13results about How to "Accurate life" patented technology

The invention discloses a metal structure material service behavior evaluation method and system based on a large-model multi-modal analysis technology, belongs to the technical field of metal structure materials, and solves the problem of obvious limitation in coping with a complex and changeable service environment. Comprising the steps of selecting a proper data source, determining a data crawling target, cleaning and labeling crawled data, performing training by using a deep learning model, and constructing a knowledge base; designing an experiment, collecting experiment data, combining the experiment data with other data through an intelligent agent, and carrying out multi-modal data fusion analysis; comparing a multi-modal data fusion analysis result with experimental data, calibrating a prediction model, and optimizing an analysis process; an intelligent decision support system is constructed, an experiment scheme is automatically generated, the experiment process is optimized, and suggestions are provided. The dynamic change of the material in the service process can be responded in real time, the prediction model is automatically adjusted, and the adaptability and real-time performance of the system in a complex environment are ensured.

The invention discloses a wind loading key part service life prediction method based on fretting wear and damage accumulation. The wind loading key part service life prediction method comprises the steps of establishing a multi-rigid-body system dynamic model of wind power equipment; constructing a multi-flexible body system dynamics finite element model of the key parts of the wind power equipment; constructing a multi-field coupling model of the key parts; carrying out fretting wear analysis by adopting a multi-field coupling model of the key part; constructing a life prediction model and a damage accumulation model; and inputting stress-strain data of each node of the key part into the life prediction model and the damage accumulation model to obtain a life prediction result and an accumulated damage value of the key part of the wind power equipment, and the like. The method has the remarkable effects that the service life prediction and the fatigue damage calculation can be accurately carried out on the key parts of the wind power equipment, and the method has important significance for improving the service reliability of the wind power equipment.

The invention belongs to the technical field of epoxy resin and impregnated paper sample wafer aging defect diagnosis, and discloses an epoxy resin and impregnated paper sample wafer aging defect diagnosis and service life prediction system. Comprising a thermal aging treatment module, a dielectric property test module, a main control module, a mass loss calculation module, an aging degree analysis module, a physicochemical property detection module and a life prediction module. According to the invention, a thermal aging test platform for the epoxy resin sample wafer and the epoxy impregnated paper sample wafer is established, the research on the aging degree rule of the sample wafer is completed from multiple angles of dielectric properties, Fourier infrared spectroscopy, mass loss rate and scanning electron microscope, and the research on the aging degree rule of the epoxy resin sample wafer and the epoxy impregnated paper sample wafer along with the deepening of the aging degree is elaborated. The changes of the surface appearance and the micromolecular structure of the dry-type bushing are explained in combination with the dielectric property, and a theoretical basis is provided for subsequent dry-type bushing aging degree judgment.

The invention provides a service life evaluation system for silicon-based passive devices, which relates to the technical field of electric appliance performance evaluation and comprises an upper computer, a main control signal module, a power supply module, a constant temperature box, a multi-terminal test interface module and a plurality of silicon-based passive devices. The plurality of silicon-based passive devices are inserted into the multi-terminal test interface module; the power supply module comprises a working power supply and a high-voltage direct-current power supply; the working power supply and the high-voltage direct-current power supply are both electrically connected with the main control signal module, the main control signal module is electrically connected with the multi-terminal test interface module, and the multi-terminal test interface module is placed in the constant-temperature box; performing an accelerated stress test on the silicon-based passive device inserted into the multi-terminal test interface module to obtain an accelerated stress test result; and evaluating the service life of the silicon-based passive device based on an accelerated stress test result. According to the invention, the test efficiency is improved, and the accuracy and practicability of life prediction are enhanced.

The application discloses a kind of unmanned mine car reliable life prediction methods of fusion-field theory, comprising: based on object-field theory, multiple source performance degradation parameters are classified and extracted, and initial performance degradation dataset is constructed;And normalization processing;Using mutual information method, the correlation measure between each performance degradation characteristic and mine car reliable life after normalization processing is calculated, and according to the set threshold, the key object-field performance degradation factor is filtered out, and constitutes key factor dataset;Using piecewise linear model, the reliable life label of sample in key factor dataset is set;With the reliable life label corresponding to key factor dataset as training data, a deep neural network prediction model is constructed and trained;Using the trained deep neural network prediction model, according to the real-time or historical acquisition key object-field performance degradation factor data, the reliable life of unmanned mine car is predicted.The more accurate, dynamic prediction of the reliable life of unmanned mine car is realized.

The invention relates to the technical field of power device testing, and particularly provides a power device service life testing method, device and equipment and a storage medium, and the power device service life testing method comprises the steps: opening a path between a double-pulse testing circuit and a to-be-tested power device, and inputting continuous pulses to the to-be-tested power device through the double-pulse testing circuit; in response to the fact that the number of continuous pulses input to the to-be-tested power device reaches a first preset number, a path between the double-pulse test circuit and the to-be-tested power device is turned off, and the first preset number is smaller than the maximum pulse cycle number indicated by the rated service life of the to-be-tested power device; performing thermal resistance test on the to-be-tested power device to obtain the current junction-to-case thermal resistance of the to-be-tested power device; determining whether the to-be-tested power device fails based on the current junction-to-case thermal resistance; and if yes, determining that the actual life of the to-be-tested power device does not reach the rated life. In this way, the accuracy of the service life test of the power device can be improved.

The invention discloses a method and system for testing the service life of an acetabular cup, and the method comprises the steps: outputting a dynamic stress distribution cloud picture according to the three-dimensional structure parameters and material attributes of an acetabular cup implant; outputting a damage evolution feature vector based on the dynamic stress distribution cloud picture; outputting a cross-scale fatigue damage prediction model according to the damage evolution feature vector; outputting a dynamic damage accumulation index based on the cross-scale fatigue damage prediction model; and according to the dynamic damage accumulation index, optimizing a test parameter space through reinforcement learning, generating an accelerated life test protocol, driving a six-degree-of-freedom test board to execute multi-modal coupling loading, and outputting a life prediction confidence interval report. According to the embodiment of the invention, more accurate service life prediction and reliability evaluation can be realized.

This invention discloses a battery life prediction method and system based on a multi-scale state-space model, belonging to the field of battery health management technology. The method includes acquiring battery operating data; calculating relative characteristics at various time scales based on the operating data; generating a battery identification code based on the battery's specifications and attribute characteristics; inputting the relative characteristics at each time scale and the battery identification code into a multi-scale state-space model for fusion and processing; and outputting the battery life prediction result and health status assessment. This invention can simultaneously process batteries of different models, capacities, and production batches, significantly reducing model deployment and maintenance costs; through multi-scale feature fusion and physical constraints, it provides more accurate life prediction and health status assessment; the model output used in this invention includes degradation mode classification and uncertainty estimation, providing users with more comprehensive decision support.

The invention relates to an emergency command system informatization guarantee system full life cycle management method and system, and the method comprises the steps: obtaining the operation parameters and technical parameters of all equipment; at least one equipment influence factor is introduced, the fault rate and the service life of the equipment are predicted in combination with the operation parameters and the technical parameters of all the equipment, a fault rate change curve graph and a half-decay value of the equipment are obtained, and the service life residual value of each piece of equipment is determined; automatically scanning whether each device has an unexpected behavior or not, and performing corresponding correction operation on the device having the unexpected behavior; and when the unexpected formation of the equipment is not automatically solved and the service life residual value of the equipment is lower than a preset threshold value or is close to a half-decay value, sending an alarm prompt to a user side, and pushing an emergency disposal scheme to request a user to intervene in processing. The method has the remarkable beneficial effects of improving the operation efficiency of the system, accelerating the fault response speed, improving the fault prediction capability, reducing the maintenance cost and the like.

The present invention is applicable to the field of injection molding, and provides a virtual detection and evaluation method and system for injection molding of automotive plastic parts. The system includes: a data acquisition and real-time monitoring module, a temperature field model construction and thermal analysis module, a performance change analysis module, and a virtual experiment and performance evaluation module. The method can systematically evaluate the performance and reliability of injection molded parts under actual use conditions through accurate thermal field simulation and stress analysis. In addition, combined with fatigue theory and oxidation reaction analysis, it provides a scientific basis for predicting the service life and performance changes of materials, making the prediction results more accurate and reliable. This can not only effectively identify potential failure modes, but also provide data support for design optimization and material selection to improve product quality and durability. At the same time, the use of virtual detection technology reduces the cost and time of actual testing, improves R&D efficiency, and promotes the process of intelligent manufacturing.

The present invention relates to a method for evaluating the service life of a motor, the method comprising the following steps: obtaining the working data of the motor, and inputting the historical working data into a preset aging model for analysis to generate first aging prediction data; obtaining the working environment data of the motor, and inputting the working environment data into a preset environment judgment model to output an environmental impact factor; correcting the first aging prediction data based on the environmental impact factor to generate second aging prediction data; the preset life prediction model calculates the basic motor service life according to the second aging prediction data; obtaining the historical fault data of the motor, and generating fault life correction data according to the historical fault data; correcting the basic motor service life based on the fault life correction data to generate a corrected service life. The present application has the effect of improving the prediction accuracy of the motor service life.

The utility model belongs to the technical field of chambering cutters, particularly relates to a chambering cutter with a guide support, and aims to solve the problem that in the actual use process, as a drilling edge, a chambering edge, a chip accommodating groove, a cutter groove and an edge strip are of an integrated structure, a cutting part and a handle part need to be replaced together during replacement, so that the cost is increased. Comprising a chambering cutter clamping block, a supporting rod fixing groove is formed in the lower end of the chambering cutter clamping block, a first guiding supporting rod is movably installed at the lower end of the chambering cutter clamping block, a first chambering cutter block is movably installed at the lower end of the first guiding supporting rod, and a second chambering cutter block is movably installed above the first chambering cutter block; and a third chambering cutter block is movably mounted above the second chambering cutter block. When the broaching tool is abraded or damaged, only the first broaching tool block, the second broaching tool block and the third broaching tool block need to be replaced, the whole broaching tool does not need to be replaced, and cost is greatly reduced.

The present invention provides a method, device and readable medium for calculating the life of cooling water in a water cooling system. The method comprises: collecting temperature data and conductivity data of cooling water in the water cooling system within a preset time period; determining a target calculation strategy according to the temperature data and conductivity data of cooling water; wherein the target calculation strategy is a method for calculating the life of cooling water; performing characteristic value calculation on the temperature data and conductivity data of cooling water to obtain parameter characteristic values ​​of cooling water; and calculating the life of cooling water in the water cooling system according to the parameter characteristic values ​​of cooling water and the target calculation strategy. This solution can achieve accurate maintenance of the water cooling system by calculating the life of cooling water.