographic scene enhanced visualization method, device and equipment and a storage medium, and the method comprises the steps: obtaining a virtual geographic scene visualization request of a user terminal, considering the visualization constraint condition provided by the user terminal, and improving the visualization efficiency of the virtual geographic scene. The method comprises the following steps: rendering and mapping geographic information data into a visual display scene, constructing a scene visual feature set, and according to a selective visual expression demand of a user terminal for each scene visual feature; the scene visual features in each visual display period are subjected to display content selective expression, the scene display content with the highest visual cognition efficiency is sent to the user terminal, and finally the scene display content of the next visual display period is adjusted according to the display evaluation result fed back by the user terminal. While the operation load is reduced, the scene visualization experience of the terminal user is improved, and the scene display strategy which occupies the least system resources and can meet the current user demand is provided.

This invention discloses a weak fault diagnosis method based on chaotic signals of wind turbine stator current. The diagnostic method includes: acquiring the current signal of the wind turbine stator and preprocessing the current signal, the preprocessing including row-sequence component transformation, adaptive fundamental suppression, and detrending processing; calculating a chaos index based on the preprocessed signal; calculating a health index based on the chaos index and classifying the health status according to the health index; and outputting a diagnostic result including the health index, fault type, and graded early warning signal based on the aforementioned results.

The invention is applicable to the technical field of unmanned aerial vehicle scheduling, and particularly relates to a regional route collaborative scheduling method and system for logistics unmanned aerial vehicles. Judging whether flight interference exists based on a preset minimum interference distance, acquiring flight information of the unmanned aerial vehicle participating in the flight interference, and sending the flight information to the corresponding unmanned aerial vehicle; yaw information calculation is carried out through the unmanned aerial vehicles according to the flight information and a built-in force field simulation obstacle avoidance model, and the unmanned aerial vehicles are controlled to fly based on the yaw information; and when the distance between the unmanned aerial vehicles is greater than the minimum interference distance, outputting return flight information based on the force field simulation obstacle avoidance model, and controlling the unmanned aerial vehicles to return to the flight route. According to the regional route co-scheduling method for the logistics unmanned aerial vehicles, each unmanned aerial vehicle is regarded as an agent which autonomously moves in a three-dimensional force field, complex global path planning and real-time obstacle avoidance are decoupled, and the dimensionality and complexity of distributed calculation are greatly reduced.

The application discloses an anchor point guided clustering based data classification method, device and equipment, relates to the technical field of digital data processing, and comprises the following steps: obtaining an original data set to be classified, converting each sample data into a numerical vector, and constructing a data matrix; initializing a clustering center matrix and an anchor point matrix, and setting a fuzzy coefficient; obtaining the anchor point matrix and the clustering center matrix after joint iterative optimization; calculating the fuzzy membership degree of each sample vector; the category with the maximum fuzzy membership degree is taken as the final category label of the sample vector, and the classification results of all sample vectors are output. The application solves the problems that the existing fuzzy clustering method is sensitive to initial conditions, is easy to fall into a suboptimal solution, leads to unstable and inaccurate classification results, and cannot be directly solved by using a gradient descent algorithm, and is difficult to be applied to large-scale data sets, and realizes the enhancement of complex data classification precision and the applicability in different data scale scenes.

This application relates to a method, apparatus, equipment, and storage medium for optimizing decision-making in post-disaster casualty rescue. The method includes: acquiring multidimensional physiological parameters and individual environmental factors of the casualties; using an improved START classification method and fuzzy comprehensive evaluation for initial injury quantification; and using a Markov state transition model to predict the injury evolution trend, generating a dynamic priority queue. A collaborative optimization model integrating rescue order, rescue route, and rescue method is constructed, aiming to maximize the expected number of survivors. A decomposition-coordination strategy is used to jointly solve the model, generating a globally optimized rescue plan. An event-driven mechanism is used to trigger rescheduling based on collected dynamic environmental data. Rolling time-domain optimization is performed based on the predictive control of the collaborative optimization model, and incremental updates are used to replan only the local plans affected by disturbances, outputting adaptively adjusted rescue instructions. This method can effectively improve the expected number of survivors and overall rescue efficiency.

The present application relates to the technical field of bearing life prediction, in particular to a kind of gradient composite coating sliding bearing life prediction method, comprising the following steps: step one, build the coating degradation physical simulation model of multi-field coupling;Step two, adopt active learning algorithm to build high-precision proxy model, design active learning query strategy;Step three, online monitoring and multi-domain feature extraction;Step four, real-time state mapping and life prediction based on transfer learning;Step five, prediction result output and model updating.The present application can improve the accuracy of gradient composite coating sliding bearing life prediction, greatly reduce the operation load, and improve the prediction efficiency of bearing life.

The invention discloses background layer updating during coding. A method performed by an image processing apparatus for updating a background layer during encoding of a scene is provided. A scene is encoded based on classifying objects depicted in the scene as foreground or background. The background is divided into ranked background layers, wherein each background layer is associated with a respective depth model. The method comprises detecting (S102) a change in an image portion of a background layer. The method comprises calculating (S104) a difference between the image portion and a corresponding image portion of a background layer ranked behind the one background layer. The method comprises selecting (S106a) the background layer ranked behind the one background layer to represent the image portion when the difference is less than a threshold.

This invention provides an intelligent analysis system for photoelectric detection spectral data based on deep learning, belonging to the fields of photoelectric detection, spectral data analysis, and deep learning application technology. The system includes core units such as a spectral data acquisition unit, a preprocessing unit, a feature extraction unit, and a deep learning analysis unit, as well as auxiliary units for anomaly detection and data storage, forming a closed-loop architecture of acquisition-processing-analysis-output-optimization. It improves data quality through step-by-step preprocessing algorithms, reduces computational load by adaptively selecting key features, deeply mines spectral patterns using a model that integrates convolutional neural networks and attention mechanisms, achieves rapid scenario adaptation through transfer learning, and dynamically optimizes model parameters based on a feedback mechanism. The system solves the problems of low accuracy, poor adaptability, and long training cycles in traditional spectral analysis, achieving accurate, efficient, and intelligent spectral data analysis, and is suitable for various photoelectric detection scenarios such as qualitative and quantitative analysis of substances and environmental monitoring.

The application provides a list rendering method and device, electronic equipment, computer readable storage medium and computer program product; the method comprises the following steps: in response to a first operation for a to-be-rendered list, determining a first target object to be displayed in a viewport area of an electronic device and a second target object to be loaded outside the viewport area; calling a first coordinator located in a main execution thread, generating a first rendering instruction based on the first target object and a third target object currently displayed in the viewport area; calling a second coordinator, generating a second rendering instruction based on the second target object and a fourth target object; calling a rendering engine to obtain a current to-be-displayed view in the viewport area in response to the first rendering instruction, and calling the rendering engine to obtain a to-be-loaded view including the current to-be-displayed view in response to the second rendering instruction. Through the application, the rendering efficiency and smoothness of the list in the continuous interaction process can be improved.

The application provides a multi-agent collaborative decision-making and disambiguation method and system. The method comprises the following steps: registering the dependency relationship between the task context and the event trigger condition concerned by the agent to the coordination center, updating the dynamic dependency view through the coordination center, analyzing the knowledge update time through the coordination center, and generating a task context identifier set of the agent; constructing a fact set based on the task context identifier set, inputting the fact set into a rule reasoning engine, executing the rules in the collaborative rule base to generate a strategy, and obtaining a collaborative strategy; and distributing the collaborative strategy to the corresponding agent and executing a cleaning process at the end of the task generation period. The application solves the efficiency bottleneck of event routing in a distributed intelligent system from the system architecture level, greatly improves the real-time response capability and scalability of the system in a high-concurrency scenario while ensuring decision consistency.

The invention discloses a direct current charging interface identification and positioning method, and belongs to the technical field of automatic charging of electric vehicles. The method comprises a coarse positioning stage and a fine positioning stage. In the coarse positioning stage, the initial position of the charging port is quickly determined through image preprocessing, contour screening and ellipse fitting. In the fine positioning stage, a multi-factor cluster matching algorithm is adopted, and firstly, a matching preselected area of each feature hole is determined according to a preset geometric cluster relationship among a plurality of feature holes in the charging port; secondly, dynamically calculating scaling and rotation coefficients of the template to adapt to different postures; and finally, constructing a matching degree evaluation function in combination with a central gravitation and edge gravitation principle, and performing matching calculation on an original image and a gradient image template so as to realize accurate positioning of the feature hole. The method solves the problem that the recognition precision and efficiency of the charging port are difficult to consider at the same time in a complex light field environment, and has the advantages of high positioning precision, high processing speed, high environmental adaptability and easy engineering deployment.

The application discloses a kind of unmanned vehicle logistics directional relay network system and its coordination method, belong to intelligent logistics and unmanned vehicle application technical field, the system includes: multiple cellular airspace units, cellular airspace unit is constituted continuous grid in service area;Deployed in the center of each cellular airspace unit one micro hub, as the ground logistics node of corresponding unit;Wherein, each micro hub includes one terminal nest and at least two relay nests;Terminal nest is used to provide the storage and withdrawal interface of user goods;Each relay nest is arranged around terminal nest, and each relay nest is pre-allocated and fixedly responsible for the bidirectional goods transfer task between the unit where the micro hub is located and a particular adjacent unit;Terminal nest and each relay nest are connected by internal logistics transmission device 103.The application fundamentally simplifies scheduling and management complexity by deep coordination of cellular airspace grid, heterogeneous node division of labor, directional routing rules and high automation.

The present application relates to air conditioner detection technical field, propose a kind of air conditioner electrolytic capacitor health on-line detection method and system, the air conditioner electrolytic capacitor health on-line detection method includes collecting the voltage ripple signal of DC-DC step-down converter output in air conditioner, and detects the zero-crossing time of first time through direct current average voltage in a switching cycle, obtains first zero-crossing time;At the switching on starting moment or switching off moment of switching cycle, single sampling is carried out to output voltage ripple signal, and sampling voltage value is obtained;According to the running state of DC-DC step-down converter, it is judged that DC-DC step-down converter is currently in continuous conduction mode or discontinuous conduction mode;Based on the judgment result, corresponding capacitor parameter calculation model is selected, and the capacitance value and equivalent series resistance of output capacitor are calculated;The capacitance value and equivalent series resistance calculated are compared with preset threshold value, and if exceed threshold value, then trigger capacitor health state early warning.

The application discloses a kind of based on edge computing's distributed energy real-time monitoring system and its operating method, it is related to the technical field of energy monitoring, system includes: equipment layer, edge layer and cloud layer;Operating method includes: the original data of distributed energy equipment is collected, and original data is preprocessed;Identify the abnormal point in the data after pre-processing and the load prediction of edge node model;Based on abnormal detection result and load prediction result, according to preset rule, dynamically task scheduling is carried out to edge node, adjusts system working state;According to the current working state of system, dynamically adjust the task allocation and data interaction strategy between edge node and cloud, optimize system performance.The application can reduce data transmission delay, improve system real-time performance;Reduce the computing load of central node, improve system response speed;Optimize network bandwidth utilization, reduce operating cost;Enhance data privacy protection, improve system security.

The invention provides a surface clutter real-time generation method and device, and the method comprises the steps: determining a target time domain range and a target frequency domain range of a to-be-generated surface clutter signal according to the real-time motion state parameter of a carrier carrying a radar seeker and the beam pointing parameter of the radar seeker; generating a random clutter sequence covering the target time domain range and the target frequency domain range according to a preset amplitude statistical distribution model and a preset power spectrum model; a surface clutter signal is generated by modulating a reference radar signal, the modulation including convolving the reference radar signal using a random clutter sequence, and parameter adjusting the convolved signal to match dynamic characteristics of a carrier. According to the invention, the problem of insufficient fidelity of clutter simulation signals in the prior art is solved.

A sound signal processing method performed by a sound signal processing device includes: an acquisition step of acquiring a first sound signal indicating a first sound and including first attribute information for specifying an attribute of the first sound signal, and a second sound signal indicating a second sound and including second attribute information for specifying an attribute of the second sound signal; the second sound signal includes second attribute information for determining an attribute of the second sound signal. A determination step for determining whether or not to merge the acquired first sound signal and the acquired second sound signal on the basis of an index corresponding to a first arrival direction in which the first sound reaches a listening position, which is the position of the listener, and a second arrival direction in which the second sound reaches the listening position; a merging step for generating a merged sound signal in which the first sound signal and the second sound signal are merged when it is determined to merge the first sound signal and the second sound signal; and a reproduction step of outputting an output signal based on the generated combined sound signal.

The application discloses a sintering flue gas CO concentration optimization control method based on key influencing factor identification, and belongs to the technical field of flue gas emission reduction, and comprises the following steps: acquiring sintering production process data and corresponding sintering flue gas CO emission concentration measured values, and constructing a model sample set after pretreatment; constructing an improved grey wolf optimization algorithm, optimizing parameters of a regression algorithm, and building a sintering process CO concentration soft measurement fitting model based on the optimized regression algorithm; performing feature importance analysis by using a SHAP method, retraining the fitting model after key influencing factors are identified, and obtaining a simplified model; collecting key influencing factor data in real time, predicting CO concentration and gradient by using the simplified model; screening a regulation and control feature item that can make CO concentration decrease the most, fusing gradient descent and PPO reinforcement learning control instructions, and realizing multi-time scale optimization control of CO concentration. The application can accurately predict and efficiently reduce sintering flue gas CO concentration.

This invention discloses a synchronous update and real-time rendering method based on a tri-dexel model, relating to the fields of computer graphics and CNC machining simulation. First, the workpiece model is initialized, a tri-dexel model is established, and it is converted into voxel data and loaded onto the GPU. During machining, the tri-dexel model is dynamically updated according to the tool path, and the voxel data is synchronized to the GPU. During rendering, a line of sight is projected from the camera to the pixel, and the GPU determines the intersection in parallel. If there is an intersection, the triangular facet is reconstructed and colored; otherwise, the pixel remains uncolored. The synchronous update and real-time rendering method based on a tri-dexel model provided by this invention achieves efficient real-time rendering of high-precision models in dynamic machining, and is applicable to scenarios such as CNC milling and additive manufacturing.

The application discloses an extensible laser mapping method based on prior topological information and belongs to the technical field of multi-sensor fusion of unmanned vehicles. The method comprises the following steps: S1, multi-sensor data acquisition; S2, data preprocessing; S3, radar odometry; S3.1, IMU pre-integration; S3.2, radar point cloud matching; S3.3, pose fusion; S3.4, map construction; S4, map updating and expansion based on topological information; S4.1, dynamic loading module; S4.2, map association; S4.3, map updating evaluation and map expansion and fusion. The method realizes an incremental expansion, globally consistent and resource-efficient laser mapping system by tightly coupling multi-sensor data, embedding prior topological constraints and implementing dynamic resource management, and provides key mapping technical support for long-term autonomous navigation in a dynamic environment when the operation area is expanded.

The present application belongs to the technical field of power supply and distribution. A parallel three-level inverter modulation method, system, product, medium and equipment are proposed, which equivalent double parallel three-level inverters as a whole five-level inverter, inject zero sequence components to the initial three-phase reference signal to obtain the reference signal, identify the resultant vector through rounding and remainder operation, and then adjust the reference signal according to the sum of the three-phase state of the initial resultant vector to output a five-segment switching sequence, and then decompose the equivalent five-level reference signal into two sets of three-level reference signals, allocate the reference signals by dividing the half-carrier period and compare them with the triangular carrier to obtain a three-level vector sequence combination. The present application realizes the comprehensive optimization of common-mode voltage, zero-sequence circulating current and output current ripple, avoids complex sector judgment and duty cycle calculation, and reduces the implementation complexity and computational burden.

The invention discloses a multi-terminal fidelity display adaptation method for remote ultrasonic images, which relates to the technical field of image processing, and comprises the following steps of: firstly, acquiring heterogeneous original video streams of ultrasonic instruments of different brands / models at a clinical end, and performing standardized analysis to generate basic video streams in a unified format; then obtaining characteristic parameters such as screen resolution, proportion and decoding capability of the target terminal, and calculating a non-stretching target rendering size according to the characteristic parameters; then different areas in the video are identified through ultrasonic image feature optimization, and differential zooming processing is carried out by adopting a corresponding interpolation algorithm; and finally, calculating a structural similarity index of the core diagnosis area, if the structural similarity index is lower than a threshold value, performing feedback adjustment, and transmitting a video stream with the fidelity reaching the standard to a terminal for display. According to the method, the heterogeneous video source is standardized, and regional differentiation zooming and fidelity feedback adjustment are carried out according to the terminal features, so that compatible adaptation between various types of ultrasonic instruments and various types of display terminals is realized.

The invention relates to the technical field of power electronics, in particular to a diesel generator test system control method based on a moving average filter, and the method comprises the steps: collecting an output voltage instantaneous value of a diesel generator in real time, and obtaining a voltage sampling sequence; inputting the voltage sampling sequence into a pre-constructed moving average filter; performing moving average processing on the input voltage sampling sequence through a moving average filter to obtain an output signal; generating a current command signal based on an output signal of the moving average filter; and according to the current instruction signal, driving the diesel generator test system to simulate a load with a specific power factor through current closed-loop control, and carrying out load simulation test on the diesel generator. The moving average filter is directly used for generating a current instruction of the test system, and the lag angle of the current instruction is linearly adjusted by adjusting the point number of the filter through the linear phase-frequency characteristic of the filter, so that the accurate and convenient control of the simulation load power factor of the diesel generator test system is realized.

This invention discloses a lidar depth completion method based on hierarchical minimum surface reconstruction, relating to the fields of computer vision and image processing technology. The method includes: performing depth value inversion and morphological dilation on a sparse depth map to obtain a scene dilated depth map and a full-resolution effective mask; then downsampling to obtain a coarse-scale scene dilated map and a coarse-scale mask; using an iterative convolution kernel of the Laplacian operator to obtain a coarse-scale filled map; upsampling the coarse-scale filled map to obtain an upsampled depth map, and then fusing it with the scene dilated depth map to obtain a fused depth map; locating all remaining holes in the fused depth map using connected component analysis, and calculating the mean depth of the effective pixels within the annular pixel band around each remaining hole; using this mean depth to fill the corresponding remaining holes to obtain a hole-free depth map; and after global Gaussian blurring, performing a depth value inversion operation to obtain a scene dense depth map, thereby achieving high-precision 3D reconstruction.

The present application relates to the field of agricultural big data and fertilizer supply chain management, and particularly to a selenium-rich bio-organic fertilizer supply chain collaborative management system based on big data, comprising: a source evaluation step: a management center calls material attributes, a raw material evaluation unit analyzes source quality fluctuations to distinguish batches; an efficiency drift analysis step: in response to abnormal control signals, a conversion analysis unit performs efficiency drift evaluation feedback analysis; a supply-demand collaborative matching step: in response to regular control signals, a collaborative demand unit obtains a collaborative demand coefficient, and a matching division unit performs quantitative matching analysis of control decision; a control execution step: compare control evaluation indexes to generate control signals; the present application constructs a source fluctuation perception and supply-demand collaborative matching closed loop, solves the spatiotemporal mismatch contradiction of raw material fluctuations and soil adsorption specificity, and improves the overall efficiency of the supply chain.

The invention discloses a hydrogen fuel cell system life prediction system which comprises the following steps: a model construction module constructs an electric pile life prediction empirical model based on historical durability data of a hydrogen fuel cell system and stage characteristics of voltage attenuation of an electric pile of a hydrogen fuel cell; the life prediction module obtains a corresponding attenuation correction coefficient through a pile life prediction empirical model by utilizing historical durability data and combining with a parameter adjustment rule, obtains a pile minimum monolithic voltage attenuation curve corresponding to each reference current through the attenuation correction coefficient, and calculates a pile minimum monolithic voltage attenuation curve; and calculating to obtain a life prediction value corresponding to each reference current in the preset scene, and selecting the minimum life prediction value as a final life prediction value. By predicting the service life of the hydrogen fuel cell system, the memory occupation is reduced, and the cost is saved.

The invention discloses a table look-up type deformation matching and electromagnetic mapping digital twinning system and a table look-up type deformation matching and electromagnetic mapping digital twinning method. The system pre-constructs a multi-physical field simulation database with speed as a main key, stores a deformation three-dimensional model, pressure field data, radar cross section (RCS) data and feature point displacement, and establishes a reduced scale model deformation-speed association list. In the manual mode, the speed is directly input to call corresponding multi-physical field data; in an automatic mode, the displacement of the feature points of the reduced scale entity model is detected in real time through a displacement detection module, the current deformation quantity is calculated, a speed major key is reversely matched by adopting a minimum absolute difference method based on the association list, and then corresponding multi-physical field data is called; and synchronously displaying the deformation three-dimensional model, the pressure field pseudo-color distribution and the RCS map on a visual rendering platform, and realizing digital mapping from entity deformation to a multi-physical field state.