26 results about "Laboratory safety" patented technology

This invention belongs to the field of laboratory safety monitoring technology, and particularly relates to a method and system for real-time intervention of experimental operation violations based on multimodal behavior recognition. It includes collecting multimodal operation data during the experiment; constructing a database of standard operating procedures (SOPs); identifying the currently executed action; comparing the currently executed action with data in the SOP database in multiple dimensions; calculating a deviation score based on the comparison results; and, combined with preset hazard coefficients, environmental coefficients, and personnel coefficients, using a fuzzy logic algorithm to determine the risk level of the experimental violation, thus achieving real-time intervention for experimental operation violations. This invention is based on the deployment and data acquisition of a multimodal sensor network, performing multidimensional modeling of standard operating procedures, and then using a real-time behavior recognition algorithm for multidimensional comparison and violation determination, thereby initiating corresponding intervention measures to promptly eliminate safety hazards, resulting in significant social and economic benefits.

The application discloses a laboratory safety authentication method and device based on a Lims system, relates to the technical field of safety authentication, and solves the technical problem that the safety authentication system in the prior art is difficult to adapt to the safety authentication of specific conditions of relevant personnel, thereby reducing the efficiency of safety authentication. The method comprises the following steps: obtaining reservation information of a laboratory, generating a reference threshold value based on reservation item information in the reservation information; obtaining verification information corresponding to a pilot verification item and a plurality of verification items of the laboratory; generating a pilot verification result based on the verification information corresponding to the pilot verification item and an influence coefficient corresponding to each verification item; generating an item matching degree based on the verification information corresponding to each verification item; and generating a final authentication result based on the item matching degree, the influence coefficient and an item reference threshold value of each verification item. The accuracy of safety authentication is improved, and the efficiency of safety authentication is improved.

Multi-Function Laboratory Safety Cabinet

This utility model discloses a safety pig cage for laboratory use, comprising: a base frame with several support plates spaced apart on it; a pedal structure including several mesh panels, each mesh panel having several protruding teeth spaced apart on its side, the protruding teeth on opposite sides of adjacent mesh panels being staggered and interlocking, and support plates inserted into slots at the bottom of the protruding teeth; a fence positioned around the base frame, with entrance and exit gates on it; a feed trough assembled on the fence; and a fixed partition positioned inside the fence, dividing the space formed by the fence into several parts. This utility model can solve the problems of insufficient assembly strength and inter-plate correlation in existing pig cages, which easily lead to the plates warping under localized pressure, thus affecting the safety and service life of the pig cage.

The utility model relates to laboratory safety equipment technical field especially, more particularly to a kind of intelligent laboratory ventilation control device, including experiment cabinet and first telescopic pipe etc., controller is installed in experiment cabinet side edge, the front side of experiment cabinet is slidably connected with baffle, exhaust gas concentration detector is installed in the bottom of moving plate, exhaust fan is installed in moving plate, exhaust pipe is connected in the top of experiment cabinet, connecting pipe is connected in the top of exhaust pipe, connecting pipe is communicated with external exhaust gas treatment equipment, first telescopic pipe lower end is sealingly connected with the outer ring of the top of exhaust fan, first telescopic pipe upper end is sealingly connected with the inner ring of exhaust pipe, the front end of moving plate is provided with the isolation component for isolating exhaust gas. Through the real-time linkage of exhaust fan and exhaust gas concentration detector, according to gas concentration adjustment exhaust fan speed, while electric slide rail drives moving plate to move down and reduce exhaust gas capture distance, so that exhaust volume is always matched with exhaust gas production, reach the purpose of self-regulating air volume, while reducing invalid exhaust energy consumption.

The present application relates to the technical field of monitoring and early warning, in particular to a laboratory safety state monitoring and early warning system, which comprises a periodic acquisition module, a concentration comparison module, a rate judgment module, a grade mapping module and an early warning pushing module.In the present application, the change of gas concentration is recorded periodically and a time series index is established, so that the concentration amplitude information can be obtained while maintaining data continuity.Combined with the comparison and marking method of concentration fluctuation, the abnormal state can be dynamically identified without relying on fixed threshold triggering.The superimposed judgment of continuous amplitude trend and diffusion rate reference enables potential risks to be discovered early and the corresponding gas and time period to be determined.Further, through risk grade interval mapping, the present application realizes accurate matching with the alarm channel, so that the early warning pushing is hierarchical and targeted, thereby improving the sensitivity and timeliness of risk identification, reducing false positives and false negatives, and achieving active identification and efficient disposal of potential dangers in the laboratory environment.

The application relates to the technical field of laboratory data management, and discloses a laboratory shared instrument data management system based on an Internet of Things, which comprises a personnel management module, an instrument management module, a consumable management module and a storage module; the personnel management module is used for user registration and login, binds user information, identity information, user data and balance information to the user account, and carries out in-room examination and in-room approval on the user; the instrument management module is used for adding new instruments into an instrument library; the standardized management of users is realized through the personnel management module; the in-room examination and in-room approval ensure that the users have corresponding operation ability and safety awareness, and effectively reduce the occurrence probability of laboratory safety accidents; the instrument management module realizes the whole life cycle management of the instruments, including instrument information recording, state management, training examination and use management, and ensures the standardized use and effective maintenance of the instruments.

This invention relates to the field of laboratory safety risk assessment technology, and discloses a method and system for assessing the safety of physical and chemical laboratories. The system includes a basic information filing module, a compliance documentation and on-site verification module, a multi-dimensional risk quantification and grading assessment module, an assessment report generation and grading handling module, a non-compliance rectification closed-loop verification module, and a periodic review and assessment system iteration module. The system comprises the following steps: S1, basic information filing and assessment system construction stage; S2, documentation review and on-site verification stage; S3, risk quantification calculation and grading assessment stage; S4, assessment report output and grading handling stage; S5, rectification tracking and closed-loop verification stage; S6, periodic review and system iteration stage. This invention establishes a closed-loop management architecture covering the entire process of physical and chemical laboratory safety assessment, and establishes a standardized and quantifiable safety assessment system.

This invention provides an intelligent inspection system and method for chemical laboratories based on digital twins, belonging to the field of industrial Internet of Things and intelligent safety management technology. The system includes a physical sensing layer, a digital twin engine layer, an intelligent processing layer, and an application interaction layer. The physical sensing layer collects real-time data of the laboratory environment and equipment through a sensor network; the digital twin engine layer constructs a three-dimensional virtual model corresponding to the physical laboratory and displays the data overlay; the intelligent processing layer dynamically plans inspection paths and generates alarms based on real-time and historical data through anomaly pattern recognition and reinforcement learning; the application interaction layer provides a visual inspection interface and safety emergency handling functions. The method includes data acquisition, 3D driving, intelligent analysis, and visualization steps. This invention achieves global perception of laboratory safety status, intelligent risk early warning, and automation of the inspection process, improving the real-time performance, accuracy, and intelligence level of chemical laboratory safety management.

The utility model discloses a laboratory air environment monitoring devices, including gas detection device and elastic band, and the gas detection device realizes detachable connection through quick -detach connector. The connector includes fixed shell, backplate and elastic clamping component, one side fixed mounting of elastic band has fixed shell, and the fixed shell is provided with the slot, one side fixed mounting of gas detection device is backplate, and the other side of backplate is equipped with the stick body of extension, and the terminal of stick body is equipped with the clamping block. The laboratory air environment monitoring devices provided by the utility model wear convenient, can realize mobile air monitoring, effectively covers the monitoring blind area of traditional fixed detector, and real -time early warning toxic and harmful gas. Detection device integrated GPS / WIFI positioning module, through wireless transmission, personnel position data is uploaded to the management terminal in real time, is convenient for track tracking, area use analysis and emergency positioning, and the safety management efficiency of laboratory is improved obviously.

This application relates to a method for tracing the source of abnormal events in biological laboratories based on unified spatiotemporal data, aiming to improve laboratory safety and avoid potential biohazard risks. The method includes: deploying multiple aerosol monitoring points and location monitoring devices within the laboratory to acquire aerosol concentration and staff behavior trajectory data; constructing a health status model based on aerosol concentration data under normal operating conditions, and comparing it in real time to determine whether there is a leakage risk; if a leakage risk exists, determining the key area and propagation path of the aerosol leak using monitoring data, and identifying staff whose time and area of ​​contact with the leak overlap spatiotemporally. Through multi-point monitoring and deep fusion of spatiotemporal data, this method can accurately, efficiently, and in real time trace leakage events, especially in high-level biosafety laboratories, effectively improving safety protection capabilities.

The application discloses a laboratory internal risk prediction trolley and a risk prediction method thereof, and the trolley comprises a moving chassis, a sensing module, a computing module, a communication module, an execution module and a power module. By adopting a multi-sensor array and an autonomous moving chassis, the application realizes full-time, full-area and dead-angle-free data acquisition in a laboratory. By a weighting fusion algorithm and an LSTM-CNN fusion risk prediction model built in the computing module, multi-dimensional data such as environment, equipment, personnel and dangerous goods are comprehensively analyzed and judged, and a leap from post-alarm to pre-prediction is realized. By an execution module integrated with an audible-light alarm, a small mechanical arm and a micro-spraying unit, and by linkage with an existing safety system of the laboratory, the risk response time is significantly shortened. By a data storage and model iteration mechanism, the system can adapt to the individualized needs of different laboratories, continuously improve the prediction accuracy and provide reliable and intelligent decision support for laboratory safety management.

The application relates to a laboratory safety monitoring alarm method, device and equipment. The method comprises the following steps: acquiring environment monitoring data corresponding to a laboratory, equipment monitoring data corresponding to each device in the laboratory and personnel density data corresponding to each grid in the laboratory; performing secondary disaster probability calculation processing according to the environment monitoring data and the equipment monitoring data, to obtain a secondary disaster occurrence probability corresponding to the laboratory; for each grid, performing fusion analysis processing according to the environment monitoring data, the equipment monitoring data and the personnel density data corresponding to the grid, to obtain grid risk level data corresponding to the grid; and generating an alarm instruction in the case that the grid risk level data and the secondary disaster occurrence probability meet an alarm condition. The method can improve the accuracy of laboratory safety monitoring alarm.

The application relates to a laboratory safety control method and device, computer equipment and a readable storage medium. The method comprises the following steps: determining a comprehensive risk index of a laboratory according to sensor data of the laboratory at a current time; determining an abnormality degree value of the laboratory between a historical time and the current time based on the comprehensive risk index and configuration parameters of each sensor, wherein the historical time is earlier than a previous time of the current time; determining a safety warning threshold of the laboratory at the current time based on the abnormality degree value and a data change amount of each sensor, wherein the data change amount is a change amount between the sensor data at the current time and the sensor data at the previous time; and controlling the safety of the laboratory based on the comprehensive risk index and the safety warning threshold. The method can improve the response sensitivity to the safety hidden danger of the laboratory.

The application discloses a laboratory behavior monitoring and early warning method based on computer vision and related equipment. The application comprises: collecting experimental scene image data and reagent use related monitoring data associated with a target object; performing visual detection on the experimental scene image data and the reagent use related monitoring data to determine experimental behavior information and reagent use whole-process tracking information; based on a preset judgment rule, performing fusion analysis on the experimental behavior information and the reagent use whole-process tracking information to identify a laboratory irregular behavior type of the target object; and according to the laboratory irregular behavior type, starting a corresponding target early warning strategy. The application can realize efficient and comprehensive monitoring of a laboratory, accurately identify various irregular behaviors and timely give early warnings, effectively reduce safety hazards, solve the problems of low efficiency of laboratory monitoring and insufficient safety guarantee, improve the laboratory safety management level, and can be widely applied to the technical field of laboratory safety management.

This utility model discloses a laboratory safety monitoring device, including an electric base. A vertical rod is fixedly installed on the top of the electric base. A vertical groove is formed inside the vertical rod, and a threaded rod is rotatably installed inside the vertical groove. A threaded sleeve is threaded onto the surface of the threaded rod. Vertical plates are fixedly installed on both sides of the threaded sleeve. A lifting plate is fixedly installed on the top of the vertical plates. A lifting motor is fixedly installed on the top of the vertical rod. The output end of the lifting motor passes through the vertical rod and is fixedly connected to the top of the threaded rod. A vertical tube is fixedly installed around the top of the electric base. Vertical poles are movably installed inside the vertical tube, and the tops of the vertical poles are fixedly connected to the bottom of the lifting plate. In this laboratory safety monitoring device, when the operator starts the lifting motor, the operation of the lifting motor causes the threaded rod to rotate, which in turn causes the threaded sleeve to slide inside the vertical groove.

This invention provides a laboratory intelligent safety monitoring method based on AI machine vision recognition algorithms. The method includes the following sub-steps: S1: Real-time acquisition and preprocessing of laboratory video streams; S2: Recognition of preprocessed laboratory images; S3: Integration of recognition results to determine the laboratory safety hazard level; S4: Triggering a safety warning based on the laboratory safety hazard level. The method achieves automated monitoring by acquiring video streams in real-time via cameras, preprocessing them, and using models to identify personnel, behaviors, and environmental anomalies. It triggers tiered real-time warnings based on hazard levels, eliminating reliance on manual intervention, avoiding missed reports due to fatigue, and ensuring real-time performance. Through comprehensive monitoring including personnel protection standards and hazardous material identification, dynamic violation identification, and complex environmental anomaly identification, it fills the functional gaps of traditional sensors. Adaptive weighted fusion of multi-model confidence levels to determine hazard levels improves recognition accuracy and meets the actual safety management needs of laboratories.

The application relates to a curtain wall laboratory safety behavior monitoring method, system, device and medium, relates to the technical field of curtain wall monitoring and safety warning, and the method comprises the following steps: based on a work plan, the camera coverage range in the personnel work time is predicted, and the corresponding geographical position is configured as a predicted position associated with a work time sequence; a plurality of cameras appearing in the personnel work time are configured as a work camera group; the analysis strategy of the work camera group is pre-configured, including loading a monitoring task model before the corresponding personnel appear; based on the actual appearance of the personnel, the monitoring task of the work camera group is activated, and the personnel behavior is analyzed; based on the work time sequence, the actual appearance position of the personnel is compared with the predicted position, if the deviation exceeds a preset threshold, the analysis strategy of the work camera group is adjusted. The application can improve monitoring continuity, optimize resource allocation, and enhance multi-target personnel tracking accuracy.

This invention provides a laboratory safety self-control method and system for fault self-diagnosis. The method includes: S1 periodically and actively generating health labels through self-checks; S2 dividing the time slice of a single processor into execution time slots and self-test time slots, calculating the CRC signature of key data in the execution time slot, executing test vectors and comparing them with historical signatures in the self-test time slot, and locking the output to a safe state via independent hardwired connection in case of a fault; S3 based on incremental causal graph and online parameter learning, collecting samples using fault labels, updating the conditional probability table through online EM, automatically expanding the causal graph structure through normalized mutual information, and outputting the fault type and confidence level using confidence propagation; S4 actuator closed-loop feedback and hardwired bypass protection; S5 dynamic reconstruction degradation fault tolerance; S6 emergency shutdown and solidification. This invention achieves high-coverage fault detection with a single processor, eliminates blind spots of common faults, and simultaneously achieves small-sample adaptive and accurate fault reasoning, significantly improving system reliability and intelligence.

The application discloses a laboratory safety early warning method and system based on multi-source perception and edge computing, and relates to the technical field of laboratory safety.The application changes the traditional mode of single sensor threshold alarm by correlating and intelligently comparing environmental perception data (such as harmful gas concentration) with edge video analysis results (such as personnel presence state) in real time.The system triggers a high-level alarm only when multiple source evidence chains jointly indicate a risk (for example, "gas concentration exceeds the standard" and "there are signs of personnel being trapped on site"), thereby effectively filtering false positives caused by sensor accidental failure or non-dangerous experiment activities, realizing fusion and cross-validation of multi-modal data, and significantly reducing the false positive rate.

The invention discloses an experiment place safety supervision method and device, electronic equipment and a storage medium. The method comprises the following steps: verifying a first object according to first information to obtain a first result; determining first data according to the first result; verifying the first data to obtain a second result; and performing safety early warning according to the second result. According to the method, the first object is verified, whether the first object has an experiment permission or not is determined according to a verification result, safety monitoring is performed on the whole experiment process, and safety early warning is performed when a safety problem is monitored. Safety rules and regulations of an experiment can be converted into an executable, monitorable and traceable safety management process, and the intelligent level and risk prevention and control capability of laboratory safety management are remarkably improved.

This invention relates to the field of task allocation and execution technology, specifically disclosing a method and system for the dynamic allocation and execution of laboratory safety inspection tasks, including the following steps: Step S1: By analyzing historical data, the usage patterns of each inspection area and the operational experience of laboratory personnel are quantified into feature vectors, and the matching value between the two is calculated to assess the professional suitability; Step S2: Based on historical inspection time data, the standardized load value of each area is calculated; Step S3: A bi-objective optimization model is constructed to simultaneously minimize the variance of the task load of all personnel and maximize the total matching value of task allocation, and by solving the model, the optimal inspection personnel are dynamically allocated to each inspection area.

The application relates to the field of X-ray three-dimensional imaging technology, in particular to a low-vibration high-stability submicron CT frozen three-dimensional imaging device. The application comprises an in-situ device base, a Dewar flask, a support disc, a hollow red copper pipe, a red copper bundle, a sample clamp hollow column, an adjustable sample clamp, a high-transparency imaging area module, a heat preservation movable cover and a temperature monitoring system. The Dewar flask is arranged on the in-situ device base and is used for storing liquid nitrogen. The support disc is fixed in the Dewar flask through screw threads, the support disc is provided with a support through hole, and the hollow red copper pipe is fixed in the support disc through a loose screw. The three-dimensional imaging device can significantly improve the imaging stability. The built-in Dewar flask and the double-path cooling design can eliminate external vibration, provide a stable environment for long-time and high-resolution scanning, and simplify the device. The laboratory safety and experimental efficiency are improved.