7 results about "Component Load" patented technology

The invention belongs to the technical field of electric power safe operation, and particularly relates to a medium and long term load prediction method based on data decomposition and multi-model fusion, which comprises the following steps: processing missing values and abnormal values of historical load data of a power grid to obtain a historical load sequence of the power grid; decomposing the processed historical load sequence of the power grid into a trend component, a season component and a residual component according to a data decomposition means, and allocating weights to the three components; based on the generated three weighted components, constructing an independent CNN-LSTM prediction model for each component to obtain a load prediction sequence of each component; and performing linear addition based on the obtained component prediction results to obtain a final load prediction value. The method not only considers the overall characteristics of the load sequence, but also establishes a special prediction model for the time sequence characteristics of different components, and significantly improves the precision and reliability of load prediction.

The application provides a 3D model loading method, device, equipment and medium, and relates to the technical field of image data processing. The method comprises: performing spatial grid division on a 3D model to obtain a plurality of components; determining multi-dimensional data of the components, wherein the multi-dimensional data at least comprises semantic units; obtaining a current component loading queue of the 3D model and initial weight values of to-be-loaded components in the component loading queue; determining a scene to which the 3D model belongs, calculating fine-tuning weight values of the to-be-loaded components in the scene based on the semantic units of the to-be-loaded components, wherein the fine-tuning weight values are used to measure the importance of the to-be-loaded components in the scene; calculating target weight values according to the initial weight values and the fine-tuning weight values; sorting the to-be-loaded components in the component loading queue according to the target weight values, and loading the to-be-loaded components according to the sorting result. The application can improve the loading speed of the 3D model.

The invention relates to the technical field of component loading optimization, and discloses a dynamic component loading optimization method, which comprises the following steps: collecting and identifying current real-time operation data to obtain a corresponding prediction demand category and an actual operation state; setting a plurality of component loading nodes based on the predicted demand category, generating a first component loading strategy according to all the component loading nodes, performing analogue simulation according to the first component loading strategy, and calculating a simulation demand coefficient and a simulation state coefficient according to a simulation result; calculating a simulation application coefficient of the first component loading strategy according to the simulation demand coefficient and the simulation state coefficient, and judging whether the first component loading strategy is optimized or not, if not, issuing a loading instruction according to the first component loading strategy, and if yes, generating a second component loading strategy, the component loading strategy is dynamically adjusted according to the requirement during operation, the user requirement is met, stable operation is achieved, and meanwhile the system response speed is increased.

The invention discloses a power transmission and transformation project cost prediction method and system based on data mining, and relates to the technical field of project cost prediction, and the method comprises the steps: collecting multi-dimensional data covering project attributes, environmental factors and historical cost, and building a project database; performing missing value filling and preprocessing on the data, and calculating a correlation coefficient matrix; determining the number of principal components based on principal component analysis, calculating a principal component load matrix, and extracting a candidate key field set; and carrying out partial correlation analysis, cross validation and regression significance test on the candidate fields and the project cost data, identifying key factors which have significant influence on the cost, constructing a project cost prediction model based on the key factors, and carrying out scientific prediction on the cost of a new project. According to the method, the problems of high dependence and low data utilization rate of traditional experience estimation are solved, systematic identification and cost prediction of key factors of the cost are realized, and support is provided for investment decision and cost control of power grid construction.

The invention provides a sine load equivalence method of a multi-degree-of-freedom load system. The method comprises the following steps: calculating a principal stress and a principal stress angle according to a strain signal of a target part of a chassis; the multi-component load signals serve as a first group of load signals, and the multi-component load signals are recombined to obtain an in-phase recombined load component and a reverse-phase recombined load component to serve as a second group of load signals; identifying a frequency response function corresponding to each recombined load component in the second group of load signals according to the principal stress, and calculating a time domain response caused by the frequency response function on the chassis target part and a contribution degree to the principal stress; selecting the phase of the recombination load component with the maximum contribution degree as the phase of the equivalent sine load; and if the principal stress angle of the target part of the chassis and the principal stress angle under the action of the multi-component load signal meet a preset similar condition under the action of the equivalent sine load, setting a durability test target. According to the method, the problem that coupling among six components of an original complex road spectrum is difficult to effectively decompose in the prior art is solved.

This application relates to an intelligent fault diagnosis and management system and method for rail transit control consoles. The method includes: constructing a fault prediction probability model and an adaptive dynamic diagnostic threshold adjustment model; constructing a causal intensity quantification model based on fault features corresponding to the fault prediction probability; inputting potential root causes, fault features, and root cause contribution; and outputting a causal intensity score to classify fault root causes and obtain fault level coefficients; and constructing a dynamic parameter adaptive adjustment model based on the fault level coefficients, outputting component dynamic load parameters for dynamic adaptation of component loads. This invention supports zero-sample / small-sample fault detection, solving the problem of scarce fault samples. It adopts a fusion framework of unsupervised contrastive learning and cross-domain transfer learning, achieving anomaly identification without relying on a large number of real fault samples. By combining digital twins to generate high-fidelity virtual fault samples and optimizing their weights, it fundamentally solves the industry problem of few fault samples and difficulty in modeling in rail transit.

The invention provides a kiloton six-component load sensor calibration device which comprises a supporting assembly, the supporting assembly comprises a bottom plate, first supporting frames, second supporting frames and a supporting plate, and the first supporting frames are fixedly installed at the two ends of the top of the bottom plate respectively. According to the kiloton-level six-component load sensor calibration device provided by the invention, through mutual cooperation of the supporting assembly, the loading assembly, the loading tool, the guiding assembly, the moving assembly and other structures, a worker only needs to place a kiloton-level six-component load sensor needing to be calibrated on the top of the moving platform; the kiloton-level six-component load sensor is loaded on the loading tool, then the moving platform is pushed until the kiloton-level six-component load sensor is moved to the bottom of the loading tool, then the loading tool is pushed through the loading assembly, the kiloton-level six-component load sensor can be calibrated, other transfer equipment is not needed for cooperative operation, the operation process is simplified, and the working efficiency is improved.