Structural parameter optimization method and device for chemical oxygen self-rescue respirator

Abstract

The invention discloses a structural parameter optimization method and device for a chemical oxygen self-rescue respirator, and belongs to the field of respiratory protection equipment design, and the method comprises the steps: obtaining basic parameters of the chemical oxygen self-rescue respirator; based on the basic parameters, establishing a parameter optimization model of the chemical oxygen self-rescue respirator; performing parameter optimization analysis according to a parameter optimization model, and adjusting the external structure parameters and the internal working parameters; generating a plurality of optimization schemes based on the parameter optimization analysis result; evaluating the plurality of optimization schemes, and selecting a final optimization scheme meeting a preset performance standard; and adjusting the prototype according to a test result. The technical problems that in the prior art, due to the fact that the external structure and the internal working parameters of a chemical oxygen self-rescue respirator cannot be optimized cooperatively, the performance of the respirator is unstable, use is uncomfortable, and the working efficiency is low are solved.

Description

Technical Field

[0001] The invention relates to the field of respiratory protection equipment design, and in particular to a method and a device for optimizing structural parameters of a chemical oxygen self-rescue respirator. Background Art

[0002] Chemical oxygen self-rescue respirator is an important personal protective equipment used in hazardous environments (such as mines, tunnels, chemical plants, etc.). When there is insufficient oxygen in the environment or toxic gases are present, the chemical oxygen self-rescue respirator generates oxygen through chemical reactions for the user to breathe, ensuring that there is enough oxygen to support safe evacuation in an emergency. With the acceleration of industrialization and the continuous development of high-risk industries such as mining and chemical industry, safety accidents occur frequently, especially the risk of hypoxia or toxic gas leakage is gradually increasing, resulting in higher requirements for the performance of self-rescue equipment. In order to cope with complex and changing working environments, respirators must not only have efficient oxygen generation capabilities, but also reliable durability, comfort and ease of operation.

[0003] The current design of chemical oxygen self-rescue respirators mainly relies on experience and single parameter adjustment, which makes it difficult to achieve global optimization of external structure and internal working parameters, resulting in problems such as excessive weight, discomfort to wear, and low reaction efficiency under actual working conditions. In addition, existing respirators are difficult to ensure stable performance in complex environments, resulting in some devices being unable to provide sufficient oxygen supply in emergency situations, which seriously affects the reliability and use of the equipment. Summary of the invention

[0004] The present application provides a method and device for optimizing the structural parameters of a chemical oxygen self-rescue respirator, aiming to solve the technical problem in the prior art that the external structure and internal working parameters of the chemical oxygen self-rescue respirator cannot be coordinated and optimized, resulting in unstable performance, uncomfortable use and low working efficiency.

[0005] In view of the above problems, the present application provides a method and device for optimizing the structural parameters of a chemical oxygen self-rescue respirator.

[0006] The first aspect disclosed in the present application provides a method for optimizing structural parameters of a chemical oxygen self-rescue respirator, the method comprising: obtaining basic parameters of the chemical oxygen self-rescue respirator, wherein the basic parameters include external structural parameters and internal working parameters; based on the basic parameters, establishing a parameter optimization model of the chemical oxygen self-rescue respirator, including an external structural parameter model and an internal working parameter model; performing parameter optimization analysis according to the parameter optimization model to obtain parameter optimization analysis results, wherein the parameter optimization analysis includes analyzing the performance of the chemical oxygen self-rescue respirator under different working conditions, and adjusting the external structural parameters and the internal working parameters; based on the parameter optimization analysis results, generating multiple optimization schemes, including different external structural parameter combinations and internal working parameter combinations; evaluating the multiple optimization schemes, and selecting a final optimization scheme that meets preset performance standards; according to the final optimization scheme, optimizing a prototype of the chemical oxygen self-rescue respirator and conducting actual performance testing, and adjusting the prototype according to the test results.

[0007] Another aspect disclosed in the present application provides a structural parameter optimization device for a chemical oxygen self-rescue respirator, the device comprising: a basic parameter determination module: used to obtain basic parameters of the chemical oxygen self-rescue respirator, wherein the basic parameters include external structural parameters and internal working parameters; a parameter optimization model establishment module: used to establish a parameter optimization model of the chemical oxygen self-rescue respirator based on the basic parameters, including an external structural parameter model and an internal working parameter model; an optimization analysis result acquisition module: used to perform parameter optimization analysis according to the parameter optimization model to obtain parameter optimization analysis results, wherein the parameter optimization analysis includes analyzing the performance of the chemical oxygen self-rescue respirator under different working conditions and adjusting the external structural parameters and the internal working parameters; an optimization scheme generation module: used to generate multiple optimization schemes based on the parameter optimization analysis results, including different external structural parameter combinations and internal working parameter combinations; an optimization scheme evaluation module: used to evaluate the multiple optimization schemes and select a final optimization scheme that meets the preset performance standards; an optimization adjustment module: used to optimize the prototype of the chemical oxygen self-rescue respirator and perform actual performance testing according to the final optimization scheme, and adjust the prototype according to the test results.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0009] By adopting a technical solution of establishing a parameter optimization model for a chemical oxygen self-rescue respirator based on basic parameters, performing parameter optimization analysis, and generating multiple optimization solutions, the technical problem in the prior art that the external structural parameters and the internal working parameters cannot be optimized synergistically, resulting in unstable performance and uncomfortable use, is solved. The technical effect of improving the stability, comfort and work efficiency of the respirator under different working conditions is achieved, thereby improving the reliability of the respirator.

[0010] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 A flow chart of a method for optimizing structural parameters of a chemical oxygen self-rescue respirator is provided for an embodiment of the present application.

[0012] Figure 2 A structural schematic diagram of a structural parameter optimization device for a chemical oxygen self-rescue respirator is provided for an embodiment of the present application.

[0013] Explanation of the accompanying drawings: basic parameter determination module 11, parameter optimization model establishment module 12, optimization analysis result acquisition module 13, optimization scheme generation module 14, optimization scheme evaluation module 15, optimization adjustment module 16. DETAILED DESCRIPTION

[0014] The overall idea of ​​the technical solution provided by this application is as follows:

[0015] The embodiment of the present application provides a method and device for optimizing the structural parameters of a chemical oxygen self-rescue respirator. By obtaining the basic parameters of the chemical oxygen self-rescue respirator, an optimization model of external structural parameters and internal working parameters is established. Based on this model, parameter optimization analysis is performed to generate multiple optimization schemes, which are then evaluated and the final optimization scheme is selected. By verifying and adjusting the optimization scheme, the comprehensive optimization of the structure and performance of the respirator is finally achieved.

[0016] After introducing the basic principles of the present application, various non-limiting implementation methods of the present application will be specifically described below in conjunction with the drawings in the specification.

[0017] Embodiment 1, as Figure 1 As shown, the embodiment of the present application provides a method for optimizing structural parameters of a chemical oxygen self-rescue respirator, the method comprising:

[0018] Step S100: obtaining basic parameters of the chemical oxygen self-rescue respirator, wherein the basic parameters include external structural parameters and internal working parameters.

[0019] Specifically, a chemical oxygen self-rescue respirator is a personal protective device used in emergency situations to generate oxygen for the user to breathe through chemical reactions. It is usually used in environments such as mines and chemical plants, and can provide users with a safe supply of oxygen under dangerous conditions. Basic parameters refer to the key parameters for the design and performance optimization of chemical oxygen self-rescue respirators, including external structural parameters and internal working parameters. Among them, the external structural parameters involve the physical shape, size, material, weight, sealing performance, etc. of the equipment. For example, whether the shape design of the equipment is convenient to carry, and whether the material has sufficient heat and corrosion resistance. Internal working parameters refer to the performance indicators involved in the internal operation of the equipment, including chemical reaction efficiency, oxygen generation rate, energy conversion efficiency, thermal management, etc. For example, the reaction speed of oxygen generation, the control of heat generation, and the smoothness of air circulation inside the equipment.

[0020] First, basic data on external structure and internal working parameters are obtained through detection and data recording equipment. For external structural parameters, 3D scanners or CAD (computer-aided design) software can be used to measure and model the equipment to obtain data such as the geometric dimensions and material properties of the equipment. For example, a 3D laser scanner can be used to measure the volume and weight of a respirator; a material database or material analysis tool can be used to determine the material's density, compressive strength and other properties.

[0021] For internal working parameters, experimental measurements and data recording tools are used. For example, the measurement of oxygen release rate can be achieved through a flow meter or a dedicated respiratory gas analyzer. These devices can accurately record the oxygen release and chemical reaction rate of the respirator under different conditions. At the same time, it is also necessary to record the working conditions of the equipment under different temperature and pressure conditions to evaluate its stability. For example, a high pressure or low oxygen environment can be simulated in a laboratory environment to measure the performance of the respirator under different conditions.

[0022] In addition, a large amount of historical data can be obtained from the existing respirator design and test database through data mining technology. These data include the performance of similar models of respirators in actual use or testing, such as usage time, failure rate, response efficiency, etc. Database management systems (such as SQL databases) or data mining software (such as MATLAB or Python data processing libraries) can be used to collect and organize these data to form a complete basic data set.

[0023] By obtaining accurate and comprehensive basic parameters, not only can reliable data support be provided for subsequent model optimization and performance analysis, but it can also help designers fully understand the performance of the equipment under different conditions and discover potential design defects in advance.

[0024] Step S200: Based on the basic parameters, a parameter optimization model of the chemical oxygen self-rescue respirator is established, including an external structure parameter model and an internal working parameter model.

[0025] Specifically, the parameter optimization model refers to a model that uses mathematical and computational tools to model the external structural parameters and internal working parameters of the respirator to achieve performance optimization. It can predict the behavior and performance of the respirator under different conditions. The external structural parameter model focuses on the external design characteristics of the respirator. The internal working parameter model focuses on the internal chemical reactions of the respirator and its working mechanism.

[0026] Based on the basic parameters, a parameter optimization model is constructed using machine learning algorithms and mathematical modeling techniques. The external structural parameter model uses regression analysis, neural networks and other methods to predict the portability and user comfort of the respirator. The internal working parameter model uses kinetic models, thermodynamic models and other methods to simulate chemical reactions and energy conversion processes.

[0027] By establishing a parameter optimization model for chemical oxygen self-rescue respirators, the performance of the respirators can be predicted and optimized more accurately.

[0028] Step S300: performing parameter optimization analysis according to the parameter optimization model to obtain parameter optimization analysis results, wherein the parameter optimization analysis includes analyzing the performance of the chemical oxygen self-rescue respirator under different working conditions and adjusting the external structural parameters and the internal working parameters.

[0029] Specifically, parameter optimization analysis refers to the process of adjusting and analyzing the external structural parameters and internal working parameters of the chemical oxygen self-rescue respirator using a parameter optimization model, aiming to find the optimal parameter combination to improve the performance of the respirator. Working conditions refer to the various environmental conditions and usage scenarios encountered by the chemical oxygen self-rescue respirator in actual use.

[0030] First, clarify the range of working conditions encountered by the chemical oxygen self-rescue respirator as the basis for subsequent analysis and optimization. Use the parameter optimization model to simulate the performance of the respirator under different working conditions. By comparing the simulation results with the preset performance standards, identify the bottlenecks of the respirator's performance under different working conditions. Adjust the external structural parameters and internal working parameters for the identified performance bottlenecks. These adjustments involve multiple iterations until satisfactory performance is achieved. Finally, evaluate the impact of the adjusted parameters on the performance of the respirator.

[0031] Through parameter optimization analysis, the performance bottleneck of the chemical oxygen self-rescue respirator under different working conditions can be identified more accurately, and the external structural parameters and internal working parameters can be adjusted accordingly.

[0032] Step S400: Based on the parameter optimization analysis results, multiple optimization schemes are generated, including different external structural parameter combinations and internal working parameter combinations.

[0033] Specifically, the parameter optimization analysis results refer to the optimal combination of external structural parameters and internal working parameters determined by analyzing the performance of chemical oxygen self-rescue respirators under different working conditions. The optimization scheme refers to multiple optional schemes generated based on the parameter optimization analysis results, each of which contains different combinations of external structural parameters and internal working parameters.

[0034] First, based on the results of parameter optimization analysis, identify the parts of the external structural parameters with potential for improvement. Use a combinatorial optimization algorithm to automatically generate combinations of external structural parameters. Each combination represents an optimization solution. Similarly, analyze the performance of internal working parameters to determine which parameters need to be adjusted. Use machine learning algorithms to conduct in-depth analysis of historical performance data and generate multiple combinations of internal working parameters. Match different combinations of external structural parameters with internal working parameter combinations to generate multiple complete optimization solutions. Each solution includes a set of external structural designs and a set of internal working configurations. Use simulation tools (such as MATLAB, ANSYS) to simulate and evaluate the performance of each optimization solution. Through simulation analysis of the performance of the equipment under different working conditions, screen out those solutions with the best performance.

[0035] By optimizing the combination and matching of external structural parameters and internal working parameters, multiple optimization schemes were generated, which not only improved the external physical properties of the chemical oxygen self-rescue respirator such as weight and volume, but also significantly improved the internal working efficiency and usage time, and improved the reliability of the equipment in harsh environments.

[0036] Step S500: Evaluate the multiple optimization schemes and select a final optimization scheme that meets preset performance standards.

[0037] Specifically, the preset performance standards refer to the key performance indicators set when the equipment is designed, which are used to determine whether the optimization solution meets the standards. They include equipment durability, reaction efficiency, comfort, weight, safety and other aspects. Standards are usually based on industry specifications, user needs and design goals. The final optimization solution refers to the solution with the best comprehensive performance and meets the preset standards after evaluation. It is the final output of the design and is used for actual production and further testing.

[0038] First, a multi-dimensional evaluation system needs to be established, covering the key performance indicators of chemical oxygen self-rescue respirators. Each indicator will have a specific threshold value set according to industry standards or user needs. Use simulation tools (such as MATLAB, ANSYS) to evaluate the performance of each optimization solution. Through simulation technology, the performance of the respirator under different working conditions can be simulated to obtain specific performance data for each solution, such as reaction time, temperature change, airflow control, etc.

[0039] Compare the performance data of each optimization solution with the preset performance standards to evaluate whether it meets the standards. On the basis of evaluating the performance, it is also necessary to conduct a cost-benefit analysis of each solution, including material cost, production cost, maintenance cost, etc. The evaluation should not only look at whether the performance meets the standards, but also consider whether the cost is reasonable.

[0040] Use multi-criteria decision analysis methods (such as AHP or TOPSIS) to comprehensively rank multiple options. This method can consider the relative importance of multiple indicators and give the best option ranking based on the weight of each performance and cost.

[0041] Based on performance evaluation, cost analysis and comprehensive ranking, the solution that best meets the preset performance standards and has the highest cost-effectiveness is selected as the final optimization solution.

[0042] By evaluating multiple optimization schemes, we can systematically analyze the advantages and disadvantages of different schemes to ensure that the final scheme selected not only meets all preset performance standards, but also achieves optimal control in terms of cost. The final optimization scheme significantly improves the overall performance of the chemical oxygen self-rescue respirator under different working conditions, reduces production costs, and achieves a balance between technology and cost.

[0043] Step S600: According to the final optimization scheme, the prototype of the chemical oxygen self-rescue respirator is optimized and actual performance tests are performed, and the prototype is adjusted according to the test results.

[0044] Specifically, a prototype refers to a physical sample of a device made according to the final optimization plan, which is used for actual performance testing and verification. It is a preliminary version that can reflect the main features of the design, but still needs to be adjusted and improved in terms of function and structure.

[0045] According to the final optimization plan, a prototype of the chemical oxygen self-rescue breathing apparatus is produced. The prototyping process needs to ensure that the size, material and structure of the device are consistent with the final design so that the performance of the device can be truly reflected in the test.

[0046] After the prototype is completed, a series of performance tests need to be carried out in the laboratory or in a real working environment. These tests usually include the following aspects: Chemical reaction efficiency test: Evaluate the efficiency of the generation of chemical reactants and oxygen in the prototype to ensure that it can provide sufficient oxygen supply within the specified time. Mechanical strength test: Through pressure, impact and vibration tests, ensure that the respirator can be used normally in extreme environments. Temperature resistance test: Simulate high temperature working conditions to test the high temperature resistance of the respirator to ensure that it will not fail in harsh environments. Comfort test: Through wearing tests, evaluate the comfort of the respirator, especially the comfort under long-term wearing conditions. For example, if the respirator needs to be used in a mine, the actual test can simulate the low oxygen environment, high temperature and high pressure conditions in the mine to test the performance of the respirator under these extreme conditions.

[0047] If the test results show that the prototype does not meet the expected standards in some aspects, adjustments need to be made. For example, if the test finds that the outer shell material of the respirator is prone to deformation in a high temperature environment, you can consider replacing it with a high-temperature resistant composite material. In this process, local optimization can be carried out with the help of finite element analysis (FEA) or multi-physics simulation tools. For example, if it is found that the internal chemical reaction rate is not ideal, the simulation software can be used to analyze the reaction process of different chemical components, optimize the ratio of reactants or the structure of the reaction chamber. The adjusted prototype will be tested again to verify whether the modified design has solved the problem. If there are still deficiencies, continue to adjust and repeat the test until all performance standards are met.

[0048] By making a prototype based on the final optimization plan and conducting actual performance tests, the performance of the design in a real environment can be quickly verified to ensure its safety and reliability under extreme conditions. The repeated testing and adjustment process helps to eliminate potential design defects and optimize the overall performance of the equipment.

[0049] Furthermore, the parameter optimization model of the chemical oxygen self-rescue respirator is established based on the basic parameters, including: based on the basic parameters, obtaining historical performance data of the chemical oxygen self-rescue respirator through data analysis and data mining; using a machine learning algorithm to analyze the correlation of the historical performance data, constructing the external structure parameter model, analyzing the chemical reaction efficiency and energy conversion efficiency in the historical performance data, and constructing the internal working parameter model; integrating the external structure parameter model and the internal working parameter model to obtain an initial parameter optimization model; preliminarily verifying the initial parameter optimization model to obtain preliminary verification results; based on the preliminary verification results, iteratively optimizing the initial parameter optimization model to obtain the parameter optimization model.

[0050] Specifically, data analysis and data mining refer to the process of extracting useful information and knowledge from large amounts of data through statistical methods, machine learning techniques, and database queries. Historical performance data refers to the performance indicator data recorded during the past use or testing of chemical oxygen self-rescue respirators, such as oxygen generation, energy conversion efficiency, and breathing resistance. The initial parameter optimization model refers to the first version of the model obtained by integrating the external structural parameter model and the internal working parameter model, which is used for subsequent verification and optimization.

[0051] Through data analysis and data mining, obtain historical performance data of chemical oxygen self-rescue respirators from experimental records, user feedback and market surveys. Use database management tools (such as MySQL) or data analysis software (such as Python's Pandas library) to organize and clean the data to ensure the accuracy and completeness of the data.

[0052] Use machine learning algorithms to analyze the correlation of historical performance data to build external structural parameter models and internal working parameter models. The external model can use regression analysis or support vector machines to study the impact of external parameters (such as material type, equipment shape) on performance; while the internal working parameter model can use dynamic models and thermodynamic models to analyze chemical reaction efficiency and energy conversion efficiency.

[0053] The external structural parameter model and the internal working parameter model are integrated to obtain the initial parameter optimization model. This process can be implemented through MATLAB or Simulink. The initial parameter optimization model is verified and the actual test data is compared with the model prediction results to evaluate the accuracy of the model.

[0054] According to the preliminary verification results, the initial parameter optimization model is iteratively optimized. This process can use methods such as genetic algorithms and particle swarm optimization to make multiple adjustments and optimizations based on the model deviations found, and finally form an accurate parameter optimization model.

[0055] Through this step, the established parameter optimization model can more accurately predict the performance of chemical oxygen self-rescue breathing apparatus under different environmental conditions. It not only improves the efficiency of the design process, but also helps to quickly identify potential problems and make effective improvements.

[0056] Furthermore, the external structure parameter model and the internal working parameter model are integrated to obtain an initial parameter optimization model, including: determining the key connection points between the external structure parameter model and the internal working parameter model; designing and implementing a data interface for seamless data exchange between the external structure parameter model and the internal working parameter model; using multi-physics field simulation technology to simulate the impact of external structure changes on internal working parameters, and the feedback effect of internal working parameter adjustments on the external structure; and combining optimization strategies to jointly optimize the external structure parameter model and the internal working parameter model to obtain an initial parameter optimization model.

[0057] Specifically, critical connection points refer to the mutual influence and action points between external structural parameters and internal working parameters. For example, the material selection of the equipment not only affects the weight and durability, but also affects the efficiency of the internal chemical reactions. Data interface A design tool used to exchange data between the external structural model and the internal working model to ensure that the two models can work seamlessly together. Multi-physics simulation technology is a technology used to simulate the interaction between different physical fields (such as mechanics, thermal, electromagnetic fields, etc.) to predict the overall performance of equipment under different design and working conditions. Joint optimization refers to finding the combination with the best overall performance by adjusting the external structural parameters and internal working parameters at the same time during the optimization process.

[0058] First, we need to analyze how external structural parameters (such as the material and shape of the device) affect internal working parameters (such as chemical reaction rate and energy conversion efficiency). These key points can be determined through experimental data and empirical formulas. For example, the thermal conductivity of the material affects the heat management of the chemical reaction and can therefore be considered a key connection point.

[0059] In order to ensure seamless data exchange between the external structural parameter model and the internal working parameter model, a data interface needs to be designed. This can be achieved by writing code or using existing interface tools. For example, using interface functions in MATLAB or Python, seamless data transfer between models can be achieved. For example, the thickness of the material can be passed as an input parameter to the internal model to affect the simulation results of heat conduction.

[0060] Use multi-physics simulation software (such as COMSOL Multiphysics) to simulate the impact of external structural changes on internal operating parameters. For example, how changing the external material and size of the respirator will affect the internal chemical reaction efficiency and energy conversion. This simulation process can reveal the complex impact of external structural changes on internal chemical reactions. At the same time, the simulation can also simulate the impact of adjustments to internal operating parameters on external structural feedback, for example, how the reaction heat affects the surface temperature of the device.

[0061] Optimization strategies such as genetic algorithms and particle swarm algorithms are used to jointly optimize external structural parameters and internal operating parameters. Optimization tools such as Optimization Toolbox in MATLAB can help to jointly optimize multiple variables and find the optimal parameter combination. For example, optimize the material selection and size design of the respirator to ensure that the device is lightweight without sacrificing its internal chemical reaction efficiency. By jointly optimizing multiple groups of parameters, the best external structure and internal performance matching solution can be obtained.

[0062] By integrating the external structural parameter model with the internal working parameter model and using multi-physics field simulation technology and joint optimization strategies, the optimized chemical oxygen self-rescue respirator has achieved a comprehensive improvement in performance. Specifically, the weight of the device has been significantly reduced, which has improved the wearing comfort, while maintaining an efficient chemical reaction rate and extending the service life. In addition, the optimized respirator performs stably under different working conditions, ensuring the safety and reliability of the equipment.

[0063] Furthermore, according to the parameter optimization model, a parameter optimization analysis is performed to obtain a parameter optimization analysis result, wherein the parameter optimization analysis includes analyzing the performance of the chemical oxygen self-rescue respirator under different working conditions, and adjusting the external structural parameters and the internal working parameters, including: defining the working condition range of the chemical oxygen self-rescue respirator; using the parameter optimization model to simulate the performance of the chemical oxygen self-rescue respirator within the working condition range to obtain performance indicator data; identifying potential factors for performance degradation under specific working conditions to obtain performance degradation factors; designing different external structural parameter adjustment schemes for the performance degradation factors, and at the same time, adjusting the internal working parameters; evaluating the adjusted external structural parameters and internal working parameters, and obtaining the parameter optimization analysis result through comparative analysis.

[0064] Specifically, the operating condition range refers to the various environmental conditions encountered by chemical oxygen self-rescue respirators in actual use, such as temperature, pressure, oxygen concentration, humidity, etc. Defining these ranges helps ensure that the equipment can work normally under various extreme conditions. Performance indicator data refers to the performance data of the respirator under different conditions obtained through simulation or actual testing, usually including key indicators such as reaction rate, gas generation, working time, structural stability, etc. Performance degradation factors refer to factors that cause the performance of the equipment to deteriorate under certain specific conditions, including insufficient chemical reaction, material fatigue, insufficient sealing, etc.

[0065] First, define the working condition range of the chemical oxygen self-rescue respirator. This includes ambient temperature, air pressure, humidity, and the breathing rate of the respirator user. For example, the working environment in a mine is usually high temperature, high humidity, and low oxygen. The condition range is set to a temperature between 20°C and 60°C, an oxygen concentration of 15% to 20%, and a pressure of 1-5 atmospheres. By defining such working conditions, ensure that the optimization analysis can cover all usage scenarios.

[0066] The performance of the respirator under the above working conditions is simulated by using parameter optimization models. This can be achieved through tools such as finite element analysis (FEA) and fluid dynamics simulation. For example, finite element analysis can simulate the deformation of the respirator shell material under high pressure, while fluid dynamics simulation can analyze the gas flow and chemical reaction efficiency inside the respirator. Through these simulation tools, the performance index data of the respirator under various conditions, such as gas generation rate, continuous oxygen supply time, etc., can be obtained.

[0067] Analyze simulation results to identify factors that cause the performance of the respirator to degrade under certain conditions. For example, if the reactants inside the respirator are not fully decomposed under high temperature and high pressure conditions, resulting in insufficient oxygen generation, this is a performance degradation factor. Another example is the material fatigue problem of the shell under high pressure. If the shell material is too thin, it will deform or crack during long-term use, affecting the safety of the equipment.

[0068] Design different external structures and internal operating parameter adjustment solutions for the identified performance degradation factors. For example, to address the problem of insufficient decomposition of reactants, the structure of the reaction chamber can be optimized or the composition ratio of the reactants can be adjusted. For the shell material, a more pressure-resistant composite material can be selected to enhance its strength. The optimization tool can use advanced optimization methods such as genetic algorithms and particle swarm optimization algorithms to perform multiple iterative optimizations on the external structure and internal operating parameters. Through these adjustments, the best design combination is found.

[0069] By simulating the adjusted external structure and internal working parameters, the performance test is conducted again to obtain a new round of performance data. The performance data before and after the adjustment are then compared and analyzed to evaluate the pros and cons of each adjustment plan.

[0070] Through detailed analysis and comparison based on parameter optimization model, not only can the key factors affecting the performance of chemical oxygen self-rescue respirator be identified, but also effective optimization scheme can be designed. The final optimization analysis results will help improve the stability, reliability and safety of the respirator under various working conditions.

[0071] Furthermore, based on the parameter optimization analysis results, multiple optimization schemes are generated, including different external structure parameter combinations and internal working parameter combinations, including: based on the parameter optimization analysis results, using a combination optimization algorithm to generate multiple external structure parameter combination schemes, and also using a combination optimization algorithm to generate multiple internal working parameter combination schemes; matching the external structure parameter combination scheme with the internal working parameter combination scheme to form multiple optimization schemes.

[0072] Specifically, combinatorial optimization algorithms are used to find the optimal combination of multiple variables (such as external structural parameters and internal working parameters). Commonly used combinatorial optimization algorithms include genetic algorithms, simulated annealing algorithms, particle swarm algorithms, etc. These algorithms can quickly find multiple combination schemes close to the optimal solution in a complex multivariable space. The external structural parameter combination scheme is a combination of different external structural parameter combinations designed based on the optimization analysis results, such as the shape, material, size and other changes of the respirator, aiming to improve its physical properties such as weight, durability, comfort, etc. The internal working parameter combination scheme is an optimization scheme designed for the working mechanisms such as chemical reactions and gas flow inside the respirator, including reactant ratios, reaction chamber structure, gas flow rate, etc. These combination schemes directly affect the reaction efficiency and gas generation of the respirator.

[0073] First, based on the results of parameter optimization analysis, the key parameters that affect the performance of the external structure are identified. Next, a combinatorial optimization algorithm is used to generate multiple external structure parameter combination schemes. Similarly, the combinatorial optimization algorithm is used to optimize the internal working parameters. In this step, the simulated annealing algorithm is used to adjust parameters such as the reactant ratio and the reaction chamber volume. The simulated annealing algorithm simulates the thermodynamic annealing process to avoid falling into the local optimal solution and thus find the global optimal solution.

[0074] The external structural parameter combination scheme is matched with the internal working parameter combination scheme to form multiple overall optimization schemes. This process involves pairing in multi-dimensional parameter space to ensure that different combinations can achieve the optimal balance in performance.

[0075] By generating multiple external structural parameter combinations and internal working parameter combinations based on the parameter optimization analysis results, the overall performance of the chemical oxygen self-rescue respirator can be improved. This process can efficiently explore the best solution combination in a multi-dimensional space by utilizing combinatorial optimization algorithms and simulation tools.

[0076] Furthermore, the evaluation of the multiple optimization schemes to select a final optimization scheme that meets the preset performance standards includes: establishing an evaluation index system, wherein the index system covers key performance indicators of chemical oxygen self-rescue respirators; according to the multiple optimization schemes, using the parameter optimization model to obtain performance index data of each optimization scheme under different working conditions; comparing the performance index data with the preset performance standards, evaluating the degree of compliance of each optimization scheme, and obtaining performance evaluation results; considering cost-benefit analysis, including material cost, manufacturing cost, and long-term maintenance cost, conducting cost evaluation on the multiple optimization schemes to obtain cost evaluation results; comprehensively analyzing the performance evaluation results and cost evaluation results, using a multi-criteria decision analysis method to sort the multiple optimization schemes to obtain an optimization scheme ranking; and selecting the final optimization scheme based on the optimization scheme ranking.

[0077] Specifically, performance indicator data refers to the numerical data generated when each optimization scheme runs under specific conditions, which is used to measure the performance of the scheme. For example, the duration of oxygen supply of a certain structure in a high temperature environment or the startup reaction time in a low temperature environment. Multi-criteria decision analysis (MCDA) is an analysis method used to deal with multiple decision criteria (such as performance, cost, durability, etc.). It aims to provide a reasonable ranking for each scheme by considering the weights of different criteria, and finally select the optimal scheme. Commonly used MCDA methods include the analytic hierarchy process (AHP), TOPSIS (topic ideal solution method), etc.

[0078] First, according to project requirements and standard specifications, the key performance indicators of chemical oxygen self-rescue respirators are determined, such as oxygen supply time, weight, reaction efficiency, durability, etc. Each performance indicator is given a different weight to reflect its relative importance.

[0079] According to each optimization scheme, the parameter optimization model is used to simulate its performance under different working conditions. The obtained performance index data is compared with the pre-defined performance standards (such as national standards or internal enterprise standards) to evaluate the compliance of each scheme.

[0080] After the performance evaluation, a cost-benefit analysis is also required. By calculating the material cost, manufacturing cost, and long-term maintenance cost, the cost of each solution can be determined. For example, if Solution B has the best performance, but the material cost is higher and the manufacturing is complex, further trade-offs are required.

[0081] Comprehensive performance evaluation and cost-benefit analysis, use multi-criteria decision analysis to rank multiple optimization schemes. For example, using the TOPSIS method, the relative distance between each scheme and the ideal solution can be calculated, and then the schemes can be ranked according to the distance to obtain the optimal scheme. For example: Although scheme B has the best performance, it has a high cost. Scheme A has a lower cost and its performance is close to the ideal solution. Finally, scheme A is selected as the optimal scheme.

[0082] Based on the ranking results of each solution, the final solution that meets the preset performance standards and has the best cost-effectiveness is determined. This process requires multiple iterations and adjustments to ultimately determine the solution with the best performance and cost.

[0083] By systematically evaluating multiple optimization schemes, the optimal scheme that meets the performance standards of chemical oxygen self-rescue respirators can be effectively screened out. During the evaluation process, not only the performance of the respirators under different environmental conditions was compared in detail, but also the cost-effectiveness was comprehensively considered through multi-criteria decision analysis, so as to select the optimization scheme with both high performance and low cost.

[0084] Furthermore, the establishment of the evaluation index system includes: determining the key performance indicator categories of chemical oxygen self-rescue respirators; refining specific indicators for the key performance indicator categories; setting evaluation thresholds for the specific indicators based on industry standards and user needs; using hierarchical analysis to evaluate the relative importance of each key performance indicator category and determine the weight coefficient; integrating the specific indicators, the evaluation thresholds and the weight coefficients to obtain the evaluation index system.

[0085] Specifically, the key performance indicator category refers to the most important performance area of ​​chemical oxygen self-rescue respirators in design and use. It usually includes indicator categories of different dimensions such as oxygen supply time, weight, reaction efficiency, durability, and wearing comfort. Specific indicators refer to the detailed measurement standards under the key performance indicator category. Specific indicators are specific data or characteristics that quantitatively or qualitatively describe the performance of the respirator. For example, under the oxygen supply time category, the specific indicator can be "continuous oxygen supply time (minutes)". The evaluation threshold refers to the minimum or maximum standard value set for each specific indicator, which is usually determined according to industry standards, user needs or technical levels. Analytic Hierarchy Process (AHP) is a multi-criteria decision-making method used to determine the relative importance between different indicator categories. The weight coefficient of each performance indicator is determined through expert scoring or comparative analysis, thereby providing a reference for decision-making.

[0086] First, it is necessary to determine the core performance dimensions of the chemical oxygen self-rescue respirator based on its design objectives and actual applications, which usually include oxygen supply time, weight, chemical reaction efficiency, wearing comfort and durability.

[0087] For each key performance category, further refine the specific indicators that can be measured. For example, for the "oxygen supply time" category, the specific indicator can be "maximum oxygen supply duration (minutes)". For the "weight" category, the specific indicator is "total equipment weight (kg)". According to industry standards and user needs, set the minimum or maximum required value for each specific indicator.

[0088] In order to determine the importance of each key performance category, the analytic hierarchy process (AHP) is used. This method compares and analyzes the importance of different categories to obtain the relative weight of each category. AHP can be calculated by expert scoring using software tools such as MATLAB or Python to generate corresponding weight coefficients.

[0089] All specific indicators, thresholds and weight coefficients are integrated into a complete evaluation indicator system. This system can be used as a performance evaluation standard when designing, testing and optimizing respirators. After using AHP analysis, the weight of oxygen supply time is determined to be 50%, weight is 30%, and durability is 20%. After integrating these indicators and weights, an evaluation system is established, which becomes the basis for subsequent program evaluation and decision-making.

[0090] By establishing an evaluation index system, the performance of different chemical oxygen self-rescue respirator solutions can be measured more scientifically and systematically. This system not only ensures that each key performance indicator is fully evaluated, but also through AHP weight analysis, it can reasonably weigh the importance of different indicators according to user needs and practical application priorities, and ultimately provide an accurate basis for the selection and optimization of solutions. It significantly improves decision-making efficiency, avoids the situation where other key factors are ignored due to excessive focus on a certain performance during the design process, and ensures that the comprehensive performance of the final product is more in line with user needs and industry standards.

[0091] In summary, the structural parameter optimization method for a chemical oxygen self-rescue respirator provided in the embodiments of the present application has the following technical effects:

[0092] 1. By establishing a parameter optimization model for chemical oxygen self-rescue respirators based on basic parameters, the performance of the respirator can be predicted and optimized more accurately, thereby improving design efficiency and product reliability and reducing the R&D cycle. The model integrates external structure and internal working parameters and provides a systematic optimization solution.

[0093] 2. Collecting historical performance data through data analysis and data mining techniques can provide rich basic data support, thereby improving the prediction accuracy of the model through machine learning algorithms and ensuring that the model has adaptability and robustness under different working conditions.

[0094] 3. Based on parameter optimization analysis, multiple combinations of external structures and internal working parameters are generated, which can provide the design team with diverse design options and explore the performance of different solutions under different conditions, thereby achieving multi-angle performance optimization.

[0095] Embodiment 2, based on the same inventive concept as the structural parameter optimization method for chemical oxygen self-rescue respirator in the previous embodiment, as Figure 2 As shown, the embodiment of the present application provides a structural parameter optimization device for a chemical oxygen self-rescue respirator, the device comprising:

[0096] Basic parameter determination module 11: used to obtain basic parameters of the chemical oxygen self-rescue respirator, wherein the basic parameters include external structural parameters and internal working parameters;

[0097] Parameter optimization model building module 12: used to build a parameter optimization model of the chemical oxygen self-rescue respirator based on the basic parameters, including an external structural parameter model and an internal working parameter model;

[0098] The optimization analysis result obtaining module 13 is used to perform parameter optimization analysis according to the parameter optimization model to obtain parameter optimization analysis results, wherein the parameter optimization analysis includes analyzing the performance of the chemical oxygen self-rescue respirator under different working conditions and adjusting the external structural parameters and the internal working parameters;

[0099] Optimization scheme generating module 14: used to generate multiple optimization schemes based on the parameter optimization analysis results, including different external structural parameter combinations and internal working parameter combinations;

[0100] Optimization scheme evaluation module 15: used to evaluate the multiple optimization schemes and select a final optimization scheme that meets the preset performance standards;

[0101] Optimization and adjustment module 16: used to optimize the prototype of the chemical oxygen self-rescue respirator according to the final optimization plan and conduct actual performance tests, and adjust the prototype according to the test results.

[0102] Furthermore, the parameter optimization model building module 12 is also used to perform the following steps:

[0103] Based on the basic parameters, historical performance data of the chemical oxygen self-rescue respirator is obtained through data analysis and data mining;

[0104] Using a machine learning algorithm, analyzing the correlation of the historical performance data, constructing the external structural parameter model, analyzing the chemical reaction efficiency and energy conversion efficiency in the historical performance data, and constructing the internal working parameter model;

[0105] Integrate the external structural parameter model and the internal working parameter model to obtain an initial parameter optimization model

[0106] Performing preliminary verification on the initial parameter optimization model to obtain preliminary verification results;

[0107] Based on the preliminary verification result, the initial parameter optimization model is iteratively optimized to obtain the parameter optimization model.

[0108] Furthermore, the parameter optimization model building module 12 is also used to perform the following steps:

[0109] Determining key connection points between the external structural parameter model and the internal working parameter model;

[0110] Design and implement a data interface for seamless data exchange between the external structural parameter model and the internal working parameter model;

[0111] Use multi-physics simulation technology to simulate the impact of external structural changes on internal working parameters, as well as the feedback effect of internal working parameter adjustments on external structures;

[0112] Combined with the optimization strategy, the external structural parameter model and the internal working parameter model are jointly optimized to obtain an initial parameter optimization model.

[0113] Furthermore, the optimization analysis result obtaining module 13 is also used to perform the following steps:

[0114] Define the range of working conditions for chemical oxygen self-rescue breathing apparatus;

[0115] Using the parameter optimization model, the performance of the chemical oxygen self-rescue respirator within the working condition range is simulated to obtain performance index data;

[0116] Identify potential factors that degrade performance under specific working conditions and obtain performance degradation factors;

[0117] According to the performance degradation factor, different external structural parameter adjustment schemes are designed, and at the same time, the internal working parameters are adjusted;

[0118] The adjusted external structural parameters and internal working parameters are evaluated, and the parameter optimization analysis results are obtained through comparative analysis.

[0119] Furthermore, the optimization scheme deletion module 14 is further configured to perform the following steps:

[0120] Based on the parameter optimization analysis results, a combination optimization algorithm is used to generate multiple external structural parameter combination schemes, and a combination optimization algorithm is also used to generate multiple internal working parameter combination schemes;

[0121] The external structural parameter combination scheme is matched with the internal working parameter combination scheme to form multiple optimization schemes.

[0122] Furthermore, the optimization scheme evaluation module 15 is also used to perform the following steps:

[0123] Establishing an evaluation index system, which covers key performance indicators of chemical oxygen self-rescue respirators;

[0124] According to the multiple optimization schemes, using the parameter optimization model, obtaining performance indicator data of each optimization scheme under different working conditions;

[0125] Compare the performance indicator data with the preset performance standard, evaluate the degree of compliance of each optimization scheme, and obtain a performance evaluation result;

[0126] Considering cost-benefit analysis, including material cost, manufacturing cost, and long-term maintenance cost, cost evaluation is performed on the plurality of optimization schemes to obtain a cost evaluation result;

[0127] Combining the performance evaluation results and the cost evaluation results, a multi-criteria decision analysis method is used to sort multiple optimization schemes to obtain the optimization scheme ranking;

[0128] According to the ranking of the optimization solutions, the final optimization solution is selected.

[0129] Furthermore, the optimization scheme evaluation module 15 is also used to perform the following steps:

[0130] Determine the key performance indicator categories for chemical oxygen self-rescue breathing apparatus;

[0131] For the key performance indicator categories, refine the specific indicators;

[0132] Set evaluation thresholds for the specific indicators according to industry standards and user needs;

[0133] Using the analytic hierarchy process, evaluate the relative importance of each of the key performance indicator categories and determine the weight coefficient;

[0134] The specific indicator, the evaluation threshold and the weight coefficient are integrated to obtain the evaluation indicator system.

[0135] Any step of the method described above can be stored as a computer instruction or program in an unlimited computer memory, and can be called and recognized by an unlimited computer processor to implement any method in the embodiments of the present application, without any unnecessary restrictions.

[0136] Furthermore, the first or second mentioned above not only represents an order relationship, but also represents a specific concept, and / or refers to the selection of multiple elements individually or in whole. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application intends to include these modifications and variations.

Claims

1. A method for optimizing structural parameters of a chemical oxygen self-rescue respirator, characterized in that: The method comprises: Obtaining basic parameters of the chemical oxygen self-rescue respirator, wherein the basic parameters include external structural parameters and internal working parameters; Based on the basic parameters, a parameter optimization model of the chemical oxygen self-rescue respirator is established, including an external structural parameter model and an internal working parameter model; According to the parameter optimization model, a parameter optimization analysis is performed to obtain a parameter optimization analysis result, wherein the parameter optimization analysis includes analyzing the performance of the chemical oxygen self-rescue respirator under different working conditions and adjusting the external structural parameters and the internal working parameters; Based on the parameter optimization analysis results, generating multiple optimization schemes, including different external structural parameter combinations and internal working parameter combinations; Evaluate the multiple optimization solutions and select a final optimization solution that meets the preset performance criteria; According to the final optimization scheme, the prototype of the chemical oxygen self-rescue respirator is optimized and actual performance tests are carried out, and the prototype is adjusted according to the test results.

2. The structural parameter optimization method for a chemical oxygen self-rescue respirator according to claim 1, characterized in that: The method of establishing a parameter optimization model of a chemical oxygen self-rescue respirator based on the basic parameters includes: Based on the basic parameters, historical performance data of the chemical oxygen self-rescue respirator is obtained through data analysis and data mining; Using a machine learning algorithm, analyzing the correlation of the historical performance data, constructing the external structural parameter model, analyzing the chemical reaction efficiency and energy conversion efficiency in the historical performance data, and constructing the internal working parameter model; Integrating the external structural parameter model and the internal working parameter model to obtain an initial parameter optimization model; Performing preliminary verification on the initial parameter optimization model to obtain preliminary verification results; Based on the preliminary verification result, the initial parameter optimization model is iteratively optimized to obtain the parameter optimization model.

3. The structural parameter optimization method for a chemical oxygen self-rescue respirator according to claim 2, characterized in that: The step of integrating the external structural parameter model and the internal working parameter model to obtain an initial parameter optimization model comprises: Determining key connection points between the external structural parameter model and the internal working parameter model; Design and implement a data interface for seamless data exchange between the external structural parameter model and the internal working parameter model; Use multi-physics simulation technology to simulate the impact of external structural changes on internal working parameters, as well as the feedback effect of internal working parameter adjustments on external structures; Combined with the optimization strategy, the external structural parameter model and the internal working parameter model are jointly optimized to obtain an initial parameter optimization model.

4. The structural parameter optimization method for a chemical oxygen self-rescue respirator according to claim 1, characterized in that: According to the parameter optimization model, a parameter optimization analysis is performed to obtain a parameter optimization analysis result, wherein the parameter optimization analysis includes analyzing the performance of the chemical oxygen self-rescue respirator under different working conditions, adjusting the external structural parameters and the internal working parameters, including: Define the range of working conditions for chemical oxygen self-rescue breathing apparatus; Using the parameter optimization model, the performance of the chemical oxygen self-rescue respirator within the working condition range is simulated to obtain performance index data; Identify potential factors that degrade performance under specific working conditions and obtain performance degradation factors; According to the performance degradation factor, different external structural parameter adjustment schemes are designed, and at the same time, the internal working parameters are adjusted; The adjusted external structural parameters and internal working parameters are evaluated, and the parameter optimization analysis results are obtained through comparative analysis.

5. The structural parameter optimization method for a chemical oxygen self-rescue respirator according to claim 1, characterized in that: Based on the parameter optimization analysis results, a plurality of optimization schemes are generated, including different external structural parameter combinations and internal working parameter combinations, including: Based on the parameter optimization analysis results, a combination optimization algorithm is used to generate multiple external structural parameter combination schemes, and a combination optimization algorithm is also used to generate multiple internal working parameter combination schemes; The external structural parameter combination scheme is matched with the internal working parameter combination scheme to form multiple optimization schemes.

6. The structural parameter optimization method for a chemical oxygen self-rescue respirator according to claim 1, characterized in that: The step of evaluating the plurality of optimization schemes and selecting a final optimization scheme that meets a preset performance standard includes: Establishing an evaluation index system, which covers key performance indicators of chemical oxygen self-rescue respirators; According to the multiple optimization schemes, using the parameter optimization model, obtaining performance indicator data of each optimization scheme under different working conditions; Compare the performance indicator data with the preset performance standard, evaluate the degree of compliance of each optimization scheme, and obtain a performance evaluation result; Considering cost-benefit analysis, including material cost, manufacturing cost, and long-term maintenance cost, cost evaluation is performed on the plurality of optimization schemes to obtain a cost evaluation result; Combining the performance evaluation results and the cost evaluation results, a multi-criteria decision analysis method is used to sort multiple optimization schemes to obtain the optimization scheme ranking; According to the ranking of the optimization solutions, the final optimization solution is selected.

7. The structural parameter optimization method for a chemical oxygen self-rescue respirator according to claim 6, characterized in that: The establishment of the evaluation indicator system includes: Determine the key performance indicator categories for chemical oxygen self-rescue breathing apparatus; For the key performance indicator categories, refine the specific indicators; Set evaluation thresholds for the specific indicators according to industry standards and user needs; Using the analytic hierarchy process, evaluate the relative importance of each of the key performance indicator categories and determine the weight coefficient; The specific indicator, the evaluation threshold and the weight coefficient are integrated to obtain the evaluation indicator system.

8. A structural parameter optimization device for a chemical oxygen self-rescue respirator, characterized in that: Used to implement the structural parameter optimization method for a chemical oxygen self-rescue respirator according to any one of claims 1 to 7, the device comprising: Basic parameter determination module: used to obtain basic parameters of the chemical oxygen self-rescue respirator, wherein the basic parameters include external structural parameters and internal working parameters; Parameter optimization model building module: used to build a parameter optimization model of the chemical oxygen self-rescue respirator based on the basic parameters, including an external structural parameter model and an internal working parameter model; Optimization analysis result acquisition module: used to perform parameter optimization analysis according to the parameter optimization model to obtain parameter optimization analysis results, wherein the parameter optimization analysis includes analyzing the performance of the chemical oxygen self-rescue respirator under different working conditions and adjusting the external structural parameters and the internal working parameters; Optimization scheme generation module: used to generate multiple optimization schemes based on the parameter optimization analysis results, including different external structural parameter combinations and internal working parameter combinations; Optimization scheme evaluation module: used to evaluate the multiple optimization schemes and select the final optimization scheme that meets the preset performance standards; Optimization and adjustment module: used to optimize the prototype of the chemical oxygen self-rescue respirator according to the final optimization plan and conduct actual performance tests, and adjust the prototype according to the test results.

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