233 results about "Instrument Data" patented technology

The invention belongs to the field of pollution prevention and control data processing, and particularly relates to a laboratory instrument data automatic acquisition and quality tracing system and a laboratory instrument data automatic acquisition and quality tracing method. A distributed search traceability mapping space is constructed through the storage mapping module to realize space-time-semantic composite indexing and classification detection of data, and a causal reasoning model of the quality judgment module is used for performing anomaly judgment; a reverse Hash traceability mechanism is innovatively designed, an index-traceability node graph and a segmented Hash heterogeneous node anchoring strategy are combined, Hash head, body and tail fragments are stored in three types of nodes of acquisition, storage and detection, and tamper-proof traceability of abnormal data and dynamic optimization of acquisition parameters are realized through cross-node aggregation verification; according to the invention, the problems of low data credibility and poor abnormal traceability efficiency in ecological environment monitoring are solved, and full-chain closed-loop management of data acquisition-analysis-traceability-acquisition configuration adjustment is supported.

The invention provides an intelligent laboratory full-process collaborative management system and method based on multi-dimensional data fusion, and the method comprises the steps: obtaining an original data stream from laboratory instrument equipment, carrying out the format recognition and conversion of heterogeneous instrument data through a standard protocol adapter, and generating a first data set in a unified format; aiming at the first data set, executing automatic analysis by adopting data middleware, and integrating into a structured second data set based on a metadata rule of field mapping and unit conversion; according to the second data set, a multi-source data fusion model is constructed, data are classified according to instrument types through batch processing and aggregated according to timestamps, and a fused third data set is generated; aiming at the initial process configuration, adjusting a node sequence and a parameter threshold value by using a visual design tool, and generating an optimized process configuration adaptive to the diversified scene; according to the optimized process configuration, process scheduling is executed through a dynamic process engine, execution time and resource occupation are monitored in real time, and a process execution log is generated.

The invention relates to the technical field of sports competition real-time penalty, and discloses a sports competition real-time penalty system and method based on multi-modal sensing and AI algorithms, and the system comprises a monitoring identification module, an instrument tracking module, a rule parameter construction module, a fusion penalty module, an output and snapshot module, and a wireless linkage and energy management module. The method comprises the following steps: acquiring image and instrument data, and constructing a multi-modal sensing structure; calling a rule base to generate a penalty vector and loading a structure constraint; fusing the image and the instrument features to generate a feature tensor; inputting an AI model to judge the legality of the action and outputting a penalty result; driving the snapshot logic to generate an image record and synchronizing the image record to the terminal; and adjusting the energy consumption strategy according to the task load and the equipment state. According to the invention, a multi-modal perception input structure fusing instrument motion data and a visual image flow is introduced, so that the system can synchronously acquire displacement, acceleration and attitude images in the action recognition process, and a penalty basis is checked in a cross manner from multiple dimensions.

The invention provides a TFT instrument data interaction and cloud collaborative management system, and relates to the technical field of TFT display, and the system comprises a communication collection module which is used for deploying a plurality of integrated thin film transistor display screen units in a transport vehicle, and each unit collects the operation parameter data of the vehicle in real time through a vehicle-mounted sensor network; and the cloud receiving module is used for receiving and analyzing the operation parameters of the transport vehicle, determining the vehicle position, the operation state, the real-time parameter information content and the display mode position which need to be displayed on the monitoring interface, and mapping related data into interface elements to generate a motorcade monitoring interface. According to the invention, real-time data intelligent analysis and cloud cooperation are realized, full-link visualization and remote optimization of the vehicle state are realized, the operation efficiency is improved, and the maintenance cost is reduced.

The invention discloses a laboratory instrument data automatic acquisition and analysis method and system, and relates to the technical field of laboratory instrument acquisition and analysis, and the method comprises the steps: obtaining sample identification information, automatically sorting and distributing the sample identification information to different analyzers, uploading detection data to a central database in real time, and associating a sample number, a detection timestamp and an instrument number; the method comprises the following steps: constructing a multi-dimensional feature space based on historical detection data, performing sub-cluster division by adopting a density clustering algorithm, establishing a cross-index logic constraint relationship in combination with an expert rule base, mapping real-time detection data to the multi-dimensional feature space, judging a data exception type according to sub-cluster affiliation and the logic constraint relationship, and when judging that the data is exceptional, judging that the data is abnormal. And triggering a secondary detection process, automatically dispatching a mechanical arm to send the sample back to a specified instrument to execute differentiated reinspection operation, and generating a comprehensive report containing detection process tracing. According to the invention, the automation level of detection is improved, the labor cost is reduced, the detection quality and efficiency are improved, and the laboratory detection work efficiency is improved.

The utility model relates to an existing cavern compressed air energy storage physical model test system, which comprises a physical model, a hydraulic loading system, an air circulation charging and discharging system and a monitoring system, and is characterized in that the physical model comprises a surrounding rock and an air storage part, the surrounding rock comprises an external rock block and an internal rock block, the internal rock block is provided with a hole, and the hole penetrates through the internal rock block along the axial direction of the internal rock block; one or more prefabricated cracks are formed in the wall of the hole, the outer rock block is arranged on the outer side of the inner rock block in a surrounding mode, at least part of the air storage part is arranged on the two sides of the inner rock block in the axial direction, and the air storage part can seal the hole; the hydraulic loading system can apply a load from an external rock block to an internal rock block to the physical model, and the air circulation inflation and deflation system can inflate and deflate the hole; the monitoring system comprises a monitoring instrument and a data acquisition system, the monitoring instrument can perform data monitoring on the physical model, and the data acquisition system is in data connection with the monitoring instrument and can perform data transmission and processing.

The invention discloses an intelligent developing active packaging film thickness uniformity detection method and system, and relates to the field of film thickness uniformity detection.The intelligent developing active packaging film thickness uniformity detection method comprises the steps that a terahertz time-domain spectrum detection device is arranged, and area scanning is conducted on a to-be-detected developing active packaging film; network edge nodes are set, and data acquisition, data preprocessing and film thickness uniformity judgment are processed step by step; based on a convolutional neural network algorithm, preliminarily confirming the film thickness of the developing active packaging film; environment data are collected, and the film thickness of the color developing active packaging film is corrected through an environment error compensation algorithm; analyzing the influence of different film thicknesses of the developing active packaging films on the data of the terahertz time-domain spectroscopy instrument, and performing feedback correction on the film thicknesses of the developing active packaging films; and carrying out uniformity evaluation on the to-be-detected developing active packaging film area. The method has the advantages that non-contact detection is adopted, the efficiency of detecting the film thickness uniformity of the developing active packaging film is effectively improved, and the error influence caused by the film thickness and the environment is avoided.

The application provides a weather load-based air conditioner energy control method and device and a storage medium, wherein the method comprises the following steps: saving PLC bottom layer instrument data, indoor temperature sensor data and public data to a cloud platform server; processing the above data, calculating first index data in units of predetermined working time, calculating an optimized load amount according to the first index data; selecting a date closest to a predicted load day comprehensive temperature T in historical operation data as a reference day, taking the load of the reference day as a reference day load; and adjusting air conditioner energy according to the optimized load amount through two preset optimization conditions and the reference day load. The application predicts future load change rules by mining the corresponding relationship among climate, indoor temperature and load change rules through historical data, so as to realize the purpose of precise energy supply and effectively avoid energy waste.

The application discloses a kind of transformer substation in-station instrument automatic meter reading method and system, it is related to power station inspection technical field, including: meter reading work is completed by transformer substation in-station instrument meter reading software, including automatic meter reading module and meter reading photo analysis module;Automatic meter reading module is used to use mobile terminal and main control room computer to establish network communication, obtains meter reading photo by photographing field instrument to mobile terminal, and is returned to main control room computer, is downloaded and is transmitted to meter reading photo analysis module calculation;Meter reading photo analysis module is used to initialize meter reading photo, position target and calculate the instrument contained in meter reading photo, extract the outline of target, identify the edge coordinates of instrument pointer by contour matching mode, calculate the instrument reading pointed by instrument pointer by looking up black and white boundary in binary image.The application can replace artificial field meter reading, automatically obtain the reading of transformer substation instrument by field photo identification, generates instrument data report.

The invention discloses an instrument data reading and collecting system and method based on image recognition, relates to the field of instrument image recognition, introduces a specially trained Meter-CornerNet deep learning model, and can accurately position four key angular points of an instrument panel from an original image containing perspective distortion and uneven illumination. After the angular points are obtained, an inclined instrument area is corrected into a standard front rectangular view through perspective transformation, and illumination normalization is carried out, so that the interference of the angle and illumination problems on the image quality is improved. And then, digital segmentation and OCR identification are carried out on the processed high-quality image, a result is verified, and finally, an accurate reading is sent to an Internet of Things platform. According to the method, high robustness and high accuracy of the whole system in a complex real scene are ensured through a strategy of first accurate correction and then identification verification.

The invention discloses a remote cooperative verification and communication management system and method for a metering instrument, and relates to the technical field of instrument intellectualization. The method comprises the following steps: acquiring environment data and original instrument data of a plurality of metering stations through an Internet of Things communication protocol, and transmitting the original data to a remote communication management center for protocol adaptation processing to generate standard data frames in a unified format; further performing semantic standardization on the standard data frame to obtain a data set for verification; and constructing a cross-site mutual parameter verification model based on the data set and the environmental data, calculating a deviation value of each metering instrument, determining a cooperative verification priority index of the metering instruments in combination with a historical error change trend, generating a remote cooperative verification list containing verification task distribution information, and sending the remote cooperative verification list to a server. And the information is issued to each site for execution through an Internet of Things communication protocol. The remote automatic verification scheduling and data consistency guarantee of heterogeneous instruments is realized, and the efficiency and reliability of multi-site collaborative verification are improved.

The invention relates to the technical field of laboratory information management systems, and discloses an LIMS (Laboratory Information Management System)-based full-category detection data integration and quality tracing management system, which comprises a data modeling module for automatically generating domain ontology extension by adopting a method of combining ontology modeling and natural language processing; the data processing module is used for acquiring original data of the multi-source heterogeneous instrument data, and performing format recognition and semantic mapping on the original data by adopting a full-category detection data unified model; the block chain traceability module is used for storing traceability standardization detection data in a classified manner and establishing a layered framework; the quality prediction and early warning module is used for constructing a quality influence factor library and generating a prediction result based on the quality influence factor library; the cross-system integration module is used for obtaining a cross-system integrated data management platform by adopting a containerization technology and an event traceability architecture; according to the invention, the quality tracing query response time is shortened, and the credibility and timeliness of quality management are improved.

The invention relates to the technical field of data synchronization, and particularly discloses a multichannel instrument data synchronization method and system. The method comprises the following steps: acquiring time sequence data and timestamps of each channel of a multi-channel instrument, calculating a data sampling period and a clock drift rate according to the time sequence data and the timestamps so as to quantify time synchronization deviation, extracting a transient energy ratio and a spectrum distortion degree of a time sequence signal, measuring signal stability, performing normalization processing, and combining dynamic drift risk indexes of the time sequence signal, the spectrum distortion degree and the signal stability so as to obtain a time sequence signal. The low-risk data form a synchronization group, the high-risk data are isolated and corrected and then merged into the synchronization group to form synchronization data, and through dynamic risk assessment and grading processing, the influence of single-channel abnormity on overall synchronization is avoided, the clock and signal stability is considered, and the synchronization reliability is improved.

In an example, a system includes a processor that may receive instrument data from a surgical instrument related to operation of the surgical instrument during a surgical procedure; (ii) receiving, from the surgical navigation system, position data indicative of a position of the surgical instrument relative to the patient's anatomy during the surgical procedure; (iii) determining kinematic data based on the position data; (iv) determining a plurality of surgical performance indicators indicative of characteristics of the surgical performance using the instrument data and the kinematic data; (v) analyzing (a) kinematic data and instrument data with respect to (b) a plurality of surgical performance metrics; and (vi) causing the user interface to output information based on the analysis to provide feedback to a surgeon and / or stakeholder (e.g., a hospital administrator) relating to the performance of the surgical procedure.

The present invention provides a method and system for monitoring the status and predictive maintenance of a liquid chromatography instrument, which relates to the technical field of data processing. By jointly modeling the sensor data of the liquid chromatography instrument (such as continuous parameters like flow rate, temperature, pressure, etc.) and the log data (such as discrete information like alarm status, equipment events, etc.), and performing data dimensionality reduction based on the geometric similarity of data points, the local structure and global information of the liquid chromatography instrument data are maintained, while reducing the information loss during the dimensionality reduction process. Further, a status monitoring model is used to process the data, enhancing the context awareness ability of the model. When anomalies or faults occur, it can comprehensively consider various factors for accurate diagnosis, showing higher accuracy and reliability in monitoring the complex status changes of the liquid chromatography instrument.

The invention discloses an analysis instrument data management system and method based on cloud computing, and belongs to the technical field of data management. According to the method, gas inspection task requirements are collected and converted into feature data, background interference, response time and application occasions are comprehensively analyzed through a trained artificial intelligence model, and adaptive analysis instruments are screened to form a set; qualified parts are screened in combination with task requirements to form a candidate set, a graph structure is constructed through physical, technical and functional compatibility analysis, and an instrument and part matching set is generated. Establishing a mechanism-driven virtual simulation environment, restoring a dynamic working condition, embedding a three-class coupling effect mathematical model, and performing dynamic linkage simulation on a matching pair; setting a multi-dimensional quantitative index score, superposing the coupling effect correction value to obtain an execution score, and selecting an optimal matching pair through descending sorting. Physical integration and debugging are completed according to configuration, an actual gas inspection task is put into use, and accurate adaptation and efficient execution of the whole process are achieved.

The invention relates to the technical field of purified water systems, and discloses an intelligent control and cleaning method of a two-stage reverse osmosis purified water system, which comprises the following steps: step 1, acquiring water temperature, pH value, conductivity and instrument data of a water inlet and a water outlet in the purified water preparation process; 2, comparing the obtained data of each instrument with a set data reference and fluctuation range, and judging whether the data of each instrument is abnormal or not; and step 3, when the instrument data is abnormal, obtaining estimated correct data of the abnormal instrument according to the normal and abnormal instrument data and the historical data. According to the method, whether part of instrument data is abnormal or not is judged through various data in the pure water preparation process, when the instrument data is abnormal, estimated correct data is obtained according to association characteristics of an abnormal instrument and other normal data and the obtained various data, and then the obtained estimated correct data is verified.

The invention discloses a health detection instrument data processing system and method based on the Internet of Things, and relates to the technical field of data analys.The method comprises the following steps that sampling intervals are determined, a CGM sensor is controlled to collect data according to the corresponding sampling intervals, and a frequency mixing blood glucose data set is formed; constructing an input data set, and introducing a sampling interval weight to construct a basic trend model; based on the input data set, introducing a correction item to construct a scene correction model, and outputting a final prediction value at the current next moment; setting a future prediction time interval and a prediction moment number N, generating N prediction values based on the basic trend model and the scene correction model, and integrating the N prediction values to form a prediction sequence; setting a threshold value to analyze whether the prediction sequence is abnormal or not and the abnormal type; when an anomaly is detected, a feedback mechanism is triggered. The method can effectively improve the situation that in the prior art, dynamic blood glucose monitoring sampling frequency lacks scene adaptability and is insufficient in frequency mixing data processing capacity.

A method for processing data of an analytical instrument for analyzing biological samples is presented. The method comprises receiving instrument data from the analytical instrument at a data processing module communicatively connected with the analytical instrument, generating metadata from the received instrument data at the data processing module, applying a first encryption to the instrument data at the data processing module, applying a second encryption to the generated metadata at the data processing module, and transmitting the encrypted metadata and encrypted instrument data to a remote server. The remote server and the data processing module are communicatively connected. The method also comprises removing the second encryption from the metadata at the remote server and forwarding the instrument data encrypted by the first encryption from the remote server to a management system of the analytical instrument.

The invention relates to the technical field of Internet of Things and intelligent metering, in particular to a metering production equipment instrument data acquisition and integration method and system. Accessing different types of instruments by using a multi-protocol acquisition terminal, and unifying the format of protocol data through a protocol analysis engine; preprocessing the original data through edge computing nodes; performing data routing through a distributed message queue, and distributing the data to a corresponding cloud integration engine according to a production line to which the equipment belongs; and the cloud integration engine performs data modeling based on the unified data model. Through deep combination of theoretical innovation and engineering practice, the industrial measurement data acquisition and integration system with high compatibility, high real-time performance and high reliability is constructed, a standardized data infrastructure solution is provided for the fields of intelligent manufacturing, energy internet and the like, and the industrial measurement data acquisition and integration system has remarkable technical leading and industrial application value.

The present application relates to a kind of for the radiation protection detection in nuclear magnetic machine room, including: shielding sleeve box, by diamagnetic material is made, for shielding external static magnetic field, its internal cavity shape is adapted according to the shape of the used patrol instrument;Ray detection mesh, set up on shielding sleeve box corresponding to the position of patrol instrument probe, by diamagnetic material is made, allow X or gamma ray to penetrate;Instrument data reading mesh, set up on shielding sleeve box corresponding to the position of patrol instrument display screen, by diamagnetic material is made, allow detection personnel to read data directly visually;The import and export of instrument that can be closed, be set on shielding sleeve box, and be equipped with the sealing cover made of diamagnetic material, for the input and output of patrol instrument, the sealing cover is in closed state when detecting.The present application solves the phenomenon that the radiation diagnosis and treatment machine room adjacent place is the radiation protection detection difficult to implement for nuclear magnetic resonance machine room.

1. Name of the design product: data processing equipment. 2. Use of the design product: used in the automobile industry, general industrial automation production line and intelligent instrument data acquisition and diagnosis analysis system. 3. Design points of the design product: in shape. 4. Pictures or photos that best show the design points: perspective view 1.

This invention provides a method and system for verifying and tracing file fingerprints for scientific instrument data, comprising: Step S1, acquiring user identity information and instrument identifier of the scientific instrument, identifying the original data file through file monitoring and automatically collecting basic metadata to generate labeled metadata; Step S2, calculating the file fingerprint based on the algorithm identifier using a digest algorithm and writing it into a fingerprint database; Step S3, performing fingerprint comparison on the file fingerprints; if the fingerprints are the same, reusing the existing content object identifier and adding a new version record; if they are different, creating a new content object identifier and adding a new version record; and when the same reservation identifier, upload time difference not exceeding a preset threshold, and fingerprint inconsistency are met, creating a version fork and recording the fork reason code and fork reason payload for traceability; Step S4, performing verification processing on the downloaded file. The beneficial effect is that this invention can meet the comprehensive requirements of traceability, auditability, and real-time performance for the security management of scientific instrument data.

Systems for electronically automating reduction component selection, conversion, disaggregation, and assignment are provided. An intermediate database is populated or synchronised from a reduction dampening instrument database, the intermediate database is spatially indexed with entries each associated with a reduction component and location data. The system identifies a segment associated with each reduction component and identifies all reduction components within a segment. A reduction concentration is determined for each segment by totalling the concentrations for each reduction component within a segment. The reduction concentration is compared to an Available Reduction Threshold to determine if facility capacity has been exceeded for new reduction components and for previously assigned reduction components.

The invention discloses a measuring instrument data correction calculation method and system, and the method comprises the steps: calculating corresponding correction data in a measuring instrument range according to a correction result in a verification certificate of a measuring instrument, firstly, determining a target measuring instrument needing to be corrected, and obtaining a correction table in the verification certificate of the target measuring instrument; forming an initial correction value of the target measuring instrument; then determining the minimum endpoint value of the measuring range of the target measuring instrument, determining a calculation range by using two minimum adjacent endpoint values in the initial correction values, and sequentially calculating correction values corresponding to all the minimum endpoint values belonging to the determined calculation range by using a linear interpolation method to form an intermediate correction value; the intermediate correction value is corrected according to a four-circle six-in-five-in-two correction rule, an endpoint correction value is finally obtained, an endpoint correction table corresponding to the minimum endpoint value of the measuring range of the target measuring instrument is formed as a reference, and the result of each time of reading of the target measuring instrument is accurately corrected.

The invention belongs to the technical field of digital information transmission, and particularly relates to instrument data acquisition, in particular to an instrument data acquisition system and an instrument data acquisition method.According to the instrument data acquisition system, after acquisition equipment is connected with instrument equipment, a time parameter of a first code element is obtained; the Baud rate is preliminarily determined according to the time parameter of the first code element, data acquisition is carried out according to the preliminarily determined Baud rate, an oscillogram is constructed according to the acquired data, the final Baud rate is determined in the oscillogram according to the effective area, and after the final Baud rate is determined, data interaction is carried out between the instrument equipment and the final Baud rate. Therefore, the Baud rate of the instrument equipment can be quickly and accurately determined, the acquisition equipment can conveniently adopt the Baud rate corresponding to the instrument equipment for communication, and accurate transmission of instrument data is completed.

The invention discloses a health information management system based on an intelligent frontal sinusitis therapeutic apparatus, and the system comprises a therapeutic apparatus main body. A user information module, a therapeutic instrument data acquisition module, a symptom input module, a data analysis module, a therapeutic scheme adjustment module, a health reminding module, a remote medical module and a data storage module are integrated on the therapeutic instrument main body. Personal basic information, medical history information, allergy history information and family medical history information of a patient are stored through the user information module, therapeutic instrument working data and therapeutic effect related data are collected in real time through the therapeutic instrument data collection module, daily symptom information is input into the patient through the symptom input module, and comprehensive collection of multi-dimensional health information is achieved.

The present application relates to a kind of lung function instrument data processing method and system based on data analysis, including multiple expiratory peak flow meter and cloud platform, cloud platform is connected with multiple medical systems.Expiratory peak flow meter is used to measure lung function parameters.Database of cloud platform has user table and multiple data tables, user table is used to store individual information input by user and user mark, data table is used to store lung function parameters, measurement time, F-V curve and V-T curve and the feature vector structured in combination with user individual information.Various data tables in which, the latest data table is the first data table, when the data quantity stored in the first data table exceeds the first preset value, then create second data table.When the prediction result of XGBoost classification model output after training is not consistent with actual result, then the prediction result and its corresponding data table and user that are not consistent with actual result are marked, to update data table and user table.

The application provides an instrument reliability detection method, system, device and medium, and relates to the technical field of instrument detection. The method comprises the following steps: acquiring an i-th detection instrument and an i-th detection strategy. The i-th detection strategy is determined according to at least one of the following data: an instrument value of the i-th detection instrument and an operating parameter of a linkage device. The linkage device is a device in a grinding production line that affects the instrument value of the i-th detection instrument. An instrument data set of the i-th detection instrument is acquired. The instrument data set comprises a plurality of instrument values collected by the i-th detection instrument within a preset time period. According to the instrument data set of the i-th detection instrument and the i-th detection strategy, a reliability evaluation factor of the i-th detection instrument is determined. The reliability evaluation factor comprises at least one of the following: a communication state, a logic state and a value state. According to the reliability evaluation factor, a reliability state of the i-th detection instrument is determined. The application improves the detection efficiency of the detection instrument.

This invention discloses a method, system, and storage medium for verifying instrument data records. Based on a received data verification command, each record in the instrument data record table is sequentially retrieved. The corresponding screen layout information is retrieved from the instrument information database according to the instrument model. Then, the display features in the screen image are identified and analyzed, and compared with the screen area shape and measurement data layout information stored in the instrument information database. If they are not similar, an instrument model entry error message is triggered. If they are similar, the identified instrument measurement parameters are compared with the recorded parameters in the data record. If they are not the same, a measurement parameter entry error message is triggered. By using screen image content to automatically verify and verify the instrument model and measurement parameters in electronic experimental records, the inefficiency and error-prone nature of existing manual verification methods are overcome.