10 results about "Time coefficient" patented technology

The invention relates to a rainfall objective prediction method based on an intelligent algorithm, and the method comprises the steps: decomposing the midsummer rainfall observation data of a time sequence based on an empirical orthogonal function, obtaining a spatial mode and a time coefficient, calculating a circulation field mean value of a target time period based on an atmospheric circulation field monthly value data set predicted by a climate mode, and obtaining the rainfall objective prediction result. The method comprises the following steps: obtaining a circulation abnormal field through a difference value with a same-period climate state circulation field, carrying out correlation analysis on a time coefficient and the circulation abnormal field, identifying and extracting a first correlation region with high correlation, carrying out correlation analysis on the time coefficient and atmosphere reanalysis data, obtaining a second correlation region with high correlation, and identifying and extracting a second correlation region with high correlation. And extracting a circulation anomaly average value of a similar region in the first related region and the second related region as an input feature, training a prediction model according to the input feature and a corresponding time coefficient, obtaining the corresponding time coefficient according to the prediction model and circulation anomaly feature data in the second time period, and performing reduction to obtain rainfall prediction data. And the accuracy of rainfall prediction is improved.

The application discloses a wheel speed correction method for intelligent driving, and the speed time coefficient calibration method under different road conditions and variable load conditions is used in an IMU+wheel speed fusion odometer scheme, wheel speed error is reduced, and the precision of the local odometer is improved. In addition, the final result is to generate a speed scale coefficient lookup table. Through calibration, the GNSS signal is fixed in the lookup table, the situation without GNSS can be met, and because there is no online calibration calculation, the computing power is saved, the computing power requirement of the operation platform is relatively low, and the embedded scheme is promoted.

The embodiment of the invention provides a motor overload detection method and device, electronic equipment and a storage medium, and relates to the technical field of motor overload detection, and the electronic equipment can obtain the current current value of a motor and the duration corresponding to the current current value; determining a thermal time coefficient corresponding to the current current value based on a pre-calibrated corresponding relation; according to the determined thermal time coefficient and the duration, determining the heat variation of the motor in the duration; and determining the current accumulated heat based on the heat variation and the accumulated heat, and determining whether the motor is overloaded based on the size relationship between the current accumulated heat and a preset threshold value. Thus, the thermal time coefficient corresponding to the current current value can be quickly determined in a table look-up mode, and then the heat variation is calculated based on the duration and the determined thermal time coefficient without complex differential or exponential operation, so that the required calculation amount can be reduced, and the determination efficiency and the real-time performance can be improved.

This invention relates to a data processing method and storage medium for ice-elastic plate compression tests in the field of ship structural mechanics. The method includes the following steps: performing a compression test by compressing an ice sample with an elastic plate; after the compression test, obtaining the test pressure value and strain gauge test values ​​of the ice sample under compression; selecting a preset order mode shape using the modal superposition method to obtain a fitted deflection function; determining the fitted strain value corresponding to each test point of the elastic plate based on the fitted deflection function; calculating the time coefficient by combining the strain gauge test values ​​and the fitted strain values ​​using the least squares method to obtain the fitted deflection distribution function of the elastic plate; and calculating the compression energy of the elastic plate and the ice sample based on the fitted deflection distribution function and the test pressure value. This method focuses on the deformation of the elastic plate to explore the interaction between ice and the structure from an energy perspective, considering the feedback influence of structural deformation on the action process, thus forming a universal method for predicting ice loads.

The invention discloses a vortex type fluid machinery flow field prediction method, and relates to the field of flow field prediction, and the method comprises the steps: carrying out the grid division of a fluid region in a geometric model; performing CFD calculation on the divided fluid region to obtain unsteady flow field data of each grid in each time step within a preset time period after the flow field is stable; interpolating the unsteady flow field data of each grid to a static background grid corresponding to the fluid region; carrying out POD decomposition on the flow field data in the static background grid after interpolation; clustering the time coefficients to obtain a plurality of categories; respectively inputting all time coefficients in the category into a time sequence prediction model corresponding to the category to obtain predicted time coefficients corresponding to all spatial modals in the category; and predicting the flow field of the target vortex type fluid machine according to the prediction time coefficients corresponding to all the spatial modes and all the spatial modes. The computing cost can be reduced, the computing efficiency can be improved, and the requirement for hardware performance is not high.

The invention provides a computing equipment control method and device, electronic equipment and a medium, and belongs to the technical field of computing equipment control. The method comprises the steps that a task real-time coefficient is determined based on a response requirement field of a target task; determining an average response time and a thread wakeup frequency based on the task behavior data of the target task, and calculating a task real-time score based on the average response time and the thread wakeup frequency; determining a dynamic task type of the target task based on the task real-time coefficient and the task real-time score; determining a target resource allocation strategy based on the dynamic task type and the task priority of the target task; selecting a target resource from the device hardware resource data of the computing device based on the resource demand information of the target task and a target resource allocation strategy; and scheduling a target resource of the computing device to enable the computing device to execute the target task through the target resource. The problems of unreasonable resource allocation and low resource utilization rate in the prior art can be solved.

The application discloses a cloud-computing-based intelligent management system for servo motor controllers and relates to the technical field of servo motor management. For each device, the data response time of the operation data of the servo motor is obtained to obtain a time coefficient; the specific data value of the operation data is obtained to calculate a data deviation coefficient; the task end time is used to calculate a task progress coefficient; the corresponding device priority coefficient is calculated according to the time coefficient, the data deviation coefficient and the task progress coefficient, and the operation data of the servo motor of the corresponding device is uploaded to a cloud platform in the order from large to small according to the priority coefficient, so that the operation data of the servo motors of multiple devices is uploaded to the cloud platform in the order from large to small according to the priority coefficient to manage the servo motor controllers of the devices, the occupation of network bandwidth is good, data transmission delay or packet loss and other problems are reduced, the data received by the cloud platform is consistent with the actual data, and the control accuracy of the servo motors of the partial or multiple devices is ensured.

The invention discloses a rapid assessment method for effective power capability of strong impact load on typical members, and the method comprises the following steps: for rectangular cross-section opposite-edge constraint members, bringing key characteristic parameters such as pressure peak value and action time of strong impact uniformly distributed load into a unified calculation framework; a peak pressure ratio coefficient and a natural vibration period of a loaded component are calculated by acquiring a pressure peak value and action time of a strong impact uniform load and an elastic modulus, density, component span and section height of the loaded component, a time coefficient is determined according to the action time and the natural vibration period, and then an effective acting ratio is calculated based on the peak pressure ratio coefficient and the time coefficient. Effective power capability rapid comparison of different strong impact uniformly distributed loads acting on the same component and effective power capability rapid comparison prediction of the same strong impact uniformly distributed load acting on different components are realized. According to the method, an evaluation result with consistent comparability can be obtained, and the efficiency of engineering scheme type selection, parameter optimization and rapid decision can be remarkably improved.

A steam generator heat transfer tube wear prediction method based on numerical simulation and nuclear power plant overhaul data comprises the steps that a wear coefficient in an overhaul time node is decomposed into a time coefficient constant and a space basis function form, and the degree of freedom is reduced; in combination with a numerical simulation vibration curve and actual wear overhaul data of the nuclear power plant, correcting the actual wear overhaul data through measurement errors, and iterating an equation set to finally obtain a time constant coefficient meeting requirements; the obtained wear coefficient is subjected to space and time dimension expansion, and the wear depth amount of a certain spatial position point during future overhaul is calculated in combination with a vibration curve obtained through numerical simulation. The problems of large deviation between a simulation result and a real working condition, difficulty in accurately obtaining a wear coefficient, insufficient reliability of a prediction result and the like in an existing wear prediction technology are solved.

The application discloses a large-scale assimilation method for ocean dynamic downscaling. The application is based on a to-be-corrected variable in a high-resolution model, selects reference data, uses the EOF expansion of a space-time matrix, obtains a large-scale spatial mode of the to-be-corrected variable of the high-resolution model, projects the to-be-corrected variable and the reference data to the large-scale mode to respectively obtain time coefficients, and realizes the approximation of the large-scale signal of the high-resolution model to the large-scale signal of the reference data based on the obtained time coefficients, thereby improving the simulation of the large-scale signal of the high-resolution model. The application has the advantages that the large-scale signal is obviously improved through the EOF approximation of the large-scale signal of the high-resolution model, the small-scale signal which is not limited can also become more accurate through the interaction of the large-scale and the small-scale in the nonlinear coupling, the decoupling problem of the high-resolution nested simulation of the ocean model is solved, and the simulation capability of the small-scale process in the high-resolution model is improved.