639 results about "Quality information" patented technology

The invention relates to the technical field of digital management, in particular to an offshore platform component processing full life cycle quality tracing system which comprises a component unique identification code generation module, a multi-source processing data acquisition module, a quality judgment and tracing code association module, a holographic digital archive construction module and a three-dimensional visual tracing module. Wherein the component unique identification code generation module is used for generating a unique identification code; the multi-source processing data acquisition module is used for acquiring processing process data associated with the unique identification code of the component in real time; the quality judgment and traceability code association module is used for generating a quality judgment result based on a preset quality rule base; and the holographic digital archive construction module is used for generating a full-life-cycle data chain of the component. According to the method, the whole life cycle data chain with the unique traceability code as the index is constructed and mapped to the BIM model, and structural management and space-time visual traceability of the quality information of the offshore platform component are achieved.

The invention relates to a lightweight component surface defect quantitative evaluation method, system and device, and the method comprises the steps: obtaining a multispectral surface image, laser three-dimensional data and ultrasonic detection data of a lightweight component, and carrying out the fusion registration based on a preset multi-sensor synchronization protocol, and obtaining a component joint data set; performing dynamic pruning analysis on the component joint data set to obtain geometric contour features, and performing internal feature extraction on the component joint data set to obtain internal abnormal response features; stress gradient distribution data and volume ratio parameters are carried out on the geometric contour features and the internal anomaly features; and obtaining an original working condition data set of the lightweight component, carrying out service working condition coupling analysis on the multi-dimensional prediction matrix, and carrying out multi-dimensional quality l parameter identification to obtain component comprehensive quality information. According to the method, the morphology mechanical coupling feature extraction precision of composite defects such as cracks and holes can be improved.

The invention provides a carbon footprint calculation-oriented multi-source heterogeneous data intelligent fusion method and device, and the method comprises the steps: obtaining the multi-source heterogeneous data of a product, the multi-source heterogeneous data comprising the basic information of the product and the carbon footprint data of the whole life cycle of the product; analyzing the data type of the multi-source heterogeneous data, and selecting an algorithm matched with the data type to convert the multi-source heterogeneous data into structured data to obtain a structure standardized data set; based on the loaded carbon footprint domain ontology, performing semantic extraction on the structure standardized data set to obtain a semantic standardized triple data set; performing quality evaluation on the semantic standardized triple data set, and constructing an initial carbon footprint data set including quality information based on a quality evaluation result; and performing conflict detection and conflict ablation on the initial carbon footprint data set to obtain a final carbon footprint data set of the product. Through the method disclosed by the invention, effective fusion of multi-source heterogeneous data in carbon footprint calculation can be realized.

The invention discloses a supply chain full-link risk early warning platform and method based on big data. The platform comprises a supply chain division module, a data acquisition module, a risk assessment module, an alternative supplier module, a risk path conduction module and a risk plan module. Supply chain information is divided according to link nodes, then multi-source data is collected, supplier quality information is generated in combination with supplier data, consumption behavior data and public opinion data, suppliers are bound, the number of alternative suppliers is dynamically adjusted based on the real-time fluctuation rate, and risk conduction paths containing path nodes of different risk levels are constructed. And finally, generating a risk plan adaptive to the link scene. According to the invention, through multi-dimensional data fusion and a dynamic threshold mechanism, the cascade effect capture capability of supply chain risk conduction is enhanced, and collaborative improvement of risk early warning timeliness and plan accuracy is realized.

Embodiments of the present disclosure relate to methods, devices and computer readable media for communication. A terminal device determines CSI and channel quality information based on a measurement on a set of RSs from a network device, and determines a compression method at least based on the channel quality information. The terminal device compresses the CSI based on the compression method, and transmits, to the network device, the channel quality information and the compressed CSI. The network device determines the compression method applied for the compressed CSI based on the channel quality information, and recoveries CSI based on the compressed CSI and the compression method. In this way, CSI feedback overhead and compression performance may be balanced.

A control unit (130) of a control apparatus (10) acquires a position of a first communication device (40A) and first quality information about a plurality of links. The first communication device (40A) is positioned in a first site in which a first base station (20A1) for a first private network is arranged, and is connectable to the plurality of links including the first private network. The control unit (130) acquires a position of a second communication device (40B) and second quality information about the plurality of links. The second communication device (40B) is positioned in a second site in which a second base station (20B1) for a second private network is arranged, and is connectable to the plurality of links including the second private network. The control unit (130) acquires first and second communication information about the first and second communication devices (40A and 40B). The control unit (130) uses the first and second communication information and first and second quality information to determine a communication route satisfying a desired quality between the first and second communication devices (40A and 40B), and gives notice of route information.

The invention provides a cloud-edge collaborative intelligent tool magazine tool life prediction method and system, and relates to the field of fault prediction and health management.The method comprises the steps that in a cloud data center, a current tool health index is obtained according to workpiece machining quality information and tool surface image evaluation; according to the current cutter health index, a cutter damage monitoring and early warning mechanism is configured and sent to an edge processing unit; according to the adaptive monitoring frequency, a sensor is controlled to conduct data monitoring, multi-source monitoring data are judged according to the adaptive early warning indexes, if not triggered, dynamic updating of a tool damage monitoring and early warning mechanism is conducted in an iteration mode, and if triggered, tool damage early warning is conducted. The invention aims to solve the technical problem that the accuracy and the reliability of tool damage early warning are insufficient due to the fact that a traditional early warning mechanism is difficult to adapt to the dynamic change of a tool machining state, and can improve the adaptation degree of a monitoring early warning mechanism and the tool machining state and remarkably improve the accuracy and the reliability of early warning by introducing a dynamic monitoring early warning mechanism.

The invention relates to an intelligent welding robot control method and system based on a deep learning model, and relates to the technical field of welding robos.The intelligent welding robot control method comprises the steps that image detection information generated when a workpiece is welded and welding parameter information of a welding gun are obtained; analyzing and determining a welding position point according to the welding parameter information; based on the welding position points, welding spot image information corresponding to the welding position points and original image information when welding is not conducted are determined from the image detection information; analyzing and determining quality demand information according to the original image information; welding spot quality information is analyzed and determined according to the welding spot image information; and quality adjustment control information is determined according to the deviation condition between the welding spot quality information and the quality demand information, and the quality adjustment control information is output to the welding robot for welding adjustment. The welding device has the effect of improving the welding efficiency.

The invention discloses a knowledge base-based field intelligent decision-making method and system, and belongs to the field of equipment operation and inspection. The invention is oriented to the field of equipment operation and inspection, combines advanced technologies and ideas such as layout analysis, named entity recognition, text generation, large language model fine tuning, text classification and target detection, and constructs a knowledge base-based field intelligent decision method and system for efficient processing and decision support of equipment fault information. The method comprises the following steps: constructing and organizing multi-source heterogeneous data, and integrating high-quality information into a maintenance knowledge base; on the basis, generating a self-adaptive text maintenance strategy by utilizing domain knowledge and responding to a dynamic operation context; and finally, fusing image modal data through an anomaly detection method, accurately positioning a fault, and improving the generation quality of a text maintenance strategy. According to the method, a complete process from multi-source heterogeneous data to multi-dimensional strategy generation is realized, key problems in equipment maintenance are effectively solved, and efficiency and accuracy are remarkably improved.

The invention provides a wireless resource scheduling method and device, equipment, a medium and a program product, and relates to the field of wireless transmission, and the method comprises the steps: collecting a current network resource use condition; receiving measurement data sent by the terminal during operation of the target service, and evaluating the service quality of the target service based on the measurement data to obtain service quality information; synchronizing the service quality information and the network resource use condition to a first control unit so as to generate service quality target information through the first control unit; calling a second control unit to generate a first resource scheduling instruction based on a preset artificial intelligence model in combination with the service quality target information, the service quality information and the configuration information of the terminal; the first control unit is a non-real-time wireless access network intelligent control unit, the second control unit is a near-real-time wireless access network intelligent control unit, and the first resource scheduling instruction is used for scheduling wireless resources for the terminal. And the response speed of the base station to the wireless resource scheduling is improved.

A method for enhancing summary reply capability of an intelligent question-answering system based on graph clustering comprises the following steps: step 1, acquiring text data of a document, and converting unstructured text data into a structured text information graph; step 2, performing hierarchical clustering on the text information atlas, and dividing the text information atlas into a plurality of different information communities; step 3, generating an information abstract for each information community, selecting an information abstract similar to a user question, and generating a candidate document set; and step 4, integrating the candidate document set to obtain a final summary reply. According to the method, firstly, the text information atlas and the graph clustering technology are creatively combined, and LLM optimization is supplemented, so that the summarization reply capability of the intelligent question-answering system is remarkably improved. Secondly, the deep semantic structure and the document content are organically combined, so that the recall quality, the information comprehensive efficiency and the reply continuity of the intelligent question-answering system are improved, and efficient and reliable technical support is provided for application of the intelligent question-answering system in a complex task scene.

A system may receive, from a client device, a query requesting quality information of a target device. The system may access a set of data records associated with the target device, pre-process the set of data records for extracting raw data associated with the target device from the set of data records, and convert the pre-processed data to normalized data using a first large language model (LLM). The system may apply a second LLM to the normalized data for generating an output result, which includes the requested quality information of the target device. Applying the second LLM may include: retrieving contextual information related to the target device; generating a prompt to the second LLM, the prompt comprising at least the normalized data, the retrieved contextual information, and the query requesting quality information of the target device; and providing the generated prompt to the second LLM to receive the output result.

The invention discloses a modulation parameter adjustment method, relates to the technical field of frequency modulation, and aims to solve the problem that the communication quality and reliability of a communication system are affected due to poor modulation accuracy of the frequency of the communication system. Comprising the steps that signal quality information, channel capacity and environment information are collected, the signal quality information comprises the signal-to-noise ratio, the bit error rate and the frequency offset, and the environment information comprises the environment temperature value, the environment humidity value and the electromagnetic interference frequency; determining the channel quality according to the signal-to-noise ratio, the bit error rate, the frequency offset and the channel capacity; comparing the environment information with standard environment information to obtain a comparison result, and determining whether the environment information affects channel quality according to the comparison result; if it is determined that the environmental information affects the channel quality, determining an influence parameter according to the environmental information, and determining a channel evaluation parameter through the influence parameter and the channel quality; and determining whether to adjust the carrier frequency modulation parameter according to the channel evaluation parameter.

The invention relates to the technical field of hot melt glue machines, in particular to a hot melt glue machine multi-path glue discharging control method and device, equipment and a storage medium. Glue discharging is executed based on the target, and actual glue discharging quality information of each glue path is obtained; according to the information and a preset target, a multi-path glue outlet state deviation matrix is generated; inputting the matrix into a multi-glue-path coupling cooperative control model to obtain cooperative control parameters of each glue path; and finally, cooperative control is carried out on each glue path actuator according to the parameters so as to eliminate the glue output quality difference among the glue paths. According to the method, the global glue discharging state is intelligently sensed, and the multi-path coupling relation is accurately modeled and compensated, so that high-precision cooperative control on the glue discharging quality of the multi-path hot melt glue machine is realized, the systematic technical problem of non-uniform glue discharging of multiple glue paths is effectively solved, and the quality and consistency of packaged or coated products are remarkably improved.

The invention discloses a non-reference image quality evaluation method and device based on multi-perception feature fusion and dynamic enhancement, and the method comprises the steps: obtaining the quality information of a multi-domain distorted image based on superpixel segmentation and Gaussian kernel filtering texture generation; quality related feature extraction is performed on multi-domain information through a semantic perception module and a distortion perception module, bidirectional modulation is performed on global visual features of an original distorted image through a cross attention mechanism, and dynamic fusion of multiple perception features is realized; through a parallel feature enhancement unit formed by local adaptive filtering of a visual self-attention block and a dynamic residual block, dynamic allocation of perception modes to different content areas is realized; generating a weighted quality score consistent with human visual perception through a weighted dual-path regression device; and outputting a predicted score consistent with the human score from the distorted image through the three sub-networks. According to the method, the problems of insufficient adaptability to complex content of a distorted image and low local distortion sensitivity are effectively solved.

The invention relates to the technical field of gas appliance quality control, and discloses a quality data analysis management system based on gas appliance production and after-sales service. A data acquisition module of the system acquires a process parameter time sequence from a distributed production terminal, and acquires a running state alarm event flow from a user service terminal in real time; the feature analysis module performs abnormal fluctuation compensation on a process parameter time sequence in a quality information fusion analysis mode, generates a multi-dimensional quality defect feature spectrum and determines a process tracing period; the risk conduction module obtains part circulation path information and analyzes defect correlation characteristics to obtain quality coupling data, and the production batch quality safety situation level is determined in combination with an alarm event flow; and the regulation and control execution module intervenes the full-life-cycle dynamic quality management and control blind area according to the process tracing cycle and the quality safety situation level. The system realizes integrated management of production and after-sales service quality data, and improves the effectiveness of quality management and control.

A method is performed by a user equipment (1100) for reporting quality of experience information. The method comprises transmitting, to a network node (1200) of a communications network, a quality of experience measurement report comprising quality of experience measurement data associated with an application session between the user equipment (1100) and the communications network. The method further comprises transmitting, to the network node (1200), an indication of a connectivity state of the user equipment (1100) with respect to the communications network when the application session was initiated.

The invention provides a confidence evaluation method and device, electronic equipment and a storage medium. The method comprises the steps that key information and semantic features of a query instruction are accurately captured by query features; the search result features comprehensively represent the core key points and the text features of the document; semantic difference features are determined based on the semantic difference between the query instruction and the search result, text difference features are determined based on the text difference between the query instruction and the search result, and the internal relation between the query instruction and the search result in the semantic and text level is deeply mined; the query features, the search result features, the semantic difference features and the text difference features can comprehensively reflect the matching degree and quality information of the query instruction and the search result, so that confidence coefficient prediction is performed based on the query features, the search result features, the semantic difference features and the text difference features to obtain a confidence coefficient score result; the performance of the RAG retrieval module can be efficiently evaluated, and dependence on external reference data and a complex large language model is got rid of.

Embodiments of this application provide a communication method and apparatus. The method includes: A first network element determines that quality information of a first clock needs to be obtained, and sends first indication information to a second network element, where the first clock is a reference clock of a wireless communication system, and the first indication information indicates to obtain the quality information of the first clock. The first network element receives the quality information of the first clock from the second network element, and sends the quality information of the first clock to a terminal device.

Techniques are disclosed to determine driver scoring that consider road quality and / or conditions in driver score computations. In contrast to the conventional approaches, the use of road conditions and / or road quality in the computation of driver scores allows for the consideration of road conditions and / or quality to improve upon conventional scoring techniques.

Disclosed are a product quality incident early warning method and system based on a convolutional neural network, the method includes: obtaining product quality information, determining product quality compliance, and issuing an early warning for a quality incident; inspecting product quality to obtain production-related parameters and appearance parameters, which are used to determine a production benefit value and a finished product qualification rate of the product, respectively, thereby determining a product quality compliance value; comparing the product quality compliance value with a preset quality compliance threshold to screen out quality anomaly index information of the product, and constructing a product quality anomaly convolutional neural network model to issue an early warning for the quality incident, such that product quality information can be obtained in a more accurate and rapid manner, allowing for quicker and more efficient identification of a product quality incident.

The invention discloses a medical oncology specimen collection and management system, and relates to the technical field of specimen management, and the system comprises a collection and detection unit which is used for collecting biopsy specimens and corresponding specimen data; the tracking quality control unit is used for storing full-process information of the biopsy specimens by utilizing a block chain and dynamically evaluating and tracing quality information of the biopsy specimens; the integrated learning unit is used for constructing a multi-omics database, generating a tumor multi-omics knowledge graph and carrying out dynamic knowledge updating through data mining; and the decision management unit is used for sharing resources and monitoring authorized use records of the biopsy specimens. By integrating the block chain, federal learning and process reconstruction, full-chain upgrading of medical oncology specimens from'collection 'to'application' is realized, tumor diagnosis and treatment are promoted to step forward from'experience-driven 'to'data-driven', digitization, standardization and traceable management of biopsy specimen full-process information are realized, and the efficiency of medical oncology diagnosis and treatment is improved. And data support and decision support are provided for clinical practice and scientific research.

The disclosure relates to a 5G or 6G communication system for supporting higher data rates. The disclosure provides a method performed by a base station of an NTN. The method includes: transmitting, to a terminal, a first PDSCH in first slots, wherein the first slots include at least one slot where the first PDSCH is scheduled without HARQ feedback; receiving, from the terminal, channel quality information and feedback information, wherein the feedback information includes HARQ feedback information and RLC status information associated with a transmission of the first PDSCH in the at least one slot; predicting a MCS and a repetition number for a second PDSCH, based on the information associated with the channel quality information and the feedback information; transmitting, to the terminal, information on the MCS and information on the repetition number; and transmitting, to the terminal, the second PDSCH in second slots.

The invention relates to the technical field of building informatization, and particularly discloses a BIM construction quality dynamic monitoring method and system based on edge computing, and the method comprises the steps: S1, collecting the physical parameters of a construction site through an Internet of Things sensor according to a preset initial frequency, and transmitting the original data to an edge computing node; s2, preprocessing the original data through edge computing nodes to generate a structured data set; s3, comparing the structured data set with design parameters in a BIM model database to generate a quality inspection intermediate result; according to the method, automation, refinement and real-time performance of construction quality inspection are realized, the quality management and control efficiency and the problem response speed are remarkably improved, deep association and dynamic updating of quality information and the BIM model are ensured, a strong data driving capability is provided for risk early warning, decision support and archive management in the construction process, and the construction efficiency is improved. And the engineering quality is effectively guaranteed by dynamically optimizing the monitoring resources.

The invention discloses a tea processing big data analysis and quality tracing system and method, and relates to the technical field of agricultural informatization management. The tea processing big data analysis and quality tracing system is constructed, full-process data collection, real-time monitoring and accurate tracing from fresh leaves to finished products are achieved, key parameter data in the processing process are collected in real time through a sensor, key factors influencing the tea quality are extracted through an advanced data analysis algorithm, and the quality of the tea is accurately traced. According to the method, the quality of tea leaves can be accurately identified, quality abnormal points are accurately positioned, the problems of incomplete data acquisition, lagged analysis and inaccurate tracing in a traditional method are solved, meanwhile, a unique tracing code is generated for each processing batch, a full-process data mapping table is constructed, dynamic updating and real-time query of quality information are realized, the quality management level of tea leaf processing is remarkably improved, and the method is suitable for large-scale popularization and application. The requirements of consumers on transparency and high quality are met.

The embodiment of the invention discloses a quality monitoring method and device for a space anchor point, equipment and a medium. A specific embodiment of the method comprises the following steps: constructing an initial scanning area corresponding to a space anchor point based on the space anchor point corresponding to a space object; generating map information according to the initial scanning area and each visual frame corresponding to the spatial anchor point; according to the map information, monitoring index information is generated, and the monitoring index information comprises scene quality information; and generating quality feedback information of the space anchor point according to the monitoring index information. According to the implementation mode, the initial scanning area is constructed, the map information and the monitoring index information are generated, accurate space anchor point quality information is obtained, guidance and feedback are provided for a user, the stability and reliability of the space anchor point in AR application are improved, and the use experience of the user is enhanced.

A method for beam adjustment in a base station disclosed herein may comprise the steps of allocating a first resource for transmitting candidate beams determined on the basis of the number of sweeps and the number of subcarriers of which beams are squinted in an angle search space; transmitting, to a terminal, first resource information indicating the allocated first resource; mapping beam indexes to each of the candidate beams; transmitting, to the terminal, information about the beam indexes mapped to each of the candidate beams; transmitting a reference signal by using the first resource; receiving reception quality information for the reference signal from the terminal; and determining a transmission beam on the basis of the reception quality information.

The invention provides a signal transmission method, apparatus and device, a medium and a program product. The method comprises the steps of sending an access response message and an uplink measurement signal configuration signaling to a target terminal; receiving an uplink measurement signal periodically sent by the target terminal according to the uplink measurement signal configuration signaling; obtaining uplink channel quality information; the target terminal is indicated to report downlink channel quality information; determining a target main link and a target auxiliary link with the target terminal according to the uplink channel quality information and the downlink channel quality information, and sending a main link configuration signaling of the target main link to the target terminal; receiving a main link configuration completion signaling sent by the target terminal according to the main link configuration signaling; and sending a link resource configuration signaling to the target terminal through the target main link. According to the invention, the main link and the auxiliary link are determined based on the channel states of the two links, so that the resource utilization rate and the transmission reliability are effectively improved.

The invention provides a self-service zooming method of a camera system based on depth-guided image quality evaluation. The method comprises three core links of multi-scale depth perception, depth-guided image quality evaluation and joint-driven intelligent focusing control. By fusing lightweight feature coding and a multi-scale optimization strategy, accurate depth information is generated, and a spatial perception basis is provided for subsequent processing; the depth features and the image texture features are combined, a focusing fuzzy evaluation model is constructed, and reliable feedback of the imaging quality is achieved; a key focusing area is identified based on depth and quality information, a target focal plane is decided, and a lens is driven through an intelligent control algorithm to complete rapid and accurate focusing. Through collaborative fusion of depth perception and image quality evaluation, intelligent zoom control of the camera system in a dynamic scene is realized, the imaging consistency and focusing precision are effectively improved, the method is suitable for multiple camera devices such as smart phones, security monitoring and automatic driving, and the imaging experience of users is improved.

This application relates to the field of medical technology and provides a medical application scenario matching method, electronic device, and computer program product. The medical application scenario matching method includes: acquiring a medical image sequence; determining image information of the medical images in the medical image sequence, the image information including key information, which includes one or more of the following: imaging object information, phase information, lesion detection information, and image quality information of the corresponding medical image; and outputting at least one target application scenario adapted to the medical image sequence based on the key information. Embodiments of this application can prevent doctors from using unsuitable medical image sequences in specific application scenarios, thus helping to improve doctors' work efficiency.