13 results about "Occupational hygiene" patented technology

The invention relates to the technical field of occupational health safety monitoring and artificial intelligence data processing, in particular to an occupational health comprehensive risk management evaluation system based on reinforcement learning, which comprises a multi-source data acquisition step: acquiring multi-source heterogeneous monitoring data of a target operation scene; an ideal benchmark construction and simulation step: constructing an ideal benchmark model based on a standard operation program, and generating a virtual risk simulation data vector by using a reinforcement learning agent; a double-track difference calculation step: respectively calculating a real residual feature vector and a theoretical residual feature vector based on the ideal reference model; a similarity analysis and optimization step: performing feature space similarity analysis on the two to generate a risk assessment result and a strategy update reward signal; the problem that cumulative occupational hazards and transient environment fluctuation are difficult to distinguish is solved, and generalization ability and risk identification precision in a complex industrial environment are improved.

The invention provides a method for simultaneously detecting dichloroacetic acid and trichloroacetic acid in urine, and belongs to the technical field of analysis detection and occupational health / environmental health. According to the method disclosed by the invention, a synergistic pretreatment strategy of acidic sample loading, WAX / reversed-phase mixed mode solid-phase extraction, water / low-proportion organic phase step-by-step leaching and ammonia-water-containing organic phase elution is adopted; a technical route of protein precipitation, acidification pH regulation, purification and enrichment by adopting WAX / reversed-phase mixed mode solid-phase extraction on a 96-well plate and stable isotope internal standard isotope dilution LC-MS / MS quantification is adopted, the method can effectively reduce the matrix effect and realize high-throughput analysis in a high-salinity urine matrix, the quantitation limits of DCEA and TCAA are not higher than 0.30 g / L and 0.20 g / L respectively, and the method has the advantages that the method is simple and convenient to operate, and the method is suitable for large-scale popularization and application. The method is suitable for biological monitoring and risk assessment of occupational and environmental low-level exposure crowds.

The utility model relates to a silencer device for pumping pump, including the silencer cylinder, the silencer cylinder bottom side is equipped with the air inlet, the silencer cylinder bottom is equipped with the gas outlet, the silencer cylinder inside is equipped with the several layers of baffle that divide the silencer cylinder inside space into multilayer chamber in height direction, the baffle one side region is provided with a plurality of through -holes, and the through -hole area position of upper and lower two layers of baffle is staggered. The utility model relates to a silencer device for pumping pump novel structure, reasonable in design, the baffle of inside staggered setting is used, and the noise is weakened, offset in the chamber while the gas is rapidly discharged, and the sound attenuation effect is good, improves the working environment, improves environmental comfort, is helpful to the physical and mental health of staff, reduces the occupational health risk, also reduces the security, quality risk caused by inconvenient communication simultaneously.

The invention provides a health monitoring method. The method comprises the following steps: acquiring original occupational health monitoring data in an Excel format from multiple channels; analyzing the original occupational health monitoring data in the Excel format, and identifying a fixed column and a dynamic column in the original occupational health monitoring data; storing the fixed column into a main table database, and storing the dynamic column into a sub-table database; and in response to a user request, integrating data in the main table database and the sub-table database to generate a visual report. According to the method, the original occupational health monitoring data in the Excel format is obtained from multiple channels and analyzed, the fixed column and the dynamic column are stored in the main table database and the sub-table database respectively, finally, the data are integrated according to the user request to generate the visual report, and efficient processing and storage of the health monitoring data are achieved. According to the mode, the tedious process that an Excel table is manually input and special statistical software is imported for analysis traditionally is avoided, and the operation efficiency is greatly improved.

The invention discloses an occupational health detection method and system for mine workers, and particularly relates to the technical field of occupational health detection. According to the method, environmental hazard factor continuous monitoring data and physiological index continuous monitoring data of corresponding operation time periods of mine workers are collected, an environmental hazard factor sudden increase interval and a physiological index abnormal fluctuation interval are divided, a time sequence overlapping relation is extracted, and exposure response correlation fragments are constructed; calculating an environmental hazard factor change slope and a physiological index recovery time difference, constructing an individual load coupling unit, distinguishing an instant load state and a cumulative load state, and generating an individual dynamic risk table set; identifying a risk upgrading condition based on a preset occupational health judgment rule and generating an individual risk early warning result; backtracking the individual exposure response sequence, updating the key monitoring section of the subsequent detection period, and forming an occupational health detection result; according to the invention, individual and dynamic occupational health risk assessment and early warning of mine workers are realized.

The utility model discloses a gas chromatograph for acid gas analysis. The gas chromatograph comprises a sample introduction system, a separation system and a thermal conductivity detector, the sample introduction system and the thermal conductivity detector are connected to the separation system; the separation system comprises a first separation system and a second separation system which are arranged in parallel; a ten-way valve is arranged in each of the first separation system and the second separation system; the ten-way valve of the first separation system is connected with the ten-way valve of the second separation system through a pipeline, the ten-way valve of one separation system is connected with a sample injection system, and the ten-way valve of the other separation system is connected with an external recovery system; and the first separation system and the second separation system are respectively connected with a thermal conductivity detector. According to the gas chromatograph, the analysis of H2, O2, N2, CH4, CO, CO2, H2S, COS and SO2 in the acid gas can be completed within 10 minutes through one-time sample injection, the situation that the analysis result is inaccurate due to system errors caused by multiple times of sample injection is avoided, the time for an operator to make contact with a sample is shortened, and occupational health safety is effectively provided.

The utility model discloses a device for testing sampling efficiency in occupational health, which comprises an acrylic box, a sample box and a sample box, wherein the acrylic box is used for simulating gas-state, vapor-state and aerosol-state chemical substance environments with different concentrations and is of a closed structure; the air sampling combination comprises an air sampler and an air sampling pipe communicated with the air sampler, and the air sampling pipe partially penetrates into the acrylic box; the at least two air collectors are connected to the air sampling pipe in series, are used for directly sampling gas, are positioned outside the acrylic box, are detachably arranged and are in a detached state during pretreatment. A feasible device is provided for a sampling efficiency test, the structure is simple, raw materials can be easily obtained, quantitative production can be achieved, and machining is convenient; on-site environments with different concentrations can be simulated, volatile target substances are effectively collected, and the collection efficiency is improved; and gas volatilization is carried out in the acrylic box, so that environmental pollution can be reduced.

The invention discloses a continuous closed solid-liquid separation device and method for an abamectin crude product crystallization solution, and belongs to the technical field of biopesticide preparation. The invention relates to a continuous closed solid-liquid separation device and method for an abamectin crude product crystalline liquid, the continuous closed solid-liquid separation device comprises a barrel assembly and an end socket assembly, and further comprises a pressing plate assembly, the pressing plate assembly is installed below the end socket assembly, a plurality of jacking oil cylinders are arranged on the outer side of the barrel assembly, the jacking oil cylinders are arranged to be of a telescopic structure, and the pressing plate assembly is arranged on the outer side of the barrel assembly. One end of the jacking oil cylinder is connected with the end socket assembly through the upper support. In order to solve the problems that a centrifugal machine is poor in separation effect, the dissolution proportion cannot be reduced, the crystallization rate is low, and in short, different types of centrifugal machines have the problems in the aspects of quality, peculiar smell control, safety and the like, a six-in-one filter-pressing pulping non-discharging method is adopted. And the risks of environmental hazards, influence on occupational health of staff and possible poisoning explosion caused by using a centrifugal machine in the prior art are effectively avoided.

The present application relates to the technical field of industrial internet and intelligent occupational health supervision, and particularly relates to an occupational health detection and evaluation data acquisition system based on a cloud platform, comprising: a data acquisition terminal configured to collect real-time detection data of occupational health hazards in a target detection area in real time, and upload the real-time detection data to a cloud processing platform; a data access interface configured to communicate with a production management system of a tested enterprise, and upload operation load data to the cloud processing platform; and the cloud processing platform configured to receive the real-time detection data and the operation load data, and output a compliance determination result of the detection data; wherein the compliance determination result comprises a real compliance state, an abnormal working condition state and a human intervention state; the present application realizes deep audit of logical authenticity of emission data.

The invention relates to the technical field of occupational health, in particular to a big data quantification-driven occupational disease hazard factor evaluation and prevention and treatment system, which comprises a data optimization processing module, a data feature acquisition module, an occupational disease index evaluation module and an occupational disease early warning and prevention and treatment module, outputting the reconstructed phase space matrix and data information corresponding to different time points; the data feature obtaining module obtains feature information and a classification result of occupational health data for the reconstructed phase space matrix and the data information by using a feature learning network model; the occupational disease index evaluation module determines weights of different occupational disease indexes based on the feature information and the classification result, and analyzes a comprehensive hazard index of the occupational disease indexes in combination with a hazard index level evaluation model; and the occupational disease early warning and prevention module sends an occupational disease early warning signal based on the comprehensive hazard index and matches a prevention scheme. The modules work cooperatively to achieve occupational disease evaluation and prevention and control, and the prevention and control efficiency and effect are improved.

The invention belongs to the field of occupational health detection, and provides a trace SF6 gas sampler without a memory effect, which comprises a sample introduction unit, a constant pressure control unit, a six-way valve 5, a quantitative sampling ring 6, a sample introduction analysis system and a flow channel cleaning system, the sampling unit is sequentially connected with the six-way valve 5 and the quantitative sampling ring 6, and the constant pressure control unit is arranged on a pipeline between the sampling unit and the six-way valve 5; and the six-way valve 5 is also respectively connected with a sample introduction analysis system, a flow channel cleaning system, a sample introduction pipeline and a sample discharge pipeline. According to the invention, cross contamination-free and long-term stable sampling of trace gas is realized. Through the design of the process, the flow channel, key equipment and the like, the possibility of cross contamination of sample gas is fundamentally eradicated, and the sampling stability and reliability are ensured by adopting a constant-pressure control system and a flow channel cleaning system, so that a reliable technical guarantee is provided for accurate collection of trace gas.

The application discloses a professional health examination result prediction method based on an expert system and machine learning, and the method is: after adding the number of visits information to the physical examination archive information to form an original data set after cleaning and standardizing, important features are extracted through deep learning to obtain a new data set by recombination; all hazard factor types of each physical examination personnel in the new data set are identified; the corresponding prediction label is obtained through logical judgment of each hazard factor according to the occupational health standard to form a decision set; the decision set is marked with occupational contraindications and suspected occupational diseases respectively, and the corresponding feature SOD and feature OC of the marked results are added to the new data set; the new data set after the expert system link is randomly divided into a training set and a test set, and more than two machine learning models are selected to train the training set to obtain respective prediction results; the prediction results of the more than two models are weighted and averaged through a weighted voting method to obtain the final output result. The application can more effectively identify the occupational health risk.