Communication system, method and respiratory protection system applied to respiratory protection equipment

Abstract

The present invention belongs to the field of respiratory protection technology, and in particular, relates to a communication system, method and respiratory protection system applied to respiratory protection equipment. The communication system includes: a pairing transmission module, including a first pairing unit and a second pairing unit; a main control module, including a communication unit, a control unit and a storage unit: the communication unit is connected to the pairing transmission module for information transmission; the control unit collects and processes the identity information of the first pairing unit and / or the second pairing unit, and the pairing information. Effective communication between the respiratory protection equipment and the main control module can be achieved through the communication system, and a database of multiple respiratory protection equipment can be established through the main control module. The data can be analyzed, mined and visualized to discover the correlation and regularity between the data, so as to provide support for decision-making; the unified platform or system can also be integrated with other systems to achieve automated decision-making control and monitoring management, and improve the intelligence level of the system.

Description

Technical Field

[0001] The present invention belongs to the technical field of respiratory protection, and in particular relates to a communication system and method applied to respiratory protection equipment and a respiratory protection system. Background Art

[0002] Electric breathing equipment generally includes a main unit that can be worn around the human body's waist, a filter component detachably mounted on the main unit, a mask, a connecting tube between the main unit and the mask, a battery pack and other components.

[0003] In order to ensure that users get the best use effect, first of all, it is necessary to ensure the installation stability of the above components. For example, it is necessary to ensure that the filter components such as filter elements and gas filter canisters are installed in place to achieve effective filtration, and it is necessary to ensure the installation stability of the connecting pipe to ensure the smooth flow of air between the host and the mask, etc.; secondly, it is also necessary to ensure that some components are within the effective use time, which is particularly critical for the filter components. For example, for users who use respiratory protection equipment in toxic situations, the gas filter canister can only provide respiratory protection for a limited time. Once it is used for more than the set time, it is very likely to be suddenly exposed to toxic gas. Breaking may cause harm to the personal safety of the user. Therefore, it is necessary to record the usage time of each gas filter canister to remind the user that the gas filter canister is likely to reach the breakthrough time and needs to be replaced in time to avoid damage to personal safety. In addition, according to the noise limit requirements, different air volume controls are required according to different filter components. For example, the resistance of the gas filter canister is greater than the resistance of the filter element. Only when working in the first gear can the gas filter canister meet the relevant quiet requirements. Therefore, the air volume gear needs to be lowered for the gas filter canister, while the air volume supply of the ordinary filter element can be achieved in the second or third gear.

[0004] In response to the above-mentioned needs, effective technical means are currently available, such as using a positioning detection device to detect whether the filter component is installed in place, and accurately identifying the type and usage duration of the filter component; however, the current detection and identification data results only correspond to the use of independent respiratory protection equipment, and the user can only manually judge and operate the usage status of the respiratory protection equipment based on the corresponding data.

[0005] With the development of product technology, effective analysis and decision-making control at the big data level has become one of the directions of product design and control. This requires integrating the above data into a unified platform or system. Therefore, a dedicated system that can realize data communication of respiratory protective equipment has become a technical requirement in this field. Summary of the invention

[0006] The present invention provides a communication system, method and respiratory protection system applied to respiratory protection equipment, which can effectively solve the problems in the background technology.

[0007] In order to achieve the above object, the technical solution adopted by the present invention is:

[0008] Communication systems for respiratory protective equipment, including:

[0009] A pairing transmission module, comprising a first pairing unit and a second pairing unit which are paired and connected within a set position range and are respectively installed on different components of the respiratory protective device;

[0010] The main control module is connected to the pairing transmission modules, and includes a communication unit, a control unit and a storage unit:

[0011] The communication unit is communicatively connected with the pairing transmission module to perform information transmission;

[0012] The control unit collects and processes the identity information of the first pairing unit and / or the second pairing unit, and the pairing information of the first pairing unit and the second pairing unit, wherein the identity information at least includes component information of the corresponding respiratory protective device;

[0013] The storage unit stores the collection and processing results of the identity information and pairing information.

[0014] Furthermore, it also includes a positioning module installed at a set position of the respiratory protection device;

[0015] The communication unit is communicatively connected with the positioning module;

[0016] The control unit collects and processes the positioning information of the positioning module;

[0017] The storage unit stores the collection and / or processing results of the positioning information.

[0018] Furthermore, the control unit collects and processes the identity information, including:

[0019] Continue to determine whether a new pairing transmission module is successfully paired, until the determination result is yes, then collect the identity information of the first pairing unit and / or the second pairing unit in the pairing transmission module;

[0020] Assign the identity information:

[0021] A unique identification part, recording a unique identification of a setting component corresponding to the first pairing unit and / or the second pairing unit installed on the respiratory protective device;

[0022] The dynamic identification part records the real-time setting parameters of the setting component.

[0023] Furthermore, the storage unit stores the unique identification part only once through the first storage area, and stores the dynamic identification part corresponding to the unique identification part through the second storage area.

[0024] Furthermore, establishing the correspondence between the first storage area and the second storage area includes:

[0025] Establishing a virtual file system in the first storage area to map each unique identifier to a unique file path or file name;

[0026] The dynamic data of the real-time setting parameters are stored in the second storage area in the form of files, and the path or file name of each file corresponds to the unique identifier.

[0027] Furthermore, the main control module also includes a data processing unit for processing and analyzing the data stored in the storage unit, and realizing the prediction of the use status of the respiratory protection equipment according to the analysis result.

[0028] Furthermore, the data processing unit includes:

[0029] A data processor processes the data obtained from the storage unit, wherein the processing includes at least data cleaning, conversion, normalization and feature engineering;

[0030] Data analysis algorithms conduct in-depth analysis and mining of processed data to discover trends and correlations in the data and obtain analytical results;

[0031] A prediction model is established based on the analysis results and is used to predict the future usage status of respiratory protective equipment.

[0032] Furthermore, the prediction model is an LSTM model, comprising:

[0033] An input layer, receiving the analysis result;

[0034] An LSTM layer that learns the long-term dependencies of the time series data in the analysis results and generates an internal representation;

[0035] An output layer, receiving the internal representation from the LSMT layer and generating a final prediction result;

[0036] The sliding window divides the time series data from the analysis result into different windows, and moves on the time axis by sliding the window to generate a series of subsequence data, and inputs the subsequence data into the LSTM layer.

[0037] A communication method for a respiratory protective device, using the communication system of the respiratory protective device as described above, comprising:

[0038] Collecting pairing information of two components installed on the respiratory protective equipment and need to be installed relative to each other, and collecting component information of at least one of the components;

[0039] Transmitting the pairing information and component information via a communication connection;

[0040] Processing the transmitted pairing information and component information;

[0041] The processing results of the different pairing information and component information are centrally stored.

[0042] Respiratory protection systems, comprising a number of respiratory protective equipment and a communication system as described above for use with the respiratory protective equipment;

[0043] The communication system includes a plurality of paired transmission modules, which are respectively installed on two different components on a plurality of respiratory protective equipment that need to be installed relative to each other;

[0044] The communication system collects, processes and stores the identity information and pairing information from different respiratory protective equipment in a centralized manner through the main control module and the pairing transmission modules;

[0045] The main control module is connected to the fan of the respiratory protection equipment, and controls at least the air supply volume of the fan according to the processing result, and monitors the use status of the setting component.

[0046] The technical solution of the present invention can achieve the following technical effects:

[0047] The communication system can realize effective communication between the respiratory protection equipment and the main control module. By establishing a database of multiple respiratory protection equipment through the main control module, the data can be analyzed, mined and visualized to discover the correlation and regularity between the data, thereby providing support for decision-making; based on the results of data analysis, corresponding decision-making and control strategies can be formulated, such as formulating equipment maintenance plans, optimizing equipment design, improving production efficiency, etc. At the same time, a unified platform or system can also be integrated with other systems to realize automated decision-making control and monitoring management, thereby improving the intelligence level of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0049] Figure 1A block diagram of the communication system used for respiratory protective equipment;

[0050] Figure 2 A flowchart of the control unit's collection and processing of identity information;

[0051] Figure 3 A framework diagram of a data processing unit. DETAILED DESCRIPTION

[0052] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0053] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0054] Embodiment 1

[0055] like Figure 1 As shown, the communication system applied to respiratory protective equipment includes:

[0056] A pairing transmission module, comprising a first pairing unit and a second pairing unit which are paired and connected within a set position range and are respectively installed on different components of the respiratory protective device;

[0057] The main control module is connected to several paired transmission modules, including a communication unit, a control unit and a storage unit:

[0058] The communication unit is communicatively connected with the paired transmission module to transmit information;

[0059] The control unit collects and processes the identity information of the first pairing unit and / or the second pairing unit, and the pairing information of the first pairing unit and the second pairing unit, wherein the identity information at least includes component information of the corresponding respiratory protective device;

[0060] The storage unit stores the collection and processing results of the identity information and pairing information.

[0061] In this embodiment, by setting the first pairing unit and the second pairing unit in the pairing transmission module, the assembly judgment of each component in the respiratory protection equipment can be effectively solved. During use, the first pairing unit and the second pairing unit are respectively installed on the two components waiting to be relatively installed, so as to judge whether the two components are installed in place by establishing or releasing the pairing connection; in the application of the communication system, for example, the first pairing unit in a pairing transmission module is installed on the filter component, and the second pairing unit is installed on the shell. The result of successful pairing of the first pairing unit and the second pairing unit can be used to determine whether the filter component is installed in place relative to the shell; for another example, the first pairing unit in a group of pairing transmission modules is installed at one end of the connecting tube, and the second pairing unit is installed on the host or the mask. The result of successful pairing of the first pairing unit and the second pairing unit can be used to determine whether the connecting tube is installed in place relative to the host or the mask.

[0062] The main control module is connected to several pairing transmission modules, and can simultaneously realize the installation accuracy judgment of multiple groups of components on multiple respiratory protective equipment, and serve as a platform for data storage and processing; the work performed by the main control module includes the collection and processing of the identity information of the first pairing unit and / or the second pairing unit, including the collection and processing of the identity information of only the first pairing unit, the collection and processing of the identity information of only the second pairing unit, and the collection and processing of the identity information of the first pairing unit and the second pairing unit at the same time; in the implementation process, the purpose of identifying the identity information at least includes judging the component information of installing the first pairing unit and the second pairing unit through the identity information, for example, installing the first pairing unit on the filter component, and reflecting the model, usage time, working status, etc. of the filter component through the identity information.

[0063] The storage unit stores the acquisition time, original data, processing results, etc. of the above information for subsequent use.

[0064] The above communication system can realize effective communication between respiratory protection equipment and the main control module. Through the main control module, a database of multiple respiratory protection equipment can be established, and the data can be analyzed, mined and visualized to find the correlation and regularity between the data, so as to provide support for decision-making. For example, the service life of filter components of different models and the stability of equipment under different pairing conditions can be analyzed. Based on the results of data analysis, corresponding decision-making and control strategies can be formulated, such as formulating equipment maintenance plans, optimizing equipment design, and improving production efficiency. At the same time, a unified platform or system can also be integrated with other systems to realize automated decision-making control and monitoring management, and improve the intelligence level of the system.

[0065] In the implementation process, the pairing signal can be transmitted through one or more of Bluetooth, zigbee, wireless broadband (Wi-Fi), ultra-wideband (UWB), NFC (13.56MHz, 433MHz, 860MHz-960MHz) and 2.4G devices; and the communication connection between the communication unit and the pairing transmission module can be achieved through one or more of GPRS / CDMA wireless communication technology, digital radio communication, spread spectrum microwave communication, wireless bridge, satellite communication, shortwave communication, etc. When selecting communication technology, it is also necessary to consider factors such as communication security, cost, energy consumption, and compatibility with device hardware and software. After comprehensively considering the above factors, the most appropriate communication technology can be selected according to actual needs to ensure the stability and reliability of communication.

[0066] As a preferred embodiment of the above, the communication system applied to the respiratory protection equipment further includes a positioning module installed at a set position of the respiratory protection equipment;

[0067] The communication unit is communicatively connected with the positioning module;

[0068] The control unit collects and processes the positioning information of the positioning module;

[0069] The storage unit stores the collection and / or processing results of the positioning information.

[0070] The location information collected by the positioning module can realize effective management and maintenance of respiratory protective equipment. Users can easily track the location history of the equipment, understand the usage and location changes of the equipment, and help to formulate more effective maintenance plans and management strategies; the positioning module provides accurate positioning information, which is very useful for scenarios that require operation in complex environments or require rapid positioning. For example, in an emergency, the location of the equipment and the user can be accurately located to speed up rescue; location data can be used to analyze the usage patterns and behaviors of the equipment. By analyzing the usage of the equipment in different locations, potential improvement points and optimization solutions can be identified, thereby improving the performance and efficiency of the equipment.

[0071] For communication system products, the positioning module can be integrated with the first pairing unit and / or the second pairing unit in the pairing transmission module and installed as a whole, which reduces the difficulty of installation and is beneficial to the application of the communication system.

[0072] As a preferred embodiment of the above, Figure 2 As shown, the control unit collects and processes identity information, including:

[0073] Continue to determine whether a new pairing transmission module is successfully paired, until the determination result is yes, then collect the identity information of the first pairing unit and / or the second pairing unit in the pairing transmission module;

[0074] Give identity information:

[0075] The unique identification part records the unique identification of the setting component corresponding to the first pairing unit and / or the second pairing unit installed on the respiratory protective device;

[0076] The dynamic identification part records the real-time setting parameters of the setting components.

[0077] In the above embodiment, the system is able to promptly identify and record new pairing situations. Except for the initial installation, during the subsequent replacement of filter components, this process is particularly critical for the identification of new filter components, which helps to ensure that the real-time status of each component in the device is accurately monitored and recorded, thereby improving the real-time and reliability of the system.

[0078] During the implementation process, it is not necessary to collect identity information for some components of the respiratory protection equipment. For example, when installing the filter component relative to the shell of the respiratory protection equipment, it is necessary to identify the relative installation positions of the two through the first pairing unit connected to the shell and the second pairing unit connected to the filter component. As for the identity information, it is only necessary to identify the component information of the filter component through the second pairing unit, and there is no need to identify the component information of the shell through the first pairing unit. Specifically, it is necessary to collect component information for components with more critical service life, such as battery packs, host machines, filter components, etc., while masks, connecting tubes, shells, etc. can be selected according to actual needs.

[0079] The unique identification part is given to the identity information, which can record the unique identification of the setting component corresponding to the first pairing unit and / or the second pairing unit in the pairing transmission module. Such a design can ensure that each component has unique identity information, avoid information confusion and misidentification, and improve the accuracy and credibility of the data; the dynamic identification part records the real-time setting parameters of the setting component, which means that the system can record the current status and parameter information of each component of the equipment in real time, which helps users to understand the working status and performance parameters of the equipment in a timely manner, and facilitates timely adjustment and optimization of the working efficiency and performance of the equipment; by recording the unique identification and dynamic parameters of each setting component, the system can realize personalized management and optimization of each component. For example, personalized maintenance plans and optimization strategies can be formulated for different components, thereby improving the service life and performance of the equipment.

[0080] By continuously collecting and processing identity information, the system can accumulate a large amount of data for data analysis and decision support. By analyzing the pairing status of each component of the equipment and the dynamic parameter changes, potential problems and improvement points can be discovered, thereby guiding future equipment design and management strategies.

[0081] From the perspective of data storage optimization, as a preferred embodiment of the above embodiment, the storage unit stores the unique identification part only once through the first storage area, and stores the dynamic identification part corresponding to the unique identification part through the second storage area.

[0082] In the above optimization scheme, by storing the unique identification part only once, the repeated storage of the same identity information is avoided, and the storage space is effectively saved. This is particularly important for the storage and management of large amounts of data, and helps to reduce system costs and improve storage efficiency. The dynamic identification part and the unique identification part are correspondingly established in a storage area to ensure the consistency and relevance between the data. This design enables related data to be stored and managed in the form of groups, improving the reliability and management efficiency of the data. By establishing a storage area for the dynamic identification part, related data can be organized and stored together, which is convenient for subsequent data retrieval and processing, which helps to improve the access speed and processing efficiency of the data, and improves the performance and responsiveness of the system. By optimizing the design of the storage unit, the redundant storage of the same data is avoided, and the risk of data redundancy is reduced. This helps to maintain the consistency and integrity of the data and reduce the complexity and risk of data management.

[0083] As a preference of the above embodiment, establishing the correspondence between the first storage area and the second storage area includes:

[0084] Establishing a virtual file system in the first storage area, mapping each unique identifier to a unique file path or file name;

[0085] The dynamic data of the real-time setting parameters are stored in the second storage area in the form of files, and the path or file name of each file corresponds to the unique identifier.

[0086] During the implementation process, it is necessary to ensure that each unique identifier in the first storage area has its corresponding dynamic data file, and the naming rules of the path or file name can be clearly corresponded to the unique identifier. In this way, when it is necessary to obtain the dynamic data corresponding to a unique identifier, you only need to use the unique identifier to construct the file path or file name to accurately find the corresponding dynamic data file.

[0087] In the first storage area, a virtual file system is established, in which each unique identifier is mapped to a unique file path or file name. For example, assuming the unique identifier is ID_001, it can be mapped to the path / unique_id / ID_001 or the file name ID_001.txt; in the second storage area, the corresponding dynamic data file can be stored in the path / dynamic_data / ID_001_data.txt or the file name ID_001_data.txt.

[0088] The collection and processing of pairing information by the control unit usually includes the following aspects:

[0089] When the pairing is successful, the control unit will record the time of successful pairing, the unique identifier of the device, and the structural information of the successful pairing, such as the pairing of the filter component and the housing. This information can help with subsequent data analysis and device management;

[0090] The control unit verifies and parses the pairing information to ensure the accuracy and completeness of the information, which at least involves verifying the structural information of the successful pairing, such as checking whether the structure of the successful pairing meets the expected situation of the device assembly;

[0091] The control unit often further processes the pairing information to meet specific needs. For example, it can analyze the assembly status of the device based on the structural information of successful pairing to monitor the assembly accuracy and stability of the device. If the control unit detects that the pairing information is abnormal or inconsistent, it may trigger an alarm or exception handling mechanism. For example, if the pairing information shows that the pairing structure does not match or is unreasonable, it may be necessary to trigger an alarm and perform further inspection and processing.

[0092] As a preferred embodiment of the above embodiment, the main control module also includes a data processing unit for processing and analyzing the data stored in the storage unit, and realizing the use status prediction of the respiratory protective equipment according to the analysis result.

[0093] In this preferred embodiment, since the data processing unit obtains data directly from the storage unit, it can ensure that the processed data is consistent with the stored data, avoiding data inconsistency or conflict; the data stored in the storage unit is updated in real time, so the data processing unit can instantly obtain the latest data, thereby performing real-time processing and analysis; the data in the storage unit is stored after verification and confirmation, so the accuracy and reliability of the data can be guaranteed, and the data processing unit performs processing and analysis based on these accurate data to obtain accurate prediction results.

[0094] During the implementation process, by predicting the usage status of respiratory protective equipment, potential problems or signs of failure can be discovered in time, and preventive maintenance measures can be taken to avoid equipment shutdown or damage due to unexpected failures, thereby improving the reliability and sustainability of the equipment; the prediction results can be used to rationally plan and optimize the use of resources, including manpower, materials and equipment, thereby improving resource utilization efficiency and reducing production costs; in addition, according to the prediction results, corresponding measures can be taken to reduce excessive use or improper operation of equipment, extend the service life of equipment, and reduce equipment maintenance and replacement costs. Safety hazards or risk factors in the equipment can be discovered in time, and corresponding safety measures can be taken to ensure the safety of operators and the production environment.

[0095] As a preferred embodiment of the above, Figure 3 As shown, the data processing unit includes:

[0096] A data processor processes the data obtained from the storage unit, and the processing includes at least data cleaning, conversion, normalization and feature engineering;

[0097] Among them, data cleaning is used to detect and correct errors, missing or outliers in the data to ensure the quality and consistency of the data; data conversion includes converting data from the original format to a format suitable for analysis and modeling, such as encoding data into digital types, converting categorical variables into numerical types, etc.; data normalization is used to adjust the scale and range of the data to ensure that the weights between different features are relatively consistent to avoid some features from having too much influence on the model; feature engineering refers to improving the data representation ability by creating new features or combining existing features to make the data more explanatory and predictive;

[0098] Data analysis algorithms conduct in-depth analysis and mining of processed data to discover trends and correlations in the data and obtain analytical results;

[0099] Data analysis algorithms include statistical analysis, machine learning algorithms, deep learning algorithms, etc. Specifically, data analysis algorithms usually include the following aspects:

[0100] Statistical analysis is the basis of data analysis. It describes the basic characteristics and distribution of data by calculating various statistical quantities of data, such as mean, variance, correlation coefficient, etc. Statistical analysis can help understand the central tendency, degree of dispersion and correlation between different variables of the data, thereby revealing the overall characteristics of the data.

[0101] A machine learning algorithm is a type of algorithm that can learn and extract patterns and regularities from data. By learning and training on large amounts of historical data, a machine learning algorithm can discover hidden patterns in the data and establish a predictive model to predict future trends and states. The machine learning algorithms that can be applied to this embodiment include linear regression, decision trees, support vector machines, random forests, etc.

[0102] The deep learning algorithm is a machine learning method based on artificial neural networks. It learns the complex features and representations of data through a multi-level neural network structure. The deep learning algorithm performs well in processing large-scale data and complex pattern recognition tasks. It can automatically learn abstract representations in the data and apply it to tasks such as prediction, classification, and clustering.

[0103] A prediction model is established based on the analysis results to predict the future usage status of respiratory protective equipment.

[0104] Predictive models can be established using various machine learning algorithms or statistical models, such as linear regression, decision trees, random forests, neural networks, etc. These models convert the features and correlations obtained from data analysis into patterns and rules that can be used for prediction, thereby enabling accurate predictions of future equipment status. The establishment of predictive models requires training and verification to ensure that they have good generalization capabilities and predictive accuracy to meet the needs of practical applications.

[0105] Data analysis algorithms provide the foundation and support for predictive models, helping to identify patterns and correlations in the data; predictive models are built using these analysis results to predict future trends and conditions. By combining these two processes, data can be more fully understood and utilized, thereby improving the accuracy and reliability of predictions.

[0106] Among them, the prediction model is an LSTM model, including:

[0107] Input layer, receiving analysis results;

[0108] LSTM layer, which learns the long-term dependencies of time series data in the analysis results and generates internal representations;

[0109] The output layer receives the internal representation from the LSMT layer and generates the final prediction result;

[0110] Sliding window, divides the time series data from the analysis results into different windows, and moves on the time axis by sliding the window to generate sub-sequence data of the series and input it into the LSTM layer.

[0111] Using deep learning models such as LSTM for prediction can better capture long-term dependencies and complex patterns in time series data, thereby improving the accuracy and stability of predictions. Combined with sliding window technology, it can increase the diversity and richness of data and improve the generalization ability and prediction effect of the model.

[0112] As an example, let's assume that you need to predict the life of a filter component in a respiratory protective device:

[0113] First, a series of data on the use status of the filter components in the respiratory protective equipment is collected, which may include working time, working temperature, working humidity, etc. Then, these data are processed and analyzed, including data cleaning, conversion, normalization, etc., to obtain a set of analysis results for prediction.

[0114] Next, these analysis results are input into the prediction model: at the input layer, these analysis results are passed to the LSTM layer, which will learn the time series patterns and long-term dependencies in the data, such as how the usage patterns of the filter components change over time. By learning these patterns, the LSTM layer will generate internal representations to capture the underlying laws and trends in the data; at the output layer, the internal representation from the LSTM layer is received and converted into the final prediction result, i.e., the life prediction of the filter component. This prediction result can show when the filter component may need to be replaced in the future, so that corresponding maintenance measures can be taken in advance to avoid equipment shutdown or impact on usage due to failure of the filter component.

[0115] In addition, by introducing the sliding window method, the original time series data can be divided into different windows and slid on the time axis to generate a series of sub-sequence data. The advantage of this is that it can increase the diversity and richness of the data, thereby improving the generalization ability and prediction accuracy of the model.

[0116] The above model structure is suitable for processing various types of component data, including but not limited to filter components, battery components, sensor components, etc. Regardless of the type of component data, it can be analyzed and predicted through the prediction model to achieve effective management and maintenance of the use status of each component of the respiratory protection equipment. For the specific application scenarios of respiratory protection equipment, some component data have obvious time characteristics. For example, the service life of the filter component changes over time, the battery capacity and performance may gradually decrease as the number of charge and discharge cycles of the battery increases, and the sensor component may be affected by environmental factors during long-term use, resulting in performance degradation or failure, etc. The LSTM model can well capture the long-term dependencies and patterns in this time series data, thereby achieving accurate prediction of the component use status. The sliding window technology can increase the diversity and richness of the data, better reflect the time characteristics of the data, and improve the generalization ability and prediction effect of the prediction model.

[0117] In the implementation process, the sliding mode of the sliding window can be achieved by setting two key parameters:

[0118] Window size: refers to the amount of time series data contained in each window. The window size setting usually needs to be determined based on the characteristics of the data and the prediction task, and can be tuned based on experience or experiments.

[0119] Sliding step size: Indicates the distance that each sliding window moves on the time axis, also known as the sliding interval, which is used to control the overlap and continuity between windows. A smaller sliding step size can increase the overlap between windows, thereby improving data utilization and model stability, but will increase the amount of calculation; a larger sliding step size can reduce the overlap and reduce the amount of calculation, but may result in some loss of information.

[0120] As a preferred method, the relationship between the window size and the sliding step size can be optimized as follows:

[0121] S=W×(α+β) / 2

[0122] Among them, S represents the sliding step, W represents the window size, α and β represent the periodic factor and trend factor respectively, which are adjusted according to the trend in the analysis results of the data analysis algorithm; S represents the sliding step, and its unit depends on the unit of the window size W; W represents the window size, and its unit is usually a time unit, such as day, hour, etc.; α and β represent the periodic factor and trend factor respectively, which are pure numerical values ​​without units. Their values ​​are usually between 0 and 1, indicating the influence of the corresponding factors on the sliding step.

[0123] Specifically, the cyclical factor α is used to consider the cyclical changes in the data, such as the impact of seasonal changes or periodic events on the use status of respiratory protective equipment. A common method for calculating the cyclical factor is to use Fourier transform or autocorrelation function to analyze the cyclical characteristics of the data and extract the value of the cyclical factor from it. The specific calculation method may involve complex frequency domain analysis technology to determine the cyclical components in the data and quantify their impact. The trend factor β is used to consider the trend changes in the data, such as the continuous growth or downward trend of the data over time. The method for calculating the trend factor can be based on linear regression, moving average or other time series analysis techniques to determine the overall trend direction and change speed of the data. The specific calculation method may involve fitting the data or estimating the trend line to obtain the value of the trend factor.

[0124] In general, both the cyclical factor α and the trend factor β are adjusted to better reflect the characteristics of the data, but they focus on the cyclical and trend changes in the data respectively, and therefore play different roles in adjusting the sliding window.

[0125] In the specific scenario of respiratory protective equipment, the technical advantages of adopting the above solution are reflected in the following aspects:

[0126] More accurate prediction: By adjusting the periodic factor α and the trend factor β, the size and step size of the sliding window can better adapt to the periodic changes and trend changes in the use status of respiratory protective equipment. For example, if there are seasonal changes or long-term trends in the equipment, adjusting these two factors can make the sliding window more effective in capturing these characteristics, thereby improving the accuracy of the prediction.

[0127] More efficient data utilization: By optimizing the sliding window, the continuity between windows can be increased while maintaining a certain degree of overlap, thereby improving data utilization. In the scenario of respiratory protective equipment, if the data in a certain time period has an important impact on the prediction of the equipment status in the next time period, then the use of a suitable sliding window design can make better use of this information, allowing the model to more accurately capture changes in the equipment status.

[0128] Reduce information loss: By adjusting the sliding step size, the amount of calculation can be reduced while maintaining prediction accuracy. A smaller sliding step size can increase the overlap between windows and increase the continuity of data, thereby reducing information loss; while a larger sliding step size can reduce the amount of calculation and improve the efficiency of model training and prediction. In the prediction task of respiratory protective equipment, this means that a large amount of time series data can be processed more efficiently while ensuring prediction accuracy.

[0129] Embodiment 2

[0130] A communication method applied to a respiratory protective device, using the communication system of the respiratory protective device as described in the first embodiment, comprises:

[0131] Collecting pairing information of two components installed on the respiratory protective equipment and need to be installed relative to each other, and collecting component information of at least one of the components;

[0132] Transmitting pairing information and component information via a communication connection;

[0133] Process the transmitted pairing information and component information;

[0134] The processing results of different pairing information and component information are centrally stored.

[0135] The technical effects of this embodiment are as described in Embodiment 1 and will not be repeated here.

[0136] Embodiment 3

[0137] A respiratory protection system, comprising a plurality of respiratory protection devices, and a communication system applied to the respiratory protection devices as described in the first embodiment;

[0138] The communication system includes a plurality of paired transmission modules, which are respectively installed on two components on a plurality of respiratory protective equipment that need to be installed opposite to each other;

[0139] The communication system collects, processes and stores the identity information and pairing information from different respiratory protective equipment in a centralized manner through the main control module and several pairing transmission modules;

[0140] The main control module is connected to the fan of the respiratory protection equipment, and controls at least the air supply volume of the fan according to the processing result, and monitors the use status of the setting component.

[0141] During the implementation process, compared with the technical effects that can be achieved in Example 1, in this embodiment, more precise control of the respiratory protection equipment can be further effectively achieved. For example, by controlling the air volume supplied by the host, the air volume of different filter components can be adjusted accordingly to meet the set noise requirements. Specifically, when the filter component adopts a gas filter canister, the air volume needs to be reduced due to its large resistance, and when the filter component adopts an ordinary filter element, the air volume can be appropriately increased due to its small resistance; by controlling the air volume supplied by the fan through the main control module, the air volume can be adjusted according to the characteristics of different filter components to meet the set noise requirements. This fine control can ensure the performance and comfort of the respiratory protection equipment under different working conditions.

[0142] As for the monitoring of the usage status, the detailed information of each component can be effectively obtained through the component information, including the production date, material, version, etc., as well as the usage time of the filter element and the canister, the remaining power of the battery pack, etc. This information helps to monitor the operating status of the equipment in real time, find problems in time and take corresponding measures, and improve the reliability and safety of the equipment. The main control module can realize remote control of respiratory protective equipment. This function allows operators to remotely adjust the working parameters of the equipment, perform remote maintenance and management, and improve the intelligence level and convenience of use of the equipment.

[0143] The respiratory protection system in this embodiment improves the monitoring, control and management capabilities of respiratory protection equipment through further technical improvements and functional enhancements, providing users with a safer, more convenient and comfortable use experience. In specific implementation, a display device can be set, which can be displayed through a display screen, including an LCD screen, a broken code screen, a touch screen, etc., and its display content can include one or more of the following functions: components, including the connection status of filter elements, gas canisters, hoses, etc., usage time, aging degree, ventilator usage status, various alarm reminders, including filter elements not installed, blocked, gas canisters not installed, or too long usage time, fan abnormality, mainboard abnormality, battery pack abnormality, etc.

[0144] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. Communication systems used in respiratory protective equipment, It is characterized in that include: A pairing transmission module, comprising a first pairing unit and a second pairing unit which are paired and connected within a set position range and are respectively installed on different components of the respiratory protective device; The main control module is connected to the pairing transmission modules, and includes a communication unit, a control unit and a storage unit: The communication unit is communicatively connected with the pairing transmission module to perform information transmission; The control unit collects and processes the identity information of the first pairing unit and / or the second pairing unit, and the pairing information of the first pairing unit and the second pairing unit, wherein the identity information at least includes component information of the corresponding respiratory protective device; The storage unit stores the collection and processing results of the identity information and pairing information; The main control module also includes a data processing unit, which processes and analyzes the data stored in the storage unit, and realizes the use status prediction of the respiratory protective equipment according to the analysis results; The data processing unit comprises: A data processor processes the data obtained from the storage unit, wherein the processing includes at least data cleaning, conversion, normalization and feature engineering; Data analysis algorithms conduct in-depth analysis and mining of processed data to discover trends and correlations in the data and obtain analytical results; A prediction model, established based on the analysis results, for predicting the future use status of respiratory protective equipment; The prediction model is an LSTM model, including: An input layer, receiving the analysis result; An LSTM layer that learns the long-term dependencies of the time series data in the analysis results and generates an internal representation; An output layer receives the internal representation from the LSTM layer and generates a final prediction result; Sliding window, dividing the time series data from the analysis result into different windows, and moving on the time axis by sliding window to generate a series of subsequence data, and inputting the subsequence data into the LSTM layer; The relationship between window size and sliding step size is set as: S=W×(α+β) / 2 Among them, S represents the sliding step, W represents the window size, α and β represent the periodic factor and trend factor respectively, which are adjusted according to the trends in the analysis results of the data analysis algorithm; the unit of S depends on the unit of W; the unit of W is the time unit; α and β are unitless pure numerical values ​​with values ​​between 0 and 1, indicating the degree of influence of the corresponding factors on the sliding step; the periodic factor α is used to consider the periodic changes in the data, and the trend factor β is used to consider the trend changes in the data.

2. The communication system for respiratory protection equipment according to claim 1, It is characterized in that Also included is a positioning module installed at a set position of the respiratory protection device; The communication unit is communicatively connected with the positioning module; The control unit collects and processes the positioning information of the positioning module; The storage unit stores the collection and / or processing results of the positioning information.

3. The communication system for respiratory protection equipment according to claim 1, It is characterized in that The control unit collects and processes the identity information, including: Continue to determine whether a new pairing transmission module is successfully paired, until the determination result is yes, then collect the identity information of the first pairing unit and / or the second pairing unit in the pairing transmission module; Assign the identity information: A unique identification part, recording a unique identification of a setting component corresponding to the first pairing unit and / or the second pairing unit installed on the respiratory protective device; The dynamic identification part records the real-time setting parameters of the setting component.

4. The communication system for respiratory protection equipment according to claim 3, It is characterized in that The storage unit stores the unique identification part only once through the first storage area, and stores the dynamic identification part corresponding to the unique identification part through the second storage area.

5. The communication system for respiratory protection equipment according to claim 4, It is characterized in that Establishing the correspondence between the first storage area and the second storage area includes: Establishing a virtual file system in the first storage area to map each unique identifier to a unique file path or file name; The dynamic data of the real-time setting parameters are stored in the second storage area in the form of files, and the path or file name of each file corresponds to the unique identifier.

6. A communication method for a respiratory protective device, comprising: using the communication system for the respiratory protective device as claimed in claim 1, It is characterized in that include: Collecting pairing information of two components installed on the respiratory protective equipment and need to be installed relative to each other, and collecting component information of at least one of the components; Transmitting the pairing information and component information via a communication connection; Processing the transmitted pairing information and component information; The processing results of the different pairing information and component information are centrally stored.

7. Respiratory protection system, It is characterized in that comprising a plurality of respiratory protective devices, and a communication system for use in respiratory protective devices as claimed in claim 1; The communication system includes a plurality of paired transmission modules, which are respectively installed on two different components on a plurality of respiratory protective equipment that need to be installed relative to each other; The communication system collects, processes and stores the identity information and pairing information from different respiratory protective equipment in a centralized manner through the main control module and the pairing transmission modules; The main control module is connected to the fan of the respiratory protection equipment, and controls at least the air supply volume of the fan according to the processing result, and monitors the use status of the setting component.

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