129 results about "DEVICE EVALUATION" patented technology

The invention relates to the field of equipment state monitoring in industrial Internet of Things, and discloses an equipment state monitoring, analysis and evaluation method and system based on big data, and the method comprises the steps: carrying out the adaptation of a multi-source heterogeneous data protocol, and carrying out the cleaning of a dynamic mask, and generating a standardized data stream; constructing a dynamic hypergraph of an embedded constraint equation based on physical topology; combining incremental tensor decomposition with manifold constraint to update a core tensor; abnormal association is positioned based on singular value distribution and a hyperedge propagation algorithm; cross-equipment model migration is realized through topological optimal transmission and knowledge distillation, and a target equipment evaluation model is generated; the system comprises a data preprocessing module, a hypergraph modeling module, a tensor analysis module, a state evaluation module, a transfer learning module and a dynamic tuning module. According to the method, through multi-source data dynamic cleaning, physical constraint hypergraph modeling, incremental tensor decomposition and manifold constraint, and in combination with an abnormal positioning closed loop and cross-equipment topology migration, equipment state monitoring and rapid model adaptation are realized.

The invention discloses a power equipment safety state assessment method and system, equipment and a readable storage medium, and relates to the technical field of power equipment assessment, and the method comprises the steps: collecting a power equipment communication interaction data flow, carrying out the time synchronization and outlier elimination, and constructing a multi-modal data matrix; evaluating the exception probability score and an exception probability threshold to obtain an exception state flag, and generating a security event data packet in combination with the preliminary exception type and the power equipment communication interaction data stream; adopting a LiNGAM causal discovery algorithm to perform non-Gaussian test and time sequence lag analysis on an abnormal event time sequence in the security event data packet, and constructing a directed acyclic causal graph; dynamically adjusting the causal intensity of the directed acyclic causal graph according to the real-time equipment load rate and the communication quality index, and outputting a dynamic causal graph; according to the method, the accuracy and adaptability of abnormal propagation analysis are improved, and finally the real-time performance and credibility of safety assessment of the power equipment are enhanced.

The invention relates to the technical field of power equipment state monitoring, in particular to a power equipment operation state evaluation and prediction method based on big data, which comprises a multi-source data acquisition module, a feature engineering processing module, an intelligent evaluation and prediction module and a decision support output module. By setting a multi-source sensing end, when the operation state of the power equipment is evaluated, the definiteness of state evaluation of different types of equipment is ensured by formulating multi-modal data fusion standard parameters and setting different state sensing weights for different types of equipment; and meanwhile, real-time state sensing is performed by fusing electrical parameters, mechanical vibration, thermal distribution and environmental stress data, so that whether a sensing blind area problem caused by a single data dimension occurs in an equipment evaluation process or not can be detected in real time, the comprehensiveness and accuracy of equipment operation state evaluation are ensured, and state sensing fragmentation errors are further reduced.

The invention belongs to the field of equipment evaluation, particularly relates to an intelligent evaluation method and system for the operation quality of a flight simulator, and aims to solve the problems of single evaluation dimension, poor real-time performance, low intelligent degree and lack of quantitative standards in the prior art. The method comprises the steps that operation data such as fault time, duration and available time are collected in real time through a sensor network; calculating core indexes such as fault frequency per unit time, accumulated duration and malignant fault rate; dynamically weighting and fusing the indexes to generate a single-machine health index; a correlation model is constructed based on fault space-time correlation between devices, and cluster health scores are output in combination with single machine indexes; when the malignant fault exceeds a threshold value, driving causal inference by utilizing a knowledge graph containing entity causal relationships of fault types, equipment parts and the like, and outputting a root cause diagnosis and maintenance scheme; and acquiring intervened data to update atlas parameters and models to form closed-loop optimization. Multi-dimensional real-time monitoring and diagnosis closed loop of the operation state are realized, and the maintenance efficiency is improved.

According to the sewage discharge data management method based on the intelligent water affair, the sewage discharge data, the equipment state data and the environment data of an enterprise are subjected to edge calculation, the initial discharge data and the equipment evaluation data are generated, localized real-time processing of the data is achieved, and the transmission amount of invalid data is reduced. And performing data implicit anomaly identification and multi-modal data cleaning on the initial emission data and the equipment evaluation data based on the sewage component chemical association rule base, accurately capturing abnormal points which do not conform to chemical association rules in the data, and generating an abnormal mark list and intermediate emission data. Data association analysis is carried out based on the abnormal mark list, the intermediate emission data and enterprise operation data corresponding to the enterprise, a data logic verification map is constructed, errors in the intermediate emission data are automatically corrected according to a logic relation in the verification map, the processing efficiency is improved, and through cross verification of multiple data sources, the data processing efficiency is improved. And target emission data and a compliance report with high accuracy are generated.

Systems and methods for monitoring structural integrity are provided. Acoustic sensors are disposed in relation to an area of interest of a structural member to detect an acoustic emission and output an acoustic emission signal. The signal is collected, and a computing device evaluates acoustic emission signal characteristics and predicts whether a crack is present. The acoustic emission signal characteristics are used to detect and predict aspects associated with formation and growth of cracks at various locations of the structural member.

The invention provides an escalator operation monitoring method and device, electronic equipment and a storage medium, and the method comprises the steps: collecting various key working state parameters of a to-be-monitored escalator during working through a sensor array arranged on the to-be-monitored escalator, the working state parameters are uploaded to edge computing equipment beside the escalator to be monitored, and the edge computing equipment evaluates the comprehensive health index of the escalator to be monitored; the edge computing device uploads the monitored working state parameters of the escalator and the evaluated comprehensive health index to the cloud end, and the cloud end continues to monitor the operation condition of the escalator according to the indication condition of the comprehensive health index. By means of the method, comprehensive understanding of the state of the escalator is enhanced, and therefore the fault rate and the maintenance cost are reduced.

The invention provides an intelligent warehouse logistics robot health degree assessment method and system, and relates to the technical field of equipment assessment, and the method comprises the steps: obtaining historical operation data of a logistics robot in different operation scenes, and carrying out the preprocessing and dividing; clustering is carried out through a DBSCAN algorithm, historical samples are screened, real-time operation data are obtained, the deviation degree between the real-time operation data and the historical samples is calculated, and the aging degree is obtained; calculating an external fault factor of the logistics robot according to the real-time environment data, and calculating an abnormal degree based on the external fault factor and the real-time performance data; according to the logistics robot health degree evaluation method and system, the association weight matrix of the logistics robots is constructed based on the cooperation relation between the logistics robots, the health degree of the logistics robots is comprehensively evaluated based on the association weight matrix, the aging degree and the abnormal degree, and the technical problems that in the prior art, the health degree is evaluated through a single operation parameter, and the evaluation result accuracy is low can be solved.

The invention relates to a method for carrying out a container inspection task in a container handling system for handling a plurality of container parts for containers, preferably plastic containers and / or bottles, wherein a transport device transports the plurality of container parts as a container part stream from at least one treatment device of the container treatment system to at least another treatment device of the container treatment system along a predetermined transport path, at least one sensor device for carrying out the container inspection task captures, preferably optically, in particular spatially resolved sensor data, preferably camera images, relating to the container parts to be inspected, and a real-time evaluation device evaluates the in particular spatially resolved sensor data, preferably camera images. According to the invention, a set of container component features is predetermined for the real-time evaluation device, said set being a set of container component features extracted automatically, in particular from a neural network, within a framework of a machine learning method performed with respect to a training container inspection task different from the container component inspection task, and the real-time evaluation device performs the container inspection task based on the set of predetermined container component characteristics.

The invention provides an equipment quality state evaluation method fusing data driving and QMU, and belongs to the technical field of equipment evaluation and detection. The method comprises the steps of collecting test data and task environment data of equipment to construct a data set, and dividing the data set into a training set and a test set; based on the data set, importance calculation is carried out on the multi-dimensional features through a limit gradient boosting tree, the features meeting the equipment quality state contribution degree requirement are screened out, and an observation list of the data set is generated; based on the observation list of the training set, a Gaussian process regression model is established, and hyper-parameters of the Gaussian process regression model are optimized; predicting the equipment state by using a Gaussian process regression model, performing uncertainty quantization on a prediction result, and outputting a mean value and a variance of an equipment state prediction value; on the basis of the performance threshold PTL or PTU of the equipment, a predicted value of the margin is calculated in combination with the average value of equipment state prediction; and calculating a confidence coefficient CF based on the variance of the predicted value and the predicted value of the margin, and affirming the quality state of the equipment.

A computer-implemented method includes: receiving, by a computing device, an input prompt; routing, by the computing device, the input prompt to one or more restructuring routes; restructuring, by the computing device, the input prompt to provide a restructured input prompt to reduce tokens; evaluating, by the computing device, the input prompt to the restructured input prompt to determine that thresholds are met; and sending, by the computing device, the restructured input prompt that meets the thresholds to a large language model.

The invention provides an equipment evaluation and maintenance suggestion method and system based on multi-modal data fusion, and relates to the technical field of equipment evaluation.According to the method, fault feature retrieval and maintenance suggestion intelligent output are achieved by constructing a classification database containing multi-modal historical fault information, combining weight factors and utilizing a large language model; a vibration signal and a temperature field are effectively fused, a bearing, a strain gauge, a motor, a guide rail and a lead screw are analyzed one by one, feature vectors are extracted, correlation analysis is performed on the feature vectors, multi-source features are fused, an equipment fault evaluation index is generated, and a numerical control machine tool state and maintenance suggestion is output based on the equipment fault evaluation index. The system improves the accuracy and sensitivity of fault diagnosis, can dynamically reflect the health state of equipment, assists a worker in taking maintenance measures in time, and remarkably improves the operation safety and production efficiency of the equipment.

The present application relates to a kind of OPGW cable health condition evaluation method, comprising: S1: collection OPGW cable equipment evaluation index data;S2: according to the first weight of index data numerical distribution calculation;S3: according to the correlation between each index data calculation second weight;S4: according to the first weight and second weight, obtain fusion weight;S5: determine OPGW cable health state index value, assess cable health state.The present application according to the first weight of index data numerical distribution calculation;According to the correlation between each index data calculation second weight;According to the first weight and second weight, obtain fusion weight;Determine OPGW cable health state index value, assess cable health state.The algorithm of the present application can accurately evaluate the health state of OPGW cable, and provide reasonable and effective theoretical support for the equipment state management and routine operation of OPGW cable.

The invention relates to the technical field of disconnecting link maintenance and transformation, in particular to an isolation disconnecting link updating and transformation method. The method comprises the following steps: S1, performing inspection and quantitative analysis, performing equipment evaluation and problem diagnosis, and identifying operation problems and function deficiency; s2, performing model selection and material optimization, and setting a standard isolation switch and an electric operation assembly; s3, defining a transformation range, dividing transformation units based on the main wiring diagram, and covering the isolation disconnecting link and the grounding disconnecting link; s4, implementing a safety locking structure, adding an electrified locking and five-prevention system, and accessing whole plant management to prevent misoperation; and S5, accessing a monitoring system, and connecting an LCU screen and a computer monitoring system to realize remote centralized control. The contact resistance and temperature rise of the contact reach the standard, ablation is completely eradicated, the operating force and time are greatly reduced, jamming is returned to zero, the five-prevention locking success rate is extremely high, the misoperation drill can reach the zero penetration level, and the on-site actual effects of mechanical zero jamming, five-prevention zero penetration, remote control zero delay and old and waste utilization are achieved.

The application relates to the technical field of electrical equipment evaluation, in particular to a multi-dimensional electrical equipment stability evaluation method and device for new energy power grid connection, which comprises the following steps: based on a multi-dimensional evaluation index system, collecting multi-dimensional index data of a target electrical equipment, performing feature enhancement processing, and generating processed enhanced features; based on a grid connection power fluctuation coefficient and an equipment operation stage coefficient of the target electrical equipment, adjusting the weight proportion of each dimension and corresponding indexes in the multi-dimensional index data to obtain dynamic weights; inputting the processed enhanced features and the dynamic weights into an evaluation model combining fuzzy comprehensive evaluation and Markov chain prediction, performing stability evaluation on the target electrical equipment for new energy power grid connection, and outputting a stability evaluation result of the target electrical equipment. Therefore, the problems that in the related art, prospective decision support cannot be provided for preventive maintenance and grid connection scheduling, and it is difficult to guarantee the safe and stable operation of the power grid under high-proportion new energy access are solved.

The invention discloses a centralized storage and unified management method, system, equipment and medium for a remote video monitoring system of a power generation enterprise, and belongs to the technical field of video monitoring. Identifying a monitoring blind area; replacing equipment according to an evaluation and classification result, and adding a high-definition network camera in a monitoring blind area; constructing a three-layer network architecture comprising an access layer, a convergence layer and a core layer, wherein the core layer adopts redundant connection; optimizing a hard disk video recorder deployment scheme based on the network topological relation; establishing a double-layer storage architecture, and adjusting a data uploading strategy according to a network state and a video recording type; unified access of devices of different manufacturers is realized through protocol conversion; and generating a monitoring interface according to the user role. Scientific classified updating of equipment is realized through a multi-dimensional equipment evaluation model, a transmission path is shortened through network hop count minimization and optimization deployment, bandwidth peak shifting utilization is realized through double-layer storage and intelligent scheduling, and unified and efficient management is realized.

A substation equipment status assessment and early warning system and method based on a digital twin platform includes the following steps: parsing the digital twin model to obtain basic equipment information and creating an equipment information mapping table; matching equipment types to select assessment algorithms and rules, and generating an equipment status assessment model; parsing inspection system data to match equipment information points; forming an equipment inspection information point table; instantiating equipment assessment objects and matching information points, algorithm parameters, and rules; initiating status assessment using a sliding window and event triggering mechanism to generate an assessment result file; analyzing historical data to predict equipment status and issuing alarms when anomalies occur. This method establishes an assessment model for complex primary and secondary equipment in substations, abstracts and concretizes multi-source data such as primary equipment, secondary equipment, monitoring, inspection, and operation and maintenance systems, and adopts flexible combinations of algorithms and evaluation rules to shield the differences between equipment and the diversity of algorithms, thereby improving the accuracy of the assessment and early warning function and the standardization of assessment results.

The present application discloses an evaluation system and method for an electroencephalogram (EEG) signal acquisition device. The system includes a standard control signal generation module for generating a standard control signal; an evaluation module for acquiring an EEG acquisition signal obtained by the EEG signal acquisition device, processing the EEG acquisition signal, displaying the EEG acquisition signal and the standard control signal, and comparing the waveforms and parameters of the EEG acquisition signal and the standard control signal, as well as determining the percentage of samples whose relative amplitude difference between the EEG acquisition signal and the labeled control signal exceeds a set threshold among all sample points. The present application evaluates the degree of signal distortion by calculating the normalized amplitude difference percentage, comprehensively considering the difference between the acquisition signal and the standard control signal, quantifying the distortion, and providing a reliable indicator for signal quality evaluation.

The invention discloses a multi-source data fusion and traffic mechanism driven checkpoint equipment closed-loop evaluation method, relates to the technical field of checkpoint equipment evaluation, and solves the technical problem of poor evaluation effect of existing checkpoint equipment. The method comprises the following steps: constructing an upstream equipment mapping table of the bayonet equipment based on road network information and position information of the bayonet equipment; verifying the historical traffic mode of the gate based on the historical traffic data, calculating the real-time accuracy of the gate device based on the floating car trajectory data, and finally comparing the traffic conditions of the to-be-evaluated gate device and the upstream gate device through the upstream device mapping table to judge whether the traffic is conserved or not; determining a mistakenly shot license plate number according to a license plate verification rule; the real license plate number of the mistakenly shot license plate number, the association algorithm and the hardware information are determined by using similar vehicles in the upstream and downstream vehicles, factors which can influence the equipment effect are analyzed, and improvement measures are adopted in a targeted manner; according to the method, environment interference, algorithm output characteristics and hardware state parameters are associated to form a closed-loop feedback mechanism.

This invention discloses a detachable electric field probe and calibration method for measuring the specific absorptivity of a vehicle-mounted human body model. The probe includes a metal dipole, a polytetrafluoroethylene (PTFE) ring, a waterproof metal casing, a ferrite magnetic ring, an SMA connector, and a detachable rubber sleeve. To prevent tissue fluid leakage, all components except the radiating element of the metal dipole are housed within the waterproof metal casing. The inner and outer conductors of the SMA connector connect to the upper and lower metal radiating elements, respectively. The ferrite magnetic ring is fitted onto the SMA connector, significantly improving the radiation pattern distortion problem of the electric field probe at low frequencies. The SMA connector connects to an RF receiver and a spectrum analyzer to acquire spectral information and the received power of the electric field probe, which, after calibration, reflects the magnitude of the field strength. This invention enables specific absorptivity measurement over a wide frequency range, featuring small size, low cost, and ease of use. It is suitable for specific absorptivity measurement in vehicle-mounted electromagnetic compatibility testing, medical device evaluation, and related scientific research fields.

Aspects relate to a method, a data processing system, a laboratory instrument, a computer program, and a computer readable medium. The method includes obtaining, by a computing device, a relationship result of a first clinical test. A first clinical test is performed on a biological sample by a first laboratory instrument, the biological sample being in a sample container. The relationship result includes first information and second information, the first information specifying that a laboratory result of the first clinical test is outside a reliability range of the first clinical test performed by the first laboratory instrument, and the second information specifying one or more of an upper bound and a lower bound of the reliability range. The method further includes evaluating, by the computing device, whether a condition of the laboratory rule is determinable by using the first information and the second information. The laboratory rule specifies one or more actions to be taken depending on the result of the determination of the condition. At least one of the one or more actions is to be taken on one or more of the biological sample, the sample container, and the relationship result, and / or the one or more actions include displaying information about one or more of the biological sample, the sample container, the relationship result, and the patient. If the condition may be determined and one or more actions are to be taken according to a result of the determination of the condition, the method includes causing, by the computing device, the one or more actions to be taken.

The invention discloses an electronic product reliability evaluation method fusing a failure mechanism and data analysis, and relates to the technical field of electronic device evaluation, the method comprises the following steps: obtaining a preset sensitive parameter data set of a to-be-evaluated device, and processing the preset sensitive parameter data set according to a preset degradation model to obtain a degradation data set; performing micromechanism and device structure simulation based on the degradation data set to obtain a life simulation error; fitting the degradation data set according to a preset life distribution model to obtain a reliable confidence coefficient; and obtaining an evaluation result based on the reliability confidence and the life simulation error. The invention is used for providing a degradation mode recognition system combined with a microscopic failure mechanism to improve the reliability index.

The invention discloses a packaging quality monitoring method based on MEMS, and relates to the technical field of MEMS, and the method comprises the steps: deploying an MEMS sensor, collecting technological parameters in a packaging process in real time, carrying out the preprocessing, and extracting multi-modal features; based on the multi-modal features, integrating the multi-modal features by using a multi-modal fusion algorithm to generate a multi-modal fusion data set; based on the multi-modal fusion data set, a quality prediction model is constructed through deep learning and is trained, and through the trained quality prediction model, the current packaging quality is evaluated and a packaging equipment evaluation report is generated; and on the basis of the packaging equipment evaluation report, the packaging equipment process parameters are adjusted in real time to optimize the packaging quality, and the quality prediction model is updated according to the adjusted process parameters and the quality score. According to the method, accurate monitoring and optimization of the packaging quality are realized through efficient multi-modal data fusion and a real-time updated quality prediction model.

The application relates to a device evaluation method and device, an apparatus, a readable storage medium and a program product. The method comprises the following steps: obtaining running state data corresponding to each of a plurality of configuration states of a target device; wherein the running state data comprises at least a compatibility data set and a security data set; for each configuration state, performing median aggregation and multi-dimensional weighting based on the compatibility data set in the running state data corresponding to the configuration state to obtain a compatibility score corresponding to the configuration state, and performing maximum aggregation and security failure evaluation based on the security data set in the running state data corresponding to the configuration state to obtain a security score corresponding to the configuration state; and weighting the compatibility scores and the security scores corresponding to the plurality of configuration states to obtain a device evaluation result. The method can improve the comprehensiveness of device evaluation.

To provide an evaluation device, an evaluation program, and an evaluation method for predicting a future body shape or the like.SOLUTION: In a support system in which a server device 20 is connected to a user terminal 10 and an imaging device 30 via a communication network 40, the server device, which is a support device that supports a user's fitness, includes a future posture generation unit that is a posture image generation unit that generates a future posture image of the user performing a predetermined movement based on a user image of the user and information about the user's physical constitution at a future time point predicted based on fitness activity schedule information.SELECTED DRAWING: Figure 1

The application belongs to the technical field of equipment evaluation, and discloses a kind of calculation method and system of sliding bearing dynamic characteristic coefficient, comprising: taking half of real oil film model as research object at axial symmetry plane, and setting the side surface of film and oil inlet located at axial symmetry as symmetry plane, which can significantly save computing resources and speed up the calculation speed;And the film and the oil inlet are separately divided into grids, and the outer wall surface of the film and the bottom surface of the oil inlet are set as grid interfaces, which can realize automatic grid division while ensuring grid quality;The application applies displacement, speed small disturbance to the journal in the equilibrium position by UDF in Fluent software, realizes the calculation of sliding bearing dynamic characteristic coefficient, and effectively improves the calculation accuracy.

The utility model discloses an evaluation device for tundish castable research and development, which relates to the technical field of evaluation devices and comprises an evaluation frame, a heat preservation table is welded and mounted at the middle end of the evaluation frame, a temperature controller is mounted at the front end of the heat preservation table, and a heating plate is mounted at the middle end of the heat preservation table. Through arrangement of the evaluation frame, the detector, the air cylinder, the movable plate, the detection head and the pressing spring, the movable plate is driven by the air cylinder to move downwards in the plate limiting sliding groove until the lower end surface of the movable plate is in contact with the upper end surface of a tundish pouring material block; and the detection head moves to the lowermost part in the limiting hole through the acting force of the pressing spring and is tightly attached to the tundish pouring material block, the sensed temperature is sensed to the detector for evaluation treatment, the tundish pouring material blocks with different thicknesses are adapted to be detected, and the adaptability of the evaluation work of the device is improved.

1. The name of the design product: eye movement assembly of human eye movement simulation device. 2. The use of the design product: the whole product is used to simulate the movement of human eyes, suitable for medical education, eye movement tracking test, optical product quality inspection, AR\VR device evaluation field; locally used for eye movement assembly of human eye movement simulation device. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: design 1 perspective view 1. 5. Design 1 is designated as the basic design. 6. Other circumstances that need to be explained: this patent application protects the local design: the part protected in design 1, design 2 and design 3 is the part drawn in solid line, the part drawn in dotted line in the view does not constitute the part protected by the local appearance.

The invention discloses a method and a system for evaluating the electrical life of a circuit breaker, and a medium. Relates to the technical field of device evaluation. The method is improved on the basis of the prior art, contact resistance errors in original data are removed according to the difference between a measuring device and a circuit breaker contact during dynamic contact resistance measurement to obtain evaluation data, and parameters are extracted from the evaluation data to evaluate the electrical life of the circuit breaker. On the basis of multiple groups of dynamic contact resistance curves, dynamic contact resistance data corresponding to the multiple groups of dynamic contact resistance curves are decomposed and filtered, and the difference between a measuring line and a circuit breaker contact point is quantitatively extracted in combination with actual working conditions, so that the accuracy of a dynamic contact resistance measuring result can be improved; therefore, the accuracy of circuit breaker electrical life evaluation is improved.

The application discloses a correction method and device for quantum response data of a two-end laminated battery, electronic equipment and a storage medium. The method comprises the following steps: judging whether the quantum response data of the two-end laminated battery is abnormal data; and when the quantum response data of the two-end laminated battery is abnormal data and the abnormal data is caused by the light transmission problem, correcting the abnormal data caused by the light transmission problem. The technical scheme provided by the embodiment of the application eliminates the influence of the light transmission problem, so that more accurate quantum efficiency values can be obtained, the quantum efficiency values are more in line with the actual situation, and the device evaluation or process debugging can be further facilitated.