501 results about "Laboratory device" patented technology

The invention provides an AI-based laboratory equipment scheduling optimization method and system, and the method comprises the steps: firstly obtaining a state monitoring data set containing the characteristics of equipment operation power consumption, idle time length, environment interference factors and the like in real time, and then carrying out the multi-dimensional analysis of the state monitoring data set; generating an availability evaluation index set containing characteristics of equipment load fluctuation, maintenance period prediction, compatibility matching and the like, and an experiment task priority queue, performing cross decision analysis on the availability evaluation index set and the experiment task priority queue based on a preset dynamic resource allocation model, and obtaining a scheduling strategy set containing a task allocation path, a cooperative operation rule and a conflict resolution mechanism; scheduling strategy parameters are calibrated according to experimental task operation log data, an optimized execution instruction set is generated, instructions are fed back to an equipment control system to adjust the equipment state, a dynamic resource allocation model is iteratively updated according to execution feedback data, and efficient scheduling optimization of laboratory equipment is achieved.

The invention discloses a laboratory automatic process management and multi-source data fusion system based on the Internet of Things, and belongs to the technical field of laboratory management. The system comprises a sensing layer, an analysis layer, an intelligent management layer and an application layer. The sensing layer carries out global data acquisition and real-time analysis; the analysis layer integrates data, mines an association relationship and optimizes task matching; the intelligent management layer performs full-process automatic management and control on a laboratory, and comprises an equipment cooperation module, a dynamic detection module, a dynamic configuration module, a real-time simulation module, a preset trigger module and an intelligent auditing module; and the application layer performs multi-terminal collaborative interaction and intelligent assistant assistance processing. According to the system, intelligent collaboration of laboratory equipment, automatic detection of samples, dynamic optimization of equipment parameters and automatic early warning and processing of abnormal conditions are realized through technical means such as knowledge graph construction, a digital twinborn technology and multi-mode biological recognition, and the laboratory management efficiency and the data processing accuracy are effectively improved.

The invention provides a laboratory equipment access and configuration method and system based on dynamic protocol analysis, and the method comprises the steps: firstly, monitoring a physical connection signal of a port, automatically triggering communication link configuration, calling a preset protocol parameter based on an interface type, and obtaining first identification information of equipment; then, based on a preset protocol mapping table or a dynamic matching rule base, determining a protocol type, and based on the protocol type, performing segmented analysis on the original data stream, identifying an effective frame and checking integrity to obtain a field definition, an instruction template and a communication parameter for binding storage with the unique identifier of the equipment; and finally, automatically generating an instruction according to the communication configuration, performing communication interaction with laboratory equipment, and triggering retransmission or link recovery operation when the communication state is abnormal by monitoring the communication state in real time. In addition, the communication condition of the laboratory equipment is displayed in real time through the interaction platform. According to the method, the deployment cost is reduced through full-automatic identification configuration, and the communication stability is improved through communication link optimization and exception handling.

The invention provides an intelligent laboratory man-machine interaction control method and system, and relates to the technical field of control, and the method comprises the steps: collecting experimenter and equipment images through a visual collection device, recognizing equipment operation state parameters based on a deep learning model through a processing server, including a switch state, an indicating lamp state, a display screen state and a fault indication state, and transmitting the state parameters to a server; and comparing the identification result with a preset parameter to generate an evaluation result. And the processing server receives the user voice instruction, extracts the content of the control instruction, and determines the target equipment and the control action. And verifying the legality of the instruction and judging whether an execution condition is met by combining an equipment state evaluation result. And a cooperative control strategy is generated according to the control instruction and the evaluation result, the cooperative control strategy comprises a control time sequence, parameters and a data interaction mode, and the control instruction is sent through the field bus network to realize multi-device cooperative control. According to the invention, intelligent management and control of laboratory equipment are realized, and the experiment efficiency and safety are improved.

The invention provides an intelligent guard system for large-scale micro-nano processing laboratory equipment, and the system comprises a data collection module, a risk early warning module, a fault positioning module and an operation and maintenance management module, the fault is traced by using the collected real-time environment data, real-time state data, experimental data, real-time behavior data and identity information, so that the details of the fault can be known in time, and fault maintenance, responsibility investigation and the like can be carried out; the operation and maintenance management module can carry out multi-dimensional operation and maintenance management on the laboratory according to the collected real-time environment data, real-time state data, experimental data, real-time behavior data and identity information, so that the efficiency, the performance and the service life of equipment are improved, the maintenance cost of the equipment is reduced, and effective utilization of social resources is facilitated.

The invention provides a micro-nano processing laboratory equipment information control method and device. The method comprises the following steps: acquiring user login information; calling item information to which a user belongs, user experiment reservation information, user associated equipment information and user historical query information according to the user login information; predicting the attention weight of the user to each piece of laboratory equipment management information in combination with the user identity permission, the item information to which the user belongs, the user reservation experiment information, the user associated equipment information and the user historical query information; adjusting the display sequence and the detailed degree of each piece of laboratory equipment management information in combination with the attention weight; and the data board is used for sending laboratory equipment management information to the user according to the display sequence and the detailed degree.

The invention discloses a laboratory risk control method based on a graph neural network, and the method comprises the following steps: S1, constructing a dynamically updated interaction event graph based on an interaction event sequence of laboratory equipment, personnel and environment; s2, dynamically updating the state space of each node according to the event preorder relation, and generating a synchronous node state sequence; s3, generating an early warning feature set of a node state change trend by adopting a graph convolution operation; s4, constructing an inter-node risk incidence matrix according to the early warning feature set, and generating an updated risk propagation path; s5, evaluating the probability of transition from the node state to the abnormal state, and generating a state risk prediction value; and S6, inputting a wolf pack optimization algorithm, and optimizing a parameter combination to obtain a laboratory risk prediction result. According to the invention, the real-time performance and accuracy of laboratory risk prediction are improved.

The invention discloses a method for determining the demulsification speed of emulsified asphalt, and relates to the technical field of online detection and intelligent monitoring of road engineering materials, and by integrating a lightweight time sequence prediction model and a self-adaptive processing mechanism, the practicability and reliability of the determination of the demulsification speed of the emulsified asphalt are remarkably improved; in the aspect of portability, an edge model based on a gating circulation unit structure is adopted, so that the dependence on computing resources is reduced, the method can be operated on handheld equipment, the problem that traditional laboratory equipment is heavy is avoided, and construction personnel can conveniently and quickly deploy the equipment on site; the real-time performance is enhanced, the adaptive sliding window dynamically adjusts the window length and step length according to the data stability to ensure that the inference frequency is matched with the demulsification process, and the model can immediately respond to environmental changes such as temperature fluctuation and output a demulsification speed estimated value without obvious delay in combination with an online learning mechanism, so that the paving and compacting opportunities are guided; and construction interruption is reduced.

The invention discloses a management platform and a management method for a laboratory. The method comprises the following steps: acquiring an environment-related data set and an equipment-related data set of a target laboratory; according to the environment related data set, calculating an environment state index representing environment quality of the target laboratory; according to the equipment related data set, calculating an equipment state index representing the equipment operation stability degree of the target laboratory; and according to the environment state index and the equipment state index, determining an overall state index and a state level of the target laboratory so as to be used for management of the target laboratory. According to the embodiment of the invention, the method can achieve the evaluation and management of the overall operation condition of the laboratory, guarantees the stable operation of laboratory equipment, guarantees the high-quality state of the environment, and improves the overall management efficiency of the laboratory.

The invention belongs to the technical field of laboratory equipment management, and provides a laboratory equipment tracking system based on RFID and Bluetooth, an RFID reader-writer and a Bluetooth receiver are respectively arranged in a laboratory, and each piece of equipment in the laboratory is equipped with an RFID tag or a Bluetooth tag; and the central management module is configured to collect and process data from the RFID reader-writer and the Bluetooth receiver, and calculate the real-time position of each device in the laboratory according to the signal intensity and the position of the reader-writer or the receiver. The laboratory equipment management system has the advantages that real-time positioning, management and monitoring of the laboratory equipment are realized through hardware arrangement, system integration and data management, the management efficiency of the laboratory equipment can be effectively improved, and the risks of equipment loss and use management are reduced.

The invention relates to the related technical field of laboratory equipment, and discloses a laboratory intelligent management system based on a safety monitoring function, which comprises an experiment table, an operation table is arranged on the experiment table, a first shell is arranged at the upper end of the operation table, and a collection and treatment assembly is arranged in the first shell; an S-shaped channel can be formed in the middle of the interior of the second shell through a first inclined plate and a second inclined plate, so that the moving stroke of poisonous gas in the second shell is prolonged, and the treatment effect on the poisonous gas is improved; the conical cover moves downwards to be close to the position above a source where the harmful gas is generated, so that the toxic gas is prevented from being diffused into a laboratory; and finally, by reducing the width of an S channel in the second shell, the height of the multiple adsorption particles in the second shell is increased, the contact time of the toxic gas and the multiple adsorption particles is further prolonged, and the toxic gas treatment effect of the collecting and treating assembly is improved according to the amount of the toxic gas.

The invention relates to the technical field of automatic control, and discloses a decontamination control method and system for laboratory automatic feeding equipment and a storage medium, the method is based on a decontamination cleaning device arranged on a tail frame of laboratory equipment, and the method comprises the following steps: firstly obtaining an image above a tail frame of a conveying belt to obtain a dirt image, and identifying a first dirt feature according to a specific dirt threshold value; and calculating the corresponding first dryness and humidity and the first distribution uniformity. The immersion depth of the cleaning rolling brush in the disinfectant is adjusted according to the first dryness and humidity in an anti-correlation mode, if the dryness and humidity are high, immersion is shallow, and if the dryness and humidity are low, immersion is deep; the thickness of the cleaning rolling brush is adjusted in an inverse correlation mode according to the first distribution uniformity, if the uniformity is high, the rolling brush is thin, and if the uniformity is low, the rolling brush is thick. Then acquiring a side image of the tail bracket of the conveying belt, identifying a second dirt feature, calculating the dirt height, and adjusting the pressure of the scraper pressing the conveying belt and the rotating speed of the cleaning rolling brush according to positive correlation, wherein if the dirt height is high, the pressure is high, the rotating speed is high, and if the dirt height is low, the pressure is low, and the rotating speed is low. By means of the scheme, automatic and efficient decontamination can be achieved.

The invention relates to the technical field of food detection equipment, in particular to a food processing heavy metal detection device and method. According to the technical scheme, the atomic absorption spectrometer comprises an atomic absorption spectrometer body and reagent bottles arranged in a straight line, the atomic absorption spectrometer body is provided with a conveying pipe for conveying reagents in the reagent bottles, and the atomic absorption spectrometer further comprises a drawer groove formed in the bottom of the atomic absorption spectrometer body. Through the design of the structures of the atomic absorption spectrometer body, the clamping seat mechanism, the transmission mechanism, the clamping rod mechanism and the like, the falling risk caused by careless touch of the reagent bottle is avoided, the reagent bottle and laboratory equipment are protected, the risk of reagent leakage is reduced, and the safety and accuracy of experimental operation are ensured. And a plurality of reagent bottles in the supporting pulling block move in a reciprocating manner in order, so that the reagent bottles are prevented from being disordered or mistakenly poured during use, the taking process is optimized, the operation time and errors are reduced, and the smoothness of the whole workflow is improved.

The invention discloses a safety early warning method and system, and the method comprises the steps: obtaining environment data and equipment data corresponding to each piece of laboratory equipment, the environment data and the equipment data being data collected by a detection sensor corresponding to the laboratory equipment, and deploying at least one piece of laboratory equipment in a laboratory, a single laboratory device is correspondingly provided with at least one detection sensor, and the detection sensor is detachably installed in the communication network of the access server; comparing the environment data and the equipment data with a preset parameter threshold to obtain a comparison result; inputting the equipment data and the environment data into a pre-trained anomaly evaluation model for identification to obtain an anomaly score; determining an abnormal event and an early warning strategy corresponding to the abnormal event according to the comparison result and the abnormal score; and sending the early warning information to the target early warning equipment to indicate the target early warning equipment to execute the early warning strategy. According to the invention, the timeliness and accuracy of the detection and response of the laboratory abnormal event are improved.

The invention discloses a laboratory intelligent inspection and maintenance method based on cooperation of the Internet of Things and a robot, and relates to the technical field of laboratory management, and the maintenance method comprises the following specific steps: S100, data collection and transmission: deploying a plurality of Internet of Things sensors at key positions of a laboratory, collecting environment data and equipment operation state data in real time, and sending the environment data and the equipment operation state data to a server; according to the method, data models of different disciplines are constructed by combining knowledge of multiple disciplines of chemistry, physics and biology, real-time data are analyzed and monitored in real time, abnormal conditions in operation of a laboratory can be found in time, and in a knowledge graph fault traceability stage, the fault traceability of the laboratory is improved. According to the method, the map covering laboratory equipment, experimental process and environmental factor knowledge is constructed, and the comprehensive association degree of the fault features and related entities in the knowledge map is evaluated, so that the fault generation root can be quickly judged, the fault processing time is shortened, the fault processing accuracy is improved, and the fault processing efficiency is improved. Powerful support is provided for the operation of a laboratory.

In one embodiment, a method is disclosed to determine one or more biological cells of interest to identify and count in a mixed biological sample fluid with differing biological cells. The method can include selecting cell markers associated for biological cells to which conjugated antibodies can attach with differing fluorescent dyes; displaying a panel builder graphical user interface window to display a co-expression matrix by biological cell type to assist in selecting cell markers to assign co-expression; and selecting cell markers to assign co-expression with an input device.

The invention belongs to the field of smart laboratory management, relates to a data analysis technology, and aims to solve the problem that dynamic parameter setting cannot be performed on the basis of static data of equipment in the prior art, in particular to a smart laboratory comprehensive management method and system fused with big data analysis. The comprehensive management platform is in communication connection with a static analysis module, a dynamic adjustment module, a fault monitoring module, a management optimization module and a database; the static analysis module is used for performing static data analysis on the equipment of the intelligent laboratory; the laboratory equipment put into use is marked as an analysis object, and the analysis object is marked as a conventional object or an indented object through a maintenance proximity value and a consumable stock value; static data analysis can be carried out on the equipment in the smart laboratory, the fault probability of the equipment in the experiment process is predicted according to the maintenance stage of the equipment and the consumable stock number, and data support is provided for the dynamic adjustment process.

The invention discloses a system for simulating the contact condition of a pantograph and a contact net after an earthquake. Relates to the field of railway bridge contact net anti-seismic tests. The system comprises a contact network simulation assembly, a train simulation assembly and a vibration table assembly. The contact network simulation assembly comprises a winch, a contact rope and two supporting columns. The two supporting columns are fixedly arranged at intervals, the winch is arranged at the top ends of the supporting columns and used for driving the contact rope to slide between the two supporting columns, the train simulation assembly comprises a train body, wheel parts arranged below the train body and a pantograph arranged on the train body, and the pantograph is in contact with the contact rope; the vibration table assembly comprises a table body and a vibrator used for vibrating the table body. The table body comprises a plurality of table tops which are independently arranged; the wheel part is placed on the table body; the vibration table assembly is adopted, each wheel below the train head is placed on the corresponding vibration table, and compared with the situation that a large vibration table top is placed below each wheel of a front bogie and a rear bogie, the real situation that the vibration states of all the wheels are different when a train runs on an unsmooth track after an earthquake is better met, the requirement for laboratory equipment conditions is lower, and the working efficiency is improved. Theoretically, test simulation is easier to realize, and the test result is more real, accurate and comprehensive.

The invention discloses an inertial navigation system calibration method and device based on a cold atom interferometer, and relates to the technical field of inertial navigation, guidance and control, an accelerometer and a gyroscope are used for collecting original data and correcting errors, and then calibration is carried out by combining the earth gravity acceleration and rotation angular velocity collected by the cold atom interferometer. And through calculation of an attitude rate differential equation and a displacement angular rate differential equation and attitude fusion, accurate attitude output is obtained. According to the invention, the pose measurement precision is greatly improved; the system has an autonomous traceability, and gets rid of the dependence of traditional calibration on laboratory equipment or specific devices; the rearranged algorithm enhances the precision of long-time navigation in a complex environment, and is suitable for long-endurance and combined navigation systems; the online calibration function of the calibration system can correct system parameter drift in real time, continuous high-precision operation of the navigation system is guaranteed, and the overall performance and reliability of the inertial navigation system are effectively improved.

The invention relates to a mobile energy storage terminal, which comprises a shell assembly, and a power output module, a water tank assembly, an air filter assembly, a battery, a main control circuit board assembly, a water system and a mobile assembly which are arranged in the shell assembly, mobile power supply is supported through a built-in battery, the service life of a filter element is monitored through the air filter assembly, the water system integrates UV sterilization and automatic water level management, and the main control circuit board assembly provides touch screen interaction and wireless control functions. The system solves the problems that traditional laboratory equipment is complex in construction and single in function, and has the advantages of being highly integrated, movable and intelligent in management. The system integrates water, electricity and wind, can adapt to various application scenes without electricity, water and air purification systems, simplifies laboratory hardware installation and reduces laboratory construction cost.

The invention discloses a spectrogram data management method based on laboratory equipment, and relates to the technical field of medical data management, and the method comprises the steps: constructing a topological graph through a graph theory method, describing the incidence relation between different target drugs, collecting the drug component data of a target drug sample through the laboratory equipment, in combination with a traditional Chinese medicine compatibility theory and a formula standard, edges and weights between different nodes are initialized, the relation between attributes of the nodes and the edges in the topological graph is adjusted by comparing with a medicine component database in an existing pharmaceutical standard, and finally the verified and optimized topological graph is stored as standardized spectrogram data. According to the method, the relationship among the medicine components is visualized through a graph theory method, and the edges and the weights of the edges among the nodes in the topological graph are generated in combination with the attributes and interaction of the medicine components, so that researchers can visually check the action relationship among the components, and the research efficiency is improved. And the problems of information isolation and difficult query in traditional experimental data management are reduced.

The invention belongs to the field of laboratory equipment management, relates to a data analysis technology, is used for solving the problem that in the prior art, optimal matching of execution equipment cannot be carried out for experiment types, and particularly relates to an intelligent laboratory equipment state real-time control method and system based on the Internet of Things. Comprising an equipment monitoring module, an experiment evaluation module, a reconstruction analysis module and an operation and maintenance management module which are connected in sequence, and the equipment monitoring module, the experiment evaluation module, the reconstruction analysis module and the operation and maintenance management module are in communication connection with a database; according to the method, reconstruction optimization analysis can be carried out on execution equipment in the experiment process, comprehensive analysis and calculation are carried out in combination with the mark states of all monitoring equipment under the same equipment type in the monitoring period to obtain the reconstruction coefficient, and therefore a reconstruction data set is generated for the experiment type; the execution equipment of the experiment process is dynamically matched by taking the monitoring period as a unit, so that the accident rate and the equipment failure rate of the experiment process are reduced.

The invention is suitable for the technical field of equipment management, and provides a laboratory equipment management method and system for chemical detection, and the method comprises the following steps: receiving an experimental equipment use demand inputted by a user, the experimental equipment use demand comprising an experimental item, user information, demand equipment and a demand time period; judging whether the demanded equipment needs to be queued for use, if so, calling the priority, the credit and the integrity of the corresponding user information, and calculating to obtain an equipment use cardinal number of the user information; determining the deadline of the demand time period, and determining user information allocated to the equipment at the deadline; and calling historical equipment use data of the distributed user information, analyzing the historical equipment use data, and sending equipment training information to the user account. According to the invention, based on a multi-dimensional equipment allocation strategy, the equipment use cardinal number is determined by calling the priority, the credit and the integrity of the user information, so that the fairness and the reasonability of equipment allocation are realized.

The invention provides a reverse instruction identification and concurrent management method and system for laboratory equipment and a medium, and the method comprises the steps: firstly, dynamically analyzing a user instruction through a pre-configured protocol table, converting a parameter into a binary control frame which can be identified by the equipment, and breaking through the coarseness limitation of a conventional switch type instruction; then, multi-thread asynchronous scheduling and device-level independent task queues are adopted, a control queue is distributed for each device, a priority label is embedded, transmission channels are dynamically switched in combination with network link quality, and non-blocking control over the devices in a high-concurrency scene is achieved; finally, the instruction receiving frequency is dynamically adjusted based on the equipment state, so that the instruction execution success rate is increased; in addition, an equipment grouping management mechanism is introduced, according to an equipment group unified instruction issued by a user, the equipment group unified instruction is automatically disassembled into sub-instructions, and the sub-instructions are executed in batches according to a strategy, so that the experiment cooperation efficiency is greatly improved.

The invention relates to a laboratory system including at least one laboratory device which is designed to analyse and / or synthesise a chemical substance; at least one laboratory software module which is designed to process data obtained from the at least one laboratory device; a data processing device with control software that provides an interface for operating the at least one laboratory device and / or the at least one laboratory software module; and a portable device with a microphone, wherein the device is connected interoperably to the control software via a network, wherein the device is designed, in interoperation with the control software, to allow a user to operate the at least one laboratory device and / or the at least one laboratory software module without manual intervention, by speaking into the microphone.

The invention discloses a detection method based on combination of anti-NF155 antibody detection and enzyme-linked immunosorbent assay. According to the detection method, an analysis model based on an XGBoost model algorithm is established by adopting anti-NF155 antibody detection of a patient and detection data of an enzyme-linked immunosorbent assay in combination with autologous clinical data of the patient, so that CIDP subtype classification is performed on the patient, and personalized treatment scheme suggestions are provided in combination with illness state dynamic data of the patient. Meanwhile, the invention provides a corresponding detection system which comprises a laboratory, a data storage library and an analysis unit, the anti-NF155 antibody detection is executed through laboratory equipment, and detection data and patient autologous clinical data are stored in the data storage library. The analysis unit establishes an analysis model based on an XGBoost model algorithm based on a machine learning algorithm.

The invention discloses a laboratory equipment fault diagnosis and maintenance decision generation system based on a large language model, and relates to the technical field of fault diagnosis. According to the system, a cross-device and multi-data type intelligent maintenance system in an AI For Science black light laboratory scene is constructed, standardized processing and intelligent fusion of multi-modal data are realized, and fault diagnosis, root cause tracing and executable maintenance decision generation are enabled through association of a large language model and knowledge, so that the maintenance efficiency is improved. A self-learning optimization closed loop is formed based on decision feedback and a knowledge vector library, the maintenance operation convenience is improved in combination with man-machine collaborative interaction, manual misjudgment and downtime are reduced, intelligent, standardized and traceable support is provided for full-life-cycle operation and maintenance of black light laboratory equipment, and the maintenance efficiency is improved. The problems that traditional maintenance is slow in response and low in accuracy, fault diagnosis lacks semantic understanding and causal reasoning ability, operation and maintenance knowledge is difficult to accumulate and inherit, and a full-life-cycle maintenance closed loop is lacked are solved.

The invention provides a semiconductor experiment platform experiment reservation process auxiliary method and device, a storage medium and equipment, and the method comprises the steps: obtaining the login information of basic information inputted by a user in a semiconductor experiment platform, and calling the related information of the user from the semiconductor experiment platform according to the login information of the user, the associated information comprises user basic information, user communication records and user historical experiment records; generating a user portrait according to the associated information; obtaining an experiment reservation process node of a user on the semiconductor experiment platform; and generating experiment appointment process prompt information of the semiconductor experiment platform in combination with the experiment appointment process node and the user portrait. Specific experiment reservation process prompt information is generated by combining the specific portrait of the user and the experiment reservation process node where the user is located, so that the semiconductor experiment platform can remind different users and specific experiment reservation contents. And the user process node management efficiency of the semiconductor experiment platform and the operation efficiency of laboratory equipment are improved.

The utility model belongs to the field of laboratory devices, and relates to a burette support which comprises a base, a stand column, a moving part, a rotating shaft, a rotating rod and a butterfly clamp, the moving part is sleeved on the stand column and can slide up and down, the moving part can be fixed on the stand column through a moving part fixing nut, and the moving part, the rotating rod and the butterfly clamp can be connected through the rotating shaft. A plurality of burettes can be installed at the same time by installing a plurality of moving pieces, 360-degree space with the stand column as the center can be fully utilized by adjusting the directions of the moving pieces, the height of the burettes can be freely adjusted by adjusting the angle of the rotating shaft, use is flexible, convenient and fast, and the working efficiency can be greatly improved.