Sound recognition sensor based on porous foam structure and preparation method and application thereof

Abstract

The invention discloses a sound recognition sensor based on a porous foam structure and a preparation method and application thereof, and the sensor comprises a porous foam sensing layer which is prepared from hydroxylated multi-walled carbon nanotubes, wet-process polyurethane resin, hydrolysis-resistant protein wet-process resin and ultra-dry N, N-dimethylacetamide; the PI adhesive tape electrode is formed by adhering copper foil to a PI adhesive tape; the porous foam sensing layer is clamped between the upper PI adhesive tape electrode and the lower PI adhesive tape electrode, and the surfaces, attached with the copper foils, of the two PI adhesive tape electrodes are in close contact with the two sides of the porous foam sensing layer respectively; the copper foils extend out of the PI adhesive tapes and are respectively connected with leads, and packaging and fixing of the sensor are achieved by pasting the PI adhesive tapes on the two sides. The mechanical toughness of the material is enhanced by constructing a polyurethane / protein composite matrix, meanwhile, the dispersion effect is optimized by utilizing the hydroxylated multi-walled carbon nanotubes, a stable conductive network is formed, and finally the sound recognition sensor capable of efficiently capturing and converting sound wave vibration signals is developed.

Description

Technical Field

[0001] This invention relates to a sound recognition sensor based on a porous foam structure, its preparation method, and its application, belonging to the field of dynamic pressure sensing technology. Background Technology

[0002] Voice recognition sensors are electronic devices that capture sound signals, convert them into electrical signals, and then process them using built-in algorithms to identify specific sound patterns or commands. In the field of voice recognition sensing, traditional sensors generally suffer from problems such as poor flexibility, difficulty in conformally fitting to irregular human body surfaces, and insufficient low-frequency response.

[0003] While emerging flexible polymer foam sensors can sense pressure by utilizing the deformation of pore structures, they still face two major technical bottlenecks: First, a single polymer matrix is ​​difficult to balance high elasticity and toughness, and is prone to plastic deformation or fatigue damage under frequent acoustic vibration deformation; second, conventional conductive fillers such as carbon black and unmodified carbon nanotubes are prone to agglomeration, resulting in poor stability of the conductive network, which in turn causes the sensor to have low sensitivity and poor signal-to-noise ratio in response to small pressure fluctuations caused by sound. Summary of the Invention

[0004] To address the problems existing in the prior art, this invention provides a sound recognition sensor based on a porous foam structure, its preparation method, and its application. By constructing a polyurethane / protein composite matrix to enhance the mechanical toughness of the material, and by utilizing hydroxylated multi-walled carbon nanotubes to optimize the dispersion effect and form a stable conductive network, a sound recognition sensor that can efficiently capture and convert sound wave vibration signals is finally developed.

[0005] To achieve the above objectives, the present invention employs a sound recognition sensor based on a porous foam structure, comprising:

[0006] The porous foam sensing layer is prepared from hydroxylated multi-walled carbon nanotubes, wet-process polyurethane resin, hydrolysis-resistant protein wet-process resin and ultra-dry N,N-dimethylacetamide.

[0007] PI tape electrode, made by adhering copper foil to PI tape;

[0008] The porous foam sensing layer is sandwiched between the upper and lower PI tape electrodes, and the copper foil attached to the two PI tape electrodes are in close contact with the two sides of the porous foam sensing layer respectively; the copper foil extends out of the PI tape and is connected to the wires respectively, and the sensor is encapsulated and fixed by pasting the PI tape on both sides.

[0009] As an improvement, the porous structure of the porous foam sensing layer is induced by wet phase separation using ultra-dry N,N-dimethylacetamide.

[0010] As an improvement, each PI tape electrode consists of a PI tape and two independent copper foils. The two copper foils are respectively adhered to both ends of the PI tape, and a preset interval is maintained between the two copper foils to ensure independent conductivity.

[0011] A second aspect of the present invention also provides a method for preparing the sound recognition sensor based on a porous foam structure, comprising the following steps:

[0012] S1. Preparation of porous foam sensing layer

[0013] a) Weigh out hydroxylated multi-walled carbon nanotubes, wet-process polyurethane resin, and hydrolysis-resistant protein wet-process resin, and mix them thoroughly to form a prepolymer mixture;

[0014] b) Pour the prepolymer mixture into a molding container for shaping;

[0015] c) The shaped prepolymer mixture is placed in an ultra-dry N,N-dimethylacetamide solution and subjected to dynamic stirring.

[0016] d) The prepolymer mixture after treatment is placed in an oven and dried to obtain a porous foam sensing layer;

[0017] S2. Preparation of PI tape electrodes

[0018] The PI tape and copper foil are cut to the size of the porous foam sensing layer. The copper foil is then adhered to one side of the PI tape, with the end of the copper foil extending out of the PI tape to connect the wires, thus obtaining the PI tape electrode.

[0019] S3, Sensor Packaging

[0020] The porous foam sensing layer is placed between the upper and lower PI tape electrodes, so that the copper foil adhered to the two PI tape electrodes are tightly attached to the two sides of the porous foam sensing layer. The copper foil extending out of the PI tape is then connected to the wires. The sensor is encapsulated and fixed by pasting the edges of the PI tapes on both sides.

[0021] As an improvement, in step a), the weight ratio of hydroxylated multi-walled carbon nanotubes, wet-process polyurethane resin, and hydrolysis-resistant protein wet-process resin is 1:(150-250):(250-350).

[0022] As an improvement, in step a), the mixing process is carried out using a stirring paddle for 5-15 minutes; in step b), the setting time is 5-15 minutes.

[0023] As an improvement, in step c), the concentration of the ultra-dry N,N-dimethylacetamide solution is 15-20%, and the dynamic stirring time is 10-15 h.

[0024] As an improvement, in step d), the drying temperature of the oven is 60-80℃.

[0025] A third aspect of the present invention also provides a sound recognition sensor based on a porous foam structure prepared by the described method, which is used in at least one of the following applications:

[0026] (1) Application in human motion monitoring equipment;

[0027] (2) Application in health monitoring equipment;

[0028] (3) Application in human voice recognition devices.

[0029] Mechanism of the invention:

[0030] This invention uses wet-process polyurethane resin (WPU) and hydrolyzable protein wet-process resin (HVP) as matrices. Phase separation and recombination are induced by dynamic stirring with an ultra-dry N,N-dimethylacetamide (DMF) solution, ultimately resulting in a flexible porous foam with a cross-linked network structure through thermosetting. The core principle lies in the swelling, unentanglement, and redistribution of WPU and HVP in a DMF solution through prolonged dynamic stirring. During this process, the soft and hard microphase separation structure of WPU intertwines with HVP, and is subsequently fixed through physical interactions such as hydrogen bonding during drying, constructing an elastic three-dimensional porous framework. Hydroxylated multi-walled carbon nanotubes (MWCNT-OH) serve as conductive fillers, and their content directly affects the foam's conductivity: MWCNT-OH disperses within the matrix during stirring and forms conductive pathways within the porous structure. When pressure is applied to the foam, the porous structure undergoes reversible deformation, causing changes in the contact resistance between the internal MWCNT-OH particles, thereby converting mechanical signals into electrical signals. After encapsulation, the copper electrode collects the resistance change and uses external circuitry to detect and output the piezoresistive signal. The WPU provides high elasticity and deformation recovery, while the HVP enhances the material's toughness and structural stability. Together, they ensure the foam maintains structural integrity and response repeatability under cyclic pressure. The physical bond between MWCNT-OH and the polymer matrix also helps maintain the connectivity and stability of the conductive network during deformation, thus endowing the sensor with reliable piezoresistive performance.

[0031] Compared with the prior art, the beneficial effects of the present invention are:

[0032] 1. Process Innovation and Structural Controllability: Unlike traditional direct blending foaming or coating methods, this invention involves dynamically stirring the pre-formed WPU / HVP blend in a DMF solution of a specific concentration (18%) for 12 hours. This crucial step utilizes the principle of solvent-induced phase separation, allowing the polymer chains to rearrange and separate from the phase under swelling and dynamic shearing, resulting in a more precise and controllable formation of a uniform, fine, and highly interconnected three-dimensional porous network structure. This structure provides an ideal framework for stress transfer and deformation.

[0033] 2. Enhanced filler dispersion and interfacial bonding: The prolonged dynamic stirring environment not only acts on the polymer matrix but also strongly promotes the physical dispersion and directional distribution of MWCNT-OH in the viscous prepolymer system, effectively preventing the agglomeration of nanofillers. MWCNT-OH is uniformly fixed on the formed porous framework, constructing a stable and efficient conductive pathway network, thus improving the conductivity uniformity of the sensor.

[0034] 3. Optimized Mechanical and Sensing Properties: The composite matrix, composed of WPU (providing high elasticity) and HVP (enhancing toughness), combined with the aforementioned unique porous structure, endows the foam material with excellent flexibility and outstanding deformation recovery. This allows the sensor to produce significant and reversible deformation under minute pressure, making it extremely sensitive to pressure changes (high sensitivity). Simultaneously, good elasticity ensures the sensor's rapid response, recovery, and stability during long-term cyclic use.

[0035] 4. Integrated Molding and Simplified Integration: This method directly obtains a complete foam block with a cross-linked network structure through integrated solution treatment and thermal drying, avoiding complex post-processing steps. The resulting foam is easy to cut into customized shapes and can be quickly fabricated into sensor devices through simple copper electrode bonding and polyimide tape encapsulation. The process is simple, has good repeatability, and is conducive to large-scale production.

[0036] 5. Performance Adjustability: By systematically changing the amount of MWCNT-OH added, the conductivity, pore structure and overall mechanical properties of the foam can be continuously and effectively controlled, thereby optimizing key performance indicators such as sensor sensitivity, detection range and linearity, and providing the possibility of customizing sensor performance for different application scenarios. Attached Figure Description

[0037] Figure 1 This is a structural diagram of the sound recognition sensor of the present invention;

[0038] Figure 2 This is a flowchart illustrating the fabrication process of the sound recognition sensor of the present invention.

[0039] Figure 3 This is an electron microscope image of the sound recognition sensor of Embodiment 3 of the present invention;

[0040] Figure 4 The sensitivity test results of the sound recognition sensor in Embodiment 3 of the present invention;

[0041] Figure 5 The results are the response / recovery time test results of the sound recognition sensor in Embodiment 3 of the present invention;

[0042] Figure 6 This is a current change response diagram of the sound recognition sensor under different pressures in Embodiment 3 of the present invention;

[0043] Figure 7 This is a current change response diagram of the sound recognition sensor at different frequencies in Embodiment 3 of the present invention;

[0044] Figure 8 The results of the repeatability test of the sound recognition sensor in Embodiment 3 of the present invention;

[0045] Figure 9 The results are the test results of the sound recognition sensor sound recognition application in Embodiment 3 of the present invention. Detailed Implementation

[0046] The following embodiments are further illustrations of the present invention and serve as explanations of the technical content of the present invention. However, the essence of the present invention is not limited to the embodiments described below. Those skilled in the art can and should know that any simple changes or substitutions based on the spirit of the present invention should fall within the protection scope claimed by the present invention.

[0047] All raw materials used in the experiment were industrial-grade and readily available. Specific supplier information is as follows:

[0048] Hydroxylated multi-walled carbon nanotubes: purchased from Shenzhen Suiheng Graphene Technology Co., Ltd.

[0049] Wet-process polyurethane resin: purchased from Shanghai Huide Technology Co., Ltd.;

[0050] Hydrolyzable protein wet-process resin: purchased from Shanghai Huide Technology Co., Ltd.;

[0051] Ultra-dry N,N-dimethylacetamide: purchased from Anhui Zesheng Technology Co., Ltd.

[0052] Example 1

[0053] This embodiment provides a sound recognition sensor based on a porous foam structure, the structure of which is as follows: Figure 1 As shown, the specific preparation method is as follows:

[0054] 1. Preparation of porous foam sensing layer

[0055] (1) Weigh 28.8g of wet polyurethane resin and 43.2g of hydrolyzable protein wet resin at a weight ratio of 2:3, mix them thoroughly to form a prepolymer mixture, and stir with a stirring paddle for 10 minutes during the mixing process;

[0056] (2) Pour the above prepolymer mixture into a petri dish and allow it to set for 10 minutes;

[0057] (3) Prepare an 18% N,N-dimethylacetamide solution, place the shaped prepolymer mixture in the solution and stir dynamically for 12 hours to induce the formation of a porous structure through wet phase separation (NIPS);

[0058] (4) The prepolymer mixture after solution treatment is placed in an oven and dried. The oven temperature is set to 70°C to obtain a porous foam sensing layer. The sensing layer is made of wet polyurethane resin, hydrolyzable protein wet resin and N,N-dimethylacetamide.

[0059] 2. Preparation of PI tape electrodes

[0060] (1) Cut the PI tape and copper foil to the same size as the width of the porous foam sensing layer mentioned above;

[0061] (2) Attach two copper foils to the side of the PI tape that is in contact with the porous foam sensing layer, keeping a gap between the two copper foils so that the ends of the two copper foils extend out of the PI tape. The extended parts are used to connect external wires, thus obtaining the PI tape electrode.

[0062] 3. Sensor Packaging

[0063] The prepared porous foam sensing layer is placed between two layers of PI tape electrodes, with the copper foil-attached sides of the two PI tape electrodes in contact with both sides of the porous foam sensing layer. The copper foil extending from the PI tape is connected to wires, and the layer is encapsulated and fixed by attaching the PI tape to both sides. The encapsulation process is as follows: Figure 2 As shown.

[0064] 4. Performance testing connection

[0065] One end of the wire is connected to external experimental equipment to measure the performance of the sensor.

[0066] Example 2

[0067] This embodiment provides a sound recognition sensor based on a porous foam structure. Its preparation method is basically the same as that in Embodiment 1, with the only difference being:

[0068] In the prepolymer preparation stage of the porous foam sensing layer, 28.8g of wet polyurethane resin, 43.2g of hydrolysis-resistant protein wet resin and 0.072g of hydroxylated multi-walled carbon nanotubes were weighed in proportion and mixed to form a conductive prepolymer mixture.

[0069] The remaining preparation steps (sizing, solution treatment, drying, electrode preparation, and packaging) are the same as in Example 1.

[0070] Example 3

[0071] This embodiment provides a sound recognition sensor based on a porous foam structure. Its preparation method is basically the same as that in Embodiment 1, with the only difference being:

[0072] In the prepolymer preparation stage of the porous foam sensing layer, 28.8g of wet polyurethane resin, 43.2g of hydrolysis-resistant protein wet resin and 0.144g of hydroxylated multi-walled carbon nanotubes were weighed in proportion and mixed to form a conductive prepolymer mixture.

[0073] The remaining preparation steps (sizing, solution treatment, drying, electrode preparation, and packaging) are the same as in Example 1.

[0074] The porous foam sensing layer in this embodiment has a porous structure, such as Figure 3 As shown, this porous foam sensing layer was prepared using a wet phase separation technique, exhibiting a uniformly distributed and interconnected open porous structure. The pores are irregular in shape and diverse in size, forming a three-dimensional network morphology with a high specific surface area. This interconnected porous feature is beneficial for mass transfer and interfacial response, providing an effective structural basis for its sensing function.

[0075] The sensing performance of the voice recognition sensor prepared in this embodiment was tested, and the results are as follows:

[0076] like Figure 4As shown, the voice recognition sensor prepared in Example 3 exhibits segmented high sensitivity (0-0.5MPa low-pressure region S1=24.013, 0.5-1.1 MPa medium-pressure region S2=11.729, 1.1-5 MPa high-pressure region S3=4.662), which is directly related to its unique morphological structure: through a dynamic solvent-induced phase separation process, MWCNTs are uniformly dispersed and anchored on a three-dimensional interconnected porous elastic framework with uniform pore size distribution formed by WPU / HVP. Under low pressure (0-0.5MPa), this structure causes the thin layer of pore walls to undergo significant elastic bending and contact, resulting in rapid reconstruction of the MWCNT conductive pathway and generating extremely high initial sensitivity; as the pressure increases, the porous structure gradually densifies, and the increased deformation resistance leads to a decrease in the sensitivity gradient, but still maintains a significant response. Compared to sensors prepared by conventional physical blending / molding foaming or coating methods, traditional methods often result in low initial sensitivity (typically less than 10 across the entire range), narrow linear range, and significant hysteresis due to uneven MWCNT dispersion and inconsistent pore sizes. However, the structural improvement of this invention utilizes controllable phase separation to form a homogeneous porous network and a stable, dispersed conductive path, enabling the sensor to achieve a multiple-fold increase in sensitivity over a wide pressure range (especially in the critical low-pressure detection range), while maintaining good response linearity and repeatability. This fully demonstrates the significant advantages of this fabrication process in constructing high-performance flexible piezoresistive sensing materials.

[0077] like Figure 5 As shown, the voice recognition sensor prepared in Example 3 achieves a fast response / recovery time (140ms / 150ms), which is directly related to its unique micro / nano structure design: the three-dimensional interconnected, highly elastic, thin-walled porous network formed by dynamic solvent-induced phase separation of the WPU / HVP matrix endows the material with extremely low mechanical hysteresis and excellent deformation recovery ability, enabling the structure to undergo rapid reversible deformation under pressure loading / unloading; at the same time, MWCNTs are uniformly dispersed and firmly anchored in the pore walls, forming a stable and responsive conductive path, ensuring the synchronous and efficient conversion of electrical signals and mechanical deformation. Compared with existing traditional sensors that use dense composite materials, disordered macroporous foams, or fillers that are prone to detachment, the latter often suffer from problems such as high viscoelasticity of the matrix, closed or non-interconnected pores, and weak bonding between the filler and the matrix, resulting in a longer response / recovery time (usually >300ms) and a tendency for signal drift or residue. This invention significantly improves the dynamic mechanical properties and electrical response speed of materials through structural homogenization and interface strengthening, achieving sub-second-level rapid signal tracking. This is crucial for applications such as real-time monitoring of dynamic pressure, vibration, or biosignals, demonstrating its significant performance advantage in response speed.

[0078] like Figure 6As shown, the sound recognition sensor prepared in Example 3 exhibits a reliable and repeatable stress response under different pressure stimuli. This performance is directly attributed to its unique morphological structure: the cross-linked elastic matrix composed of WPU / HVP forms a three-dimensional interconnected, highly ordered, and moderately strong porous network through dynamic solvent-induced phase separation. This structure has the following core advantages: (1) Its uniform porous distribution ensures that stress is uniformly transmitted within the material, avoiding stress concentration, thereby generating linear or quasi-linear stable deformation under different pressure levels; (2) The uniformly dispersed MWCNTs form a continuous and stable conductive network in the pore walls, which can track the contact / separation changes of the pore walls in real time and accurately, converting the macroscopic deformation of the structure into a reliable resistance signal; (3) The excellent high elasticity and deformation recovery capability of the matrix (derived from the synergistic effect of the elasticity of WPU and the toughness of HVP) ensures that the sensor can quickly recover to the initial structure and resistance state after cyclic loading / unloading, exhibiting low hysteresis and high repeatability response characteristics. Compared to many existing flexible sensors based on random foaming, easy agglomeration of fillers, or high viscoelasticity of the matrix, the latter often suffer from problems such as significant nonlinearity in stress response, signal drift, large hysteresis loops, and poor repeatability due to structural inhomogeneity, unstable conductive paths, or plastic deformation of the matrix. The structure of this invention fundamentally improves the structural stability and electrical reliability of the sensing unit over a wide pressure range, achieving repeatable mapping of pressure signals. This is crucial for applications requiring precise pressure quantification (such as electronic skin, medical monitoring, and voiceprint recognition), demonstrating a significant improvement in measurement accuracy and reliability.

[0079] like Figure 7As shown, the sound recognition sensor prepared in Example 3 exhibits good dynamic stability, which is fundamentally due to its integrated, highly elastic and robust micro-nano structure design. Through dynamic solvent-induced phase separation process, MWCNTs are uniformly and stably anchored in a tough and highly cross-linked three-dimensional porous elastic network formed by WPU / HVP. The core advantages of this structure are: (1) Toughness and high elasticity of the matrix: WPU provides excellent elastic recovery force, and the reinforcing effect of HVP significantly improves the toughness of the pore walls, so that the structure can effectively resist fatigue damage and plastic deformation in repeated compression-rebound cycles and maintain the integrity of the structure; (2) Stable conductive network: MWCNTs and polymer matrix form a strong interfacial bond through physical entanglement and hydrogen bonding, which avoids the slippage, detachment or agglomeration of fillers under dynamic stress and ensures the stability of the conductive path in long-term cycling; (3) Uniform and interconnected pore structure: The homogeneous porous network allows stress to be uniformly distributed, preventing structural collapse or crack initiation caused by local stress concentration, and ensuring the long-term reliability of the sensing mechanism. Compared to many existing traditional sensors based on physical blending, with filler migration or high viscoelasticity / brittleness of the matrix, the latter often suffer from signal attenuation, baseline drift, decreased response consistency, and even structural failure during dynamic cyclic testing. This invention, through a strategy of "structural integration" and "interface reinforcement," significantly improves the signal repeatability and durability of the sensor under different compression rates and cycle counts. This is crucial for practical applications that need to handle complex dynamic loads (such as motion monitoring and sound signal acquisition).

[0080] like Figure 8As shown, the voice recognition sensor prepared in Example 3 can still maintain excellent cycling stability after 2000 cycles. This key performance is directly due to its highly integrated, tough and self-healing three-dimensional cross-linked network structure constructed by the dynamic solvent-induced phase separation process. The specific connections are as follows: First, the strong, elastic, and fully cross-linked polymer matrix formed by WPU and HVP provides the entire foam structure with excellent fatigue resistance and deformation recovery capabilities, enabling it to effectively resist plastic deformation or the generation and propagation of microcracks caused by repeated stress during long-term, high-frequency compression cycles. Second, MWCNTs are uniformly dispersed and firmly anchored (through physical entanglement and hydrogen bonding) to the elastic framework during dynamic stirring, constructing a conductive network with extremely high mechanical stability. This prevents the migration, detachment, or aggregation of nanofillers under cyclic stress, ensuring the long-term stability of the electrical signal transmission path. Finally, the homogeneous, highly interconnected micro / nano porous structure with moderate pore size formed by this process can effectively disperse and dissipate cyclic stress, preventing local structural collapse caused by stress concentration, and fundamentally ensuring the structural durability of the sensing unit. Compared with many existing flexible sensors based on physical blending, weak interfacial bonding, or easily aging matrices, the latter often exhibit significant signal attenuation, baseline drift, or increased hysteresis after hundreds of cycles, and may even fail due to structural damage. In contrast, the material design of this invention achieves a three-in-one approach of "structural elasticity", "interface stability" and "conductive network robustness", which keeps the performance degradation of the sensor under long-term dynamic working conditions at an extremely low level. This is crucial for practical applications requiring high reliability and long lifespan, such as wearable electronics and long-term health monitoring, and fully demonstrates the significant advantages of this solution in terms of cycle stability.

[0081] like Figure 9As shown, the sound recognition sensor prepared in Example 3 was successfully applied to sound recognition, fundamentally benefiting from the synergistic effect of its unique three-dimensional porous structure and excellent dynamic response characteristics. Specifically, the highly elastic, low-density, thin-walled, and highly interconnected porous network formed by the WPU / HVP matrix has extremely low mechanical impedance, enabling it to sensitively sense the micro-amplitude, high-frequency air pressure fluctuations induced by sound waves (pressure waves) and efficiently convert them into its own minute deformation. Simultaneously, the highly sensitive and stable conductive network constructed by MWCNTs uniformly dispersed and firmly anchored in the pore walls can convert this minute and rapid deformation into a measurable resistance change signal in real time and accurately. This combination of a "low-modulus structure" and a "high-sensitivity conductive network" endows the sensor with excellent high-frequency response capability, a low detection limit, and high discrimination against weak sound pressure signals, enabling it to capture and distinguish the characteristic vibration patterns caused by different sounds (such as different vowels and consonants), thereby achieving sound signal recognition. Compared to traditional sensors based on dense membrane materials, rigid structures, or slow response speeds, existing technologies often struggle to effectively respond to high-frequency, weak sound wave signals due to high structural damping, inherent frequency mismatch, or insufficient sensitivity. This results in limitations in sound recognition applications, such as low sensitivity, poor signal-to-noise ratio, and inability to distinguish subtle acoustic features. This invention, through "structural acoustic matching design," significantly improves the sensor's sound wave energy capture efficiency and conversion sensitivity, demonstrating its enormous application potential in emerging fields such as wearable voice interaction, non-contact acoustic sensing, and bioacoustic monitoring. It represents a direct leap from material structure design to high-end application performance.

[0082] Example 4

[0083] This embodiment provides a sound recognition sensor based on a porous foam structure. Its preparation method is basically the same as that in Embodiment 1, with the only difference being:

[0084] In the prepolymer preparation stage of the porous foam sensing layer, 28.8g of wet polyurethane resin, 43.2g of hydrolysis-resistant protein wet resin and 0.216g of hydroxylated multi-walled carbon nanotubes were weighed in proportion and mixed to form a conductive prepolymer mixture.

[0085] The remaining preparation steps (sizing, solution treatment, drying, electrode preparation, and packaging) are the same as in Example 1.

[0086] The sound recognition sensors based on porous foam materials prepared through Examples 1 to 4 can systematically study and reveal the influence of MWCNT-OH content on the structure and properties of foam materials (such as establishing the threshold and rules for conductive network formation, regulating and optimizing piezoresistive sensing performance, analyzing the influence of MWCNT-OH on porous structure, balancing mechanical properties and sensing performance, and verifying the controllability of material design and process). This provides a key basis for optimizing sensor performance, effectively improving the sensitivity and detection range of sound recognition sensors, and enabling the final piezoresistive sensor to achieve the best balance between sensitivity, stability, flexibility, and manufacturing cost, thereby promoting the practical application of this sensor in fields such as human motion monitoring, health monitoring, and sound recognition.

[0087] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions or improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A sound recognition sensor based on a porous foam structure, characterized in that, include: The porous foam sensing layer is prepared from hydroxylated multi-walled carbon nanotubes, wet-process polyurethane resin, hydrolysis-resistant protein wet-process resin and ultra-dry N,N-dimethylacetamide. PI tape electrode, made by adhering copper foil to PI tape; The porous foam sensing layer is sandwiched between the upper and lower PI tape electrodes, and the copper foil attached to the two PI tape electrodes are in close contact with the two sides of the porous foam sensing layer respectively; the copper foil extends out of the PI tape and is connected to the wires respectively, and the sensor is encapsulated and fixed by pasting the PI tape on both sides.

2. The sound recognition sensor based on a porous foam structure according to claim 1, characterized in that, The porous structure of the porous foam sensing layer is induced by wet phase separation using ultra-dry N,N-dimethylacetamide.

3. The sound recognition sensor based on a porous foam structure according to claim 1, characterized in that, Each PI tape electrode consists of a PI tape and two independent copper foils. The two copper foils are respectively adhered to both ends of the PI tape, and a preset interval is maintained between the two copper foils to ensure independent conductivity.

4. The method for fabricating a sound recognition sensor based on a porous foam structure as described in any one of claims 1-3, characterized in that, Includes the following steps: S1. Preparation of porous foam sensing layer a) Weigh out hydroxylated multi-walled carbon nanotubes, wet-process polyurethane resin, and hydrolysis-resistant protein wet-process resin, and mix them thoroughly to form a prepolymer mixture; b) Pour the prepolymer mixture into a molding container for shaping; c) The shaped prepolymer mixture is placed in an ultra-dry N,N-dimethylacetamide solution and subjected to dynamic stirring. d) The prepolymer mixture after treatment is placed in an oven and dried to obtain a porous foam sensing layer; S2. Preparation of PI tape electrodes The PI tape and copper foil are cut to the size of the porous foam sensing layer. The copper foil is then adhered to one side of the PI tape, with the end of the copper foil extending out of the PI tape to connect the wires, thus obtaining the PI tape electrode. S3, Sensor Packaging The porous foam sensing layer is placed between the upper and lower PI tape electrodes, so that the copper foil adhered to the two PI tape electrodes are tightly attached to the two sides of the porous foam sensing layer. The copper foil extending out of the PI tape is then connected to the wires. The sensor is encapsulated and fixed by pasting the edges of the PI tapes on both sides.

5. The method for fabricating a sound recognition sensor based on a porous foam structure according to claim 4, characterized in that, In step a), the weight ratio of hydroxylated multi-walled carbon nanotubes, wet-process polyurethane resin, and hydrolysis-resistant protein wet-process resin is 1:(150-250):(250-350).

6. The method for fabricating a sound recognition sensor based on a porous foam structure according to claim 4, characterized in that, In step a), the mixing process is carried out using a stirring paddle for 5-15 minutes; in step b), the setting process takes 5-15 minutes.

7. The method for fabricating a sound recognition sensor based on a porous foam structure according to claim 4, characterized in that, In step c), the concentration of the ultra-dry N,N-dimethylacetamide solution is 15-20%, and the dynamic stirring time is 10-15 h.

8. The method for fabricating a sound recognition sensor based on a porous foam structure according to claim 4, characterized in that, In step d), the drying temperature of the oven is 60-80℃.

9. A sound recognition sensor based on a porous foam structure, prepared by the method according to any one of claims 1-3 or any one of claims 4-8, in at least one of the following applications: (1) Application in human motion monitoring equipment; (2) Application in health monitoring equipment; (3) Application in human voice recognition devices.

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