A self-driven dustproof monitoring intelligent mine mask and a preparation method thereof

Abstract

This invention relates to the fields of personal protective equipment, self-driven sensing, and air filtration technology, specifically to a self-driven intelligent mining mask with dust monitoring and its manufacturing method. The mask includes a mask body with a breathing valve. Inside the breathing valve is a filter unit based on a triboelectric nanogenerator. The filter unit comprises, from the inside out, an inner porous conductive metal layer, a positive friction layer, a spacer layer, a negative friction layer, an outer porous conductive metal layer, and a fixed circular frame. The inner and outer porous conductive metal layers are each connected to a signal processing unit via external wires. The signal processing unit is connected to an alarm display unit via wires. This invention utilizes the continuous electrostatic field generated by the triboelectric nanogenerator driven by breathing to enhance the electrostatic adsorption capacity for particulate matter. Simultaneously, without the need for an external power source, it can monitor the wearer's breathing status in real time and provide a warning of danger in case of abnormalities.

Description

Technical Field

[0001] This invention relates to the fields of personal protective equipment, self-driven sensing, and air filtration technology, specifically to a self-driven intelligent mask for mining with dust monitoring and its preparation method. Background Technology

[0002] In the high-dust environment of mines, micron- and submicron-sized suspended dust particles such as coal dust and rock dust are ubiquitous. Due to their small particle size and large specific surface area, these particles remain in the air for a long time and are easily inhaled into the deep respiratory system. Long-term exposure may lead to pneumoconiosis, chronic respiratory diseases, and other occupational health risks. Therefore, providing stable and reliable respiratory protection for personnel under mining conditions is a crucial foundation for ensuring the occupational health of miners and safe production in mines. Mine dust masks not only need to efficiently capture small-diameter particles but must also maintain stable filtration performance under continuous wear, complex working conditions, and long-term operation. Furthermore, modern mine safety management requires personal protective equipment to not only meet basic protective functions but also possess health status monitoring and safety early warning functions. Therefore, researching intelligent mining mask technology that balances long-term filtration stability and monitoring and early warning functions, specifically tailored to the unique environment of mines, has significant engineering application value and practical significance for reducing occupational disease risks and promoting the intelligent development of mine safety equipment.

[0003] Currently, most mining dust masks use electrostatically electret treated meltblown nonwoven fabric as the core filter material. This type of material introduces electrostatic charges onto the fiber surface, enabling it to efficiently capture micron- and submicron-sized dust particles, such as PM2.5, metal fumes, and rock dust, not only through the physical blocking effect of the fiber pores but also through electrostatic adsorption. Ideally, the filtration performance of meltblown fabric is closely related to the electret charge strength. However, in the high-dust environment of mines, the filtration efficiency of existing meltblown fabrics decreases significantly over time. The deposition and coverage of a large number of dust particles on the fiber surface weakens the electrostatic field's ability to adsorb newly entering particles, causing the filter mechanism to gradually degrade from electrostatic adsorption to physical interception. Therefore, its protective performance is difficult to maintain long-term stability, and there is a risk that its protective ability will decrease with wearing time. Furthermore, most existing mining dust masks are typical passive protective structures, their function limited to air filtration, lacking any energy conversion or state sensing capabilities. The masks cannot sense changes in the miner's breathing state during wear, nor can they provide feedback information on the working status of the filter material. In actual mining operations, existing masks are insufficient to provide timely auxiliary monitoring or early warning signals when miners experience abnormal breathing, fatigue, or changes in ambient dust concentration. Furthermore, most of these monitoring and early warning functions require external power, resulting in issues such as low battery power density, short lifespan, and portability, making them unsuitable for meeting the evolving needs of modern mine safety management and health monitoring.

[0004] Triboelectric nanogenerators are a novel energy conversion technology capable of converting mechanical energy into electrical energy under low-frequency mechanical stimulation, particularly suitable for utilizing low-frequency energy sources such as human respiration and minute airflows. Through triboelectric charging and electrostatic induction, triboelectric nanogenerators can continuously output electrical signals or electrostatic fields without an external power source. Introducing this technology into mining protective masks not only creates a continuous electrostatic environment near the filter material to compensate for or enhance the particle trapping capacity after electrostatic decay of traditional electret materials, but also enables self-powered signal output during breathing for respiratory status monitoring. This provides a clear and feasible new technological direction for next-generation self-powered dustproof smart mining masks with real-time monitoring capabilities. Summary of the Invention

[0005] This invention addresses the technical problems of existing mine dust masks, such as the decreasing filtration efficiency over time in high-dust environments, the difficulty in maintaining stable long-term protective performance, and the reliance on external power sources for respiratory monitoring devices, resulting in high power consumption. It provides a self-driven intelligent dust monitoring mask for mining. Building upon the physical blocking effect of a multi-scale nanofiber membrane on dust particles, it enhances the electrostatic adsorption capacity of dust particles by generating a continuous electrostatic field through a breathing-driven triboelectric nanogenerator. Simultaneously, without requiring an external power source, it can monitor the wearer's breathing status in real time and issue a danger warning when abnormalities occur, achieving long-term, highly efficient particulate filtration while possessing self-driven respiratory status monitoring capabilities.

[0006] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: a self-driven dust monitoring smart mask for mining, comprising a mask body, a breathing valve on the mask body, and a filter unit based on a triboelectric nanogenerator installed inside the breathing valve. The filter unit includes, from the inside out, an inner porous metal conductive layer, a positive friction layer, a spacer layer, a negative friction layer, an outer porous metal conductive layer, and a fixed circular frame. The inner and outer porous metal conductive layers are respectively connected to a signal processing unit via external wires. The signal processing unit is connected to an alarm display unit via wires. Both the signal processing unit and the alarm display unit are installed on the outside of the mask body. The signal processing unit includes a noise filtering, signal amplification, and digital-to-analog conversion module for the acquired signal. The alarm display unit includes a micro-display, a buzzer, and a power management module. The signal processing unit is responsible for noise filtering and signal amplification of the received characteristic electrical signal, and transcoding it. The processed electrical signal is received by the alarm display unit and displayed on the micro-display.

[0007] As a further limitation of the technical solution of the present invention, the positive friction layer is a nylon / chitosan quaternary ammonium salt composite multi-scale nanofiber membrane, the negative friction layer is a polyvinylidene fluoride-hexafluoropropylene nanofiber membrane, the spacer layer is a foam pad, and the inner porous metal conductive layer and the outer porous metal conductive layer are both porous conductive copper tapes.

[0008] The present invention also provides a method for preparing a self-driven dust monitoring smart mask for mining, comprising the following steps: S1, Preparation of the positive friction layer First, nylon 66 and chitosan quaternary ammonium salt were dissolved together in trifluoroethanol solvent and stirred continuously at room temperature for 12 hours to form a uniform and transparent spinning precursor solution. The spinning precursor solution was loaded into a syringe, installed on an electrospinning machine, and spun. The fibers were collected on a polypropylene nonwoven fabric substrate 12 cm away from the needle tip to form a multi-scale nanofiber membrane of nylon 66 / chitosan quaternary ammonium salt composite with nano and submicron diameter distribution, which served as a positive friction layer. S2, Preparation of the negative friction layer First, polyvinylidene fluoride-hexafluoropropylene was dissolved in N,N-dimethylformamide solvent and stirred at room temperature for 6 hours before electrospinning. The fibers were collected on a polypropylene nonwoven fabric substrate 12 cm from the needle tip to obtain a polyvinylidene fluoride-hexafluoropropylene nanofiber membrane, which served as a negative friction layer. S3. Fabrication of a filter unit based on a triboelectric nanogenerator Perforated copper tape, cut and punched with an ultraviolet laser, serves as the inner and outer porous metal conductive layers. Polyvinylidene fluoride-hexafluoropropylene nanofiber membranes and nylon 66 / chitosan quaternary ammonium salt composite multi-scale nanofiber membranes are respectively adhered to the two porous copper tapes. Polyurethane foam material, after being cut, serves as a spacer between the two friction layers, and positive and negative friction layers are respectively attached to the left and right sides of the spacer. Wires are installed between the inner and outer porous metal conductive layers and their adjacent friction layers to achieve connection with external circuits. S4. Preparation of intelligent masks for mining. The signal processing unit and alarm display unit are installed on the mask body, the filter unit is installed inside the breathing valve, and the signal processing unit is connected to the filter unit and alarm display unit respectively through external wires, thereby preparing a smart mask for mining.

[0009] As a further limitation of the technical solution of the present invention, the mass ratio of nylon 66, chitosan quaternary ammonium salt and trifluoroethanol in step S1 is 3:4:50.

[0010] As a further limitation of the technical solution of the present invention, the syringe in step S1 is a 10mL syringe with an 18-gauge metal needle, and the electrospinning conditions are: voltage 20kV, feed rate 0.5mL / h, roller speed 170r / min, ambient temperature 23~27℃, and relative humidity 40%~90%.

[0011] As a further limitation of the technical solution of the present invention, the mass ratio of polyvinylidene fluoride-hexafluoropropylene to N,N-dimethylformamide in step S2 is 3:20.

[0012] As a further limitation of the technical solution of the present invention, the conditions for electrospinning in step S2 are: voltage 10kV, roller speed 200r / min, and humidity 50±5%.

[0013] As a further limitation of the technical solution of the present invention, in step S3, the copper tape has a thickness of 60μm and a pore size of 200μm; the polyurethane foam material has a thickness of 2mm.

[0014] As a further limitation of the technical solution of the present invention, the inner diameter and outer diameter of the spacer layer in step S3 are 30mm and 40mm, respectively.

[0015] Compared with the prior art, the present invention has the following beneficial effects: This invention introduces a triboelectric nanogenerator composed of a nylon 66 / chitosan quaternary ammonium salt composite multi-scale nanofiber membrane and a polyvinylidene fluoride-hexafluoropropylene nanofiber membrane. Through the periodic contact and separation of the two materials driven by respiratory airflow, a stable triboelectric charge is continuously generated on the material surface. This structure allows the triboelectric charging process to occur repeatedly with breathing. Compared to traditional meltblown fabrics that rely on disposable electret treatment, it can provide a continuous electrostatic effect on the filtration area during use, thereby achieving effective adsorption of dust particles and overcoming the drawback of traditional masks where filtration efficiency severely declines with long-term use in dusty environments. The electrostatic field is self-maintained and self-repaired through breathing behavior, ensuring filtration stability under long-term use.

[0016] Meanwhile, this invention does not require gas-sensitive materials. Since the electrical signal of the triboelectric nanogenerator comes directly from the contact behavior between the nanofiber membranes, its signal amplitude and period change with the breathing airflow, which can be used as a physical characterization of the breathing state, realizing self-powered monitoring without external power source and gas-sensitive materials. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the structure of the intelligent mining mask of the present invention.

[0018] Figure 2 This is a cross-sectional view of the filter unit based on a triboelectric nanogenerator in the intelligent mining mask of the present invention.

[0019] Figure 3 This is a schematic diagram illustrating the working principle of the filter unit based on a triboelectric nanogenerator in the intelligent mining mask of this invention.

[0020] Figure 4 The diagram shows the open-circuit voltage performance of the intelligent mining mask filter unit of this invention under multiple cycles, with the right image being a partial enlarged view of the left image.

[0021] Figure 5 The diagram shows the output voltage of the triboelectric nanogenerator compared to a Nylon 66 positive friction layer without chitosan quaternary ammonium salt and a polyvinylidene fluoride nanofiber membrane as the negative friction layer (left side of the dashed line), and a Nylon 66 / chitosan quaternary ammonium salt composite positive friction layer with a polyvinylidene fluoride-hexafluoropropylene nanofiber membrane as the negative friction layer (right side of the dashed line).

[0022] The markings in the image are as follows: 1-Mask body, 2-Breathing valve, 3-Filter unit, 31-Inner porous metal conductive layer, 32-Positive friction layer, 33-Spacer layer, 34-Negative friction layer, 35-Outer porous metal conductive layer, 36-Fixing ring frame, 4-Signal processing unit, 5-Alarm display unit, 6-External wire. Detailed Implementation

[0023] The present invention will be further described below with reference to specific embodiments. Example 1

[0024] like Figure 1 As shown, a self-driven dust monitoring smart mask for mining includes a mask body 1. The mask body 1 has a breathing valve 2, and a filter unit 3 based on a triboelectric nanogenerator is installed inside the breathing valve 2. The filter unit 3 includes, from the inside out, an inner porous metal conductive layer 31, a positive friction layer 32, a spacer layer 33, a negative friction layer 34, an outer porous metal conductive layer 35, and a fixing ring frame 36. The inner porous metal conductive layer 31 and the outer porous metal conductive layer 35 are respectively connected to a signal processing unit 4 via external wires 6. The signal processing unit 4 is connected to an alarm display unit 5 via wires. Both the alarm display unit 5 and the alarm display unit 1 are installed on the outside of the mask body 1; the signal processing unit 4 includes noise filtering, signal amplification, and digital-to-analog conversion modules for the acquired signals, and the alarm display unit 5 includes a miniature display, a buzzer, and a power management module (the power management module is existing technology, which is a module built by integrating the development program and hardware onto a miniature PCB board. It mainly includes some functions required by the Arduino Uno3 development board); the signal processing unit 4 is responsible for noise filtering and signal amplification of the received characteristic electrical signals, and the processed electrical signals are received by the alarm display unit 5 and then transcoded and displayed on the miniature display.

[0025] Furthermore, the positive friction layer 32 is a nylon 66 / chitosan quaternary ammonium salt composite multi-scale nanofiber membrane, the negative friction layer 34 is a polyvinylidene fluoride-hexafluoropropylene nanofiber membrane, and the spacer layer 33 is a foam pad. The positive friction layer 32 and the negative friction layer 34 are separated by the foam pad, forming a triboelectric nanogenerator structure that can periodically contact and separate with the breathing airflow. The inner porous metal conductive layer 31 and the outer porous metal conductive layer 35 are both porous conductive copper tapes. The outer surfaces of the two fiber membranes are respectively attached to the porous conductive copper tapes, which serve as electrodes and are connected to the signal processing unit 4 through thin and flexible wires.

[0026] The continuous filtration and monitoring mechanism of a self-driven dust monitoring smart mask for mining: The self-driven dust monitoring intelligent mask for mining utilizes a filtration and power generation function based on a synergistic mechanism of physical interception and electrostatic adsorption, and achieves self-powering through breathing. Regarding physical interception: the positive friction layer 32 employs a nylon 66 / chitosan quaternary ammonium salt multi-scale nanofiber membrane, composed of interwoven nanofibers and submicron fibers, forming a multi-level pore size distribution. This composite structure can efficiently capture ultrafine dust particles through inertial collision, direct interception, and diffusion effects. Regarding electrostatic adsorption: when the wearer breathes, the airflow drives the positive and negative electrode fiber membranes to periodically contact and separate. Due to the difference in electron affinity between nylon 66 and polyvinylidene fluoride-hexafluoropropylene, electrons transfer from the nylon 66 / chitosan quaternary ammonium salt composite multi-scale nanofiber membrane to the polyvinylidene fluoride-hexafluoropropylene nanofiber membrane upon contact, making the nylon 66 / chitosan quaternary ammonium salt composite multi-scale nanofiber membrane positively charged and the polyvinylidene fluoride-hexafluoropropylene nanofiber membrane negatively charged. A potential difference is generated between the electrodes upon separation. This surface electrostatic charge can adsorb polarized dust particles, improving filtration efficiency. Simultaneously, through triboelectric charging and electrostatic induction coupling effects, the mechanical energy generated by the wearer's breathing airflow can be converted into an electrical signal, which can reflect real-time changes in breathing status. Because the triboelectric nanogenerator is arranged inside the breathing valve 2, directly facing the wearer's mouth and nose, it can directly sense changes in breathing airflow, causing the friction layer to contact and separate during breathing, thereby generating an electrical signal. The amplitude and period of the electrical signal change with the breathing frequency, intensity, and rhythm, reflecting the wearer's physiological state. The signal processing unit 4 is located on the outside of the mask and is connected to the triboelectric nanogenerator. It is responsible for noise filtering and signal amplification of the received characteristic electrical signal, and transcoding it. The processed electrical signal is received by the alarm display unit 5 and displayed on a micro display. Example 2

[0027] The present invention relates to a method for preparing a self-driven dust monitoring smart mask for mining, comprising the following steps: S1. First, prepare the positive friction layer 32. 6% Nylon 66 and 8% chitosan quaternary ammonium salt were dissolved together in trifluoroethanol and stirred at room temperature for 12 hours to form a uniform spinning solution. The precursor solution was added to a 10mL syringe equipped with an 18-gauge needle. Using an electrospinning device, under the conditions of 20kV voltage, injection rate of 0.5mL / h, receiving distance of 12cm, roller speed of 170r / min, ambient temperature of 23-27℃, and humidity of 40-90%, the spinning solution was spun onto a polypropylene nonwoven fabric substrate to form a multi-scale nanofiber membrane (approximately 20μm-40μm thick) composed of nanofibers and submicron fibers. The membrane was then left to stand at room temperature for 24 hours to eliminate residual static electricity.

[0028] S2. Preparation of negative friction layer 34: 15% by mass of polyvinylidene fluoride-hexafluoropropylene is dissolved in N,N-dimethylformamide solvent. After stirring for 6 hours, the precursor solution is added to a 10mL syringe equipped with an 18-gauge needle. Electrospinning is performed under the conditions of 10kV voltage, 12cm receiving distance, 200r / min roller speed, and 50±5% humidity to obtain a polyvinylidene fluoride-hexafluoropropylene nanofiber membrane (thickness approximately 15μm-30μm). The membrane is then left to stand at room temperature for 24 hours to eliminate residual static electricity. S3. Fabrication of a filter unit based on a triboelectric nanogenerator 3 A 60μm thick copper tape is cut and perforated with a 200μm aperture using an ultraviolet laser to form the inner porous metal conductive layer 31 and the outer porous metal conductive layer 35. A 2mm thick polyurethane foam material is cut to have inner and outer diameters of 30mm and 40mm respectively, serving as the spacer layer 33. Polyvinylidene fluoride-hexafluoropropylene nanofiber membranes and nylon 66 / chitosan quaternary ammonium salt composite multi-scale nanofiber membranes are respectively bonded to the porous copper tape electrode. The two fiber membranes are bonded together with double-sided adhesive to both sides of the spacer layer 33, i.e., the cut polyurethane foam material, which serves as both elastic support and spacer. Two wires are respectively sandwiched between the copper wire and the two films and connected to the signal processing unit 4 on the outside of the mask.

[0029] S4. Preparation of intelligent masks for mining The entire triboelectric nanogenerator is placed inside the breathing valve 2 of the mask and encapsulated with a fixed circular frame 36. The signal processing unit 4 and the alarm display unit 5 are installed on the mask body 1. The signal processing unit 4 is connected to the filter unit 3 and the alarm display unit 5 of the triboelectric nanogenerator through external wires 6, forming a complete smart mask for mining.

[0030] The core filter layer of this invention's intelligent mining mask utilizes a nylon 66 / chitosan quaternary ammonium salt composite multi-scale nanofiber membrane prepared by electrospinning technology. This membrane is composed of nanofibers and submicron fibers of different sizes, forming a gradient-distributed microporous structure. It provides continuous and efficient filtration of small particles through physical mechanisms such as interception, inertial collision, and diffusion. Simultaneously, the introduction of chitosan quaternary ammonium salt not only improves the electrostatic properties of the fiber membrane, but the cationic groups also significantly increase particle adsorption.

[0031] If the positive friction layer uses only nylon 66 nanofiber membrane without adding chitosan quaternary ammonium salt, the nylon 66 spinning solution has low conductivity, resulting in insufficient electric field stretching of the jet during electrospinning. This leads to larger fiber diameters and a tendency for bead-like defects, resulting in larger pore sizes and lower specific surface areas, thus reducing its physical interception ability for submicron-sized dust particles. Simultaneously, the lack of cationic groups in chitosan quaternary ammonium salt reduces the charge density, polarity, and electrostatic adsorption capacity for charged dust particles on the fiber membrane surface, leading to insufficient surface potential and local electric field strength after triboelectric charging, making it difficult to form a stable electrostatic trapping effect. Therefore, without adding chitosan quaternary ammonium salt, although the mask filter unit can still form a triboelectric power generation structure of nylon 66 / negative friction layer, its filtration efficiency, humidity stability, and triboelectric charge maintenance ability are significantly lower than the nylon 66 / chitosan quaternary ammonium salt composite multi-scale nanofiber membrane structure of this application. Furthermore, the test results are as follows... Figure 5 As shown, compared to the nylon 66 positive friction layer without chitosan quaternary ammonium salt (left side of the dashed line), the output voltage of the triboelectric nanogenerator is significantly improved when using the nylon 66 / chitosan quaternary ammonium salt composite positive friction layer in this application (right side of the dashed line), and a more stable electrical output is formed after continuous contact-separation cycles. This is because the chitosan quaternary ammonium salt contains quaternary ammonium cationic groups, which can increase the surface charge density and polarity of the positive friction layer, resulting in more significant charge transfer and electrostatic induction signals between the positive and negative friction layers during the breath-driven contact-separation process.

[0032] Compared to polyvinylidene fluoride (PVDF), the introduction of hexafluoropropylene structural units into PVDF-hexafluoropropylene improves the fluorine-containing structure, flexibility, and film-forming stability of the negative friction layer. This facilitates full and reversible contact and separation with the positive friction layer under the drive of breathing airflow, thereby enhancing the stability of the triboelectric process. Simultaneously, the PVDF-hexafluoropropylene electrospun membrane can form a relatively loose, coarse-fiber porous structure, which is conducive to smooth airflow and reduces filtration pressure drop. Its surface has good hydrophobicity, reducing the rapid dissipation of charge caused by breathing moisture, making it suitable for use in masks worn by miners for extended periods for filtration and self-driven sensing units. Furthermore, test results show that compared to the comparative sample using PVDF nanofiber membrane as the negative friction layer (left side of the dashed line), this application achieves a higher or more stable open-circuit voltage (right side of the dashed line) when using PVDF-hexafluoropropylene nanofiber membrane as the negative friction layer. The reason is that polyvinylidene fluoride-hexafluoropropylene has strong negative triboelectric properties, forming a more obvious triboelectric polarity difference between it and the nylon 66 / chitosan quaternary ammonium salt positive triboelectric layer; at the same time, its flexible nanofiber membrane structure is conducive to achieving full and repeatable contact-separation under the action of breathing airflow, thereby improving the stability of charge generation, separation and induction output.

[0033] I. The self-driven dustproof principle based on triboelectric nanogenerator is as follows: Figure 2 This is a cross-sectional view of the filter unit based on a triboelectric nanogenerator in the intelligent mining mask of this invention. In this invention, filter unit 3 serves as a sensing module. The working principle of the sensing module is divided into five instantaneous states, specifically the contact and separation processes experienced by the nylon 66 / chitosan quaternary ammonium salt composite multi-scale nanofiber membrane and the polyvinylidene fluoride-hexafluoropropylene nanofiber membrane under the drive of periodic airflow (inhalation and exhalation). This process utilizes the coupling effect of contact charging and electrostatic induction to convert respiratory motion into electrical signals. Figure 3 As shown in (a), in the initial state, there is no charge transfer between the two friction layers: the nylon 66 / chitosan quaternary ammonium salt composite multiscale nanofiber membrane and the polyvinylidene fluoride-hexafluoropropylene nanofiber membrane. During exhalation ( Figure 3 (b) The airflow forces the two fiber membranes into contact. Due to the different electron affinities of nylon 66 and polyvinylidene fluoride-hexafluoropropylene, the nylon 66 / chitosan quaternary ammonium salt composite multi-scale nanofiber membrane loses electrons and becomes positively charged, while the polyvinylidene fluoride-hexafluoropropylene nanofiber membrane gains electrons and becomes negatively charged. By forming a strong electrostatic field around the fibers, electrostatic adsorption can actively capture polarized dust particles. At the end of exhalation, the charge transfer between the two layers reaches equilibrium, neutralizing the induced charge between the friction layers. The surface charge remains on the contact surface, maintaining the potential difference between the electrodes, such as... Figure 3As shown in (c), during the inhalation process, the nylon 66 / chitosan quaternary ammonium salt composite multi-scale nanofiber membrane separates from the polyvinylidene fluoride-hexafluoropropylene nanofiber membrane. During separation, a potential difference is generated between the electrodes, causing electrons to flow from the polyvinylidene fluoride-hexafluoropropylene nanofiber membrane to the nylon 66 / chitosan quaternary ammonium salt composite multi-scale nanofiber membrane, thereby generating a reverse current, as shown in (c). Figure 3 As shown in (d). When the nylon 66 / chitosan quaternary ammonium salt composite multiscale nanofiber membrane completely recovers to its initial state and is completely separated from the polyvinylidene fluoride-hexafluoropropylene nanofiber membrane, there is no current, and the fiber membrane reaches a new electrostatic equilibrium, as shown in (d). Figure 3 As shown in (e). Therefore, the alternating current signal is generated throughout the respiratory airflow cycle.

[0034] To achieve consistently stable filtration performance, this mask incorporates a self-replenishing charge mechanism: each breath constitutes a triboelectric charging cycle, continuously replenishing the surface charge that decays due to natural relaxation. After multiple breathing cycles, the charge accumulates to dynamic saturation, allowing subsequent breaths to maintain electrostatic adsorption. Even after prolonged use and charge decay, only a few normal breaths are needed to restore the surface potential and filtration efficiency to their optimal state. In summary, this mask, through the synergistic effect of physical interception and breath-driven electrostatic adsorption, constructs an intelligent protective system that requires no external energy and relies solely on human respiration to continuously maintain high filtration efficiency. This provides mine workers with an efficient and reliable personal respiratory protection solution.

[0035] II. The intelligent mining mask of this invention performs respiratory monitoring: This invention's mask monitors the user's breathing status in real time using voltage signals output from a triboelectric nanogenerator. During normal breathing, the voltage signal exhibits a regular sinusoidal waveform with low amplitude and stable frequency. When breathing is rapid, the waveform frequency increases significantly, and the amplitude becomes larger and irregular, reflecting potential exertion, stress, or high-load conditions. After signal acquisition, the weak electrical signal generated by the triboelectric nanogenerator is amplified by a commercial electrostatic amplifier TLV2372, allowing for further processing. After amplification, the analog signal is converted to a digital signal by an MCP3008 analog-to-digital converter for further analysis and judgment. When the electrical signal generated by the triboelectric nanogenerator exceeds a set threshold, the MCP3008 converts the signal to a high level (5V); otherwise, it converts it to a low level (0V). Based on the high and low levels, the digital signal is then processed by a program uploaded to the microprogram control unit to determine if it meets program conditions. Finally, the electrical signal generated by breathing and the converted digital signal are displayed in real time on a micro-display. This process enables real-time monitoring of the wearer's breathing status and transmits the data to the subsequent control system for analysis. The alarm display unit 5 includes an Arduino Uno3 development board, a commercial low-power buzzer, and a miniature display. The Arduino Uno3 development board is used to program and control the buzzer alarm. When a breathing electrical signal is detected exceeding a set threshold, the system activates the buzzer to sound an alarm.

[0036] Working principle: When a user is under stress or high load, the amplitude of the electrical signal generated is higher than during normal breathing. Therefore, using 0.3V generated by normal adult breathing as a threshold, exceeding this threshold indicates that the wearer is in a special state such as exercise. A discrimination program is written into the microprogram control unit. When the electrical signal generated by breathing is higher than the threshold voltage (0.3V), a high level (voltage value of 5V) is output; when the electrical signal generated by breathing is lower than the threshold voltage (0.3V), a low level (voltage value of 0V) is output. During deep breathing, the high and low level signals obtained from the digital-to-analog converter are used as the discrimination criteria, and this continues for more than 5 seconds as a judgment condition. When the condition is met, it is determined to be a special state such as exercise. Conversely, with sudden cessation of breathing, the generated electrical signal will disappear, the high level signal generated by the digital-to-analog converter will also disappear, and the microprogram control unit will feed back to the buzzer alarm, causing it to sound an alarm.

[0037] The polyvinylidene fluoride-hexafluoropropylene nanofiber membrane and the nylon 66 / chitosan quaternary ammonium salt multi-scale nanofiber membrane of this embodiment were attached to two porous copper tapes, and the wires connecting the fiber membrane and the conductive layer were connected to a digital source meter 6514. A linear motor was used to drive the two friction layers of the triboelectric nanogenerator to perform contact separation motion, and the open-circuit voltage was measured using the digital source meter. The results show that after more than 100 cycles, the output voltage remained stable at around 35V. Figure 4 As shown.

Claims

1. A self-powered intelligent dust monitoring mask for mining, comprising a mask body (1), characterized in that, The mask body (1) is provided with a breathing valve (2), and a filter unit (3) based on a triboelectric nanogenerator is installed inside the breathing valve (2). The filter unit (3) includes, from the inside out, an inner porous metal conductive layer (31), a positive friction layer (32), a spacer layer (33), a negative friction layer (34), an outer porous metal conductive layer (35), and a fixed circular frame (36). The inner porous metal conductive layer (31) and the outer porous metal conductive layer (35) are respectively connected to a signal processing unit (4) through an external wire (6). The signal processing unit (4) is connected to the alarm display unit (5) via a wire; both the signal processing unit (4) and the alarm display unit (5) are installed on the outside of the mask body (1); the signal processing unit (4) includes a noise filtering, signal amplification and digital-to-analog conversion module for the acquired signal, and the alarm display unit (5) includes a miniature display, a buzzer and a power management module; the signal processing unit (4) is responsible for noise filtering and signal amplification of the received characteristic electrical signal and transcoding it, and the processed electrical signal is received by the alarm display unit (5) and displayed on the miniature display.

2. The intelligent mining mask with self-driven dust monitoring according to claim 1, characterized in that, The positive friction layer (32) is a multi-scale nanofiber membrane composed of nylon 66 / chitosan quaternary ammonium salt, the negative friction layer (34) is a polyvinylidene fluoride-hexafluoropropylene nanofiber membrane, the spacer layer (33) is a foam pad, and the inner porous metal conductive layer (31) and the outer porous metal conductive layer (35) are both porous conductive copper tapes.

3. The method for preparing a self-powered dust monitoring smart mask for mining according to claim 2, characterized in that, Includes the following steps: Preparation of S1, positive friction layer (32) First, Nylon 66 and chitosan quaternary ammonium salt were dissolved together in trifluoroethanol solvent and stirred continuously at room temperature for 12 hours to form a uniform and transparent spinning precursor solution. The spinning precursor solution was loaded into a syringe, installed on an electrospinning machine, and spun. The fibers were collected on a polypropylene nonwoven fabric substrate 12 cm away from the needle tip to form a multi-scale nanofiber membrane of Nylon 66 / chitosan quaternary ammonium salt composite with nano and submicron diameter distribution, which served as a positive friction layer (32). S2, Preparation of negative friction layer (34) First, polyvinylidene fluoride-hexafluoropropylene was dissolved in N,N-dimethylformamide solvent and stirred at room temperature for 6 hours before electrospinning. The fibers were collected on a polypropylene nonwoven fabric substrate 12 cm from the needle tip to obtain a polyvinylidene fluoride-hexafluoropropylene nanofiber membrane as a negative friction layer (34). S3. Preparation of a filter unit based on a triboelectric nanogenerator (3) Perforated copper tape cut and punched by ultraviolet laser is used as the inner porous metal conductive layer (31) and the outer porous metal conductive layer (35); polyvinylidene fluoride-hexafluoropropylene nanofiber membrane and nylon 66 / chitosan quaternary ammonium salt composite multi-scale nanofiber membrane are respectively adhered to the two porous copper tapes; polyurethane foam material is cut and used as the spacer layer (33) between the two friction layers, and positive friction layer (32) and negative friction layer (34) are respectively pasted on the left and right sides of the spacer layer (33); wires are respectively set between the inner porous metal conductive layer (31) and the outer porous metal conductive layer (35) and their adjacent friction layers, and the connection with the external circuit is realized through the wires; S4. Preparation of intelligent masks for mining. The signal processing unit (4) and the alarm display unit (5) are installed on the mask body (1), the filter unit (3) is installed in the breathing valve (2), and the signal processing unit (4) is connected to the filter unit (3) and the alarm display unit (5) respectively through the external wire (6), thereby preparing a mining smart mask.

4. The method for preparing a self-powered dust monitoring smart mask for mining according to claim 3, characterized in that, In step S1, the mass ratio of nylon 66, chitosan quaternary ammonium salt, and trifluoroethanol is 3:4:

50.

5. The method for preparing a self-powered dust monitoring smart mask for mining according to claim 3, characterized in that, In step S1, the syringe is a 10mL syringe with an 18-gauge metal needle. The electrospinning conditions are: voltage 20kV, feed rate 0.5mL / h, roller speed 170r / min, ambient temperature 23~27℃, and relative humidity 40%~90%.

6. The method for preparing a self-powered dust monitoring smart mask for mining according to claim 3, characterized in that, In step S2, the mass ratio of polyvinylidene fluoride-hexafluoropropylene to N,N-dimethylformamide is 3:

20.

7. The method for preparing a self-powered dust monitoring smart mask for mining according to claim 3, characterized in that, The conditions for electrospinning in step S2 are: voltage 10kV, roller speed 200r / min, and humidity 50±5%.

8. The method for preparing a self-powered dust monitoring smart mask for mining according to claim 3, characterized in that, In step S3, the copper tape has a thickness of 60 μm and a pore size of 200 μm; the polyurethane foam material has a thickness of 2 mm.

9. The method for preparing a self-powered dust monitoring smart mask for mining according to claim 3, characterized in that, In step S3, the inner diameter and outer diameter of the spacer layer 33 are 30 mm and 40 mm, respectively.

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