Integrated design method of multi-environment self-adaptive wearable protective equipment

Abstract

An integrated design method of multi-environment self-adaptive wearable protective equipment comprises the following steps: comprehensively analyzing various factors of a target use environment, including but not limited to extreme climate conditions, types and concentrations of chemical pollutants, physical impact strength and specific activity requirements of a user; a big data analysis technology is utilized to predict an environment change trend and specific requirements of changes on the performance of protective equipment, functional modules with self-adaptive characteristics are designed, the functional modules comprise an intelligent temperature control system, a chemical protective layer, a physical impact absorption structure and an energy management system, and each functional module is made of an intelligent material. By integrating the intelligent temperature control system, the chemical protection layer, the physical impact absorption structure and the energy management system, the safety of a user in different environments is ensured, and the environment change and the influence of the environment change on the performance can be predicted by using big data analysis and machine learning algorithms and equipment, so that the state of a functional module is adjusted in advance, and potential risks are avoided.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of adaptive protection, and specifically relates to an integrated design method of a multi-environment adaptive wearable protective equipment. BACKGROUND

[0002] In the rapidly developing modern society, people are facing increasingly complex and changing environmental challenges. From extreme weather conditions to potential chemical pollutant exposure, to physical impact risks, these environmental factors all pose higher requirements for personal safety protection.

[0003] Traditional wearable protective equipment often has single function, is difficult to adapt to changes in multiple complex environments, and often lacks intelligence and adaptability, which cannot meet the safety needs of users in different environments.

[0004] In particular, in terms of chemical protection, traditional equipment often uses single protective materials, which are difficult to provide effective targeted protection for different types of chemical pollutants. At the same time, when facing physical impact, the energy absorption effect and stress dispersion ability of traditional equipment are limited, which cannot fully protect users from harm.

[0005] In terms of energy management, traditional wearable equipment usually lacks intelligent adjustment mechanism, which cannot intelligently allocate energy according to the working state of the functional module and the user demand, thereby limiting the use time of the equipment. At the same time, due to the lack of effective user feedback mechanism, the performance optimization and continuous improvement of the equipment are often hindered. SUMMARY

[0006] In view of the above situation, in order to overcome the defects of the prior art, the application provides an integrated design method of a multi-environment adaptive wearable protective equipment, to at least partially solve the above technical problems.

[0007] The technical scheme adopted by the application is as follows:

[0008] The application provides an integrated design method of a multi-environment adaptive wearable protective equipment, comprising the following steps:

[0009] Step one, first, comprehensively analyze multiple factors of the target use environment, including but not limited to extreme weather conditions, types and concentrations of chemical pollutants, physical impact intensity, and user specific activity requirements; use big data analysis technology to predict environmental change trends and specific requirements of the change on the performance of the protective equipment;

[0010] Step two, based on the results of the environmental demand analysis, design functional modules with adaptive characteristics, including intelligent temperature control system, chemical protection layer, physical impact absorption structure and energy management system, each functional module uses intelligent materials such as shape memory alloy, piezoelectric material and phase change material to realize environmental response adjustment;

[0011] Step three, using 3D printing technology, according to the user's body data to build the basic framework of wearable equipment, the framework focuses on lightweight, flexibility and durability, while integrating environmental perception sensors and adaptive control system;

[0012] Step four, embedding the adaptive control system in the integrated framework, the system can monitor environmental changes and user status in real time, predict future environmental changes through algorithm analysis, and automatically adjust the working state of the functional modules to provide the best protection effect;

[0013] Step five, after the integrated design is completed, comprehensive testing is carried out, including environmental simulation testing, user comfort testing, functional performance testing, and optimization and adjustment of the equipment according to the test results;

[0014] Step six, after the equipment is put into use, collect user feedback, and iteratively optimize the equipment to improve user experience and equipment performance.

[0015] In one embodiment of the present application, in step one, machine learning algorithms are used to analyze environmental data to identify potential environmental risk factors and predict the specific impact of these risk factors on the performance of protective equipment.

[0016] In one embodiment of the present application, in step two, the intelligent temperature control system includes a phase change material layer and a shape memory alloy adjustment mechanism, which can automatically adjust the heat preservation or heat dissipation performance according to the change of environmental temperature; the chemical protection layer adopts a multi-layer composite structure, each layer provides protection against different chemical pollutants; the physical impact absorption structure adopts a nonlinear elastic material, which can effectively absorb energy and disperse stress when impacted.

[0017] In one embodiment of the present application, in step three, 3D printing technology uses high-performance polymers or metal matrix composites to ensure the lightweight and high strength of the framework.

[0018] In one embodiment of the present application, in step four, the environmental perception sensors include temperature sensors, humidity sensors, radiation sensors and chemical sensors, which can monitor environmental changes in real time; the adaptive control system uses deep learning algorithms to predict future environmental changes based on sensor data and user historical behavior, and automatically adjusts the working state of the functional modules.

[0019] In one embodiment of the present application, in step five, environmental simulation testing includes testing under extreme environmental conditions such as high temperature, low temperature, high humidity and strong radiation; user comfort testing evaluates the comfort and breathability of the equipment when worn for a long time; functional performance testing evaluates the working performance and stability of each functional module under extreme environmental conditions.

[0020] In an embodiment of the present application, in step six, real-time analysis and processing of user feedback are performed using cloud computing and big data technology to quickly identify existing problems and improvement directions of the equipment; at the same time, a user community is established to encourage users to share their use experience and improvement suggestions to promote the continuous optimization of the equipment.

[0021] In an embodiment of the present application, the integrated design method of multi-environment adaptive wearable protective equipment further comprises the following technical features:

[0022] In the intelligent temperature control system, the shape memory alloy adjusting mechanism can automatically adjust its shape and size according to the change of the environmental temperature, thereby changing the air circulation and heat preservation performance inside the equipment;

[0023] In the chemical protection layer, a multi-layer composite structure is adopted, each layer provides targeted protection against different chemical pollutants, and a microporous structure is arranged between the layers to improve air permeability and comfort;

[0024] In the physical impact absorption structure, a honeycomb structure made of nonlinear elastic material is adopted, which can effectively absorb energy and disperse stress when impacted, protecting the user from injury.

[0025] The beneficial effects of the technical scheme of the present application are:

[0026] The present application integrates an intelligent temperature control system, a chemical protection layer, a physical impact absorption structure and an energy management system, so that the wearable protective equipment can adaptively adjust according to real-time environmental changes to ensure the safety of the user in different environments, and using big data analysis and machine learning algorithms, the equipment can predict environmental changes and their impact on performance, so as to adjust the state of the functional modules in advance to avoid potential risks.

[0027] The present application adopts a multi-layer composite structure in the chemical protection layer to provide targeted protection against a variety of chemical pollutants, ensuring that the user is protected from harmful substances, and the physical impact absorption structure uses nonlinear elastic material to effectively absorb energy and disperse stress when impacted, protecting the user from physical injury. Using 3D printing technology, the basic framework is constructed according to the user's body data to ensure that the equipment fits the user's body shape, providing the best comfort and flexibility.

[0028] The present application can intelligently adjust energy distribution according to the working state of the functional modules and user demand through the energy management system, prolonging the use time of the equipment, and through real-time analysis of user feedback by cloud computing and big data technology, a user community is established to encourage users to share experience, realizing the continuous optimization and performance improvement of the equipment, and through the adaptive control system, real-time monitoring and adjustment are realized, not only improving the multifunctionality of the equipment, but also ensuring its efficient operation in complex and variable environments.

[0029] The application realizes lightweight, high strength and personalized customization of equipment by adopting shape memory alloy, piezoelectric material and phase change material intelligent material, combining with 3D printing technology to construct a basic framework, and the innovative application not only improves the performance of the equipment, but also reduces the manufacturing cost. The environment data is analyzed and predicted by using big data analysis and machine learning algorithm, so as to realize accurate response and predictive maintenance of the equipment to the environmental change.

[0030] Additional aspects and advantages of the present application will be in part apparent and in part pointed out hereinafter. BRIEF DESCRIPTION OF DRAWINGS

[0031] The above and / or additional aspects and advantages of the present application will become apparent and be readily appreciated from the following description, taken in conjunction with the accompanying drawings, in which:

[0032] Figure 1 The structural schematic diagram of the integrated design method of the multi-environment adaptive wearable protective equipment proposed for the embodiments of the present application. DETAILED DESCRIPTION

[0033] Embodiments of the present application are described in detail below, examples of which are shown in the accompanying drawings, in which the same or similar reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the accompanying drawings are exemplary and are intended to explain the present application, and cannot be understood as a limitation of the present application.

[0034] A multi-environment adaptive wearable protective equipment integrated design method of an embodiment of the present application is described below with reference to the accompanying drawings.

[0035] As shown in Figure 1 The embodiment of the present application provides an integrated design method of a multi-environment adaptive wearable protective equipment, which comprises the following steps:

[0036] Step one, first, a comprehensive analysis is made on various factors of the target use environment, including but not limited to extreme climate conditions, types and concentrations of chemical pollutants, physical impact strength and user specific activity requirements; the trend of environmental change and the specific requirements of the change on the performance of the protective equipment are predicted by using big data analysis technology;

[0037] Step two, based on the results of the environmental demand analysis, a functional module with adaptive characteristics is designed, including an intelligent temperature control system, a chemical protection layer, a physical impact absorbing structure and an energy management system, and each functional module adopts intelligent materials such as shape memory alloy, piezoelectric material and phase change material to realize environmental responsiveness adjustment;

[0038] Step three, using 3D printing technology, according to the user's body data to build the basic framework of wearable equipment, the framework focuses on lightweight, flexibility and durability, while integrating environmental perception sensors and adaptive control system;

[0039] Step four, embed the adaptive control system in the integrated framework, the system can monitor environmental changes and user status in real time, predict future environmental changes through algorithm analysis, and automatically adjust the working state of the functional modules to provide the best protection effect;

[0040] Step five, after the integrated design is completed, comprehensive testing is carried out, including environmental simulation testing, user comfort testing, functional performance testing, and optimization adjustment of the equipment according to the test results;

[0041] Step six, after the equipment is put into use, collect user feedback and iteratively optimize the equipment to improve user experience and equipment performance.

[0042] In the specific application of the embodiment of the present application, in step one, the comprehensive analysis of the target use environment is the basis for designing multi-environment adaptive wearable protective equipment, which not only involves the investigation of extreme climate conditions, chemical pollutant types and concentrations, and physical impact strength natural factors, but also needs to deeply understand the specific activity needs of users, such as military operations, outdoor exploration or industrial work. The application of big data analysis technology can predict environmental change trends through analysis of historical data, thereby providing a scientific basis for the performance of protective equipment. For example, by analyzing historical climate data, extreme weather conditions in the future period can be predicted, thereby guiding the design of the intelligent temperature control system.

[0043] Establish an environmental database to collect and organize historical climate, pollutant emission, and physical impact related data, use big data analysis technology to build an environmental prediction model to predict the trend of the target use environment, and according to the prediction results, determine the main environmental factors that the protective equipment needs to cope with, and provide a basis for subsequent design.

[0044] In step two, based on the results of environmental demand analysis, the functional modules with adaptive characteristics are the key, including intelligent temperature control system, chemical protection layer, physical impact absorption structure and energy management system, the application of smart materials such as shape memory alloy, piezoelectric material and phase change material enables these functional modules to automatically adjust the working state according to environmental changes, thereby providing the best protection effect. For example, shape memory alloy can change shape when the temperature changes, thereby adjusting the tightness and thermal insulation performance of the equipment; piezoelectric material can generate electricity through pressure changes to provide continuous energy support for the equipment.

[0045] In step three, the basic framework of the wearable equipment is constructed using 3D printing technology, which not only improves the degree of individual customization of the equipment, but also realizes the balance of lightweight, flexibility and durability. At the same time, environmental perception sensors and adaptive control systems are integrated into the framework, enabling the equipment to monitor environmental changes in real time and make corresponding adjustments.

[0046] In step four, the embedding of the adaptive control system enables the equipment to monitor environmental changes and user status in real time, and predict future environmental changes through algorithm analysis. The system automatically adjusts the working state of the functional modules according to the prediction results to provide the best protection effect, so that the equipment can intelligently adjust according to different environmental conditions and user needs, improving the practicality and user experience of the equipment.

[0047] In step five, comprehensive testing is the key to ensuring the performance and quality of the equipment, including environmental simulation testing, user comfort testing and functional performance testing. Through testing, problems in the design or manufacturing process of the equipment can be found and optimized, so that the equipment can be strictly tested and verified before being put into use, ensuring its good performance and user experience.

[0048] In step six, collecting user feedback and iterative optimization is an important means to improve the performance and user experience of the equipment. By collecting user feedback during use, the equipment can be improved and optimized to adapt to market demand and user changes, maintaining its competitiveness and vitality.

[0049] The user feedback is analyzed and sorted to determine the aspects of the equipment that need to be improved and optimized, and an iterative optimization plan is developed to improve and optimize the equipment. The improved equipment is re-entered into the market for testing and verification to ensure that its performance and user experience are improved.

[0050] In one embodiment of the present application, in step one, machine learning algorithms are used to analyze environmental data to identify potential environmental risk factors and predict the specific impact of these risk factors on the performance of protective equipment.

[0051] In step two, the intelligent temperature control system includes a phase change material layer and a shape memory alloy adjustment mechanism, which can automatically adjust the heat preservation or heat dissipation performance according to the change of environmental temperature; the chemical protection layer adopts a multi-layer composite structure, each layer provides protection against different chemical pollutants; the physical impact absorbing structure uses nonlinear elastic material, which can effectively absorb energy and disperse stress when impacted.

[0052] In specific applications, in step one, key information is extracted from massive environmental data, and potential environmental risk factors are identified, including extreme weather, chemical pollution, and physical impact. These factors have different performance requirements for wearable protective equipment. Through machine learning algorithms, the occurrence probability and intensity of these risk factors can be accurately predicted, and their specific effects on equipment performance, such as reduced insulation performance, chemical protection layer failure, and physical structure damage, can be further analyzed.

[0053] First, data from multiple environmental sensors, including temperature, humidity, chemical pollutant concentration, and air pressure, need to be collected. Then, these data are cleaned, denoised, and normalized to improve data quality and consistency. Feature extraction techniques in machine learning algorithms are used to extract features useful for identifying environmental risk factors from preprocessed data. These features should fully reflect the complexity and variability of the environment.

[0054] Based on the extracted features, a machine learning model is constructed for training. During training, historical environmental data and known equipment performance are used as training samples to enable the model to learn the relationship between risk factors and equipment performance. After training, the model can be used to predict future environmental risk factors and their specific effects on equipment performance.

[0055] The intelligent temperature control system combines a phase change material layer and a shape memory alloy adjustment mechanism to automatically adjust the equipment's insulation or heat dissipation performance according to real-time changes in environmental temperature. The phase change material layer adjusts temperature by absorbing or releasing heat, while the shape memory alloy adjustment mechanism controls ventilation and insulation effects by changing shape, improving equipment comfort and ensuring stable performance in various climate conditions.

[0056] Select appropriate phase change materials and determine their phase transition temperature points. Then, uniformly coat the phase change materials on the inner layer or specific parts of the equipment to form a thin film with temperature regulation function. According to the structure and use requirements of the equipment, design the shape, size, and arrangement of the shape memory alloy adjustment mechanism to ensure that the adjustment mechanism accurately responds to temperature changes and controls ventilation and insulation effects by changing shape.

[0057] The phase change material layer and the shape memory alloy adjusting mechanism are connected with the intelligent control system to realize real-time collection and analysis of temperature data and sending of control instructions. The intelligent control system automatically adjusts the temperature state of the equipment according to the environmental temperature and preset performance requirements. The chemical protection layer adopts a multi-layer composite structure, each layer of which provides special protection against different types of chemical pollutants, thereby improving the protection performance of the equipment and ensuring the stability and durability of the equipment in complex chemical environments. The selection of each layer of protective material is strictly screened and tested to ensure that it has good chemical stability, corrosion resistance and air permeability.

[0058] Firstly, the chemical pollutants in the target environment are comprehensively analyzed to determine their types, concentrations and toxicity characteristics. This helps to determine the required protection type and level. According to the analysis results of the chemical pollutants, materials with corresponding protection performance are selected for testing. During the testing process, the chemical stability, corrosion resistance and air permeability of the materials are evaluated to ensure that the materials meet the design requirements. The selected protective materials are combined together in a specific order and manner to form a multi-layer composite structure, each layer of which provides protection against different chemical pollutants to ensure that the equipment can maintain excellent performance in complex chemical environments.

[0059] The physical impact absorbing structure is made of nonlinear elastic material, which has excellent energy absorption and dispersion capacity. When impacted, the nonlinear elastic material can quickly deform and absorb a large amount of impact energy, while dispersing it to a larger area, thereby reducing the damage to the equipment and human body.

[0060] Nonlinear elastic material selection and testing: suitable nonlinear elastic materials are selected and their performance is tested. During the testing process, the elastic modulus, yield strength and fracture toughness of the materials are evaluated to ensure that the materials meet the design requirements. According to the structure and use requirements of the equipment, the shape, size and arrangement of the impact absorbing structure are designed to ensure that the structure can quickly deform and absorb energy when impacted, while dispersing it to a larger area. The impact absorbing structure is connected to the main part of the equipment and overall testing is performed. During the testing process, various impact scenarios are simulated to evaluate the impact resistance and safety of the equipment.

[0061] In one embodiment of the present application, in step three, 3D printing technology uses high-performance polymer or metal matrix composite materials to ensure the lightweight and high strength of the frame.

[0062] In step four, the environmental perception sensors include temperature sensors, humidity sensors, radiation sensors and chemical sensors, which can monitor environmental changes in real time; the adaptive control system uses deep learning algorithms to predict future environmental changes based on sensor data and user historical behavior, and automatically adjust the working state of the functional modules.

[0063] In specific applications, in step three, 3D printing is introduced to manufacture the frame of wearable protective equipment, providing strong support for lightweight and high-strength frame. High-performance polymers or metal matrix composites are used as the main materials for 3D printing, which have excellent mechanical properties and corrosion resistance, enabling lightweight frame while ensuring strength. By precisely controlling the printing path and layer thickness, the structure of the frame can be further optimized to improve its carrying capacity and stability.

[0064] According to the use environment and performance requirements of wearable protective equipment, suitable high-performance polymers or metal matrix composites are selected, and comprehensive performance tests are conducted on the selected materials, including tensile strength, bending strength, and impact toughness, to ensure that they meet the design requirements. CAD software is used to design the frame model of wearable protective equipment, considering lightweight, high-strength, and ergonomic factors. Through simulation analysis, the structure of the frame is optimized, such as adding reinforcing ribs and adjusting wall thickness, to improve its carrying capacity and stability.

[0065] According to the characteristics of the selected materials and frame model, appropriate 3D printing process parameters are set, including printing speed, layer thickness, and nozzle diameter. The optimization of parameters will directly affect the printing quality and performance of the frame. After printing, necessary post-processing is performed on the frame, such as removing support structures and polishing the surface. Then, performance tests are conducted, including weight, strength, and stiffness measurements, to verify whether the frame meets the design requirements.

[0066] In step four, multiple environmental perception sensors and adaptive control systems are integrated to realize the intelligent response of wearable protective equipment to complex environments. Temperature sensors, humidity sensors, radiation sensors, and chemical sensors can monitor environmental changes in real time and provide accurate data support for the adaptive control system. The adaptive control system uses deep learning algorithms to predict future environmental changes based on sensor data and user historical behavior, and automatically adjusts the working state of functional modules, such as adjusting ventilation, heating, and chemical protection, to ensure that the equipment provides the best protection effect in various environments. According to the use environment and performance requirements of wearable protective equipment, appropriate sensor types are selected and reasonably arranged in key parts of the equipment.

[0067] The data collected by the sensors is sent to the adaptive control system through wireless transmission. The system preprocesses the received data, including denoising, filtering, and normalization, to improve the accuracy and reliability of the data. A prediction model is constructed using deep learning algorithms, and the model is trained based on historical sensor data and user behavior data. By continuously optimizing model parameters and structure, the prediction ability of the model for future environmental changes is improved.

[0068] According to the prediction result of the deep learning model, an adaptive control strategy is formulated, and when the environmental change reaches a preset threshold, the working state of the functional module is automatically adjusted, such as increasing the ventilation volume, starting the heating device, and enhancing the chemical protection. At the same time, the control strategy is continuously optimized according to user feedback and real-time data.

[0069] In one embodiment of the present application, in step five, the environmental simulation test includes tests under various extreme environmental conditions such as high temperature, low temperature, high humidity, and strong radiation; the user comfort test evaluates the comfort and breathability of the equipment during long-term wearing; and the functional performance test evaluates the working performance and stability of each functional module in extreme environments.

[0070] In step six, cloud computing and big data technology are used to analyze and process user feedback in real time, quickly identify problems and improvement directions of the equipment, and at the same time, establish a user community to encourage users to share use experience and improvement suggestions to promote the continuous optimization of the equipment.

[0071] In the specific application of the embodiment of the present application, in step five, the environmental simulation test ensures that the wearable protective equipment can work normally under various extreme environmental conditions, not only covering extreme environments such as high temperature, low temperature, high humidity, and strong radiation, but also simulating various complex working conditions encountered by the equipment, thereby comprehensively evaluating the environmental adaptability of the equipment. By simulating extreme environmental conditions, the thermal stability and weather resistance of the equipment under extreme temperature and the protection efficiency of the equipment under strong radiation environment can be detected.

[0072] The user comfort test focuses on evaluating the comfort and breathability of the equipment during long-term wearing. This test collects user feedback on the wearing experience of the equipment by simulating actual use scenarios, thereby optimizing the ergonomic design and material selection of the equipment and improving the wearing comfort of the user. The functional performance test comprehensively evaluates the working performance and stability of each functional module of the equipment in extreme environments. By simulating extreme environmental conditions, it can be detected whether each functional module of the equipment can work normally and how their collaborative performance is.

[0073] An environmental simulation test system is designed and built, including simulation devices for extreme environmental conditions such as high temperature, low temperature, high humidity, and strong radiation. According to the use environment and performance requirements of the equipment, detailed test schemes and test standards are formulated, and the equipment is tested multiple times under simulated environments, the test results are recorded and analyzed, and the environmental adaptability of the equipment is evaluated.

[0074] A functional performance test scheme and test standard are formulated, covering each functional module of the equipment and their collaborative performance. The equipment is tested multiple times for functional performance, the test results are recorded and analyzed, the working performance and stability of the equipment in extreme environments are evaluated, and the functional modules of the equipment are optimized and improved according to the test results to improve the overall performance of the equipment.

[0075] In step six, real-time analysis and processing of user feedback are performed using cloud computing and big data technology. The cloud computing platform provides powerful data processing and storage capabilities, enabling rapid collection, organization, and analysis of user feedback data. Through big data technology, user feedback can be deeply mined and analyzed to quickly identify existing problems and improvement directions for the equipment. At the same time, a user community is established to encourage users to share their experiences and suggestions for improvement. The user community is not only a platform for information exchange, but also an important channel for promoting the continuous optimization and improvement of equipment. Through the interaction and feedback of the user community, the needs and expectations of users can be more accurately understood, thereby promoting the continuous optimization and upgrading of equipment.

[0076] In one embodiment of the present application, the integrated design method of multi-environment adaptive wearable protective equipment further comprises the following technical features:

[0077] In the intelligent temperature control system, the shape memory alloy adjusting mechanism can automatically adjust its shape and size according to the change of environmental temperature, thereby changing the air circulation and heat preservation performance inside the equipment.

[0078] In the chemical protection layer, a multi-layer composite structure is used, each layer provides targeted protection against different chemical pollutants, and a microporous structure is provided between the layers to improve air permeability and comfort.

[0079] In the physical impact absorption structure, a honeycomb structure made of nonlinear elastic material is used, which can effectively absorb energy and disperse stress when impacted, protecting the user from injury.

[0080] In specific applications, the application of shape memory alloy (SMA) adjusting mechanism provides the ability to automatically adjust the internal air circulation and heat preservation performance of the equipment according to the change of environmental temperature. SMA material has a unique shape memory effect, i.e., it can return to its original shape under specific temperature conditions. The SMA adjusting mechanism, through mechanical design and sensor integration, can monitor the environmental temperature in real time and automatically adjust its shape and size according to the preset algorithm. When the environmental temperature rises, the SMA adjusting mechanism will automatically expand, increasing the air circulation channel inside the equipment, thereby improving the heat dissipation efficiency and preventing the user from overheating. Conversely, when the environmental temperature decreases, the SMA adjusting mechanism will contract, reducing air circulation and enhancing the heat preservation performance of the equipment, ensuring that the user can maintain body temperature in cold environments.

[0081] SMA materials with excellent shape memory effect and high fatigue life are selected and pretreated to optimize their performance. The mechanical structure of the SMA adjusting mechanism is designed according to the use environment and ergonomics requirements of the equipment, ensuring that it can accurately and reliably adjust the air circulation channel inside the equipment.

[0082] The integrated temperature sensor and intelligent control system monitors the environmental temperature in real-time and controls the action of the SMA adjustment mechanism according to the preset algorithm. Multiple rounds of tests are conducted on the SMA adjustment mechanism to evaluate its performance under different environmental temperatures and make necessary optimization adjustments.

[0083] The chemical protection layer adopts a multi-layer composite structure, with each layer providing targeted protection against different chemical pollutants. This not only improves the protective performance of the equipment but also ensures the safety of the user in different chemical environments. Between each layer, a microporous structure is provided to improve air permeability and comfort. The microporous structure allows air and water vapor to pass through to a certain extent while ensuring protective performance, thereby reducing the feeling of dampness and stuffiness inside the equipment and improving the user's wearing experience.

[0084] Materials with excellent chemical stability and protective performance are selected, and each material is subjected to detailed performance evaluation to determine its suitability in a specific chemical environment. Based on the types and concentrations of target chemical pollutants, a multi-layer composite structure is designed to ensure that each layer provides targeted protection.

[0085] The honeycomb structure made of nonlinear elastic material can effectively absorb energy and disperse stress when impacted, not only improving the impact resistance of the equipment but also reducing the weight and volume of the equipment. Nonlinear elastic materials have a unique stress-strain relationship that can absorb a large amount of energy during impact. The honeycomb structure disperses the absorbed energy to a larger area through its unique geometry and arrangement, thereby reducing the risk of local stress concentration and damage.

[0086] It should be noted that the relationship terms such as first and second in this text are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between the entities or operations. Moreover, the term "includes", "contains" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, article or equipment including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or equipment.

[0087] The above describes the present application and its embodiments, which are not limiting, and the drawings only show one of the embodiments of the present application, and the actual structure is not limited thereto. In general, if a person skilled in the art is inspired by it, without departing from the purpose of the present application, without creative design, similar structure and embodiments of the technical solution can be designed and belong to the protection scope of the present application.

Claims

1. An integrated design method for wearable protective equipment that is adaptive to multiple environments, characterized in that, Includes the following steps: Step 1: First, conduct a comprehensive analysis of various factors in the target environment, including but not limited to extreme weather conditions, types and concentrations of chemical pollutants, intensity of physical impacts, and specific user activity needs; use big data analytics to predict environmental change trends and the specific requirements of these changes on the performance of protective equipment. Step 2: Based on the environmental demand analysis results, design functional modules with adaptive characteristics, including an intelligent temperature control system, a chemical protective layer, a physical shock absorption structure, and an energy management system. Each functional module uses intelligent materials, such as shape memory alloys, piezoelectric materials, and phase change materials, to achieve environmental responsive adjustment. Step 3: Using 3D printing technology, construct the basic framework of wearable equipment based on the user's body data. The framework emphasizes lightweight, flexibility and durability, while integrating environmental perception sensors and adaptive control systems. Step 4: Embed an adaptive control system within the integrated framework. The system can monitor environmental changes and user status in real time, predict future environmental changes through algorithm analysis, and automatically adjust the working status of functional modules to provide the best protection effect. Step 5: After the integrated design is completed, conduct comprehensive testing, including environmental simulation testing, user comfort testing, and functional performance testing. Optimize and adjust the equipment based on the test results. Step Six: After the equipment is put into use, collect user feedback and iterate and optimize the equipment to improve user experience and equipment performance.

2. The integrated design method for multi-environment adaptive wearable protective equipment according to claim 1, characterized in that, Step one also includes using machine learning algorithms to analyze environmental data to identify potential environmental risk factors and predict the specific impact of these risk factors on the performance of protective equipment.

3. The integrated design method for multi-environment adaptive wearable protective equipment according to claim 1, characterized in that, In step two, the intelligent temperature control system includes a phase change material layer and a shape memory alloy adjustment mechanism, which can automatically adjust the heat preservation or heat dissipation performance according to changes in ambient temperature; the chemical protection layer adopts a multi-layer composite structure, with each layer providing protection against different chemical pollutants; the physical impact absorption structure uses a non-linear elastic material, which can effectively absorb energy and disperse stress when subjected to impact.

4. The integrated design method for multi-environment adaptive wearable protective equipment according to claim 1, characterized in that, In step three, 3D printing technology uses high-performance polymer or metal-based composite materials to ensure the lightweight and high strength of the frame.

5. The integrated design method for multi-environment adaptive wearable protective equipment according to claim 1, characterized in that, In step four, the environmental sensing sensors include temperature sensors, humidity sensors, radiation sensors, and chemical sensors, which can monitor environmental changes in real time. The adaptive control system uses deep learning algorithms to predict future environmental changes based on sensor data and user history, and automatically adjusts the working status of functional modules.

6. The integrated design method for multi-environment adaptive wearable protective equipment according to claim 1, characterized in that, In step five, the environmental simulation test includes tests under various extreme environmental conditions such as high temperature, low temperature, high humidity, and strong radiation; the user comfort test evaluates the comfort and breathability of the equipment under long-term wear; and the functional performance test evaluates the working performance and stability of each functional module under extreme environments.

7. The integrated design method for multi-environment adaptive wearable protective equipment according to claim 1, characterized in that, In step six, cloud computing and big data technologies are used to analyze and process user feedback in real time, quickly identifying problems with the equipment and directions for improvement. At the same time, a user community is established to encourage users to share their experiences and suggestions for improvement, thereby promoting the continuous optimization of the equipment.

8. The integrated design method for multi-environment adaptive wearable protective equipment according to any one of claims 1 to 7, characterized in that, It also includes the following technical features: In intelligent temperature control systems, shape memory alloy adjustment mechanisms can automatically adjust their shape and size according to changes in ambient temperature, thereby altering the airflow and insulation performance inside the equipment. The chemical protective layer employs a multi-layer composite structure, with each layer providing targeted protection against different chemical pollutants, while microporous structures are set between the layers to improve breathability and comfort. In physical impact absorption structures, a honeycomb structure made of nonlinear elastic material is used to effectively absorb energy and disperse stress when subjected to impact, protecting users from injury.

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