240451 results about "Electronic equipment" patented technology

The application provides a fault prediction method and apparatus, an electronic device and a storage medium. The method comprises: obtaining a vibration signal collected by a sensor installed on a target component of a target device, and cleaning and segmenting the vibration signal to obtain a target vibration signal; inputting the target vibration signal into a target anomaly judgment model to obtain an output result, and according to the output result, determining whether the target vibration signal is abnormal to obtain an anomaly judgment result; when the abnormal judgment result shows that the target vibration signal is abnormal, inputting the target vibration signal into a target fault prediction model to obtain a fault prediction result, wherein the target fault prediction model is obtained by combining an encoder of the target anomaly judgment model and a newly added full connection layer. The application solves the problem in the prior art that a faulty device cannot be timely maintained because the fault can only be monitored when the device fault is quite obvious.

An electronic device according to various embodiments comprises: a memory including instructions; and a processor that is electrically connected to the memory and executes the instructions. When the instructions are executed by the processor, the processor may: acquire a first traffic feature vector and a second traffic feature vector on the basis of traffic data generated in a wireless network device during a plurality of time intervals; generate a combined feature vector by combining the first traffic feature vector and the second traffic feature vector; and acquire predicted traffic data, to be generated in the wireless network device, on the basis of the combined feature vector. Various other embodiments are possible.

The invention discloses a server cooperative control method, a storage medium and electronic equipment, and relates to the technical field of firmware, and the method comprises the steps: employing a programmable logic device to actively take over the control authority of target equipment based on the operation parameters of a sensing device in a server starting stage, stable operation of equipment before initialization of the substrate management control device is not completed is ensured, a mechanism that a preset communication link and the substrate management control device are subjected to interactive verification is adopted, and the functional integrity and communication reliability of the substrate management control device during permission transfer are ensured through bidirectional communication verification. A dynamic permission recovery strategy based on real-time anomaly detection is adopted, control right reverse switching is triggered through a sensing device and communication link state dual monitoring mechanism, and the purpose of actively taking over equipment management responsibilities when a substrate management control device runs abnormally is achieved. Therefore, double improvement of system fault self-healing capability and equipment control continuity is realized, and the problem of difficulty in cooperative control among heterogeneous units is solved.

The present application relates to, but is not limited to, the technical field of communications. Provided are a fault diagnosis method, an electronic device, and a storage medium. The fault diagnosis method comprises: constructing an operation and maintenance knowledge graph based on a fault mode; acquiring root cause alarms of a fault, and by means of the operation and maintenance knowledge graph, determining target fault modes corresponding to the root cause alarms; performing root cause diagnosis on the basis of the target fault modes, so as to obtain fault root causes corresponding to the root cause alarms; and then, performing fusion processing on the fault root causes corresponding to the root cause alarms, so as to obtain a target fault root cause. In the solutions in the embodiments of the present application, an operation and maintenance knowledge graph based on a fault mode is constructed, and target fault modes corresponding to root cause alarms of a fault can be determined using the operation and maintenance knowledge graph, and root cause diagnosis is then performed on the basis of the target fault modes, so as to obtain fault root causes. On the basis of the solutions in the embodiments of the present application, the fault diagnosis efficiency and the automation of intelligent operation and maintenance can be greatly improved.

According to the server heat dissipation control method, the electronic equipment and the storage medium, heat dissipation control processing is firstly performed on the server according to the operation data of the server and the heat dissipation control algorithm, and then the server subjected to heat dissipation control is evaluated according to the actual heat dissipation requirement of the server, namely the preset heat dissipation condition; and optimizing a heat dissipation control algorithm according to the evaluation result and the operation data of the server after heat dissipation control. Meanwhile, a deep reinforcement learning mechanism is introduced into optimization of a heat dissipation control algorithm, and the balance problems of difficulty in parameter setting and poor system adaptability in traditional heat dissipation control are solved through cooperation of multiple algorithms and combination with edge calculation, namely, preset edge calculation equipment, so that the problem that the system adaptability is poor in the heat dissipation control of the server can be solved. The problems of difficulty in parameter setting and poor system adaptability are solved, and the technical effect of improving the efficiency and the stability of the heat dissipation system is achieved.

Disclosed in the embodiments of the present application are a defect detection method and apparatus, an electronic device, a storage medium and a program product. The method comprises: acquiring an image under test of a target workpiece and a template image of the target workpiece, and comparing the image under test with the template image so as to obtain a differential image; inputting the image under test and the differential image into a defect detection model, and executing the following processing: on the basis of the image under test and the differential image, extracting a target image feature and, on the basis of the target image feature, performing defect detection on the image under test to obtain defect detection box information of the image under test; positioning a defect area in the differential image and, according to the defect area, determining a first detection result of the target workpiece; and, according to the defect detection box information and the first detection result, determining a second detection result of the target workpiece.

An electronic device can comprise physiological sensors that can generate sensor data, a device processor, an actuator, and a controller electrically connected with the device processor and the actuator. The controller can monitor the state of the actuator; communicate a notification signal to the device processor to cause the device processor to prepare for a privacy mode responsive to determining that the actuator is in a privacy state, delay implementing the privacy mode until one or more conditions have been satisfied to allow the device processor to prepare for the privacy mode pursuant to communicating the notification signal to the device processor; and implement the privacy mode to inhibit access to the sensor data responsive to satisfaction of the one or more conditions.

The present application relates to the technical field of communications, and in particular to a network security threat processing method and apparatus, and an electronic device. The method comprises: on the basis of acquired local area network data, determining a network security attack type of a network attack event and an association relationship between entities in the network attack event; constructing a knowledge graph on the basis of the network security attack type, the association relationship between the entities in the network attack event and a configuration rule of an initial weight; using any node in the knowledge graph as an initial node, accessing each neighbor node of the initial node along adjacent edges of the initial node, and using a preset algorithm to calculate an initial weight of each neighbor node to obtain a degree-of-maliciousness weight of the initial node; and comparing the degree-of-maliciousness weight with a preset first threshold value, and deleting a node with a degree-of-maliciousness weight thereof being lower than the first threshold value in the knowledge graph, and also deleting the adjacent edges to obtain an updated knowledge graph. The solution can improve the network security threat processing efficiency.

The invention discloses an adapter life prediction system based on digital twinning and a dynamic early warning method. The system comprises a multi-source data acquisition module, a digital twinning model construction module, a data coordination module, a life prediction module and a calibration module. According to the method, the adapter full-life-cycle digital twins are constructed, the limitation of one-way static analysis of a traditional life prediction technology is broken through, and dynamic health assessment under multi-dimensional data driving is achieved; a cross-dimension feature fusion and closed-loop calibration mechanism is innovatively proposed, and the industrial problems that multi-source asynchronous data is weak in relevance and sudden abnormal response lags behind are effectively solved; through the synergistic effect of the generative adversarial network and the attention model, the stability and credibility of a prediction result are remarkably improved under a complex working condition; the technology can be adapted to a harsh use environment of an industrial adapter, and quantifiable and traceable decision support is provided for intelligent operation and maintenance of power electronic equipment.

The invention provides an electromagnetic interference source identification and positioning method based on multi-band EMI. The method comprises the following steps: carrying out preprocessing and standardization processing on acquired electromagnetic characteristic data, real-time environment data of a sensor network and operation state data of electronic equipment; based on the predicted electromagnetic environment perception result, extracting electromagnetic environment feature data, performing noise reduction and preprocessing on the electromagnetic environment feature data of different dimensions, performing weight distribution and optimal combination, and performing iterative calculation to obtain an interference source position coordinate; the optimized sensor array layout and parameter setting are applied to the test process of the electronic equipment, performance parameters of the electronic equipment in different electromagnetic environments are obtained, the performance parameters comprise electromagnetic compatibility and anti-interference capacity, and a test result is compared with a preset standard value and calibrated.

Disclosed in the present application are a multi-modal data processing method and apparatus, an electronic device, and a storage medium. The method comprises: acquiring a reference image and a reference text; extracting a reference visual feature of the reference image; by means of a multi-modal large language model, determining an embedding of the reference text, an embedding of a start mark of the reference visual feature, an embedding of the reference visual feature, and an embedding of an end mark of the reference visual feature; on the basis of the multi-modal large language model, splicing the embedding of the reference text, the embedding of the start mark, the embedding of the reference visual feature, and the embedding of the end mark into a target embedding sequence, performing attention processing on the basis of the embedding of the start mark, the embedding of the end mark, and an embedding selected by a sliding window in the target embedding sequence, and outputting a predicted sequence; and generating a predicted image and a predicted text on the basis of the predicted sequence.

A three-dimensional preview of content can be generated and presented at an electronic device in a three-dimensional environment. The three-dimensional preview of content can be presented concurrently with a two-dimensional representation of the content in a content generation environment presented in the three-dimensional environment. While the three-dimensional preview of content is presented in the three-dimensional environment, one or more affordances can be provided for interacting with the one or more computer-generated virtual objects of the three-dimensional preview. The one or more affordances may be displayed with the three-dimensional preview of content in the three-dimensional environment. The three-dimensional preview of content may be presented on a three-dimensional tray and the one or more affordances may be presented in a control bar or other grouping of controls outside the perimeter of the tray and / or along the perimeter of the tray.

Some examples of the disclosure are directed to systems and methods for displaying and interacting with a representation of a user interface of an electronic device in a three-dimensional environment. While presenting a first user interface, a first electronic device presents a representation of a second user interface of a second electronic device based on display data representing the second user interface. In response to detecting a respective event corresponding to user input, if a gaze of a user of the first electronic device is directed to the representation of the second user interface, the first electronic device causes the second electronic device to perform a first operation directed to the second user interface based on the respective event. Alternatively, if the gaze is directed to the first user interface, the first electronic device performs a second operation directed to the first user interface based on the respective event.

The invention discloses a processor and electronic equipment. The processor includes a computing unit including a tensor core configured to perform a matrix multiplication operation using a scaling factor, and a memory, the computing unit further including a scaling factor processing module configured to determine and cache a scaling factor for each tensor associated with the matrix multiplication operation, the computing unit further comprises at least one storage module arranged on a data path between the tensor core and the memory, and the at least one storage module is exclusively occupied by the tensor core when the tensor core executes tensor related operation. And the scaling factor processing module is arranged on the at least one storage module. At present, scaling factors and floating-point number quantization are completed by a vector calculation core, so that performance is reduced, and delay becomes high, and a scaling factor processing module arranged on a storage module in a calculation unit can improve the overall execution efficiency of low-precision matrix multiplication using the scaling factors.

Disclosed in the present application are a knowledge graph construction method and apparatus, and a storage medium, an electronic device and a computer program product. The method comprises: acquiring first natural language text; using an extraction model to perform entity extraction on the first natural language text, so as to obtain a first entity and a first entity relationship, and determining a corresponding first entity type and first relationship type; using a semantic encoder to determine a first semantic vector and a second semantic vector respectively corresponding to the first entity type and the first relationship type; on the basis of calculated first distances between the first semantic vector and cluster centers of a plurality of entity types and calculated second distances between the second semantic vector and cluster centers of a plurality of relationship types, determining a target entity type for the first entity type and a target relationship type for the first relationship type; and on the basis of the first entity, the first entity relationship, the target entity type and the target relationship type, constructing a target knowledge graph.

The invention provides an industrial agent decision-making method and device, electronic equipment and a storage medium. The method comprises the following steps: loading multi-source industrial data to a knowledge graph, and constructing a domain ontology and an MCP ontology; performing parameter fine tuning on a preset base large language model; receiving an industrial process planning demand input by a user, and performing semantic analysis on the industrial process planning demand; processing the query result by utilizing an MCP context strategy to generate a prompt context; inputting the prompt context and the industrial process planning demand into a fine tuning large language model to generate a first process planning scheme; performing rule verification on the first process planning scheme based on the knowledge graph, and judging whether the first process planning scheme meets a preset rule or not according to a verification result; and converting the final process planning scheme into a control script or an interface calling sequence which can be analyzed by an industrial execution system, and outputting the control script or the interface calling sequence. According to the method, the cross-software system compliance process planning with unified knowledge, automatic generation and rule verification can be realized.

A handheld fan includes a housing, a fan module, a power module, and a retractable cable module. The fan module is disposed in the housing, the power module is disposed in the housing and configured to supply power to the fan module, the retractable cable module is disposed in the housing and includes a cable retractable relative to the housing to be withdrawn into the housing or extended out of the housing, and the cable is configured to connect to an external electronic device, and supply power to the external electronic device through the power module. When a user carries the handheld fan and has a charging need, the cable is capable of being pulled out of the housing of the handheld fan, and connected to the external electronic device including a mobile phone. The power module is configured to supply power to the external electronic device.

The invention relates to the technical field of risk management and early warning, and discloses a risk early warning method comprising the following steps: collecting multi-source data including structured data, unstructured data and time series data; the invention provides a risk early warning system, which is used for performing cleaning, standardization processing and fusion on multi-source data to generate a unified data set for analysis, and comprises a data acquisition module used for acquiring the multi-source data including structured data, unstructured data and time sequence data; the data processing module is used for carrying out cleaning, standardization processing and fusion on the multi-source data and generating a unified data set, the electronic equipment comprises a memory, a processor and a communication module, and the processor implements the risk early warning method during execution. Through multi-source data fusion, a dynamic threshold model and deep learning analysis, the risk is accurately identified, the method adapts to the dynamic environment in real time, false alarms and missing alarms are reduced, and the long-term monitoring adaptability is improved.

The invention relates to the technical field of artificial intelligence chips, and provides an operator optimization method, electronic equipment, a storage medium and a program product, and the method comprises the steps: determining the block size of operator data in each dimension based on the batch size and mask mode of the operator data and the hardware parameters of computing equipment, each dimension comprises a batch dimension and a sequence length dimension; segmenting the operator data based on the block size of the operator data in each dimension to obtain a plurality of data blocks; and distributing the calculation tasks corresponding to the plurality of data blocks to a plurality of processing units on the calculation equipment, and performing parallel execution on the calculation tasks corresponding to the plurality of data blocks based on the plurality of processing units. According to the method and the device, the data are segmented in the batch dimension and the sequence length dimension at the same time, so that when the data batch is small, a plurality of processing units on the computing equipment can also participate in computing at the same time, hardware resources are prevented from being idle, the utilization rate of the hardware resources is improved, and the overall computing efficiency is improved.

The invention provides a thermal power plant boiler combustion visual monitoring and early warning method and system, a storage medium and electronic equipment. According to the method, obtained multi-measuring-point temperature data are input into a pre-constructed temperature field reconstruction model, the model comprehensively considers the geometric structure and combustion thermodynamic characteristic factors of a hearth, model parameters are dynamically adjusted through a particle swarm optimization algorithm, the temperature field reconstruction precision is continuously improved, and a three-dimensional real-time temperature distribution diagram of the hearth is generated; fusing and presenting the diagnosed combustion abnormal information and the visual image of the hearth temperature field, generating a visual in-furnace combustion state monitoring interface, and meanwhile, pushing the abnormal information to a mobile terminal to realize remote monitoring and early warning; the combustion state data in the long-period operation process of the boiler are mined and analyzed, typical combustion modes are extracted, a combustion mode library is continuously enriched and optimized, an online learning algorithm is used for adaptively updating a combustion abnormity diagnosis model, and the intelligent level of combustion state sensing and abnormity early warning is continuously improved.

The present disclosure relates to the technical field of document recognition, and provides an intelligent document recognition method and apparatus, an electronic device and a storage medium. The method comprises: extracting text information and layout information from a document to be recognized; acquiring a template containing a specified field; on the basis of an industry knowledge base corresponding to the document, adding a label to the text information; and, on the basis of the layout information and the label, using a large language model to recognize text information matched with the specified field from the text information to which the label has been added, the large language model being a large language model that has been trained by using the industry knowledge base. In the embodiments of the present disclosure, document recognition results more conform to industry attributes, improving document recognition accuracy.

The invention relates to a code generation method and system based on heterogeneous multi-agent collaboration and electronic equipment. According to the method, a special commentator agent instantiated by a heterogeneous large language model is added into a multi-agent collaboration process; according to the method, consistency and feasibility verification is carried out on a demand document given by an analyst agent by adopting a commentator agent, a modification suggestion is proposed in an early stage, deviation and problems are found in time in the early stage of a task, the cost and complexity of later correction are reduced, the robustness and reliability of codes are improved, and the method is suitable for large-scale popularization and application. And the generated result can still maintain high-level correctness under extreme conditions or specific boundary conditions. And the method has practical significance in improving software development efficiency, reducing project risks and improving the quality of an intelligent automatic solution.

The embodiment of the invention discloses a context-based big language model dialogue processing method and device and electronic equipment, and can solve the problem of how to provide a dynamic management method based on context similarity analysis and intelligent screening to optimize big language model interaction. The method comprises the steps of obtaining current text information input by a user; coding the current text information and a plurality of pieces of pre-stored historical dialogue information to obtain a current text vector and a plurality of historical dialogue vectors; according to the semantic similarity between each historical dialogue vector and the current text vector, screening the plurality of historical dialogue vectors to obtain screened target historical dialogue information; splicing the current text information and the screened target historical dialogue information to obtain a target input text; the target input text is input into a target language model, target output response information is obtained, and the target language model comprises a large language model.

The rotation shaft structure includes a main shaft assembly, and two folding assemblies that are symmetrically disposed with respect to the main shaft assembly. The two folding assemblies may rotate toward or against each other relative to the main shaft assembly. When the folding assembly is specifically disposed, the folding assembly includes a rotation assembly, a support plate, and a housing mounting bracket. The rotation assembly is rotationally connected to the main shaft assembly. The support plate is rotationally connected to the housing mounting bracket and slidably connected to the rotation assembly.

The present application provides a system energy efficiency optimization method and apparatus based on a comprehensive energy demand, an electronic device, and a storage medium. The method comprises: in response to a received target comprehensive energy demand, on the basis of comprehensive energy demand parameters, operation parameters of a target system, and environmental loss parameters of the target system, constructing an energy efficiency optimization function of the target system (S210); on the basis of a balance relationship between the energy supply and the energy consumption and a device operation demand of transmitting energy, constructing constraint conditions for optimizing the energy efficiency of the target system (S220); and on the basis of the energy efficiency optimization function and the constraint conditions, using a target algorithm to process operation parameters of a plurality of devices by taking the operation parameters of the plurality of devices in the target system as population individuals to obtain device parameters of the target system meeting the target comprehensive energy demand (S230).

The invention provides a dynamic order making method and device based on multiple rounds of dialogues and electronic equipment, and belongs to the technical field of intelligent interaction. The method comprises the steps of guiding a user to gradually fill in a form through a multi-round dialogue mechanism, generating a question based on a business logic dependency relationship, and mapping a natural language answer of the user into a structured field value in combination with semantic analysis and field dependency management; integrating a business rule engine in a multi-round dialogue mechanism process, executing field-level, logic-level and process-level multi-dimensional verification in real time in a user input process, and dynamically adjusting a verification strategy based on context; constructing and adaptively adjusting a form structure in real time based on a dynamic form generation engine, multi-round dialogue contents and business rules; based on a low-code configuration development platform, in combination with a preset intelligent interaction component and a visual tool, an intelligent filling system supporting natural language interaction is constructed. And the intelligence, flexibility and accuracy of form filling are obviously improved.

The invention discloses a model training method and device, electronic equipment and a computer storage medium. The model training method comprises the following steps: performing supervision fine tuning on an initial baseline model based on a first training sample set in a preset training sample set to obtain a supervision fine tuning model and a preference data sample; performing optimization training on the initial reward model based on the preference data sample to obtain a target reward model, and performing optimization training on the supervision fine tuning model based on the preference data sample to obtain a preference optimization model; generating a first reward signal based on the preference optimization model and the first training sample set, and generating a second reward signal based on the preference optimization model, the target reward model and a second training sample set in the preset training sample set; and performing optimization training on the preference optimization model based on the first reward signal, the second reward signal and the second training sample set to obtain a target object generation type pre-training model. By adopting the method, the generalization ability of the model can be improved.

Embodiments of the present disclosure provide a report generation method and system, an electronic device, and a storage medium. The report generation method comprises: acquiring requirement text information of a report to be generated in a target application scenario; performing requirement intent recognition on the requirement text information, to acquire a report parameter matching the report to be generated; on the basis of the target application scenario, selecting and arranging a preset intelligent agent, to obtain an intelligent agent call chain; on the basis of the report parameter, performing chain-type calling on the preset intelligent agent in the intelligent agent call chain, to generate a report matching the requirement text information. The present method can automatically and quickly generate a report matching a user requirement, effectively increasing report generation efficiency. Using the present method to generate a report does not require manual data acquisition and analysis; efficiency is higher, and costs are lower.

The embodiment of the invention provides a humanoid robot self-adaptive control method and system, electronic equipment and a storage medium, and belongs to the technical field of robot intelligent control. The method comprises the steps that electroencephalogram signals and electromyographic signals of a target object are collected; determining a first time-frequency domain feature of the electroencephalogram signal according to the electroencephalogram signal, and determining a second time-frequency domain feature of a muscle activation state according to the electromyographic signal; fusing the first time-frequency domain feature and the second time-frequency domain feature by adopting a dynamic weighting algorithm to obtain a multi-modal feature; inputting the multi-modal features into an action intention recognition model to obtain a predicted action intention; and determining a robot control instruction according to the predicted action intention and the current state of the robot so as to control the humanoid robot. The precision of self-adaptive control of the humanoid robot can be improved.