208 results about "Noise propagation" patented technology

The invention discloses a noise monitoring point site selection method and system based on a noise map, and relates to the technical field of environmental noise monitoring, and the method comprises the steps: constructing a three-dimensional topology network based on a three-dimensional noise intensity matrix, calculating an optimal sound propagation path through employing a quantum heuristic topology optimization algorithm, and obtaining an optimal sound propagation path; the weights of nodes in the three-dimensional topology network are optimized in combination with quantum annealing, and an acoustic topology characteristic spectrum is generated; extracting multi-scale noise propagation features through a convolutional neural network according to the acoustic topological feature map, constructing a gridding space demand matrix in combination with a monitoring equipment parameter library and coverage constraint conditions, and generating an optimal noise monitoring network site selection scheme according to the gridding space demand matrix; according to the invention, a quantum heuristic topology optimization algorithm is combined with quantum annealing to optimize the node weight of the three-dimensional topology network, and intelligent optimization and dynamic adjustment of the sound propagation path are realized.

The invention relates to the technical field of chip testing, and discloses a chip power supply noise influence testing method and device. The method comprises the following steps: carrying out multi-dimensional data acquisition on a chip power supply by utilizing a multi-mode sensing array to obtain original sensing data, and carrying out time synchronization calibration and signal preprocessing to obtain high-quality multi-dimensional data; carrying out time-frequency domain decomposition and correlation calculation on the processed data, and carrying out time delay and position calculation to determine noise source distribution; noise source distribution is mapped to a chip layout, multi-physical field calculation is carried out, a coupling propagation matrix is generated, and a noise propagation characteristic spectrum is obtained through characteristic value decomposition and path calculation; and designing a test condition based on the propagation characteristic spectrum, performing a chip function module performance test, establishing a response relationship between noise and function performance, determining a function failure noise critical value and a tolerance boundary, and forming a complete power supply noise influence test result. According to the method, the accurate positioning of the chip power supply noise is realized, and the evaluation accuracy of the power supply noise influence is improved.

The invention discloses a dynamic noise analysis method and device for an urban elevated road and a medium, and belongs to the technical field of noise monitoring and analysis. The method comprises the following steps: acquiring a three-dimensional geographic information model and real-time traffic flow data of a target elevated road; processing the three-dimensional geographic information model based on a sound wave propagation attenuation model to generate a noise propagation path grid; fusing the real-time traffic flow data with a noise source intensity calculation model to generate a dynamic noise source intensity sequence; calculating a real-time equivalent sound pressure level of each grid unit through a noise superposition algorithm in combination with the dynamic noise source intensity sequence and the noise propagation path grid; performing rolling prediction on the real-time equivalent sound pressure level based on a time window sliding mechanism to generate a noise space-time distribution thermodynamic diagram; and according to the noise space-time distribution thermodynamic diagram, identifying a noise exceeding area, and outputting a dynamic noise evaluation report. According to the method, the technical effect of dynamically predicting and analyzing the noise of the elevated road is achieved.

The utility model discloses a mute floor which comprises a surface treatment layer, a protection layer, a decoration layer, a first carrier, a first buffer layer and a second carrier. The surface treatment layer is arranged on one side of the protection layer, the decoration layer is arranged on the other side of the protection layer, the first carrier is arranged between the decoration layer and the first buffer layer, the first buffer layer is arranged between the first carrier and the second carrier, and the first buffer layer is of a porous structure and / or a net structure. A buffer groove is formed in at least one side face of the first buffer layer and extends to the two ends of the side face. By arranging the floor with the first buffer layer with the porous and / or honeycomb structure, noise is reflected and refracted for multiple times in the porous and / or honeycomb structure, so that sound is attenuated, a sound wave propagation path is prolonged, and the effect of more effectively reducing noise propagation is achieved.

The invention relates to a four-body coupling vehicle base vibration noise prediction optimization method and system, and relates to the technical field of rail transit operation and maintenance optimization, and the method comprises the steps: obtaining a vehicle base multi-physics field correlation monitoring data set; carrying out system level assembly in a multi-physics field co-simulation environment to generate a coupled system state parameter matrix; generating sound ray bending trajectory data; loading the vehicle operation condition time sequence data to a wave equation solver, and outputting vibration noise propagation characteristic field distribution data; building a network topology structure to form a prediction model, and executing a back propagation algorithm to train network parameters to a convergence state; designing a vehicle scheduling scheme chromosome coding structure to generate a candidate solution population; and performing selection, crossover and variation genetic operations on the primary solution set, and outputting a vehicle base operation and maintenance scheduling real-time optimization scheme. The method has the beneficial effects that the precision and generalization ability of vibration noise prediction in the future time period are greatly improved, and the fundamental transformation from passive vibration isolation treatment to active prediction optimization is realized.

The embodiment of the invention discloses a sound barrier optimization method and device based on a noise source database and a medium, and relates to the technical field of sound barriers, and the method comprises the steps: collecting the multi-source noise time sequence data corresponding to a target road, carrying out the noise feature extraction and noise prediction based on the multi-source noise time sequence data, constructing the noise source database, and obtaining the noise source database; the noise source database comprises a real-time noise feature database corresponding to a current time node and a predicted noise feature database corresponding to a future time node; performing multi-period noise propagation simulation on the noise sensitive area of the target road through the real-time noise feature database and the predicted noise feature database, determining sensitive noise data corresponding to multiple time nodes, and determining a multi-period constraint condition corresponding to the sound barrier; and based on the multi-period constraint condition and a preset multi-objective optimization algorithm, determining a corresponding sound barrier design parameter solution set, so as to determine a sound barrier optimization strategy according to the design parameter solution set.

The invention discloses a common-mode electromagnetic interference modeling and suppression method for a matrix converter, and the method comprehensively considers high-frequency parameters and topological characteristics, builds a conduction CM EMI equivalent circuit model of the matrix converter, completes the impedance network fitting of key elements and the extraction of high-frequency parasitic parameters, and achieves the modeling and suppression of the common-mode electromagnetic interference of the matrix converter. The precision of the CM EMI model of the matrix converter is improved, and the analysis of the CM EMI characteristics of the matrix converter is simplified. According to the common-mode electromagnetic interference suppression method for the matrix converter, CM EMI characteristics of the matrix converter are analyzed, a low-attenuation loop in the converter is constructed by adopting a method of combining a neutral line leading-back type structure and increasing output filter capacitor neutral-point-to-ground parasitic capacitance, the propagation proportion of noise in a linear impedance stabilization network measurement branch is reduced, and the measurement accuracy of the common-mode electromagnetic interference suppression method for the matrix converter is improved. And effective suppression of low-cost CM EMI noise is realized on the premise of not depending on an input EMI filter.

The invention relates to a graph convolution multi-modal dialogue emotion recognition method based on emotion dimension compensation. The method belongs to the field of multi-modal emotion recognition. Comprising the following steps: respectively extracting original features of texts, audios and visual modalities by utilizing a pre-training model; detecting a mode missing condition, and generating a pseudo feature by using an available mode feature and context information; the multi-modal features are mapped to a VAD three-dimensional space, and prediction and enhancement are carried out; the global level is based on VAD similarity to connect cross-utterance nodes, and emotional consistency is quantified to capture long-distance interaction. In the local level, information spreading and node updating are carried out by calculating the similarity between different modal features in the same utterance; neighbor information is accumulated through multiple layers of image volumes, node weights are dynamically adjusted to suppress noise propagation, and finally utterance-level emotional representation is generated by fusing multi-modal features through mean pooling operation. According to the method, the emotion recognition performance in a modal missing scene is remarkably improved.

The invention relates to the technical field of emotion recognition, and discloses an emotion recognition method and system based on visual and auditory synergy, and the method comprises the steps: obtaining an original video stream and an original audio stream, introducing an explicit uncertainty quantification mechanism for a visual mode and an auditory mode, extracting features, and meanwhile, carrying out the recognition of the visual mode and the auditory mode. An uncertainty sequence that assesses its reliability is generated in parallel. Furthermore, the uncertainty sequence is used as a core guiding signal, and a cross-modal cross attention fusion process is dynamically modulated. The mechanism enables the model to adaptively suppress the contribution of an unreliable mode, and focuses on the interaction of high-quality signals, thereby effectively suppressing noise propagation, realizing robust multi-mode information complementation, and finally improving the accuracy of emotion recognition.

The invention belongs to the technical field of hydroacoustic detection, and particularly relates to a high-precision multi-beam sonar with echo noise suppression, the high-precision multi-beam sonar comprises a sonar detector, a transducer and a heater, the transducer is arranged in the middle of the inner side of the sonar detector, and the heater is arranged in the sonar detector. The sonar detector converts electric energy into a sound wave signal through a transducer by arranging the flow guide cover, the honeycomb damping shell, the silica gel damping agent filling layer, the reflection energy absorption frame, the variable-diameter reflection hole and the active isolation mechanism, and the sound wave signal is propagated in water. When sound waves rebound after encountering obstacles and being reflected, the honeycomb damping shell converts sound energy into heat energy through viscous friction of the silica gel damping agent filling layer in the honeycomb damping shell, and the honeycomb structure prolongs the noise propagation time through multiple reflection paths. The active isolation mechanism guides gas in a high-pressure helium tank through a micro air pump and enables the gas to be sprayed out of an air spraying hole, a bubble curtain with the diameter smaller than 1 mm is continuously manufactured to form an impedance abrupt change layer, and the influence of noise is further reduced.

An object of the invention is to provide an electromagnetic noise analysis device capable of analyzing a propagation path in a short time even for electromagnetic noise in a high frequency band and securing a certain level of reliability of an analysis result. For this purpose, an electromagnetic noise analysis device according to the invention includes: a propagation characteristic estimation unit configured to statistically estimate an electromagnetic field characteristic in a housing based on information about a housing structure and an electric wire path to output propagation characteristic probability distribution data; a propagation amount calculation unit configured to statistically estimate a noise propagation amount propagated from a noise source to an affected device based on a frequency characteristic of noise generated by the noise source and the propagation characteristic probability distribution data to output data of noise probability distribution on the affected device; and a malfunction risk determination unit configured to determine a malfunction risk of the affected device based on the data of the noise probability distribution on the affected device.

The utility model discloses a hand dryer which comprises a shell and an air outlet assembly, the shell is provided with an air inlet and an air outlet, the air outlet assembly comprises an air outlet pipe and a fan, the air inlet of the fan and one end of the air outlet pipe penetrate through the air outlet, all parts of the air outlet assembly are connected in a sealed mode, a partition plate is arranged in the shell, and a first sealing ring is arranged between the periphery of the partition plate and the shell. The partition plate divides the shell into an air inlet chamber and an air outlet chamber, the air outlet assembly is located in the air outlet chamber, a second sealing ring is arranged between the periphery of the air outlet assembly and the shell and divides the air outlet chamber into a first chamber and a second chamber, an air inlet of the fan is located in the first chamber, and the fan is located in the second chamber. The partition plate is provided with a partition plate opening used for communicating the first chamber with the air inlet chamber, and a third sealing structure is arranged at the joint of the air outlet pipe and the air outlet. According to the hand dryer, the second chamber and the outside are kept sealed through the arranged sealing ring structure, that is, the second chamber forms a sealed cavity, noise transmission of a fan is hindered through the sealed cavity, and noise generated when the hand dryer works is effectively reduced.

The invention relates to the technical field of wind power plant optimization, and discloses a wind power plant noise control and power optimization method and device, and the method comprises the steps: obtaining the multi-source noise data of a wind power plant, constructing a multi-source noise feature database, and constructing a noise propagation theoretical model; determining a plurality of monitoring points in the wind power plant based on the noise propagation theoretical model, and collecting actual multi-source noise data and fan operation data of the plurality of monitoring points in real time; on the basis of actual multi-source noise data and fan operation data, a multi-objective optimization function fusing constraint conditions is constructed by taking minimization of dispatching instruction difference, fan operation load and noise superscale as objectives; and solving the multi-objective optimization function to generate an optimal power distribution scheme of the fan under the noise constraint. According to the invention, intelligent monitoring and intelligent control can be carried out on the noise of the wind power plant near the residential area, so that the noise influence of the wind power plant on the nearby residential area is reduced, and the contradiction between the residential area and the wind power plant is solved.

The present invention discloses a hybrid active noise cancellation superposition method based on a neural network, including: W f W(n) or / and W b (n) is implemented by a linear filter FIR or IIR, and the filter parameters are iterated according to the LMS or RLMS algorithm. Since S(z) is non-linear, S’(z) can still be estimated by a neural network, and the parameters of the neural network are iteratively solved according to the BP algorithm. For the non-linear link existing in the path of the original noise propagation from the A-bit noise source to the B-bit speaker, such as the case where the original noise is too large, resulting in non-linearity of the device, if the feedforward filter can use a non-linear filter, it can better control the noise; for the non-linear link existing in the control channel from the C-bit error microphone to the B-bit speaker, such as the non-linearity of the error microphone or the non-linearity of the amplifier, if the feedback filter can use a non-linear filter, it can better control the noise.

The invention discloses a noise reduction and impact resistance gear structure and a transmission device. The noise reduction and impact resistance gear structure comprises a gear body, a buffering assembly and a noise reduction assembly, wherein the buffering assembly and the noise reduction assembly are arranged in the gear body; the buffering assembly is arranged in the gear body, and the noise reduction assembly comprises sound absorption cotton and is mounted in mounting grooves separated by the fixing frame. The gear box has remarkable noise reduction and impact resistance and can effectively protect gears. And the lubricating device in the gear box can accurately spray oil to provide continuous lubrication for the gear. In the operation process of the gear, the sound absorption cotton can absorb part of sound waves, and noise transmission is remarkably reduced. When the gear is subjected to large impact force, the gear body drives the fixing frame to extrude the telescopic rod, the whole gear body eccentrically moves, and therefore the impact force is dispersed, after the impact force disappears, the movable spring and the sliding spring release energy, the gear body is pushed to recover to the initial state, the service life of the gear is remarkably prolonged, and the operation stability of the gear is remarkably improved.

The invention relates to the technical field of ship navigation observation equipment, in particular to a sonar and noise detection integrated marine ecological monitoring buoy system, which comprises a sonar array dynamic regulation and control module which comprises a sonar array with an adjustable spatial position and dynamically adjusts the dip angle of the sonar array according to the noise propagation direction through a stepping motor driving mechanism, obtaining sonar target data; a noise collaborative sensing module; a sonar-noise closed-loop control module: a noise feature hierarchical extraction unit; a sonar parameter dynamic generation unit; a multi-modal fusion decision unit; the self-adaptive resource scheduling module is used for calculating the effective detection radius of each sonar based on noise energy distribution and dynamically distributing transmitting power; through innovative measures of cooperative work of multiple sonar arrays, noise feature extraction, intelligent resource scheduling and the like, the adaptability and monitoring accuracy of the marine ecological monitoring buoy system in a complex environment are greatly improved, and meanwhile extraction of ecological information and effective suppression of noise are achieved.

The invention relates to the technical field of automobile interior noise control, in particular to an automobile pressure release valve noise control method based on a local resonance acoustic superstructure. The method comprises the steps of obtaining basic data of a target vehicle; carrying out multi-working-condition noise testing based on the basic data of the target vehicle, and determining a main noise frequency; a main radiation source of pressure release valve noise is positioned based on the main noise frequency, and a key path of noise propagation in a vehicle is analyzed; extracting a noise main peak frequency based on the main noise frequency, the main radiation source and the key path, and determining a core noise reduction frequency band; setting a noise reduction target based on the core noise reduction frequency band; constructing a three-dimensional finite element model of the acoustic superstructure based on the basic form of the superstructure; inputting the acoustic superstructure part into the three-dimensional finite element model for simulation analysis; and a simulation analysis result is compared with an initial test result of the target vehicle, a noise reduction effect is analyzed, and the superstructure part is optimized. The sound absorption and insulation structure for specific frequency noise can be designed according to noise sources at the positions of different vehicle types.

The invention discloses a GIS-based sound environment threshold value rapid query method, and particularly relates to the technical field of environment noise monitoring and intelligent city management. The method comprises the following steps: acquiring meteorological data and topographic data, analyzing the influence of the environment on noise propagation, calculating an actual noise influence range by combining time information and utilizing a dynamic noise propagation model, adjusting a basic noise limit value, and forming a more accurate dynamic threshold value; in combination with real-time noise monitoring data and traffic flow data, a spatial buffer area algorithm is adopted to evaluate a noise exceeding range, complaint frequency weight is introduced to calculate the noise pollution severity of complaint points, and an optimal treatment scheme is intelligently matched; by continuously monitoring the treatment effect, if the noise pollution is not effectively reduced, the treatment strategy is dynamically adjusted, and the noise propagation model is continuously optimized, so that the accuracy of noise prediction and management is improved, a self-adaptive optimization intelligent noise supervision system is constructed, and the scientificity and intelligent level of urban noise treatment are improved.

The invention discloses a needle head bubble generator device and a sound insulation measurement method, which can reduce noise propagation by generating a bubble curtain in a needle head device and utilizing the sound absorption characteristic of the bubble curtain. The method mainly comprises the following steps: determining parameters of a needle device, and constructing a bubble curtain model of the needle device; a high-speed camera is used for shooting clear pictures of the bubbles, and an edge detection algorithm is used for solving a bubble diameter distribution rule; the emission frequency is changed, and sound insulation optimization is carried out on the resonance radius of the bubble curtain; the layer number and the inflation flow of the needle head device are changed, and sound insulation optimization is carried out on the volume concentration of the bubble curtain. The method has the advantages of being easy and convenient to operate, wide in application range, remarkable in noise reduction effect and the like, and has application value for various underwater noise control occasions.

The invention discloses an EVTOL vertical takeoff and landing site selection decision-making method based on a noise propagation mechanism. The method comprises the following steps: S1, determining an environment noise limit value of a building surface corresponding to each building in an urban area; s2, constructing a noise limit value contour surface spatial distribution model of the single building; s3, calculating to obtain a noise limit value contour surface spatial distribution model of various buildings in the urban area; s4, determining whether the candidate point positions meet noise requirements on the ground plane or not; s6, determining an EVTOL aircraft running track xi; and S7, checking whether the candidate point positions meet the noise requirement of the space operation process or not, and finally determining the site selection of the vertical take-off and landing field.

The invention discloses a sound barrier sound absorption material and a preparation and application method thereof, the sound barrier sound absorption material is composed of natural rock particles, an inorganic binder, a spherical foamed ceramic material and reinforced fibers, and the foamed ceramic is prepared into a spherical shape; the high porosity and high dispersity of the spherical particles and the three-dimensional structure of the spherical particles are utilized to fully absorb and scatter sound waves with different frequencies, noise propagation is effectively reduced, meanwhile, the natural rock material is utilized to endow the sound absorption material with good structural strength and stability, the sound absorption material can bear large external force impact, wind pressure and self-weight load, and the sound absorption effect is good. And the sound screen barrier can be reliably used for a long time in an outdoor severe environment and is not easy to deform, crack and the like.

The invention discloses a liquid metal-based vibration suppression and noise reduction cooling motor structure, which comprises a shell, a motor stator and a motor rotor, and is characterized in that the interior of the shell is of a hollow structure, the inner surface and the outer surface of the shell are covered with honeycomb structure units, and the interior of the hollow shell is divided into an upper semicircular ring layer cavity and a lower semicircular ring layer cavity; cavities of the upper and lower semicircular ring layers are filled with liquid metal; liquid metal-based magnetofluid is filled between the casing and the motor stator, and sealing rings are arranged at the two axial ends, in contact with the internal honeycomb structure, of the stator core. The honeycomb structures are designed on the inner surface and the outer surface of the shell, filling of the liquid metal and application of the liquid metal-based magnetofluid are combined, the heat dissipation performance of the motor is remarkably improved, the liquid metal-based magnetofluid plays a vibration reduction role between the stator and the shell, vibration impact in the operation of the motor is relieved, and the service life of the motor is prolonged. Noise generated during operation of the motor can be absorbed and attenuated, noise propagation is further reduced through an interference path of the honeycomb structure, and the motor can operate more quietly and stably.

The invention relates to an encrypted traffic classification method and system based on semi-supervised contrast learning, and a storage medium, and the method comprises the steps: 1, carrying out the flow division of an original encrypted traffic, respectively aligning the header and load of a data packet in a network flow, and generating an enhanced header and an enhanced load according to an enhancement strategy; step 2, multi-granularity feature extraction: a double-branch feature extractor is adopted to process an enhanced head and an enhanced load respectively, a cross attention mechanism is utilized to obtain fused flow level representation, and depth features are extracted through Mama; and step 3, semi-supervised contrast learning: the contrast learning loss and the cross entropy loss of the label data and the FixMatch loss of the non-label data are integrated, and an encrypted traffic fine-grained classifier is trained. The method has the beneficial effects that the noise propagation is jointly inhibited by comparing the feature structured constraint of learning and a high-confidence threshold filtering mechanism in FixMatch, the training stability is improved, and the labeling cost is remarkably reduced.

The invention provides an aircraft noise ground monitoring data optimization method for a linear flight segment, relates to the technical field of environment monitoring and noise control, and solves the problem that the noise evaluation accuracy is limited due to the fact that the influence of the flight state of an aircraft on noise propagation is not considered in an existing method. The method comprises the following steps: acquiring an aircraft track and ground key coordinates, and converting the aircraft track and the ground key coordinates into a three-dimensional rectangular coordinate system after Gaussian coordinate system conversion; determining an aircraft noise event, matching track data corresponding to the event with noise data, dynamically adjusting a confidence interval, and correcting the noise data to a confidence boundary; polynomial fitting is carried out, the ratio of the sound level slope to the flight time is used as a constraint, the minimum global error quadratic sum of noise data fitting is used as an optimization objective function, and a model is constructed; and solving model parameters by adopting a genetic algorithm to finish an optimization process. According to the method, the optimization processing mode of the aircraft noise sound level data is perfected, and the influence of the aircraft noise around the airport can be accurately judged.

The invention discloses a semi-supervised adaptive unstructured scene segmentation method, and relates to the technical field of computer vision. The method comprises the following steps: acquiring label-free image data of an unstructured scene; inputting the weakly enhanced image into a teacher model to generate a first prediction result; inputting the strong enhancement image into the student model to generate a second prediction result; calculating the JS divergence between the first prediction result and the second prediction result, and dynamically adjusting the attenuation coefficient of the index moving average according to the JS divergence; updating teacher model parameters according to the adjusted index moving average attenuation coefficient to obtain an unstructured scene segmentation model; and inputting a to-be-predicted unstructured scene image into the trained unstructured scene segmentation model, and outputting an unstructured scene segmentation result. According to the method, the teacher model weight updating rate is reduced in the model divergence significant stage such as the initial training stage or the difficult sample processing stage so as to suppress noise propagation, and the prediction precision of unstructured scene segmentation is effectively improved.

The present application provides an actively cooled computer mainframe equipped with a solid-state drive, belonging to the field of computer mainframes, including a chassis and a base at the bottom thereof. A motherboard assembly is provided at the center inside the chassis, and a heat dissipation assembly is provided between the chassis and the motherboard assembly. In the present invention, by providing a heat conduction tube, a transmission tube, a fan blade, a servo motor and a heat dissipation block, the heat conduction tube, the transmission tube, the fan blade and the heat dissipation block all have a high heat conduction coefficient, can quickly absorb the heat generated by the solid-state drive, and at the same time make the heat transfer direction controllable. The outer surface and the inner surface of the heat conduction tube can both contact the air, thereby ensuring a good heat exchange area. The air flow in the heat conduction tube is controllable and concentrated, having a stable heat dissipation effect. The opening part on the side wall of the heat conduction tube fits the flow guide cover, ensuring that the air flow blown out of the heat conduction tube is concentrated and flows towards the flow guide cover, and at the same time limiting the noise propagation direction. The noise can reduce the energy of the sound wave after being blocked by the flow guide cover, thereby achieving the effect of noise reduction.

The application provides a vertical take-off and landing facility unmanned aerial vehicle image site selection method and system facing low-altitude economy, and belongs to the technical field of image data processing and modeling. The method obtains high-overlap-rate images and laser point cloud data by means of oblique photogrammetry and laser radar scanning of a building roof by an unmanned aerial vehicle, constructs a real scene three-dimensional grid model and an obstacle surface three-dimensional model after pretreatment, filters a preliminary layout scheme based on the model according to the available area net height of the roof, carries out airspace safety simulation and noise propagation simulation on each scheme, calculates a minimum interval distance and a noise intensity distribution map, and filters a final site selection scheme according to airspace safety and noise constraints. The application realizes automatic and accurate site selection of the vertical take-off and landing facility in a complex roof environment.

This utility model provides an air inlet grille and a range hood including the same. The air inlet grille is installed at the air inlet of the range hood and includes several layers of spaced-apart air inlet plates. Multiple air inlet holes penetrating all the air inlet plates are formed on the air inlet grille. This air inlet grille and the range hood including the same form a multi-layer grille structure through the layers of spaced-apart air inlet plates and the air inlet holes penetrating all the air inlet plates. This allows the sound waves generated by the range hood to be reflected and scattered multiple times by the multi-layer grille when passing through the air inlet holes, gradually weakening the sound wave energy, reducing noise propagation, thereby improving sound insulation and enhancing the user experience.

The application provides an exhaust assembly and a food processor. The exhaust assembly comprises a main body and a convex part which can be elastically moved up and down. The main body has an exhaust passage which penetrates up and down. The convex part is arranged on the inner side wall of the main body, extends from one side of the main body to the other side, and has a gap between the other side of the main body. In this way, the convex part blocks the exhaust passage, reduces the area through which the gas in the exhaust passage can flow, and slows down the exhaust speed, thereby reducing noise propagation. Meanwhile, when the gas flow is large, the gas can push the convex part to produce elastic deformation upward, thereby reducing the blocking of the convex part to the exhaust passage and realizing rapid exhaust.

This application discloses a novel noise reduction structure for a pressure cooker, comprising: a noise reduction seat with openings at both the top and bottom, and a noise reduction cover that can be opened and closed and is disposed above the noise reduction seat. The noise reduction seat and the noise reduction cover are fitted together to form a receiving cavity covering the pressure vent cap. The noise reduction cover has a vent hole, and the inner sidewall of the noise reduction cover protrudes towards the receiving cavity corresponding to the position of the vent cap, forming a reflux wall. This embodiment, through the enveloping receiving cavity formed by the noise reduction seat and the noise reduction cover, completely covers the pressure vent cap within a closed space, forming a physical barrier layer to directly weaken noise propagation. Simultaneously, the reflux wall forces steam to swirl downwards, reducing steam velocity and impact energy before it is discharged outwards through the vent hole. This dual effect attenuates high-frequency impact noise by over 40%, and the compact integrated structure avoids the volume defects of traditional screw-on devices.