190 results about "Intelligent electronic device" patented technology

This invention pertains to an intelligent electronic device designed for sophisticated monitoring and analysis of electrical power distribution. The device integrates at least one sensor for detecting electrical parameters from a distribution system to a load, coupled with an analog-to-digital converter to transform sensed analog signals into digital data. A processing module, linked to the converter, employs customized moving average filters to calculate the frequency of electrical power distribution, enhancing measurement accuracy by adjusting for transient fluctuations. It retrieves frequency threshold settings from memory to define operational bounds, logging frequency data around identified deviation events when measurements surpass these thresholds. This system facilitates precise frequency analysis and robust event logging, providing a comprehensive solution for maintaining electrical power distribution within defined standards.

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.

This application provides a service anomaly reminding method, an electronic device, and a storage medium, and relates to the field of intelligent electronic devices. The method includes: receiving a first message; parsing the first message to determine whether the first message includes travel information; if the first message includes the travel information, determining whether a desktop card exists on a display interface of the electronic device; and if no desktop card exists on the display interface of the electronic device, displaying guide information, where the guide information is used for guiding a user to add the desktop card. By the embodiments of this application, the user can be reminded when a scenario intelligent service is abnormal in a travel process, so that the user adjusts the scenario intelligent service, thereby improving the efficiency of travel reminding.

The invention relates to the technical field of intelligent substation configuration file checking, in particular to an intelligent substation standard circuit library autonomous learning method, which comprises the following steps of: constructing a standard IED (Intelligent Electronic Device) and a virtual terminal model, and providing a unified standard for substation components and connection; adjusting the IED information in the SCD file to match a standard IED model; extracting virtual loop configuration of the IED from the SCD file by using a standard virtual terminal model and standardizing the virtual loop configuration of the IED; summarizing all standardized loop configurations to form a to-be-effective loop library, and recording occurrence frequencies according to categories; performing pre-effective marking on the frequently appearing virtual loop configuration; comparing the pre-effective loop with the to-be-effective loop library, and marking the pre-effective loop as an effective standard loop after confirmation; extracting information from the effective standard loop, and establishing a complete standard loop library; and updating and perfecting the standard loop library by continuously learning new SCD files. The method has the beneficial effects that automatic establishment and updating of the standard virtual loop library can be realized by utilizing SCD file information extraction and statistical analysis.

The invention relates to a transformer fault multi-dimensional monitoring method based on a digital substation, and belongs to the technical field of fault monitoring. The method comprises the following steps: sending obtained original data of a sensor network to a digital substation, sampling an analog signal of the original data by the digital substation, transmitting the analog signal to intelligent electronic equipment in the substation, and generating an output data stream; performing multi-dimensional feature extraction in the monitoring intelligent electronic equipment according to the output data stream to obtain fault feature parameters of the transformer; performing fusion dimension reduction processing on the fault feature parameters through a feature fusion model to obtain a fused fault feature vector; and inputting the fused fault feature vectors into a pre-trained fault classification model for fault type identification, and automatically identifying the fault type of the transformer. The transformer fault can be accurately and rapidly monitored, and the accuracy and efficiency of fault identification are effectively improved.

Systems and methods for determining a location of a fault in a power delivery system are provided. Such a method may include receiving several single-end traveling wave fault location values and a single-end impedance fault location value based on measurements from a first intelligent electronic device at a local terminal. Based on a relationship between the single-end traveling wave fault location values, the single-end impedance fault location value, a location of the local terminal, and the location of the remote terminal, one of the several single-end traveling wave fault location values may be selected as a fault location value of highest confidence among the several single-end traveling wave fault location values.

The application belongs to the technical field of intelligent electronic devices, and particularly relates to a high-color-purity multi-color electroluminescent fiber and a preparation method and application thereof. The fiber is prepared by the following steps: preparing lead halide perovskite type nano quantum dots as light conversion particles by a hot injection method, a room temperature supersaturation recrystallization method and the like; grafting and modifying the lead halide perovskite type nano quantum dots on the surface of metal sulfide type electroluminescent particles through a surface ligand to obtain high-color-purity multi-color electroluminescent active material; compounding the light conversion particle modified electroluminescent active material and a transparent thermoplastic elastomer polymer to obtain active slurry, and coating the active slurry on the surface of a conductive fiber through a continuous limited coating process; loading an external electrode on the conductive fiber to obtain the high-color-purity multi-color electroluminescent fiber. The multi-color electroluminescent fiber prepared by the application has various colors and high color purity, and meets the color gamut range required by the luminescent fiber and display fabric.

Systems and methods for analyzing alarms to characterize electrical system issues are disclosed herein. In one aspect, a method for analyzing alarms to characterize electrical system issues includes processing electrical measurement data from or derived from energy-related signals captured or derived by at least one intelligent electronic device in the electrical system to identify events in the electrical system, and alarms triggered in response to the identified events. Information related to at least the identified events and / or the identified alarms may be aggregated, and the aggregated information may be analyzed to determine issue(s) associated with the electrical system, and origin(s), source(s), cause(s), transitions / evolutions and / or interrelationship(s) of the issue(s).

The invention relates to the technical field of fault diagnosis of intelligent electronic equipment, and particularly discloses a fault diagnosis method and system for intelligent electronic equipment, and the method comprises the steps: collecting temperature data and operation response time in real time through a high-precision temperature sensor disposed on the surface of the equipment and an external high-precision timer; a temperature anomaly feature value and an operation response time anomaly feature value are respectively calculated by adopting fast Fourier transform and an autoregression integral moving average model, and are constructed into comprehensive feature vectors, and based on the feature vectors, whether the intelligent electronic equipment has a fault state is judged by using a random forest model. And the probability that the equipment breaks down in a period of time in the future is predicted through the multiple linear regression model, and for non-fault intelligent electronic equipment, the system formulates a personalized dynamic maintenance plan according to a prediction result, so that the accuracy and high efficiency of maintenance work are ensured.

The invention relates to the technical field of anomaly detection, in particular to an anomaly detection method for plant station automation network data packets, which comprises the following steps of: extracting a source MAC address, a destination MAC address, a protocol type, a communication frequency and an average packet length of each data packet based on the plant station automation network data packets captured in real time; according to the method, the source MAC address, the destination MAC address, the protocol type, the communication frequency and the average packet length of a plant station automation network data packet are extracted in real time, a weighted directed communication map is established according to the relation between intelligent electronic equipment and a gateway, and further, a network steady-state behavior baseline is formed through quantification from the communication behavior characteristic value of a node, so that the network steady-state behavior is realized. And a sliding time window mechanism is adopted to continuously calculate a behavior deviation metric value, and a topology behavior fluctuation index is generated by comprehensively analyzing communication frequency change, protocol type change and centrality change of an SV message, so that the time and the position of network abnormity can be determined.

The invention provides a secondary circuit visualization method and device of an intelligent substation and electronic equipment. The method comprises the steps that an SCD file of the intelligent substation is acquired, IED nodes are searched for according to the SCD file so as to extract IED information, and the IED information comprises information of all intelligent electronic devices in the intelligent substation and the connection relation between the different intelligent electronic devices; and analyzing the IED information, generating a virtual terminal publishing and subscribing address table, searching ExtRef nodes under each IED node according to the virtual terminal publishing and subscribing address table so as to obtain virtual terminal description information, constructing a secondary circuit connection diagram of the intelligent substation at least according to the virtual terminal description information, and visually displaying the secondary circuit connection diagram. The problem that the planning, extension, transformation, operation and maintenance difficulty of the intelligent substation is increased due to the fact that the secondary circuit structure of an existing intelligent substation becomes invisible is solved.

The present disclosure is directed to an intelligent electronic device (IED) configured for use in an Internet of Things (IoT) environment. The IoT environment of the present disclosure may include one or more objects or things in addition to the IED coupled together via a network, where each device is configured for IoT communication.

The invention relates to the technical field of electrical systems, and discloses a method for analyzing the influence of electrical disturbance on equipment in an electrical system, which comprises the following steps of: acquiring a voltage signal, a current signal and a frequency signal of the electrical system in real time through intelligent electronic equipment, and synchronously performing time domain analysis and frequency domain analysis on the signals to obtain an analysis result; extracting disturbance feature vectors, wherein the disturbance feature vectors comprise amplitude deviation, duration, change rate, harmonic distortion rate and transient energy; and establishing an equipment sensitivity characteristic database, wherein the equipment sensitivity characteristic database stores voltage tolerance characteristics of different types of equipment. The method for analyzing the influence of the electrical disturbance on the equipment in the electrical system aims at solving the problem that in the prior art, the influence degree of the equipment cannot be predicted in real time in the electrical disturbance generation process, and consequently effective protection measures cannot be taken in time.

A system and method performing fault and event analysis in electrical substations comprises receiving a disturbance record triggered by an intelligent electronic device (IED) at an electrical substation, pre-processing the received disturbance record to extract at least one variable time series data of plurality of electrical parameters, generating a causality matrix based on the extracted at least one variable time series data by applying causal analysis, predicting, using a Machine learning (ML) module, a fault type at least based on the causality matrix, retrieving, from a knowledge database, a plurality of probable causes corresponding to the predicted fault type, determining at least one exact cause from the plurality of probable causes based on the causal pattern, and providing the fault type, the plurality of probable causes, and the at least one exact cause to a user.

The invention discloses an intelligent substation SCD automatic generation method, system and device and a storage medium. The method comprises the following steps: constructing a primary main wiring diagram, wherein the primary main wiring diagram comprises a topological relation in the intelligent substation; associating intelligent electronic equipment IED in a substation configuration description SCD file to a corresponding interval in the main wiring diagram; generating an IED configuration parameter based on the topological relation and the IED; and associating the ICD file of the IED to the SCD file, importing a loop configuration subscription relation table and a total station primary equipment interval classification, number and initial address table, and automatically generating a subnet, communication parameter configuration, port configuration and virtual loop configuration in combination with the IED configuration parameters so as to complete the configuration of the SCD file. According to the method, the SCD file meeting the specification can be automatically configured.

The invention relates to the technical field of intelligent electronic equipment, and discloses a multifunctional camera system for children, and the system comprises a dynamic resource distribution module which is used for receiving multispectral data and temperature feedback, and generating a processor frequency, an image bandwidth and a memory distribution instruction; the environment sensing module is used for integrating a dual-spectrum sensor, compressing features through a tensor decomposition network and then inputting the features into the resource scheduling evaluation module; the intelligent optimization module interacts with the resource allocation module, dynamically adjusts the reward function weight and receives strategy execution effect data; and the heat management module is used for calculating the maximum allowable frequency based on a heat conduction model and feeding back the temperature gradient data to the resource allocation decision module. Through multispectral data fusion under a reinforcement learning framework, a meta-learning driven multi-objective optimization algorithm and a thermodynamic constrained frequency control technology, collaborative optimization of adaptive resource scheduling, precise temperature control and multi-dimensional safety protection of the child intelligent camera in a complex environment is realized.