616 results about "Electrical malfunction" patented technology

The invention relates to the technical field of electrical fault diagnosis, and discloses an electrical system fault diagnosis method based on multiple parameters. According to the method, multi-dimensional operation parameters of an electrical system are collected, wherein the multi-dimensional operation parameters comprise voltage waveform data, current waveform data and temperature distribution data; time-frequency conjoint analysis is carried out on the multi-dimensional operation parameters, and multi-scale electrical features are extracted and comprise steady-state feature components and transient feature components; based on a historical fault case library, performing mode matching on the multi-scale electrical characteristics to generate an initial fault type set; performing confidence evaluation on the fault types in the initial fault type set by using a dynamic weight distribution algorithm, and screening out high-confidence fault types; and according to the high-confidence fault type, a fault evolution path model is constructed, and the fault evolution path model is used for describing a time sequence of fault features.

The invention relates to the technical field of monitoring or controlling a charging station, in particular to a charging pile safety monitoring method and system, and the method comprises the following steps: step 1, monitoring: step 1.1, electric leakage monitoring: installing a high-sensitivity electric leakage sensor in a charging pile and a charging gun line, continuously monitoring the electric leakage current in real time, and monitoring the electric leakage current in real time; the monitoring frequency is that data are collected once every 10 milliseconds; step 1.2, overload and short circuit monitoring: real-time current change of a charging circuit is monitored by using a current transformer, and the acquisition frequency is once every 5 milliseconds; step 1.3, monitoring the temperature; according to the scheme, through monitoring of electric leakage, overload and short circuit, temperature, smog and flame, charging gun safety, vision and the like in combination with intelligent analysis, the operation state and the surrounding environment condition of the charging pile can be comprehensively, timely and accurately mastered, electrical faults, temperature anomalies and potential safety hazards can be rapidly detected and judged, and the safety and reliability of the charging pile are improved. And all-around real-time monitoring of the potential safety hazard of the charging pile is realized.

The invention relates to the technical field of electronic circuits, in particular to a construction method and system of a high-speed differential signal transmission model. The method comprises the following steps: acquiring design data of the printed circuit board, and extracting differential signal line data; constructing a high-speed differential signal transmission model according to the differential signal line data; performing signal transmission simulation based on the high-speed differential signal transmission model to obtain high-speed differential signal transmission data; identifying a crosstalk source position based on the high-speed differential signal transmission data to obtain a crosstalk source coordinate; detecting via hole dislocation based on the crosstalk source coordinates to obtain via hole dislocation data, and evaluating a heat accumulation degree based on the via hole dislocation data; identifying an electrical fault area of the circuit board based on the heat accumulation degree; and extracting stack structure information according to the printed circuit board design data. Based on the electronic circuit technology, the precision and reliability of the high-speed differential signal transmission model are improved, and the signal transmission quality and the electrical fault detection rate are remarkably improved.

The invention discloses a power grid visual diagnosis system based on multi-source data fusion, and relates to the field of power grid diagnosis systems. The system comprises an information acquisition module, an electrical fault alarm module, a non-electrical quantity fault alarm module, a fault discrimination module, a communication module and a fault recording module. Firstly, information of a power grid is collected through the information collection module, then the information is transmitted to the electrical fault alarm module and the non-electrical fault alarm module for monitoring, corresponding actions are made when abnormity occurs, then the information is transmitted to the fault judgment module, input information is analyzed, and the fault type is obtained; meanwhile, the fault recording module records and broadcasts the power grid; the communication module collects information of other modules in the system and exchanges information with the monitoring system. According to the method, the abnormal information of the power grid is monitored and alarmed in combination with the multi-source data, and the fault type is judged through the data model, so that the omnibearing monitoring of the power grid is realized, and data support is provided for a subsequent maintenance plan.

The invention relates to the technical field of intelligent early warning, and discloses an aviation case electrical safety intelligent early warning method, device and equipment and a storage medium. The method comprises the following steps: carrying out voltage, current, temperature and vibration parameter acquisition on a wiring row position, an input wiring terminal position and a zero sequence current transformer installation position of the aviation intelligent distribution box to obtain an electrical parameter data set; executing dynamic adjustment of an electrical safety detection threshold to obtain an aviation environment adaptability threshold parameter; performing feature extraction on the electrical parameter data set to obtain electrical parameter abnormal features; performing electrical fault mode matching and positioning analysis on the electrical parameter abnormal characteristics to obtain fault type, position and severity information; and generating a target early warning response strategy of the aviation intelligent distribution box in combination with the flight stage characteristics of the aircraft. According to the invention, a complete electrical safety protection system is constructed, the false alarm rate and the missing report rate are significantly reduced, and the safety protection capability of the aviation intelligent distribution box electrical system is improved.

The invention is suitable for the field of electric power safety, and provides a fault prediction and maintenance method and system for safe operation of electric power equipment, and the system comprises a data collection module, a data analysis and abnormity identification module, a dynamic alarm and response module, a geographic information system integration module, and a maintenance path optimization module. The system adopts a non-contact dynamic electric field monitoring system to monitor power equipment, can identify potential insulation failures or electrical faults in real time, and significantly reduces the risk of contact between operation and maintenance personnel and high-voltage equipment. And in combination with an intelligent alarm system, real-time data are analyzed through machine learning, an alarm is automatically triggered, and the accuracy and response speed of fault identification are improved. In addition, the monitoring system is integrated with a geographic information system, automatic optimization of an optimal maintenance response path is achieved, and it is ensured that faults are rapidly processed. According to the comprehensive method, the safety of the power equipment is improved, the fault risk is reduced, the maintenance efficiency is optimized, and the comprehensive method has important practical value.

An electrical fault detection and interruption device includes a switch module coupled between input and output ends of current carrying lines, a GFCI (ground fault circuit interrupter) fault detection module for generating a ground fault signal when detecting a leakage current on the current carrying lines, an AFCI (arc fault circuit interrupter) fault detection module for generating an arc fault signal when detecting harmful arcs on the current carrying lines, a drive module for driving the switch module to disconnect the electrical connection between the input and output ends in response to the ground fault signal and / or arc fault signal, a fault signal transfer module for generate a simulated leakage current signal in response to the arc fault signal, and a monitoring module for generating a harmful arc signal to test whether the electrical fault detection and interruption device is functioning normally.

The invention provides an electrical fault detection method and an electrical fault detection system, and relates to the technical field of data processing, and the method comprises the steps: carrying out the equipment multi-dimensional correlation analysis of a target production environment, and constructing a plurality of dynamic priority detection trees; establishing a communication link between the plurality of root node devices and the fault detection cloud, and establishing a plurality of edge processing units; when the first electrical fault is identified, positioning a first root node device at the plurality of root node devices; and activating the first edge processing unit, performing progressive electrical fault detection on the target production environment by taking the first dynamic priority detection tree as a fault detection constraint, and positioning target risk equipment. The technical problems that in the prior art, electrical fault detection is always static, intelligent priority adjustment is lacked, dynamic changes of equipment operation conditions are difficult to deal with, and the accuracy and efficiency of fault detection are low are solved.

The invention relates to the technical field of electrical fault identification and response, in particular to a relay protection fault identification and response system, which comprises a fault propagation path tracking module, a regional fault monitoring module, a misoperation cumulative effect calculation module, a protection level adjustment module and a fault response module. According to the method, based on the triggering sequence and the triggering interval time of the relay protection device, a malfunction propagation mode is extracted, cascade malfunction associated devices are screened, regional power grid fault risk scores are combined, protection level setting is optimized, the malfunction accumulation trend is calculated through malfunction triggering frequency, and high-malfunction devices are identified. The method comprises the following steps: calculating a protection level adjustment factor, optimizing a relay protection level according to a power grid state, enabling a protection strategy to adapt to different operation conditions, calculating power grid operation state parameters in combination with the adjusted protection level, analyzing stability change, optimizing a relay protection response strategy, enabling a relay protection system to have adaptive adjustment capability, and reducing the sudden fault influence range.

An electrical fault detection and interruption device includes a switch module coupled between input and output ends of current carrying lines, for controlling an electrical connection between the two ends; a signal collection module, for detecting a fault signal on the current carrying lines and converting it to an electrical signal; a signal processing module, for determining whether a fault is present on the current carrying lines based on the electrical signal, and generating an electrical fault signal accordingly; a drive module, for driving the switch module to disconnect the electrical connection between the input and output ends in response to receiving the electrical fault signal; and an alarm module, for generating an alarm signal in response to receive the electrical fault signal. Thus, even when the device malfunctions and loses its protection function, it can still generate an alarm signal to alert the user.

The invention discloses a double-closed-loop cooperative control method of a direct-drive electric chassis and a power system, relates to the technical field of power control of electric special vehicles, and provides a rotating speed and torque double-closed-loop cooperative control architecture, and realizes double-core real-time cooperative operation and dynamic optimization of motor output characteristics through a 32-bit processor. A direct-drive transmission structure is combined, a traditional speed reduction device is omitted, a flat wire motor directly drives a rear axle through a transmission shaft, and a four-in-one controller is matched, so that the system loss is reduced by 33%, and the power density is improved by 15%; on the basis of real-time temperature / electric quantity data of a lithium iron phosphate battery management system, control parameters are adaptively adjusted, and the bottleneck of performance attenuation in a low-temperature environment of-35 DEG C is broken through; and a high-voltage interlocking and insulation monitoring module is integrated, and an emergency hydraulic system is automatically switched when an electrical fault occurs, so that multi-stage safety guarantee is formed. According to the technology, the energy recovery efficiency is remarkably improved by 20%, and the wind resistance stability and the extreme environment reliability are effectively enhanced.

The invention relates to the technical field of fault detection, in particular to an electrical fault detection control system which comprises a phase monitoring module, an abnormity positioning module, a current control module and a result verification module. According to the method, the phase difference is calculated by combining collection and dynamic time warping, an abnormal mark is generated by comparing a phase tolerance threshold value, the phase delay detection precision is improved, based on an adjacent node phase difference value sequence, the slope kick is analyzed through linear regression, the candidate section judgment accuracy is enhanced, and a constant current source collects a multi-node voltage difference value; the Kalman filtering smoothes the voltage drop difference and compares the threshold value, improves the anti-interference capability of the complex working condition, compares the overlapping degree of the path coordinates and forms a closed loop verification mechanism with a re-check instruction, guarantees the reliability of the positioning result, shortens the fault response time through the multi-stage collaborative optimization, reduces the misoperation, and improves the discrimination robustness through the dynamic modeling and multi-source signal fusion. The dependence on experience or threshold is reduced; and the self-adaptive capability is enhanced.

The invention relates to the field of online fault detection and alarm, and particularly discloses an online fault detection and alarm system and method for a low-voltage distribution box. The method comprises the following steps: firstly, acquiring incoming line voltages of the low-voltage distribution box at a plurality of preset time points acquired by a sensor, outgoing line voltages of the low-voltage distribution box at a plurality of preset time points acquired by the sensor, and an arc light signal oscillogram of the low-voltage distribution box acquired by an arc light sensor; and finally, a classification result is obtained through the classifier to judge whether the low-voltage distribution box has an electrical fault or not, so that accurate diagnosis of the electrical fault is realized, the maintenance cost is reduced, the service life of equipment is prolonged, and the reliability and safety of the equipment are improved.

The invention provides a vehicle small table board and a vehicle armrest box, and belongs to the technical field of vehicle parts, the vehicle small table board comprises an extension driving mechanism, the extension driving mechanism comprises an elastic energy storage part, a driving shaft and a driving gear, and the driving shaft is connected with the elastic energy storage part; the lead screw is provided with a transmission gear, the transmission gear is fixedly connected with the lead screw in the circumferential direction, and the transmission gear is meshed with the driving gear so that the driving shaft can drive the lead screw to rotate when rotating. The telescopic connecting piece is provided with a threaded sleeve, the threaded sleeve is in threaded connection with the lead screw, and the lead screw drives the telescopic connecting piece to move in the axial direction of the lead screw when rotating; the table plate body is mounted on the telescopic connecting piece; the non-motor-driven small table plate for the vehicle has the beneficial effects that the requirement for arranging a motor and corresponding electronic elements is omitted, the structure is simplified, the cost is reduced, the risk of electrical faults does not exist, and the use reliability is greatly improved.

Computational algorithms or “solvers” may be executed on intelligent electronic devices (IEDs) in an electric power delivery system to perform tasks such as locating and isolating electrical faults and restoring service to an area after an electrical fault occurs. However, executing the solvers may become a computationally prohibitive task, particularly where computing power is limited (e.g., low-power pole-top computers). In certain embodiments, computing power may be offloaded onto multi-instance networks that may enable processing of large amounts of complex data. It may be difficult for the multi-instance networks to obtain real-time or near real-time data from the electric power delivery system due to cybersecurity concerns. As such, multiple stateless services may be used to evaluate limited and / or obfuscated representations of a portion (e.g., a single feeder circuit) of the electric power delivery system.

The invention provides a permanent magnet synchronous motor electrical fault diagnosis method, and relates to the technical field of motor fault diagnosis. Comprising the following steps: S1, extracting historical electrical fault key characteristic quantity sets of a plurality of motors; s2, performing corresponding classification division on the plurality of historical electrical fault key characteristic quantity sets and different motor operation state categories to form a plurality of historical data sample sets; s3, calculating the prior probability of each motor operation state category; s4, extracting a newly collected electrical fault key characteristic quantity set to obtain a posterior probability of each motor operation state category; s5, supplementing and updating the characteristic quantity data to obtain the posterior probability of each motor operation state category; and S6, labeling the result, and storing the labeled information into a sample information base to update the historical data sample set. According to the method, the problem that most of current fault diagnosis methods cannot well meet the fault diagnosis requirement under the background of big data is solved.

In one aspect, a controller for managing electrical faults in a microgrid is provided. The microgrid includes electrical loads, electrical sources, and circuit protection devices that selectively couple the electrical loads and the electrical sources with each other. The controller comprises at least one processor configured to direct a grid tie switch to open to electrically isolate the microgrid from an electric grid, determine, in response to directing the grid tie switch to open, that an electrical fault exits in the microgrid, and determine whether a fault current of the electrical fault is less than a threshold value. The at least one processor is further configured to direct the grid tie switch to close to electrically connect the microgrid to the electric grid and increase the fault current above the threshold value in response to determining that the fault current is less than the threshold value.

The invention discloses a motor fault feature extraction and fault diagnosis method. The method comprises the following steps: step 1, collecting an MCAVFCNN training data set, wherein motor fault types comprise two major classes, namely mechanical faults and electrical faults, namely 9 subclasses; 2, an MCAVFCNN model is built, a dynamic random erasure layer, a self-adaptive weighted sound and vibration fusion layer and a self-adaptive POOLING layer are provided, and the data set collected in the step 1 is used for model training till convergence; and step 3, the trained model is used online, and the trained MCAVFCNN model is applied online. According to the method, state monitoring and fault detection can be accurately carried out on the running motor in real time, and unnecessary loss is reduced while safe running of the motor is guaranteed.

The invention relates to the technical field of electrical fault positioning, in particular to an urban rail train relay state online monitoring method and system. The specific implementation process comprises the following steps: collecting coil current, contact voltage, load current and environment vibration signals by using an electrical sensor group; when the coil current is subjected to step change, intercepting an electromechanical characteristic data set; arc energy and contact resistance fluctuation characteristics are calculated, correlation analysis is carried out in combination with environment vibration signals, and passive fluctuation and active fluctuation are distinguished; and establishing a multi-factor health degree evaluation model, dynamically adjusting the arc energy and the weight coefficient of the contact resistance according to the magnitude of the load current and the vibration intensity, monitoring the health state of the relay in real time, and predicting the residual life. Through multi-dimensional data synchronous acquisition and vibration decoupling, the interference of mechanical vibration on electrical performance monitoring is effectively eliminated, the problem that a dynamic working condition cannot be reproduced in an off-line test is improved, and the accuracy of relay state evaluation and service life prediction is remarkably improved.

Embodiments of the present disclosure may enable an electrical component within an electrical distribution equipment cabinet to be audibly monitored via an electrical fault detection device mounted on the housing of the cabinet. The electrical fault detection device may comprise a senor to detect a signal emitted from an electrical fault within the cabinet, a transducer to convert the detected signal into an electrical audio signal, and an output socket adapted for an external device that may generate an audible sound based on the detected signal. The detected sensor may be an ultrasound sensor and the detected signal may be an ultrasound emitted from the electrical fault.

The invention relates to the technical field of intelligent circuit breakers, in particular to a holographic monitoring method based on a circuit breaker intelligent algorithm. The method comprises the steps of collecting operation data of a line where the circuit breaker is located; performing data preprocessing on the operation data; performing data processing on the preprocessed operation data to obtain monitoring parameters; holographic monitoring is carried out on an electrical fault according to the monitoring parameters; wherein when the operation data is preprocessed, a dual-frequency injection method is adopted to realize the separation of resistive residual current, a 2kHz high-frequency test signal is superposed on the basis of a fundamental wave frequency, and the resistive residual current is separated; meanwhile, an intelligent algorithm is adopted to carry out de-noising processing on the signal, that is, a dynamic threshold value is adopted to carry out wavelet de-noising processing, and an interlayer correlation coefficient is fused into wavelet threshold value calculation, so that self-adaptive protection of fault features is realized, and subsequent accurate power grid holographic monitoring is facilitated.

The invention discloses an electrical fault detection method and system applied to electrical equipment, electronic equipment and a readable storage medium thereof, and relates to the technical field of electrical detection, and the method comprises the steps: collecting the operation data of the electrical equipment in real time; the waveform deviation degree is calculated, if the waveform deviation degree of any operation data and the normal working condition data is larger than a fault threshold value, it is judged that suspicious operation data exist in the equipment, and multi-dimensional fault diagnosis is triggered; the multi-dimensional fault diagnosis comprises the following steps: generating a candidate fault type set; constructing a fault-oriented directed chain in the candidate fault type set; calculating a posterior index of each candidate fault type in the candidate fault type set by adopting a causal reasoning formula; and comprehensively evaluating the fault risk of the equipment component in the power equipment based on the equipment component main body corresponding to each candidate fault type in combination with the posterior index of each candidate fault type. The method has the advantages that the incidence relation between fault types is deeply mined through a causal reasoning mechanism, and the diagnosis precision and systematicness are remarkably improved.

The present invention pertains to methods for operation, maintenance, and monitoring of rotating electrical machines, and relates to a system and a method for monitoring the operational condition and detecting mechanical, electrical, load, and process faults in rotating electrical machines. The proposed system and method, together, provide a more effective way to detect faults early on, with greater installation convenience and scalability than prior art methods, and are more efficient in avoiding production losses, improving operational performance and preventing damage to equipment and risks to operators. The developed method continuously collects electrical current and voltage signals that power the machine, utilizing a data acquisition module and current and voltage transformers. The collected data undergoes stages of compression, encryption, application of Fast Fourier Transform (FFT), subsampling, feature extraction, anomaly detection using statistical and machine learning techniques, and fault classification using machine learning techniques. The proposed system consists of one or more data acquisition modules, one or more gateway devices, a processing center on a cloud computing platform, and an operator interface. In an industrial application, the method can be continually improved with the collection of new data and with validation information from an operator in the face of an identified fault.

The invention, which relates to the technical field of the electric meter box, discloses a plugging protection type electric meter box comprising an installation device. According to the pluggable protection type electric meter box, through the design of the installation device, the electric meter cabinet is arranged between the two sliding frames, the sliding frame at the bottom is used for bearing the electric meter cabinet, the two sides of the electric meter cabinet are extruded through the clamping mechanism, so that the effect of clamping equipment is achieved, the protection mechanism is connected with the clamping block in a clamped mode, and therefore the shielding effect on the surface of the cabinet body is achieved; a pneumatic device is arranged on the outer side of the electric meter cabinet, and airflow is conveyed into the electric meter cabinet through the pneumatic device, so that the effects of ventilation and heat dissipation are achieved, the temperature in the cabinet is reduced, normal work of elements is guaranteed, condensation is reduced, electrical faults are prevented, air pressure inside and outside the cabinet is balanced, and structural deformation is avoided; the cabinet body structure damage caused by air pressure difference is avoided, the aging speed of a sealing element is reduced, and the service life of equipment is prolonged.

The invention provides an AC / DC power transmission system fault identification method based on space-time diagram convolution, and the method comprises the steps: carrying out the modeling of a diagram structure, and constructing a diagram data set; performing graph convolution on the graph data to obtain a matrix Mt; extracting time dynamic characteristics of the matrix Mt; outputting a predicted value of each fault category by adopting an activation function; solving a loss function of the fault identification model; updating the parameters of the fault recognition model according to back propagation until the loss function value meets the requirement, and obtaining a trained fault recognition model; and selecting DC system fault event data outside the graph data set, and inputting the DC system fault event data into the trained fault identification model for fault identification. According to the technical scheme, automatic diagnosis of various electrical faults of the direct-current power transmission system can be realized, and the efficiency of fault handling work is improved.

The present disclosure provides a method and apparatus for determining an interference condition in an electric power transmission line. The method includes obtaining (302) a plurality of sample values ​​corresponding to an electrical parameter measured in each phase. The method further includes determining (304) a plurality of magnitudes of the electrical parameter corresponding to each phase based on the corresponding plurality of sample values ​​and determining (306) a plurality of difference values ​​for each phase based on the corresponding plurality of magnitudes. The method includes processing (308) the plurality of difference values ​​using machine learning techniques to determine an interference condition. The interference condition is one of a load change condition, a power swing condition, and an electrical fault condition. The method also includes performing (310) at least one of a protection function and a control function based on the interference condition.

The invention relates to the technical field of transformer fault simulation, and discloses a transformer fault simulation detection system. Firstly, transformer fault data is obtained from a monitoring system, fault report and maintenance record channel of an electric power system; and corresponding parameters of the transformer during normal operation are collected for comparison; missing data are processed, wherein the parameters are cleaned and integrated by a linear interpolation method, and data standardization is performed; fault simulation data is generated, and a transformer physical model is established; fault identification is performed on the simulated data in transformer fault simulation software, specifically including extraction of electrical fault features and non-electrical fault features; a fault diagnosis model is constructed and trained; and fault data is output. The invention can more accurately judge the fault type and avoid misjudgment that may occur in single feature diagnosis.

The embodiment of the invention provides an operation scene monitoring method and system based on panoramic stitching and holder linkage, and belongs to the technical field of video monitoring. The method comprises the following steps: respectively acquiring real-time panoramic video data and historical video data of an operation scene and a partial discharge signal of high-voltage electrical equipment; simulating electrical disease characteristics of the high-voltage electrical equipment based on the partial discharge signals and the environmental parameters of the real-time panoramic video data; obtaining work prediction information of the real-time panoramic video based on the historical video data and the electrical disease features; calculating deviation information of a real-time panoramic video according to the operation prediction information and the real-time panoramic video data; positioning a risk target area of the operation scene based on the deviation information, and determining a risk early warning signal of the operation scene for the deviation information based on a preset risk rule base; and issuing the risk early warning signal to a pan-tilt camera of the operation scene, and monitoring a close-up monitoring picture of the risk target area in real time. According to the invention, the risk handling efficiency of operation scene monitoring can be improved.

A multi-phase electrical machine for use in an aircraft. The electrical machine includes a stator including a plurality of electrical phases. Each electrical phase includes phase windings. The phase windings in each phase having a first end electrically connected to a common neutral conductor, and a second end providing an electrical connection from the phase winding to an electrical power source or load. The electrical machine also including an array of magnetic elements, the rotor being rotatably mounted with respect to the stator. The electrical machine also including sensing means configured to sense a condition of the stator indicative of an electrical fault in one of the plurality of electrical phases; and at least one electrical interrupter operable to electrically disconnect at least one first end of the plurality of phase windings from the common neutral conductor.

The invention relates to a box-type substation multi-dimensional diagnosis method based on multi-network fusion and an intelligent algorithm. The method comprises the steps that S1, a provided box-type substation monitoring system comprises a multi-network data acquisition module, a multi-network data fusion module, a composite fault diagnosis and prediction module and a health state quantitative evaluation module; s2, a multi-network data acquisition module obtains data of different dimensions of the box-type substation to obtain multi-network data; s3, the multi-network data fusion module carries out space-time alignment on the multi-network data, extracts cross-network features, calculates the weight of each cross-network feature and carries out fusion to obtain a fusion feature; s4, a composite fault diagnosis and prediction module synchronously diagnoses an electrical fault, a thermal fault and an insulation fault and predicts a composite fault based on the fusion features; and S5, outputting a multi-network health index, an equipment comprehensive health score, a fault positioning result and a maintenance suggestion by a health state quantitative evaluation module. According to the invention, accurate diagnosis and potential fault prediction of the composite fault of the box-type substation can be realized.