18 results about "Chemical risk" patented technology

The embodiment of the invention discloses a chemical early warning interception method and device, electronic equipment and a medium. A specific embodiment of the method comprises the following steps: carrying out identity recognition on a target chemical detection terminal set to obtain a detection terminal identity recognition information set; performing state information extraction on the multi-modal target chemical information set to obtain a chemical multi-modal state information set; performing data deduplication on the multi-modal state information set of the chemicals and then performing association identification to obtain a multi-modal association information set; performing chemical risk identification on the de-duplicated multi-modal chemical information set to obtain a to-be-tracked chemical information set; and performing trajectory tracking early warning on the to-be-tracked chemical article information set to obtain a chemical article trajectory early warning information set, and performing early warning interception on the to-be-tracked chemical article information set. According to the embodiment, a data barrier can be broken, data sharing and safety are improved, and the accuracy of accurate interception and risk early warning of target chemicals is improved.

The invention belongs to but is not limited to the technical field of natural language processing and risk management, and discloses a PPO-RAG-based chemical risk field management and control measure generation method and system, and the method comprises the step of providing a PPO-RAG-based management and control measure generation method. In order to solve the problem that LLM has knowledge hysteresis and insufficient user preference adaptability in a management and control measure generation task, a PPO-RAG framework is established by adopting a mode of combining RAG and reinforcement learning based on human feedback. The framework aims to improve the timeliness and speciality of LLM generation management and control measures, so that the LLM generation management and control measures can better meet diversified requirements in actual application scenes. A final experiment result shows that the method effectively improves the comprehensive capability of LLM generation management and control measures. According to the embodiment of the invention, high-quality management and control measure recommendation service can be provided for the user aiming at the characteristics of high professional property and high complexity of the management and control measures in the risk field.

A dangerous chemical risk dynamic management and control system comprises a dynamic detection subsystem, an information management subsystem and a risk prediction subsystem. The dynamic detection subsystem comprises a dangerous chemical detection mechanism and an environment detection mechanism, the dangerous chemical detection mechanism is used for detecting the use dynamic state of dangerous chemicals to obtain state information, and the environment detection mechanism is used for detecting the use environment of the dangerous chemicals to obtain environment information; the information management subsystem is used for collecting and managing process information generated in the use process of the dangerous chemicals; the risk prediction subsystem is used for generating a risk prediction warning based on the state information and the environment information, generating a management and control strategy based on the risk prediction warning, and generating a management and control record based on the risk prediction warning and the process information. According to the dangerous chemical risk dynamic management and control system and method provided by the invention, whether a risk accident possibly occurs can be predicted based on dynamic information and environmental information generated in a dangerous chemical use process, and personnel and property safety is ensured.

The invention relates to a chemical risk management method integrating leakage simulation analysis and property evaluation of a vinyl chloride gas holder, and aims to accurately predict and quantify the safety risk and potential economic loss after leakage of the vinyl chloride gas holder by using an advanced simulation technology and an economic evaluation means. According to the method, [Areal Location of Hazard] ALOHA simulation software approved by the industry is adopted, the gas diffusion process after vinyl chloride leakage is simulated in a high-precision mode, and in combination with a [Quantum Geographic Information System] QGIS (Quality Geographic Information System), visual display of data is carried out. On the basis, through comprehensive consideration of key factors such as physical and chemical characteristics, process environment parameters and leakage scale of vinyl chloride, hazard indexes of fire and explosion are scientifically calculated, and then possible economic losses are deduced. By constructing a set of comprehensive and quantitative risk assessment system, powerful support is provided for safety assessment of chemical equipment, and an important basis is provided for a management layer of a chemical enterprise to formulate scientific and effective safety strategies and risk control measures.

The invention belongs to the technical field of natural language processing and risk management, and discloses a GRPO-RAG-based chemical risk field management and control measure generation method and system, and the method comprises the step of providing a GRPO-RAG-based management and control measure generation method. In order to solve the problem that LLM has knowledge hysteresis and insufficient user preference adaptability in a management and control measure generation task, a GRPO-RAG framework is established by adopting a mode of combining RAG and reinforcement learning based on human feedback. The framework aims to improve the timeliness and speciality of LLM generation management and control measures, so that the LLM generation management and control measures can better meet diversified requirements in actual application scenes. A final experiment result shows that the method effectively improves the comprehensive capability of LLM generation management and control measures. According to the embodiment of the invention, high-quality management and control measure recommendation service can be provided for the user aiming at the characteristics of high professional property and high complexity of the management and control measures in the risk field.

The embodiment of the invention provides a dangerous chemical database design method and system, and belongs to the technical field of data processing. The system comprises a system management module, a database management module, a hazardous chemical data module, a scene adaptation module and a dynamic analysis and evaluation module. The system management module comprises a user management sub-module and a role management sub-module; the database management module comprises a hazardous chemical substance data management sub-module and a report data management sub-module; the hazardous chemical substance data management sub-module is used for newly adding, editing and deleting hazardous chemical substance data; the report data management sub-module is used for newly adding, editing and deleting report data; the hazardous chemical data module is used for storing data information of chemicals; the scene adaptation module is used for adapting to different management scenes; the dynamic analysis and evaluation module is used for generating a management scheme. According to the invention, customer groups can be analyzed according to basic data, customer resources can be developed in a targeted manner, and statistical data of chemical risk assessment can be summarized and processed.

The invention relates to a hazardous chemical substance dynamic risk assessment and disposal method and system, and belongs to the field of hazardous chemical substance risk assessment. The method comprises the following steps: acquiring original data to obtain structured data; performing risk density assessment based on the structured data; source sink statistics is carried out based on the structured data, and a risk source item and a risk sink item of each grid are obtained; a risk discretization continuity equation is constructed and solved, and a risk density update value is obtained; updating the risk flow rate based on the risk density value to obtain a risk flow rate update value; based on the risk density update value and the risk flow rate update value, obtaining a risk assessment key index and outputting a risk assessment report; and generating an optimal disposal strategy based on the risk assessment report. The intelligent assessment and disposal method integrates multi-source real-time data, realizes risk field space quantification, can dynamically simulate and predict the evolution of the risk field, and has important practical significance for improving qualitative change of hazardous chemical substance safety management from passive response to active prevention and control.

The invention provides a multi-angle persistent chemical screening method based on a multi-task graph neural network, and belongs to the technical field of high-throughput screening for chemical risk management. The method aims at achieving synchronous, efficient and accurate screening of the related attributes of the durability of the chemicals. The method comprises the following steps: firstly, constructing a multi-angle chemical durability parameter data set; the method comprises the following steps: taking a molecular graph generated by a chemical structure as model input, constructing a model through a graph neural network, and finishing synchronous training by adopting a mean square error and a superposition loss function with positive sample weight cross entropy; evaluating the performance of the model through indexes such as a determination coefficient and an area under a subject working curve; and characterizing a model application domain by adopting structure-activity relationship morphology analysis. The model constructed by the research relates to more persistent parameters, is more comprehensive, larger in data volume and wider in coverage range, has good fitting ability, prediction ability, robustness and reliability, and can provide technical support for environmental risk assessment of persistent chemicals.

The invention provides a gridding dangerous chemical knowledge base establishment method, medium and system, and belongs to the technical field of knowledge base establishment methods, and the method comprises the steps: firstly collecting data, and screening high-quality data through an acceptance degree index; then constructing an accuracy evaluation model to automatically mark various types of knowledge and forming a knowledge correlation degree matrix to quantify correlation strength; establishing a gridding knowledge mapping structure, dividing knowledge grid units, calculating gridding centrality and determining knowledge point weights; automatically constructing a minimum spanning tree to process knowledge conflicts, and processing defect knowledge by applying a matrix completion algorithm; a chemical risk association network is constructed, and dangerous chemical grid indexes are calculated to quantify danger levels; then designing a knowledge reasoning mechanism and processing super-long knowledge by adopting a grid knowledge compression function; and finally, implementing an adaptive optimization algorithm to dynamically adjust the grid structure, and forming a grid dangerous chemical knowledge base which reduces manual dependence and enhances relevance expression.

The invention provides a chemical risk prediction model based on interpretable machine learning and a construction method thereof, and the method comprises the steps: S1, obtaining chemical data with risk endpoints, S2, generating a high-dimensional feature set containing physicochemical properties and structural topology for a molecular structure through employing a molecular descriptor and a fingerprint calculation platform; s3, performing comparison modeling on each risk endpoint by independently adopting different types of machine learning models, re-training an optimal model on a training set, and reporting a final result in an independent prediction set; s4, the model application range of the optimal model is determined, and an application domain framework of the model is constructed based on conformal prediction, and S5, the importance of global and sample-level key descriptors is output; and finally, batch reasoning and result exporting: outputting a prediction label, a prediction probability, an application domain framework mark, a significance level and an explanatory result one by one for a chemical list corresponding to the target chemical data.

The present application provides a kind of based on multi-sensor monitoring's dangerous chemical goods shelf anti-collapse regulation method, system and medium, belong to the field of stacking safety monitoring.The method comprises: obtaining first point cloud and second point cloud and carrying out weighted registration, obtains fusion point cloud;Determine the inclination rate of change based on fusion point cloud;According to the inclination rate of change and the material characteristics of dangerous chemical, estimate the risk occurrence time and risk occurrence position of dangerous chemical risk;And in response to risk occurrence time less than time threshold, determine the main swing characteristics of liquid in dangerous chemical stacking according to fusion point cloud;Based on main swing characteristics, generate time-varying driving signal;Based on time-varying driving signal, drive actuator to apply pulse force with the frequency, phase and amplitude indicated by time-varying driving signal to the shelf.The present application can improve the efficiency and accuracy of stacking monitoring, while the effectiveness and safety of emergency disposal are enhanced for emergency risk, and intelligent grading active regulation is realized.

The invention discloses a dangerous chemical industry risk assessment method and system, belongs to the technical field of data processing, and aims to solve the technical problem of how to improve the accuracy and efficiency of dangerous chemical risk assessment. Comprising the following steps that an evaluation index system is constructed, specifically, according to the definition of risks, multi-dimensional evaluation indexes are selected to design and construct an industry safety production comprehensive risk evaluation system, and the evaluation system follows the SMART principle; risk grading model construction: constructing a risk grading model, wherein the risk grading model is used for evaluating the real score of the index and calculating the risk value of the industry; and risk grading evaluation: sorting the industries according to the risk values of the industries based on a predefined risk grading rule.

This invention discloses a method for assessing the risk of heavy metal contamination in soil of newly constructed reservoir areas through multi-scenario coupling simulation. The method includes the following steps: selecting soil samples with the highest content of the target heavy metal in the reservoir area for Al content detection and heavy metal speciation analysis; collecting background control samples from areas far from the reservoir area for heavy metal and Al content detection and heavy metal speciation analysis; calculating enrichment factors and geoaccumulation indices to determine pollution sources at sampling points; preparing average and extreme samples; preparing simulated reservoir water; and conducting static leaching experiments, dynamic disturbance experiments, and vertical leaching experiments, covering chemical risks during quiescent periods, physical risks during disturbance periods, and long-term infiltration geological risks. This invention not only couples multiple scenarios and simulates the most unfavorable conditions to accurately identify the maximum instantaneous risk of heavy metal release, but also quantifies and determines pollution sources, possessing source tracing capabilities.

The invention discloses an early warning method and system for dangerous chemical substance risk operation behaviors, and relates to the field of dangerous chemical substance risk control. The method is applied to a risk early warning system, and the method comprises the following steps: obtaining various risk index data of hazardous chemicals in a production management process, the various risk index data including video data, sensor monitoring data and an operation log; performing semantic recognition on the multiple risk index data to obtain multiple risk operation events; calculating a risk equivalent value corresponding to each of the plurality of risk operation events and a risk increment value cooperatively caused by the plurality of risk operation events; determining a comprehensive risk value according to the risk equivalent values and the risk increment values corresponding to the plurality of risk operation events; and when the comprehensive risk value is greater than or equal to a risk threshold value, triggering risk early warning. By implementing the technical scheme provided by the invention, the problem that a traditional early warning mode cannot effectively quantify the cumulative effect and the synergistic effect of risk operation is solved.

The invention belongs to the technical field of high-throughput screening for chemical risk management, and discloses a method for screening chemicals with 90-day equivalent toxicity based on a stacked integrated model. Calculating molecular characteristics according to simplified molecular linear input specifications of chemicals, and preprocessing and screening the molecular characteristics; according to the model, a support vector machine, extreme gradient lifting and a multi-layer perceptron serve as base classifiers, logistic regression serves as a meta learning device, fusion of multi-model prediction results is achieved through a stacking integration strategy, and the stability and generalization performance of the model are improved. The performance of the model is evaluated through the accuracy rate and the area under the subject working characteristic curve, and the application domain of the model is represented by structure-activity relation morphology analysis according to the QSAR evaluation framework of the economic cooperation and development organization, so that the model is ensured to have reliability and interpretability in screening of chemicals in the application domain. According to the method, the chemicals with 90-day toxicity in the application domain are effectively screened, and a tool is provided for sound management of the chemicals.

The invention belongs to the field of chemical risk assessment and safety management, and particularly relates to a chemical compatibility testing device and method. The device comprises a track part, a capsule testing bin and a controller. The rail part comprises a first rail assembly and a second rail assembly. The capsule testing bin is constructed to contain at least two chemicals in a separated mode, and the two ends of the capsule testing bin are erected on the first track assembly and the second track assembly respectively. And the controller is configured to control the capsule test bin to reciprocate on the track part. In the reciprocating motion process, chemicals in the capsule testing bin can be mixed, and heat absorption and release and / or air pressure change conditions in the mixing process can be monitored and measured, so that the compatibility between the chemicals can be judged. The device can be used for measuring the compatibility of multiphase chemicals including solid chemicals, and has a good application prospect.

The invention discloses a method for detecting early neurodevelopment toxicity of pollutants based on a neural crest specific molecular marker and application, and belongs to the technical field of environmental toxicology and molecular diagnosis. The method comprises the following steps: 1) exposing an early embryo to a to-be-detected sample or pollutant; 2) detecting the change of the specific molecular marker of the neural crest and the peripheral neuron; and 3) evaluating the early neurodevelopmental toxicity according to the marker expression difference. According to the method, the problems of early warning lag and low sensitivity of the traditional neural behavior endpoint (zebra fish 6dpf) are solved, the early neurotoxicity of low-concentration pollutants can be detected within 24 hours of pollutant exposure (zebra fish sox10 and prph), and the method can be used for early toxicity early warning and risk assessment in environmental monitoring and chemical risk assessment.

This invention provides a method, medium, and system for establishing a gridded hazardous chemicals knowledge base, belonging to the technical field of knowledge base establishment methods. First, data is collected and high-quality data is filtered through a recognition index. Then, an accuracy evaluation model is constructed to automatically label various types of knowledge and form a knowledge association matrix to quantify the association strength. Next, a gridded knowledge mapping structure is established, knowledge grid units are divided, and grid centrality is calculated to determine the weight of knowledge points. Subsequently, a minimum spanning tree is automatically constructed to handle knowledge conflicts, and a matrix completion algorithm is applied to handle defective knowledge. Then, a chemical risk association network is constructed, and a hazardous chemicals grid index is calculated to quantify the hazard level. Next, a knowledge reasoning mechanism is designed, and a grid knowledge compression function is used to handle excessively long knowledge. Finally, an adaptive optimization algorithm is implemented to dynamically adjust the grid structure, forming a gridded hazardous chemicals knowledge base that reduces manual dependence and enhances the expression of associations.