Structural Parameter Optimization Method and Device for Chemical Oxygen Self-Rescuer

Abstract

The present invention discloses a method and device for optimizing the structural parameters of a chemical oxygen self-rescuer, belonging to the field of respiratory protection equipment design. The method includes: obtaining the basic parameters of the chemical oxygen self-rescuer; establishing a parameter optimization model of the chemical oxygen self-rescuer based on the basic parameters; performing parameter optimization analysis according to the parameter optimization model, and adjusting the external structural parameters and the internal working parameters; generating multiple optimization schemes based on the parameter optimization analysis results; evaluating the multiple optimization schemes, and selecting a final optimization scheme that meets the preset performance criteria; and adjusting the prototype according to the test results. This application solves the technical problems in the prior art that the external structure and the internal working parameters of the chemical oxygen self-rescuer cannot be optimized synergistically, resulting in unstable performance, uncomfortable use, and low work efficiency.

Description

Technical Field

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

[0002] A chemical oxygen self-rescuer is an important personal protective equipment used in dangerous environments (such as mines, tunnels, chemical plants, etc.). When there is insufficient oxygen or toxic gases in the environment, the chemical oxygen self-rescuer generates oxygen through a chemical reaction for the user to breathe, ensuring that there is sufficient oxygen to support a safe evacuation in case of an emergency. With the acceleration of industrialization and the continuous development of high-risk industries such as mining and chemical engineering, safety accidents occur frequently, especially the risk of oxygen deficiency or toxic gas leakage gradually increases, resulting in higher requirements for the performance of self-rescue equipment. To cope with the complex and changeable working environment, the respirator not only needs to have high-efficient oxygen generation ability, but also should have reliable durability, comfort and easy operation.

[0003] The current design of chemical oxygen self-rescuers mainly relies on experience and single-parameter adjustment, making it difficult to achieve global optimization of the external structure and internal working parameters, resulting in problems such as excessive weight, uncomfortable wearing, and low reaction efficiency of the respirator under actual working conditions. In addition, the existing respirators are difficult to ensure stable performance in complex environments, resulting in some equipment being unable to provide sufficient oxygen supply in case of an emergency, seriously affecting the reliability and use effect of the equipment. Summary of the Invention

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

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

[0006] In the first aspect disclosed in this application, a method for optimizing the structural parameters of a chemical oxygen self-rescue breathing apparatus is provided. The method includes: obtaining the basic parameters of the chemical oxygen self-rescue breathing apparatus, where the basic parameters include external structural parameters and internal working parameters; based on the basic parameters, establishing a parameter optimization model for the chemical oxygen self-rescue breathing apparatus, including an external structural parameter model and an internal working parameter model; according to the parameter optimization model, performing parameter optimization analysis to obtain a parameter optimization analysis result, where the parameter optimization analysis includes analyzing the performance of the chemical oxygen self-rescue breathing apparatus under different working conditions and adjusting the external structural parameters and the internal working parameters; based on the parameter optimization analysis result, generating multiple optimization schemes, including different combinations of external structural parameters and internal working parameters; evaluating the multiple optimization schemes and selecting a final optimization scheme that meets the preset performance criteria; according to the final optimization scheme, optimizing the prototype of the chemical oxygen self-rescue breathing apparatus and performing actual performance tests, and adjusting the prototype according to the test results.

[0007] In another aspect disclosed in this application, a device for optimizing the structural parameters of a chemical oxygen self-rescue breathing apparatus is provided. The device includes: a basic parameter determination module: used to obtain the basic parameters of the chemical oxygen self-rescue breathing apparatus, where the basic parameters include external structural parameters and internal working parameters; a parameter optimization model establishment module: used to establish a parameter optimization model for the chemical oxygen self-rescue breathing apparatus based on the basic parameters, including an external structural parameter model and an internal working parameter model; an optimization analysis result obtaining module: used to perform parameter optimization analysis according to the parameter optimization model to obtain a parameter optimization analysis result, where the parameter optimization analysis includes analyzing the performance of the chemical oxygen self-rescue breathing apparatus 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 result, including different combinations of external structural parameters and internal working parameters; an optimization scheme evaluation module: used to evaluate the multiple optimization schemes and select a final optimization scheme that meets the preset performance criteria; an optimization adjustment module: used to optimize the prototype of the chemical oxygen self-rescue breathing apparatus according to the final optimization scheme and perform actual performance tests, 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] Due to the technical solution of establishing a parameter optimization model for a chemical oxygen self-rescuer based on basic parameters, conducting parameter optimization analysis, and generating multiple optimization schemes, the technical problem in the prior art that the external structure parameters and internal working parameters cannot be optimized collaboratively, resulting in unstable performance and discomfort in use, is solved. The technical effects of improving the stability, comfort, and working efficiency of the respirator under different working conditions are achieved, thereby improving the reliability of the respirator.

[0010] The above description is only an overview of the technical solution of this application. In order to be able to understand the technical means of this application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features, and advantages of this application more obvious and understandable, the specific embodiments of this application are specifically exemplified below. Brief Description of the Drawings

[0011] Figure 1 This is a schematic flowchart of the structural parameter optimization method for a chemical oxygen self-rescuer provided by an embodiment of this application.

[0012] Figure 2 This is a schematic structural diagram of the structural parameter optimization device for a chemical oxygen self-rescuer provided by an embodiment of this application.

[0013] Description of the reference numerals: 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 of the Embodiments

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

[0015] An embodiment of this application provides a structural parameter optimization method and device for a chemical oxygen self-rescuer. By obtaining the basic parameters of the chemical oxygen self-rescuer, an optimization model for external structure parameters and internal working parameters is established. Based on this model, parameter optimization analysis is carried out to generate multiple optimization schemes, and then these schemes are evaluated to select the final optimization scheme. Through the verification and adjustment of the optimization scheme, the overall optimization of the structure and performance of the respirator is finally realized.

[0016] After introducing the basic principle of this application, the various non-limiting embodiments of this application will be specifically introduced below in conjunction with the drawings of the specification.

[0017] Embodiment 1, as Figure 1 shown, an embodiment of this application provides a structural parameter optimization method for a chemical oxygen self-rescuer, and the method includes:

[0018] Step S100: Obtain the basic parameters of the chemical oxygen self-rescuer, where the basic parameters include external structure parameters and internal working parameters.

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

[0020] First, obtain the basic data of the external structure and internal working parameters through detection and data recording devices. For the external structure parameters, a 3D scanner or CAD (Computer-Aided Design) software can be used to measure and model the device to obtain data such as the geometric dimensions and material properties of the device. For example, a 3D laser scanner can be used to measure the volume and weight of the breathing apparatus; a material database or material analysis tool can be used to determine the density, compressive strength, and other properties of the material.

[0021] For the internal working parameters, they are obtained through experimental measurement and data recording tools. For example, the measurement of the oxygen release rate can be achieved through a flow meter or a dedicated respiratory gas analyzer, which can accurately record the oxygen release amount and chemical reaction rate of the breathing apparatus under different conditions. At the same time, it is also necessary to record the working conditions of the device 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 breathing apparatus under different conditions.

[0022] In addition, a large amount of historical data can be obtained from the existing breathing apparatus design and test database through data mining techniques. These data include the performance of similar models of breathing apparatuses in actual use or testing, such as service life, failure rate, reaction efficiency, etc. A database management system (such as an SQL database) or data mining software (such as MATLAB or Python's data processing libraries) can be used to collect and organize these data to form a complete basic dataset.

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

[0024] Step S200: Based on the basic parameters, establish a parameter optimization model for the chemical oxygen self-rescue breathing apparatus, 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 structure parameters and internal working parameters of the breathing apparatus, thereby achieving performance optimization. It can predict the behavior and performance of the breathing apparatus under different conditions. The external structure parameter model focuses on the external design characteristics of the breathing apparatus. The internal working parameter model focuses on the internal chemical reactions and working mechanisms of the breathing apparatus.

[0026] Based on the basic parameters, use machine learning algorithms and mathematical modeling techniques to construct a parameter optimization model. The external structure parameter model uses methods such as regression analysis and neural networks to predict the portability and user comfort of the breathing apparatus. The internal working parameter model uses kinetic models, thermodynamic models, etc. to simulate chemical reactions and energy conversion processes.

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

[0028] Step S300: According to the parameter optimization model, conduct parameter optimization analysis to obtain parameter optimization analysis results, where the parameter optimization analysis includes analyzing the performance of the chemical oxygen self-rescue breathing apparatus under different working conditions and adjusting the external structure parameters and the internal working parameters.

[0029] Specifically, parameter optimization analysis refers to the process of using the parameter optimization model to adjust and analyze the external structure parameters and internal working parameters of the chemical oxygen self-rescue breathing apparatus, aiming to find the optimal parameter combination to improve the performance of the breathing apparatus. Working conditions refer to various environmental conditions and usage scenarios encountered by the chemical oxygen self-rescue breathing apparatus during actual use.

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

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

[0032] Step S400: Based on the parameter optimization analysis results, generate multiple optimization solutions, including different combinations of external structure parameters and internal working parameters.

[0033] Specifically, the parameter optimization analysis results refer to determining the optimal combination of external structure parameters and internal working parameters by analyzing the performance of the chemical oxygen self-rescuer under different working conditions. The optimization solutions refer to multiple alternative solutions generated based on the parameter optimization analysis results, and each solution includes different combinations of external structure parameters and internal working parameters.

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

[0035] By optimizing and matching the external structure parameters and internal working parameters, multiple optimization solutions are generated, which not only improve the external physical characteristics of the chemical oxygen self-rescuer such as weight and volume, but also significantly enhance the internal working efficiency and service life, and improve the reliability of the device in harsh environments.

[0036] Step S500: Evaluate the multiple optimization solutions and select the final optimization solution that meets the preset performance criteria.

[0037] Specifically, the preset performance criteria refer to the key performance indicators set during the device design to judge whether the optimization solution meets the standards. It includes multiple aspects such as the durability, reaction efficiency, comfort, weight, and safety of the device. The criteria are usually based on industry specifications, user requirements, and design goals. The final optimization solution refers to the solution selected after evaluation, which has the best comprehensive performance and meets the preset standards. 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 the chemical oxygen self-rescue breathing apparatus. Specific thresholds will be set for each indicator according to industry standards or user requirements. Use simulation tools (such as MATLAB, ANSYS) to evaluate the performance of each optimization plan. Through simulation technology, the performance of the breathing apparatus under different working conditions can be simulated, and specific performance data for each plan can be obtained, such as reaction time, temperature change, airflow control, etc.

[0039] Compare the performance data of each optimization plan with the preset performance standards to evaluate whether it meets each standard. Based on the performance evaluation, a cost-benefit analysis of each plan also needs to be carried out, including material costs, production costs, maintenance costs, 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-making analysis methods (such as the Analytic Hierarchy Process AHP or TOPSIS) to comprehensively rank multiple plans. This method can consider the relative importance of multiple indicators and give the optimal plan ranking according to the weights of various performances and costs.

[0041] Based on the performance evaluation, cost analysis, and comprehensive ranking, select the plan that best meets the preset performance standards and has the highest cost performance as the final optimization plan.

[0042] Through the evaluation of multiple optimization plans, the advantages and disadvantages of different plans can be systematically analyzed to ensure that the selected final plan not only meets all the preset performance standards but also achieves optimal cost control. The final optimization plan significantly improves the overall performance of the chemical oxygen self-rescue breathing apparatus under different working conditions and reduces the production cost, achieving a balance between technology and cost.

[0043] Step S600: According to the final optimization plan, optimize the prototype of the chemical oxygen self-rescue breathing apparatus and conduct actual performance tests, and adjust the prototype according to the test results.

[0044] Specifically, the prototype refers to the physical sample of the equipment 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 characteristics of the design, but still needs to be adjusted and improved in terms of function and structure.

[0045] Make the prototype of the chemical oxygen self-rescue breathing apparatus according to the final optimization plan. The prototype production process needs to ensure that the size, materials, and structure of the equipment are consistent with the final design so that the performance of the equipment can be truly reflected in the test.

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

[0047] If the test results show that the prototype fails to 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 breathing apparatus is prone to deformation in a high-temperature environment, a heat-resistant composite material can be considered for replacement. During this process, local optimization can be carried out with the help of finite element analysis (FEA) or multi-physics simulation tools. For example, if the internal chemical reaction rate is not ideal, simulation software can be used to analyze the reaction process of different chemical components and optimize the ratio of reaction agents or the structure of the reaction chamber. The adjusted prototype will be tested again to verify whether the modified design solves 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 according to the final optimization plan and conducting actual performance tests, the performance of the design in the real environment can be quickly verified to ensure its safety and reliability under extreme conditions. The repeated test and adjustment process helps to eliminate potential design defects and optimize the overall performance of the equipment.

[0049] Furthermore, based on the basic parameters, a parameter optimization model of the chemical oxygen self-rescue breathing apparatus is established, including: based on the basic parameters, through data analysis and data mining, obtain the historical performance data of the chemical oxygen self-rescue breathing apparatus; adopt machine learning algorithms to analyze the correlation of the historical performance data, construct the external structure parameter model, analyze the chemical reaction efficiency and energy conversion efficiency in the historical performance data, and construct the internal working parameter model; integrate the external structure parameter model and the internal working parameter model to obtain an initial parameter optimization model; conduct a preliminary verification on the initial parameter optimization model to obtain a preliminary verification result; based on the preliminary verification result, perform iterative optimization on 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 a large amount of data through statistical methods, machine learning techniques, database queries, etc. Historical performance data refers to the performance index data recorded during the past use or testing of a chemical oxygen self-rescue respirator, such as oxygen generation amount, energy conversion efficiency, breathing resistance, etc. The initial parameter optimization model refers to the first version model obtained by integrating the external structure parameter model and the internal working parameter model, which is used for subsequent verification and optimization.

[0051] Through data analysis and data mining, obtain the historical performance data of the chemical oxygen self-rescue respirator from experimental records, user feedback, and market surveys. Use database management tools (such as MySQL) or data analysis software (such as the Pandas library in Python) for data sorting and cleaning to ensure the accuracy and integrity of the data.

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

[0053] Integrate the external structure parameter model and the internal working parameter model to obtain the initial parameter optimization model. This process can be implemented through MATLAB or Simulink. Verify the initial parameter optimization model by comparing the actual test data with the model prediction results to evaluate the accuracy of the model.

[0054] According to the preliminary verification results, perform iterative optimization on the initial parameter optimization model. This process can adopt methods such as genetic algorithms and particle swarm optimization to make multiple adjustments and optimizations for the discovered model deviations, and finally form an accurate parameter optimization model.

[0055] Through this step, the established parameter optimization model can more accurately predict the performance of the chemical oxygen self-rescue respirator 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] Further, integrating the external structure parameter model and the internal working parameter model to obtain an initial parameter optimization model includes: 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 influence of external structure changes on internal working parameters and the feedback effect of internal working parameter adjustment 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, the key connection points refer to the points of interaction and influence between external structure parameters and internal working parameters. For example, the material selection of a device not only affects its weight and durability but also the efficiency of internal chemical reactions. The data interface is a design tool for data exchange between the external structure model and the internal working model to ensure seamless cooperation between the two models. Multi-physics field simulation technology is a technology used to simulate the interaction between different physical fields (such as mechanics, thermotics, electromagnetic fields, etc.) for predicting the overall performance of a device under different design and working conditions. Joint optimization means that during the optimization process, by simultaneously adjusting external structure parameters and internal working parameters, the optimal combination for overall performance is found.

[0058] First, analyze how external structure parameters (such as the material and shape of a 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 a material affects the heat management of a chemical reaction and can thus be regarded as a key connection point.

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

[0060] Use multi-physics field simulation software (such as COMSOL Multiphysics) to simulate the influence of external structure changes on internal working parameters. For example, how changing the external material and size of a respirator affects the internal chemical reaction efficiency and energy conversion. This simulation process can reveal the complex influence of external structure changes on internal chemical reactions. At the same time, the simulation can also model the influence of internal working parameter adjustment on the external structure feedback, such as how reaction heat affects the surface temperature of the device.

[0061] Adopt optimization strategies such as genetic algorithms and particle swarm algorithms to jointly optimize the external structure parameters and internal working parameters. Optimization tools such as the Optimization Toolbox in MATLAB can help with the joint optimization of multiple variables to find the optimal parameter combination. For example, optimize the material selection and size design of the breathing apparatus to ensure that the device is lightweight without sacrificing its internal chemical reaction efficiency. Through the joint optimization of multiple groups of parameters, the best matching scheme for the external structure and internal performance can be obtained.

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

[0063] Furthermore, according to the parameter optimization model, conduct parameter optimization analysis to obtain the parameter optimization analysis results. Among them, the parameter optimization analysis includes analyzing the performance of the chemical oxygen self-rescue breathing apparatus under different working conditions and adjusting the external structure parameters and the internal working parameters, including: defining the working condition range of the chemical oxygen self-rescue breathing apparatus; using the parameter optimization model to simulate the performance of the chemical oxygen self-rescue breathing apparatus within the working condition range to obtain performance index data; identifying potential factors causing performance degradation under specific working conditions to obtain performance degradation factors; for the performance degradation factors, design different adjustment schemes for the external structure parameters, and at the same time, adjust the internal working parameters; evaluate the adjusted external structure parameters and internal working parameters, and through comparative analysis, obtain the parameter optimization analysis results.

[0064] Specifically, the working condition range refers to various environmental conditions encountered by the chemical oxygen self-rescue breathing apparatus during actual use, such as temperature, pressure, oxygen concentration, humidity, etc. Defining these ranges helps ensure that the device can operate normally under various extreme conditions. The performance index data refers to the performance data of the breathing apparatus obtained through simulation or actual testing under different conditions, usually including key indicators such as reaction rate, gas generation amount, working time, and structural stability. The performance degradation factors refer to the factors causing the performance degradation of the device 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 breathing apparatus. This includes environmental temperature, air pressure, humidity, and the breathing rate of the breathing apparatus user, etc. For example, the mine working environment is usually high temperature, high humidity, and low oxygen. The condition range is set as the temperature between 20°C and 60°C, the oxygen concentration is 15% - 20%, and the pressure is 1 - 5 atmospheres. By defining such working conditions, it is ensured that the optimization analysis can cover all usage scenarios.

[0066] Utilize the parameter optimization model to simulate the performance of the breathing apparatus within the above-mentioned working condition range. This can be achieved through tools such as finite element analysis (FEA) and computational fluid dynamics simulation. For example, finite element analysis can simulate the deformation of the breathing apparatus housing material under high-pressure environments, while computational fluid dynamics simulation can analyze the gas flow and chemical reaction efficiency inside the breathing apparatus. Through these simulation tools, performance index data of the breathing apparatus under various conditions can be obtained, such as the gas generation rate, continuous oxygen supply time, etc.

[0067] Analyze the simulation results to identify which factors cause the performance of the breathing apparatus to decline under certain specific conditions. For example, if under high-temperature and high-pressure conditions, the reactant inside the breathing apparatus decomposes insufficiently, resulting in insufficient oxygen generation, this is a performance decline factor. Another example is the material fatigue problem of the housing under high pressure. If the housing material is too thin, deformation or rupture may occur during long-term use, affecting the safety of the equipment.

[0068] For the identified performance decline factors, design different external structure and internal working parameter adjustment schemes. For example, for the problem of insufficient reactant decomposition, the structure of the reaction chamber can be optimized or the component ratio of the reactant can be adjusted. For the housing material, a more pressure-resistant composite material can be selected to enhance its strength. Advanced optimization methods such as genetic algorithms and particle swarm optimization algorithms can be used as optimization tools to perform multiple iterative optimizations on the external structure and internal working parameters. Through these adjustments, the best design combination can be found.

[0069] Through simulating the adjusted external structure and internal working parameters, conduct performance tests again to obtain a new round of performance data. Then, compare and analyze the performance data before and after the adjustment to evaluate the advantages and disadvantages of each adjustment scheme.

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

[0071] Furthermore, based on the parameter optimization analysis results, multiple optimization schemes are generated, including different combinations of external structure parameters and internal working parameters, specifically: based on the parameter optimization analysis results, a combinatorial optimization algorithm is used to generate multiple external structure parameter combination schemes, and similarly, a combinatorial optimization algorithm is used to generate multiple internal working parameter combination schemes; the external structure parameter combination schemes are matched with the internal working parameter combination schemes to form multiple optimization schemes.

[0072] Specifically, a combinatorial optimization algorithm is an algorithm used to find the optimal combinations of multiple variables (such as external structure 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 multi-variable space. The external structure parameter combination schemes are different external structure parameter combination schemes designed based on the optimization analysis results, such as the shape, material, size, etc. of the breathing apparatus, aiming to improve its physical properties such as weight, durability, comfort, etc. The internal working parameter combination schemes are optimization schemes designed for the internal chemical reactions and gas flow and other working mechanisms of the breathing apparatus, including reactant ratio, reaction chamber structure, gas flow rate, etc. These combination schemes directly affect the reaction efficiency and gas generation amount of the breathing apparatus.

[0073] First, based on the parameter optimization analysis results, the key parameters affecting the external structure performance are identified. Next, a combinatorial optimization algorithm is used to generate multiple external structure parameter combination schemes. Similarly, the internal working parameters are optimized using a combinatorial optimization algorithm. In this step, a simulated annealing algorithm is used to adjust parameters such as reactant ratio and reaction chamber volume. The simulated annealing algorithm avoids getting stuck in local optimal solutions by simulating the thermodynamic annealing process, thus finding the global optimal solution.

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

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

[0076] Furthermore, evaluating the multiple optimization solutions and selecting the final optimization solution that meets the preset performance criteria includes: establishing an evaluation index system that covers the key performance indicators of the chemical oxygen self-rescue breathing apparatus; according to the multiple optimization solutions, using the parameter optimization model to obtain the performance index data of each optimization solution under different working conditions; comparing the performance index data with the preset performance criteria to evaluate the compliance degree of each optimization solution and obtain the performance evaluation result; considering cost-benefit analysis, including material costs, manufacturing costs, and long-term maintenance costs, to conduct a cost evaluation of the multiple optimization solutions and obtain the cost evaluation result; comprehensively considering the performance evaluation result and the cost evaluation result, using a multi-criteria decision analysis method to rank the multiple optimization solutions and obtain the optimization solution ranking; and selecting the final optimization solution according to the optimization solution ranking.

[0077] Specifically, the performance index data refers to the numerical data generated when each optimization solution operates under specific conditions and is used to measure the performance of the solution. For example, the oxygen supply duration of a certain structure in a high-temperature environment or the start-up reaction time in a low-temperature environment. The multi-criteria decision analysis method (MCDA) is an analysis method used to handle multiple decision criteria (such as performance, cost, durability, etc.) and aims to provide a reasonable ranking for each solution by considering the weights of different criteria and finally select the optimal solution. Commonly used MCDA methods include the Analytic Hierarchy Process (AHP), TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), etc.

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

[0079] According to each optimization solution, use the parameter optimization model to simulate its performance under different working conditions. Compare the obtained performance index data with the predefined performance criteria (such as national standards or enterprise internal standards) to evaluate the compliance of each solution.

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

[0081] Comprehensive performance evaluation and cost-benefit analysis are carried out, and multiple optimization schemes are ranked using multi-criteria decision analysis methods. For example, using the TOPSIS method, the relative distance between each scheme and the ideal solution can be calculated, and then ranked according to the distance to obtain the optimal scheme. Example: Although the performance of Scheme B is the best, its cost is high. The cost of Scheme A is relatively low and its performance is close to the ideal solution. Finally, Scheme A is selected as the optimal scheme.

[0082] According to the ranking results of each scheme, determine the final scheme that meets the preset performance criteria and has the best cost performance. This process requires multiple iterations and adjustments to finally determine the scheme 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 breathing apparatuses can be effectively screened out. During the evaluation process, not only the performance of the breathing apparatus under different environmental conditions is compared in detail, but also the cost-benefit is comprehensively considered through multi-criteria decision analysis methods, so as to select an optimization scheme with both high performance and low cost.

[0084] Furthermore, the establishment of the evaluation index system includes: determining the key performance index categories of the chemical oxygen self-rescue breathing apparatus; refining specific indicators for the key performance index categories; setting evaluation thresholds for the specific indicators according to industry standards and user requirements; using the analytic hierarchy process to evaluate the relative importance among the key performance index categories and determine the weight coefficients; integrating the specific indicators, the evaluation thresholds, and the weight coefficients to obtain the evaluation index system.

[0085] Specifically, the key performance index categories refer to the most important performance areas in the design and use of chemical oxygen self-rescue breathing apparatuses. Usually, it includes index categories in different dimensions such as oxygen supply time, weight, reaction efficiency, durability, and wearing comfort. Specific indicators refer to the refined measurement criteria under the key performance index categories. Specific indicators are specific data or characteristics that quantitatively or qualitatively describe the performance of the breathing apparatus. 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, usually determined according to industry standards, user requirements, or technical levels. The analytic hierarchy process (AHP) is a multi-criteria decision-making method used to determine the relative importance among different indicator categories. By expert scoring or comparative analysis, the weight coefficients of each performance indicator are determined, providing a reference basis for decision-making.

[0086] First of all, it is necessary to determine its core performance dimensions according to the design objectives and actual applications of the chemical oxygen self-rescue breathing apparatus. Usually, it includes oxygen supply time, weight, chemical reaction efficiency, wearing comfort, and durability, etc.

[0087] For each key performance category, specific measurable indicators are further refined. 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)". Minimum or maximum required values are set for each specific indicator according to industry standards and user requirements.

[0088] To determine the importance of each key performance category, the Analytic Hierarchy Process (AHP) is used. This method obtains the relative weights of different categories by comparing and analyzing their importance. AHP can adopt the method of expert scoring and use software tools such as MATLAB or Python for calculation to generate the corresponding weight coefficients.

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

[0090] By establishing an evaluation index system, the performance of different chemical oxygen self-rescue breathing apparatus 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, the importance of different indicators can be reasonably balanced according to user needs and the priorities of actual applications, and finally provides an accurate basis for the selection and optimization of the solution. It significantly improves the decision-making efficiency, avoids the situation of ignoring other key factors due to excessive focus on a certain performance during the design process, and ensures that the comprehensive performance of the final product better meets user needs and industry standards.

[0091] In summary, the structural parameter optimization method for chemical oxygen self-rescue breathing apparatus provided by the embodiments of this application has the following technical effects:

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

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

[0094] 3. Based on parameter optimization analysis, multiple combination schemes of external structures and internal working parameters are generated, which can provide diverse design options for the design team, explore the performance of different schemes under different conditions, and thus achieve performance optimization from multiple perspectives.

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

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

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

[0098] Optimization analysis result acquisition module 13: configured to perform parameter optimization analysis according to the parameter optimization model to obtain a parameter optimization analysis result, where 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 generation module 14: configured to generate multiple optimization schemes based on the parameter optimization analysis result, including different combinations of external structural parameters and internal working parameters;

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

[0101] Optimization adjustment module 16: configured to optimize the prototype of the chemical oxygen self-rescue respirator according to the final optimization scheme and perform an actual performance test, and adjust the prototype according to the test result.

[0102] Further, the parameter optimization model establishment module 12 is further configured to perform the following steps:

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

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

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

[0106] Conduct a preliminary verification on the initial parameter optimization model to obtain a preliminary verification result;

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

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

[0109] Determine the key connection points between the external structure parameter model and the internal working parameter model;

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

[0111] Utilize multi-physics field simulation technology to simulate the influence of external structure changes on internal working parameters and the feedback effect of internal working parameter adjustments on the external structure;

[0112] Combine optimization strategies to jointly optimize the external structure parameter model and the internal working parameter model 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 working condition range of the chemical oxygen self-rescuer;

[0115] Utilize the parameter optimization model to simulate the performance of the chemical oxygen self-rescuer within the working condition range to obtain performance index data;

[0116] Identify potential factors for performance degradation under specific working conditions to obtain performance degradation factors;

[0117] For the performance degradation factors, design different external structure parameter adjustment schemes, and at the same time, adjust the internal working parameters;

[0118] Evaluate the adjusted external structure parameters and internal working parameters, and through comparative analysis, obtain the parameter optimization analysis result.

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

[0120] Based on the parameter optimization analysis result, adopt a combinatorial optimization algorithm to generate multiple external structure parameter combination schemes, and similarly use the combinatorial optimization algorithm to generate multiple internal working parameter combination schemes;

[0121] Match the external structure parameter combination scheme with the internal working parameter combination scheme to form multiple optimization schemes.

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

[0123] Establish an evaluation index system, which covers the key performance indicators of the chemical oxygen self-rescue breathing apparatus;

[0124] According to the multiple optimization schemes, use the parameter optimization model to obtain the performance index data of each optimization scheme under different working conditions;

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

[0126] Consider cost-benefit analysis, including material costs, manufacturing costs, and long-term maintenance costs, conduct a cost evaluation on the multiple optimization schemes, and obtain the cost evaluation result;

[0127] Integrate the performance evaluation result and the cost evaluation result, and use the multi-criteria decision analysis method to rank the multiple optimization schemes to obtain the optimization scheme ranking;

[0128] Select the final optimization scheme according to the optimization scheme ranking.

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

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

[0131] Refine specific indicators for the key performance indicator categories;

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

[0133] Adopt the analytic hierarchy process to evaluate the relative importance among the key performance indicator categories and determine the weight coefficients;

[0134] Integrate the specific indicators, the evaluation thresholds, and the weight coefficients to obtain the evaluation index system.

[0135] Any step of the above-described method can be stored as computer instructions or programs in an unrestricted computer memory and can be called and recognized by an unrestricted computer processor to implement any one of the methods in the embodiments of the present application, and no redundant limitations are made here.

[0136] Further, the first or second as described above does not only represent an order relationship, but also represents a specific concept, and / or refers to the option of selecting individually or all among multiple elements. Obviously, those skilled in the art can make various changes and modifications to this application without departing from the scope of this application. Thus, if these modifications and variations of this application fall within the scope of this application and its equivalent technologies, this application is intended to include these changes and modifications.

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, optimizing the prototype of the chemical oxygen self-rescue respirator and conducting actual performance tests, and adjusting the prototype according to the test results; Wherein, the parameter optimization model of the chemical oxygen self-rescue respirator is established based on the basic parameters, including: 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, iteratively optimize the initial parameter optimization model to obtain the parameter optimization model; The step of integrating the external structural parameter model and the internal working parameter model to obtain an initial parameter optimization model includes: 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.

2. 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.

3. 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.

4. 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.

5. The structural parameter optimization method for a chemical oxygen self-rescue respirator according to claim 4, 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.

6. 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 5, 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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