39 results about "Fault modelling" patented technology

The invention provides a dry-type transformer turn-to-turn short circuit multi-physical field simulation analysis method considering insulation aging and harmonic influence, and relates to the technical field of simulation analysis, and the method comprises the following steps: constructing a physical simulation model of a to-be-tested dry-type transformer; setting physical parameters and multi-physical field operation conditions of the physical simulation model; calculating a corresponding physical field operation calculation result under each physical field operation condition; performing post-processing on the physical field operation calculation result; by establishing a detailed simulation model and accurately assigning physical property parameters of each component, physical property changes of the turn-to-turn insulating material at different aging stages and under different temperature and frequency conditions are emphatically considered; turn-to-turn short circuit fault modeling is further introduced, magnetic-thermal-flow coupling simulation calculation is carried out under multi-harmonic excitation, the multi-physical field distribution characteristics of the dry-type transformer during different turn-to-turn short circuit faults are explored, and a reliable basis is provided for design optimization and safety evaluation.

The invention discloses an unmanned aerial vehicle automatic test method, which comprises the steps of building a high-fidelity semi-physical simulation platform which comprises an unmanned aerial vehicle motion simulator, a three-dimensional environment simulator, a flight control module and a ground control station, and loading a complete machine fault model and a dynamic environment model; designing an intelligent multi-fault injection scheme, and defining a single fault scene, a combined fault scene and a fault evolution scheme; configuring a dynamic environment simulation scene including static environment parameters, dynamic environment elements and environment, and a fault interaction scene; executing a self-adaptive test process, automatically generating a test case, intelligently scheduling a test sequence and dynamically adjusting test parameters; and performing multi-source data intelligent analysis and evaluation, collecting test data, performing fusion analysis on fault influence, and generating an evaluation report. By constructing a whole machine fault and dynamic environment model, the scene authenticity is improved by 40%, and for example, the motor fault yaw deviation under strong wind is closer to a real machine compared with a traditional method.

The invention discloses an automatic control method of a molded case circuit breaker operating mechanism, and particularly relates to the technical field of molded case circuit breakers. Electrical parameters are monitored in real time and transmitted to a control system, and comparative analysis is performed based on a preset threshold value and a fault model, so that faults are detected in time and a control instruction is generated, and the system can identify and sort multiple fault scenes, automatically execute switching-on or switching-off actions and ensure the reliability and stability of a power system; a judgment mechanism based on the circuit recovery condition is introduced, after the circuit is disconnected, whether recovery operation is carried out or not is reasonably judged according to the state of the circuit breaker and the recovery condition of the power system, the self-recovery capacity and the fault diagnosis capacity of the power system are effectively improved, the method can adapt to the influences of high loads, complex environments and power grid fluctuation, and the reliability of the power system is improved. And the reliability and the precision of an automatic control system are obviously improved.

The invention relates to the technical field of circuit board detection, and discloses a circuit board detection method and system, electronic equipment and a storage medium, and the method comprises the steps: collecting historical design parameters and simulation results of a circuit board, processing the design parameters and the simulation results, and forming a data set # imgabs0 #; executing a prediction model training strategy according to the data set, and generating an output prediction model of the circuit board; obtaining current design parameters of the circuit board, and applying the design parameters to the output prediction model to obtain a model result; executing the simulation dynamic adjustment strategy, and dynamically adjusting the simulation process of the simulation tool; historical fault design parameters of the circuit board are collected, a fault model training strategy is executed, and a fault prediction model of the circuit board is generated; applying the current design parameters of the circuit board to the fault prediction model to obtain a fault probability; setting a fault probability threshold; if the fault probability is not less than the fault probability threshold. And performance prediction, simulation optimization and fault early warning and correction in the circuit board design and manufacturing process are improved.

The invention discloses a steam turbine high-pressure control valve fault detection method based on an improved attention mechanism, and the method comprises the steps: generating a fault data set for training through building a mathematical simulation model of a steam turbine control system and various fault models of a high-pressure control valve; the short-term data with the high sampling frequency and the long-term data with the low sampling frequency are spliced into a mixed sequence, short-term and long-term data features are extracted by adopting a multi-scale attention mechanism, and system operation features under different time scales are fused; and acquiring context representation of each time point through a multi-head attention mechanism, and outputting a fault type prediction result of the time point by using a full connection layer and a softmax function. Through the method, the abnormal state of the high control valve of the steam turbine is detected, and a new technical means is provided for fault detection and prevention of a power system.

According to the main shock and aftershock time sequence rapid construction method and device provided by the invention, the influence of similar source generation mechanisms of main shock and aftershock, similar propagation paths, the same field effect and the like is fully considered, and the main shock and aftershock time sequence is rapidly and accurately constructed. The method comprises the steps that 1, the most dangerous fault plane and the spatial position and size of the fault plane are determined according to seismic fault data, sub-events with different circle center positions are generated randomly, and the size of each sub-event is represented by a radius; 2, determining the magnitude of the aftershock according to the set main shock magnitude and the main and aftershock power law relationship; step 3, according to the magnitude of the main earthquake and the aftershock, using rectangles consistent with the size of a main earthquake source and aftershock source to perform frame selection on the fault plane, and using sub-events contained in the rectangles to form an earthquake source model so as to obtain an earthquake source finite fault model of the main earthquake and the aftershock; 4, a deterministic Green function is obtained through decoupling; and step 5, carrying out convolution on the seismic source finite fault model and the deterministic Green function to obtain a final main shock and aftershock sequence.

System (1) for predictive diagnosis of fault conditions of components (5) of the powertrain of a fleet (3) of electrically powered mobile working machines (4), wherein the system comprises: at least one working machine (4) with a communication module for sending operating data (BG); and a central unit (2) spatially separate from the working machine (4), which is designed to receive the operating data (BG) from the working machine (4) via a communication network, characterized by a data processing unit implemented in the central unit (2) with: a) an anomaly detection module configured to detect deviations from normal behavior in the operating data (BG) received from the working machine (4) that indicate an impending fault; and b) at least one hybrid fault model (24) configured to analyze the relevant operational data (OD) after detection of a deviation by the anomaly detection module, wherein the hybrid fault model (24) combines physical domain knowledge about the component (5) and data-driven models to specify a fault type and determine a fault severity.

The application discloses a camera fault determination method, device and computer readable storage medium. The camera fault determination method comprises the following steps: obtaining script data of a to-be-identified object; determining a fault identification threshold of the to-be-identified object according to a pre-trained fault model; and determining a fault determination result corresponding to the to-be-identified object according to the fault identification threshold and the script data. The to-be-identified object comprises a camera, a client and / or a video monitoring platform. The fault identification threshold of the to-be-identified object is determined through the pre-trained fault model, and the fault determination result of the to-be-identified object is determined based on the fault identification threshold and the script data. In this way, the offline troubleshooting efficiency of the camera and the accuracy of the fault determination are improved.

The present invention relates to a method for monitoring the operating conditions of a surge tank of a hydropower unit based on MFCC and a fault model library. A soundprint sensor is used to collect the soundprint signal of the surge tank. Based on historical data of the soundprint signal, liquid level signal, vibration signal, and pressure pulsation signal of known surge tank faults, a soundprint model library containing typical soundprint features is established for quickly comparing and identifying whether common faults are present under the current operating condition based on the soundprint signal of the current surge tank. Furthermore, a fault model library containing soundprint, liquid level, vibration, and pressure pulsation feature data is constructed for comparing and identifying whether known faults are present under the current operating condition based on the soundprint, liquid level, vibration, and pressure pulsation signals of the current unit. The present invention achieves real-time, online, high-precision, and automatic identification of surge tank faults, significantly improving the efficiency and accuracy of fault diagnosis and reducing downtime and maintenance costs caused by misdiagnosis or missed diagnosis.

Methods, computing systems, and computer-readable media for a machine learning method of modeling fault-related properties of a geological region are presented. The techniques include: obtaining seismic geological data for a geological region; obtaining from a user identifications of a plurality of faults in the geological region; automatically generating values for descriptors of respective faults of the plurality of faults; automatically partitioning faults of the plurality of faults into a plurality of groups according to the values for the descriptors; obtaining a mapping of respective groups of the plurality of groups to modeling parameter values; applying the mapping to a fault in the geological region outside of the plurality of faults to obtain a modeling parameter value for the fault outside of the plurality of faults; and modeling a fault-related property of the geological region based on the modeling parameter value for the fault outside of the plurality of faults.

The fault processing method, device, network equipment and storage medium provided by the embodiment of the application analyze the historical data of each optical module according to the model of the optical module, determine the historical data that mutates when the optical module of the corresponding model is in a fault condition, extract the corresponding original fault data from the historical data that mutates, and train a fault model according to the original fault data and the model of the optical module. Thus, by dividing according to the model of the optical module, the flexibility of collecting the historical data of the fault optical module is improved, and the application range of fault detection is further improved. In actual use, automatic updating can be achieved, the detection accuracy is continuously improved with the accumulation of fault data, and the operation and maintenance cost of the optical module is effectively reduced.

The invention provides a bearing fault detection method and device, equipment, a storage medium and a product. The method comprises the following steps: acquiring rotating speed data and vibration data of a target bearing in a running state; constructing a corresponding fault simulation model based on the structure parameters of the target bearing; based on the rotating speed data, inputting the rotating speed data into the fault simulation model for simulation to obtain a simulation signal, the simulation signal comprising potential fault features; a periodic signal in the simulation signal is analyzed and determined, a guidance information sequence is obtained, and the guidance information sequence is data of a feature area related to a fault in the identification signal; and extracting a fault feature signal according to the vibration data and the guidance information sequence to obtain a fault detection result. The physical condition of the target bearing obtained through simulation can stably capture features consistent with those of a physical fault model, and stable and accurate weak fault early warning is achieved.

The invention belongs to the technical field of motor fault simulation, and particularly relates to a single-phase open-circuit fault simulation method and system of a permanent magnet synchronous motor for a motor simulator. Steady-state switching ripples and a transient regulation process of the open-circuit phase current are avoided, and the open-circuit phase current is ensured to be zero all the time, so that the fault simulation precision is improved; meanwhile, in the fault cut-in process, through mutual cooperation of a fault control switch and a fault current buffer switch connected with the fault control switch in parallel, when the fault current buffer switch is closed, the fault control switch is switched off, and when current in the fault current buffer switch reaches a zero crossing point, single-phase open-circuit fault simulation is carried out, and open-circuit phase current is smoothly cut off. In combination with smooth switching between a normal model and a fault model, smooth switching of a single-phase open-circuit fault is finally realized, overvoltage caused by direct cutting off of an inductive current is avoided, and the simulation precision is further improved while the equipment safety is ensured.

The application provides a three-dimensional complex fault model construction method based on deduction and related equipment, including: determining fault data of a target area, and extracting and analyzing the fault data to determine attribute data, planar fault discrete points and profile elevation data; determining a first fault throw and a discrete point throw change type, and determining hanging wall discrete point coordinates and footwall discrete point coordinates according to the first fault throw and the discrete point throw change type; determining a stratigraphic layer spacing, determining a second fault throw change range and a second fault throw according to the stratigraphic layer spacing and the first fault throw; prioritizing the faults, determining a priority order, and performing intersection deduction according to the priority order to determine a first stratigraphic model; performing intersection deduction on the faults and special geological structures to determine a second stratigraphic model; encrypting the discrete points of each fault in the stratigraphic model to determine a discrete point set, and performing Delaunay triangular grid subdivision on the discrete points to generate a fault surface model.

The application discloses a satellite attitude control system event-triggered STF fault detection method, and belongs to the technical field of detection, which comprises the following steps: establishing a fault model of a satellite attitude control system; introducing an event-triggered mechanism; adopting an STF method to design an event-triggered fault detection filter; obtaining an estimation error dynamic equation and a residual signal through linearization processing of the fault detection filter, realizing complete decoupling of the residual signal and the event-triggered error; converting a design problem of a residual generator into solving a gain matrix of the fault detection filter; calculating a residual evaluation function and comparing the residual evaluation function with a threshold value to judge whether a fault occurs or not. The application utilizes the STF method to design the fault detection filter, can enable the system to keep the tracking ability to a sudden state when reaching a stable state, adopts a brand-new event-triggered framework, realizes complete decoupling of the residual signal and the event-triggered error, and effectively improves the resource utilization rate under the premise of guaranteeing the system performance.

The invention provides a transformer fault voiceprint diagnosis sample enhancement method, a transformer fault voiceprint diagnosis sample enhancement system and a storage medium. The method comprises the following steps: constructing an acoustic wave equation of vibration of an iron core and a winding in medium propagation and a medium interface boundary condition; performing sound field simulation on the fault model according to the acoustic wave equation and the medium interface boundary condition to obtain a fault simulation sound field, and determining a physical simulation data set according to the fault simulation sound field; carrying out sparse representation on the physical simulation data set to obtain a sparse dictionary and a sparse coefficient matrix, and carrying out transfer learning on a real fault sample to obtain a transfer dictionary; and performing sample enhancement according to the sparse dictionary, the sparse coefficient matrix and the migration dictionary to obtain a transformer fault voiceprint enhancement sample. According to the embodiment of the invention, the sample enhancement is carried out through the sparse dictionary, the sparse coefficient matrix and the migration dictionary, and the sample enhancement effect of the transformer fault sample can be effectively realized.

The invention relates to the field of rail transit, and relates to a rail transit troubleshooting method and system, and the method comprises the steps: constructing a tree fault model, setting a plurality of nodes for the tree fault model, each node representing a fault, and setting a logic relation between the nodes; acquiring a fault occurring in real time in the train, and selecting a corresponding tree fault model; dividing the nodes in the tree fault model into different types of nodes according to the logical relationship among the real-time vehicle-ground wireless signals, the real-time manual detection data and the nodes, and deleting the nodes of which the faults do not occur; and arranging the remaining nodes in the model, and generating a troubleshooting guide flow chart corresponding to the real-time fault of the train according to the arrangement sequence. According to the method, the real-time vehicle-ground wireless signals and the real-time manual detection data are combined, screening and updating of the tree fault model are rapidly completed, troubleshooting guidance is performed according to the updated model, the problem of low troubleshooting efficiency is solved, and the troubleshooting accuracy is improved.

The invention discloses a bank IT system fault simulation method based on chaos engineering and a related product. The method comprises the following steps: acquiring a to-be-simulated system component and a fault model type; determining a relation dependency point list of the to-be-simulated system component based on the system dependency relation graph; the relationship dependency point list comprises a plurality of nodes, and each node has a dependency relationship with the to-be-simulated system component; chaos experiment design is carried out based on the relation dependence point list of the to-be-simulated system component and the fault model type, and a chaos engineering file is obtained; and performing fault simulation on the to-be-simulated system component based on the chaos engineering file to obtain a fault coefficient of the to-be-simulated system component, and updating the system dependency relationship graph based on the fault coefficient of the to-be-simulated system component. The prediction and coping capacity of the bank IT system when facing uncertain faults is effectively enhanced, and the fault operation, maintenance and repair cost of the bank IT system is reduced especially in the aspect of cascade fault simulation caused by the dependency relationship.

This invention discloses a method for fault-tolerant control of flapping wings and actuators for bionic flapping-wing aircraft, comprising steps 1: establishing a fault model suitable for fault-tolerant control; 2: estimating and suppressing mismatched and matched interference; 3: developing a fault-tolerant control strategy for the flapping wings and actuators; and 4: designing an interference-resistant high-order sliding mode fault-tolerant controller. This invention proposes a novel control method for fault-tolerant control of flapping wings and actuators. Based on a high-order sliding mode method, combined interference estimation technology, and an adaptive control strategy, this method develops a novel control strategy with high interference immunity, excellent fault tolerance, and strong robustness.

The invention discloses a virtual reality inspection emergency method and system for safe operation of a pressure vessel, particularly relates to the technical field of virtual reality, is used for solving the problem of fault causal chain distortion in virtual emergency training, and aims to visually display fault information by utilizing a visualization technology and trigger playback through sight stay. The perception of an operator on a fault trigger point and a path is enhanced; dividing an independent time axis based on a fault process and a material failure mechanism, and dynamically adjusting the time flow rate to ensure self-consistency of simulated physical logic; the fault model and the intervention model run in parallel in the virtual engine, the behavior of an operator is responded in real time, a branch fault evolution scene is generated, and the dynamic adaptability of training is improved; by constructing the fault propagation vector field and comparing the fault propagation vector field with the preset reference, the cause and effect deviation contour surface projection is generated, personalized optimization guidance is provided for an operator, connection between virtual training and actual operation is effectively enhanced, and the emergency disposal ability of the operator is comprehensively improved.

The application provides a composite fault model library construction method and device, electronic equipment and a storage medium, which are applied to a pumped storage power station. The method comprises the following steps: obtaining multiple types of basic fault elements and historical fault reports; performing coupling relationship analysis on the multiple types of basic fault elements based on the historical fault reports, constructing a fault coupling graph atlas with the basic fault elements as nodes and the coupling relationship between faults as directed edges, and assigning a coupling probability to each directed edge; performing sub-atlas activation processing on the fault coupling graph atlas based on a current simulation working condition to obtain an activated sub-atlas associated with the current simulation working condition; performing weighted sampling on the activated sub-atlas based on the coupling probability to generate a composite fault combination; and mapping the composite fault combination to a real-time digital simulation platform through a high-fidelity injection mechanism and modifying corresponding model parameters to complete the construction of a composite fault model. In this way, a high-fidelity composite fault scene is generated, and the comprehensiveness and authenticity of fault simulation are significantly improved.

Embodiments of the present application provide a GNSS data fault simulation method and device, electronic equipment and storage medium, relating to the technical field of satellite navigation and positioning. The method comprises: obtaining original GNSS road test data under a target scene and performing RTK positioning solution to obtain a plurality of feature data, constructing a decision tree classification model based on each feature data, identifying and extracting a target scene epoch interval in the original GNSS road test data through the decision tree classification model, generating a plurality of fault models based on the target scene epoch interval and a plurality of fault data in the interval, determining a plurality of fault inclusion criteria under the target scene to obtain fault data through the corresponding fault model according to each fault inclusion criterion, and injecting the fault data into the corresponding original GNSS road test data to obtain GNSS fault simulation data. Embodiments of the present application can quickly and accurately obtain GNSS fault simulation data, meeting the data quantity requirement of autonomous driving integrity under the target scene.

The invention discloses an AR-based spacecraft electronic system diagnosis and maintenance system, solves the problems of fault diagnosis and auxiliary maintenance, and belongs to the technical field of spacecraft comprehensive test and diagnosis. Comprising a closed-loop control measurement system, an embedded diagnosis and maintenance management system, a fault injection system, a fault diagnosis and maintenance knowledge system and an AR fault maintenance interaction system. The closed-loop control measurement system achieves on-orbit real-time state monitoring of a spacecraft electronic system, the embedded diagnosis and maintenance management system completes diagnosis algorithm configuration and fault injection control, the fault injection system achieves fault injection, and the fault diagnosis and maintenance knowledge system provides fault model and maintenance knowledge support. The AR fault maintenance interaction system realizes virtual-real fusion maintenance guidance, and each subsystem realizes a data flow closed loop through a standardized communication protocol.

The present invention belongs to the technical field related to rotor dynamics, and discloses a simulation method for crack faults of a gas turbine rotor. The method includes the following steps: S1 Simplify the disk structure of the gas turbine rotor into a multi-disk rotor system, and construct the overall dynamic equation of the multi-disk rotor system; S2 Solve the area of the crack closure region and the crack stiffness matrix; S3 Use the overall stiffness matrix of the multi-disk rotor system at the current moment to solve the displacement vector at the current moment and the crack stiffness matrix at the current moment, and use the crack stiffness matrix at the current moment to update the overall stiffness matrix; S4 Use the updated overall stiffness matrix as the overall stiffness matrix at the next moment, and return to step S3, and iterate in this way to calculate the displacement vectors at all moments, thereby realizing the simulation of the gas turbine rotor fault. Through the present invention, the problem that the existing crack fault model cannot accurately simulate the crack fault of the actual gas turbine rotor is solved.

A method for vehicle fault management includes generating, for a vehicle system, a fault model including a plurality of faults using design failure mode and effect analysis information and parsing each of the faults of the plurality of faults by subsystem of the vehicle system. The method also includes determining, for a respective fault of the plurality of faults, whether the respective fault is associated with at least one existing diagnostic trouble code based on fault code requirement information. The method also includes, in response to a determination that the respective fault is associated with at least one existing diagnostic trouble code, associating, in a fault database, the at least one existing diagnostic trouble code with the respective fault.

The invention discloses a permanent magnet synchronous motor broken tooth fault diagnosis and fault-tolerant control system based on multi-source signals in the technical field of automatic control and adjustment. The system comprises a multi-source signal acquisition module, a fault diagnosis module, a disturbance estimation module and a fault-tolerant control law module. The multi-source signal acquisition module acquires a real-time operation signal; the fault diagnosis module processes the real-time operation signal and extracts a fault feature signal, and the fault diagnosis module adopts a coupling broken tooth fault model to calculate the fault feature signal; the disturbance estimation module obtains an estimated value of total disturbance based on the fault characteristic signal; the fault-tolerant control law module generates a permanent magnet synchronous motor system control instruction based on the estimated value of the total disturbance; according to the method, an FMAESO fault-tolerant control strategy is provided, disturbance and specific faults are subjected to integrated estimation and compensation, and an independent diagnosis unit is not needed; the stability and the control precision of the motor in wide speed range operation are improved, the robustness is high, and the system development period is shortened.

This invention discloses an automated control method for the operating mechanism of a molded case circuit breaker (MCCB), specifically relating to the field of MCB technology. By monitoring electrical parameters in real time and transmitting them to the control system, and performing comparative analysis based on preset thresholds and fault models, the system can promptly detect faults and generate control commands. The system can identify and prioritize multiple fault scenarios, automatically executing closing or opening actions to ensure the reliability and stability of the power system. Furthermore, this invention introduces a judgment mechanism based on circuit recovery status. After the circuit is disconnected, the system rationally determines whether to perform a recovery operation based on the status of the circuit breaker and the recovery status of the power system, effectively improving the self-recovery capability and fault diagnosis capability of the power system. This method can adapt to the effects of high loads, complex environments, and power grid fluctuations, significantly improving the reliability and accuracy of the automated control system.

The invention provides a software fault tolerance evaluation method and system based on fault injection, and the method comprises the steps: determining a fault type needing to be detected and a fault model corresponding to the fault type according to the operation logic of to-be-detected software, and generating a test case containing a fault injection position, an injection time and an injection parameter based on the fault model; executing the test case through a fault injection method, and collecting field data when a fault is triggered; calculating a software fault detection rate gamma SFDR and a software fault isolation rate based on the data of the collection site; and generating a fault-tolerant capability preliminary evaluation report based on the weighted comprehensive value of the software fault detection rate gamma SFDR and the software fault isolation rate gamma SFIR. According to the technical scheme, quantitative evaluation of the software fault detection rate and the fault isolation rate can be achieved by designing the fault model to generate the test case and combining the fault injection and data automatic collection technology, and the reliability verification efficiency of software in a complex environment is effectively improved.

The application relates to the technical field of magnetic disk, and discloses a hard disk common mode fault analysis method, device, equipment and medium based on a server, which comprises the following steps: determining a fault-related component according to pre-collected type and fault mode data of the hard disk of the server; determining a main fault factor based on the fault-related component; analyzing the main fault factor, establishing a fault model corresponding to the main fault factor, and determining a common mode fault factor of the server based on the fault model. According to the scheme, the type and fault mode of the hard disk of the server are classified, the hard disk common mode fault is considered, the hard disk working environment and the use mode are deeply analyzed, potential fault factors are effectively identified, corresponding fault models are respectively established according to the analysis of the main fault factors, the common mode failure risk is analyzed, the ability of identifying potential problems is improved, and a data basis is provided for subsequent targeted preventive measures.

This invention provides a multi-sensor fault diagnosis method for hydropower units, belonging to the field of mechanical fault diagnosis technology. The method includes collecting vibration signals from multiple sensors of a hydropower unit at different sampling frequencies; preprocessing the vibration signals to obtain standardized three-dimensional data; and enhancing the three-dimensional data. A multi-sensor fault model for the hydropower unit is constructed and trained. Based on the enhanced three-dimensional data, the trained multi-sensor fault model is used to diagnose faults in the multi-sensor system of the hydropower unit. This invention solves the problems of heterogeneous sampling frequencies, multi-scale distribution of fault features, and difficulty in capturing time-series dependencies in multi-sensor hydropower unit vibration signals. This invention is applicable to intelligent fault identification in multi-sensor monitoring scenarios such as hydropower units.