1635 results about "Sound pressure" patented technology

The invention provides an underwater sonar target detection system and method. The underwater sonar target detection system comprises an optical fiber hydrophone array module which comprises a plurality of optical fiber hydrophone units, each unit comprises an optical fiber Bragg grating sensor and a sound pressure signal demodulation device, and the optical fiber hydrophone array module is used for collecting underwater sound wave signals in real time and converting the underwater sound wave signals into first electric signals; the sonar transmitting-receiving array module comprises a broadband sonar transmitter, a multi-beam receiver and a signal preprocessing circuit, and is used for actively transmitting a frequency modulation continuous wave signal, receiving a target reflection echo and generating a second electric signal; and the multi-mode signal fusion processing module comprises a high-speed data acquisition card, a self-adaptive noise suppression unit and a time-frequency analysis unit. The underwater sonar target detection system and method provided by the invention have the advantages of relatively high reliability, relatively high detection performance, relatively accurate cross-modal signal fusion and capability of performing intelligent target identification and tracking.

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 invention discloses a three-dimensional noise mapping method and system based on point cloud, and belongs to the technical field of urban environmental noise prediction.The method comprises the steps that point cloud data driven three-dimensional modeling and parameter extraction are carried out, an urban three-dimensional model with a geometric topological structure is constructed through laser scanning point cloud data, and related parameters are extracted; based on sound field calculation of ISO 9613 standards, a multi-path propagation model including an atmospheric effect, a ground effect and obstacle diffraction is established, a green infrastructure noise reduction effect is especially considered, and propagation attenuation of noise in a three-dimensional space is simulated; and performing visual expression of three-dimensional noise, and constructing fusion expression of a sound pressure level contour surface and a three-dimensional city model. In view of difficulty in simulation of three-dimensional reconstruction and sound waves in a spatial propagation process in the prior art, the method improves the precision of quantitative prediction, and fuses a green infrastructure noise reduction effect to realize rapid and efficient regional three-dimensional reconstruction and noise mapping.

The invention relates to the technical field of sound wave detection, in particular to an intelligent detection system for a motor, which comprises a data acquisition module, an abnormality judgment module, a type judgment module, a risk determination module, an adjustment module and an alarm module. According to the invention, through combination of sound wave analysis and various real-time monitoring parameters, accurate detection of the operation state of the motor is realized, the system can acquire the sound pressure level, the vibration acceleration, the winding current, the bearing temperature, the rotating speed and the torque of the motor in real time, and rapidly determine abnormity based on a preset threshold value, and after abnormity is detected, the system is started. The system further combines current, temperature and torque information to analyze the abrasion type, and evaluates the serious risk level according to the rotating speed and the vibration acceleration, so that refined risk management is provided, and the problems of low fault judgment precision and slow response speed caused by data transmission delay and environmental interference are effectively solved.

The invention relates to a noise damping control system of an offshore wind turbine generator, and belongs to the technical field of offshore wind power generation. The coupling state evaluation module is used for determining a coupling state evaluation index through a preset deep neural network model based on the platform motion information, the vibration spectrum data and the sound pressure signal; the cooperative control strategy generation module is used for determining target rigidity and target damping according to the coupling state evaluation index and the vibration spectrum data; according to the invention, the coupling state evaluation module processes platform motion information, vibration spectrum data and sound pressure signals acquired by the data acquisition module through a preset deep neural network model; the preset model is endowed with strong nonlinear fitting capability through offline supervised learning of massive historical working condition data; and an accurate and quantitative risk basis which cannot be reached by the prior art is provided for subsequent control decisions.

The invention discloses an intelligent control method and system for a motor driver, and the method comprises the steps: building an acoustoelectric incidence matrix through collecting harmonic current and sound pressure fluctuation data in the operation process of a motor, and forming a fault feature library; identifying an available fault mode to determine an energy collection point, and performing phase deviation processing on the collection point to generate an auxiliary driving signal; performing spectrum analysis on the sound pressure fluctuation data to obtain an acoustic characteristic spectrum, extracting an efficiency indication tone through characteristic decomposition, mapping the efficiency indication tone into a torque optimization parameter, and establishing a noise reduction control table; performing spectrum analysis on the enhanced control domain to identify a high-energy frequency band, executing a frequency shift operation to generate a safety frequency band signal, and forming a multi-frequency band management strategy in combination with a noise reduction control table; a management strategy is decomposed into parallel control flows for sequential staggered arrangement, and an energy-saving control matrix is generated; and generating a PWM control signal based on the matrix, carrying out edge reconstruction, and obtaining a softened edge waveform through an anti-resonance injection technology to complete intelligent control of the motor driver.

The invention belongs to the technical field of underwater sound, and discloses an underwater target sound scattering modeling method and system based on a physical information neural network. The method comprises the following steps: establishing a loss function of a physical information neural network by establishing an underwater target acoustic-structure coupling mathematical model; a decoupling parallel dual-network architecture is established, a fluid domain neural network is used for learning and outputting a scattering sound pressure field of a fluid domain, an elastomer domain neural network is used for learning and outputting a displacement field of an elastomer domain, and the two networks realize physical coupling by sharing a sampling point and a corresponding boundary condition loss function at an acoustic-structure coupling boundary; and generating training data, performing iterative training on the decoupling parallel physical information neural network, and calculating a scattering sound pressure field outside the target and a displacement field inside the elastomer by using a trained model. According to the method, the physical information neural network is innovatively applied to the underwater target sound scattering field, and a new thought and a new way are provided for accurately forecasting the underwater target sound scattering field.

The embodiment of the invention discloses a noise reduction regulation and control method and device for a self-adaptive sound barrier and a medium, and relates to the technical field of noise reduction, and the method comprises the steps: collecting multi-source vehicle noise data which comprises current sound pressure signal time sequence data, preposed sound pressure signal time sequence data and preposed vehicle point cloud data, according to the front sound pressure signal time sequence data and the front vehicle point cloud data, determining a noise source position prediction result corresponding to a sound barrier front node so as to perform sound field prediction on the sound barrier node, and determining a corresponding sound field energy distribution thermodynamic diagram; according to a preset sensitive frequency band threshold value, a target noise high-frequency band needing to be offset is determined in the sound field energy distribution thermodynamic diagram, so that a reverse sound wave signal corresponding to a phase array offset module is generated, and the target noise high-frequency band is offset; and according to the current sound pressure signal time sequence data and the reinforcement learning strategy, determining dynamic sound absorption regulation and control parameters of the dynamic sound absorption module so as to absorb a low-frequency band.

The invention discloses a bionic joint humanoid robot navigation positioning method, device and equipment, and the method comprises the steps: monitoring a landing shock wave signal and reflection echo data of a robot, carrying out the time domain expansion of the shock wave signal to form a pulse characteristic spectrum, extracting multipath propagation components, and carrying out the time difference correlation to generate an environment response value. Screening a direct wave component by using an environmental response value, positioning a sound wave propagation trajectory, and detecting impedance mutation to construct an acoustic matrix. A strong reflection zone is identified through node analysis, a sound pressure gradient field is extracted to determine an obstacle boundary, and a landmark feature bit is determined in combination with an environmental response value. And adjusting a dynamic stride frequency interval based on a landmark feature bit, forming an adaptive detection sequence, and performing sparse processing to construct path configuration. The mechanical vibration component of the shock wave signal is used for piezoelectric conversion to generate recycled electric quantity, the recycled electric quantity is matched with path configuration power to determine a sensing period, intermittent sensing is executed to obtain detection data to construct a detection convergence field, and finally an accurate positioning window is determined and converted into position coordinates.

A calibration method comprises adjusting an operating frequency of an air-pulse generating device, such that a sound pressure level (SPL) of the air-pulse generating device is within a specific range. The sound producing module comprises the air-pulse generating device configured to produce sound via generating a plurality of air pulses at a pulse rate corresponding to the operating frequency.

The invention provides a spherical complex vibration type vector hydrophone based on an MEMS accelerometer, and relates to the technical field of underwater acoustic signal detection, and the spherical complex vibration type vector hydrophone comprises an MEMS accelerometer, a built-in core, a piezoelectric ceramic spherical shell, a sound transmission sealing shell, and a suspension ring. The MEMS accelerometer is orthogonally arranged in the built-in core; the built-in core is nested in the lower half ball of the piezoelectric ceramic spherical shell; the upper hemisphere of the perforated piezoelectric ceramic spherical shell is adhered to the upper edge of the built-in core; the sound transmission sealing shell coats the piezoelectric ceramic spherical shell through an encapsulation process; the suspension ring is bonded with the sound transmission sealing shell, and the hydrophone is suspended on the fixing support for use. The composite hydrophone can detect sound pressure signals and vibration velocity signals at the same position underwater, solves the problem of omnidirectional detection of the composite hydrophone on the sound pressure signals, and has the advantages of small size, simple structure, high reliability, wide application range and the like.

The invention provides a physical model driven deep neural network sound field reconstruction method under a small sample condition. The method comprises the steps of obtaining a training sample; establishing a deep learning neural network, wherein the input and output of the neural network are spatial position coordinates and sound pressure values corresponding to the coordinate positions respectively; training a neural network model by using the training sample; and performing sound field reconstruction on the target area by using the trained neural network model. According to the invention, the physical law of sound wave propagation is introduced into the training process of the neural network, so that the neural network not only can learn the characteristics of data in the training process, but also can follow the physical characteristics of sound wave propagation, thereby realizing sound field reconstruction with higher precision.

The invention discloses a method for realizing ocean sound field prediction based on a pre-training optimized physical information neural network, which comprises the following steps of: pre-training: constructing a hypothetical ocean environment, generating simulation data in a sound pressure envelope form by using an acoustic numerical calculation tool, and pre-training the physical information neural network to learn a physical rule of sound field propagation; fine tuning: adjusting an energy scale factor according to the proportion of the sound pressure amplitude of the actual measurement point to the sound pressure amplitude of the pre-trained environment, and performing fine tuning by using the envelope amplitude data of the actual measurement sound field for the pre-trained physical information neural network to obtain an ocean sound field prediction model through a pre-training-fine tuning dual-stage strategy; and ocean sound field prediction: according to the ocean sound field prediction model, obtaining a target position envelope from the to-be-predicted range, and then converting the target position envelope into a sound pressure result to realize ocean sound field prediction. The method can improve the high-frequency sound field modeling precision and training efficiency, and can be widely applied to the fields of ocean sound field modeling, sound source localization and environment inversion.

The invention relates to the technical field of concrete bubble monitoring, in particular to an aluminum film system concrete bubble dynamic monitoring and regulating method which comprises the following steps: applying a high-frequency alternating current with a first preset parameter to an aluminum film system to induce eddy current in an aluminum film and enable the aluminum film to generate thermally induced acoustic vibration; meanwhile, an eddy current thermally induced acoustic response signal reflected by an internal interface of the concrete is obtained; based on the response signal, determining current bubble state information in the concrete, including amplitude attenuation characteristics based on the sound pressure signal, frequency spectrum characteristics based on the sound pressure signal and phase delay information; and based on the bubble state information, a regulation and control instruction of a second preset parameter is generated, the regulation and control instruction is executed to adjust the parameter of the high-frequency alternating current applied to the aluminum film system, and directional traction regulation and control are conducted on the bubbles in the concrete. According to the invention, by means of an eddy current thermally induced sound technology, dynamic distribution, including the number, the particle size, the motion trail and the like, of bubbles is captured in real time, and instantaneous changes in the pouring process can be accurately reflected.

The invention discloses a spatial projection regularization method for sound source localization and sound field reconstruction and a related device, and belongs to the technical field of sound source localization. Specifically, according to the method, an equivalent source method model is utilized, and an external radiation sound field of a sound source to be measured is simulated through a series of virtual sources. Then, according to the first sound pressure transfer matrix from the virtual source arrangement surface to the holographic measuring point plane and the sound pressure of the holographic measuring point, a space projection regularization algorithm is used for solving the inverse problem, and therefore the equivalent source intensity is obtained; and then, reconstructing an external radiation sound field of the sound source to be detected by using the second sound pressure transfer matrix and the equivalent source intensity. And finally, by taking the maximum sound pressure amplitude as a standard, screening field points in an external radiation sound field so as to determine the position of the sound source to be detected. According to the space projection regularization algorithm, truncation processing of the vector space is carried out with the projection size of the measurement information in the vector space as the criterion, real information is reserved, and noise interference is restrained to the maximum extent.

The invention provides a wave finite element and boundary element mixed composite board structure sound insulation performance prediction method, and the method belongs to the acoustics field, and comprises the steps: carrying out the post-processing of a wave finite element model based on the wave finite element model of a composite board structure and a corresponding equivalent nodal force, and obtaining the wave finite element equation of the whole composite board structure; based on a sound-structure coupling equation, through a boundary element method, a discrete boundary element equation related to the surface vibration speed of the composite board and the radiation sound wave pressure is constructed; coupling the wave finite element equation and the discrete boundary element equation of the whole composite board structure, and determining the sound pressure of radiation sound waves of the composite board structure and the surface vibration speed of the composite board; and based on the sound pressure of the radiation sound wave of the composite board structure and the surface vibration speed of the composite board, obtaining a sound insulation performance prediction result by calculating the sound power of the incident sound wave and the radiation sound wave, and completing prediction of the sound insulation performance of the composite board structure. The problems that the sound transmission loss of large plates and medium-high frequency plates is difficult to predict and the calculation cost is high are solved.

The invention belongs to the technical field of acoustics, and particularly relates to an index type open-pore rigid plate internal vector sound field calculation method, program and equipment and a storage medium. According to a Webster equation satisfied by a simple harmonic plane sound source excitation sound pressure field, circular piston radiation acoustic impedance on an infinite baffle plate is adopted to represent radiation impedance at an opening of an exponential open pore, a sound field analytical solution of any depth in the open pore of the exponential open pore rigid plate is constructed, system calculation is carried out in combination with sound source conditions, and a sound field of any depth in the open pore of the exponential open pore rigid plate is obtained. Therefore, sound field quantities such as internal accurate sound pressure and vibration velocity of the exponential type open-pore rigid plate under the vertical incidence condition can be quickly solved, and sound field distribution conditions under different section change rules and different open-pore rigid plate sizes can be calculated. According to the method, the calculation complexity is low, the influence problem caused by sound field changes under the non-free field condition can be solved, and the calculation stability and reliability under the complex boundary condition are ensured.

The invention provides a big data-based material detection method and system, relates to the field of material quality detection, and solves the technical problems of insufficient detection precision and poor supply chain quality control linkage in an existing material detection method. The method comprises the following steps: transmitting sweep-frequency sound waves to warehouse-in materials of a peripheral warehouse by using a sound wave transmitting device; collecting vibration velocity spectrum data and sound pressure gradient data of the warehouse-in material after the warehouse-in material receives the frequency sweep sound wave; according to the vibration velocity spectrum data and the sound pressure gradient data, calculating a defect index of the warehouse-in material; and when the defect index is greater than a preset threshold value, marking the warehousing material as a defective material, sending a traceability detection instruction to a previous node warehouse, and starting a grading detection process of the previous node warehouse. The method and the device are used for warehousing detection, quality traceability and full-chain management and control processes of the materials in the supply chain.

The invention discloses a novel induction-type magneto-thermo-acoustic detection method for the conductivity of a supercapacitor, and relates to the technical field of nondestructive material detection.The method comprises the steps that a steady-state static magnetic field and a pulse alternating magnetic field are introduced to form a composite excitation field, and a magneto-acoustic effect and a thermo-acoustic effect are simultaneously and cooperatively excited in a solid-state electrode material; the magnetoacoustic-thermoacoustic coupling effect is formed, eddy current induced by a pulse alternating magnetic field in the material not only generates joule heat, but also generates a direct carrier of Lorentz force under the action of a steady-state static magnetic field, the two physical effects are derived from the same electromagnetic excitation process, but the mechanisms for generating acoustic signals are complementary to each other, so that the effect of the magnetoacoustic-thermoacoustic coupling is achieved. The two effects are coupled as a unified sound source item, a sound pressure wave equation is established, the equation describes a sound field excitation process under the combined action of a force source and a heat source, the coupling mechanism remarkably enhances the strength and information abundance of ultrasonic signals, and the inherent defect that a single thermoacoustic detection method is insensitive to a high-conductivity material is overcome.

The invention provides a multi-sound-velocity photoacoustic image reconstruction method and device based on implicit neural representation, and relates to the technical field of image processing. The method comprises the following steps: adjusting parameters of an implicit neural representation network: obtaining first initial sound pressure distribution and first sound velocity distribution through the implicit neural representation network based on space coordinates in an imaging area, obtaining a predicted detector signal based on the first initial sound pressure distribution and the first sound velocity distribution through a differentiable acoustic forward propagation model, and minimizing the difference between the predicted detector signal and the detector measurement signal to update parameters of the implicit neural representation network; iteration is carried out in this way until a preset convergence condition is met; and using the implicit neural representation network after parameter adjustment to obtain second initial sound pressure distribution based on the space coordinates in the imaging area. According to the invention, photoacoustic image reconstruction can be realized without a sound velocity distribution diagram or a pairing truth value.

The invention provides an ultrasonic detection method for internal defects of an insulating part of a power system based on a piezoelectric ultrasonic transducer, and belongs to the technical field of insulating part detection. After wavelet denoising and deep attenuation compensation are carried out on echo signals, sound path distance time delay and sound pressure amplitude parameters are extracted, defect identification and position estimation are carried out by utilizing a layered variational auto-encoder, a high-frequency transducer is switched to aiming at tiny defects, a harmonic component is extracted by adopting a nonlinear ultrasonic method, and a characteristic size is calculated; a defect distribution space feature matrix is generated based on a synthetic aperture focusing technology, a unified or personalized processing strategy is selected according to an acoustic characteristic homogenization degree evaluation value, a complete defect detection result is output, and the technical problem that deep weak defects in the electric insulation part are difficult to accurately detect and recognize is solved.

The invention discloses a sound barrier sound insulation characteristic evaluation method suitable for a real ship complex sound field, and belongs to the technical field of real ship sound barriers, and the method comprises the steps: arranging hydrophone arrays at acoustic mirror symmetry positions at two sides of a real ship fairing sound barrier to form an in-situ measurement pair; controlling the ship to sail at a plurality of navigational speeds, and synchronously acquiring sound pressure time domain signals on two sides; carrying out preprocessing and time-frequency analysis on the signals, and calculating sound pressure levels of a sound facing surface and a sound backing surface to obtain an in-situ sound pressure level difference; and based on the sound pressure level difference at different navigational speeds, analyzing the change rule of the sound insulation performance along with the frequency and the navigational speed, and carrying out comprehensive evaluation. In addition, by arranging a vibration sensor and a turbulence measuring device, path separation of structural sound and flow-induced noise is achieved, spatial coherence weighted average is introduced, and the accuracy and representativeness of evaluation under a complex sound field are improved. The method overcomes the limitations of laboratory test environment distortion and single working condition, and can truly and comprehensively reflect the actual sound insulation efficiency of the sound baffle in the dynamic navigation of a real ship.

The invention discloses a low-frequency sound propagation loss forecasting method suitable for a polar region sea area, and the method comprises the steps: building a two-dimensional ice layer model of a forecast sea area according to remote sensing data based on the setting that sea ice of the polar region sea area is a uniform elastic medium; calculating hydrological conditions of the ocean sound channel of the polar sea area; establishing a forecast sea area two-dimensional seabed model according to the seabed topography sediment database; an under-ice sound field model is constructed based on a three-dimensional cylindrical coordinate system, sound pressure from unit intensity sound sources with different sizes and depths to a receiving point in a forecast sea area is calculated through a frequency domain finite element method in combination with a PML technology, and sound propagation loss of a needed position is obtained through calculation. According to the method, the application limitation of traditional ray and normal wave theories under complex boundary conditions is broken through through a finite element method, a synergistic effect mechanism of actual ice layer parameter space change, submarine topography fluctuation and sound velocity profile gradient characteristics is systematically analyzed, and sound field modeling is more accurately carried out on different ice layers and submarine topographies in the Chukong sea region all year round; the influence of sound wave propagation is simulated.

The application discloses a bottle-shaped sound-electricity conversion power generation device, which comprises a shell, a PVDF film, a metal net and a piezoelectric component.

The invention relates to the technical field of acoustic analysis, in particular to a self-adaptive acoustic analysis method and system, and the method comprises the following steps: obtaining a sound pressure amplitude screening channel, extracting a main sound point time index, judging a fluctuation direction to generate a path identifier, and completing channel alignment and path binding to generate an analysis result. According to the invention, by acquiring the maximum sound pressure amplitude of each channel and dynamically screening the effective channel, the capability of capturing significant sound in a complex sound source environment is improved, and by combining directional extraction and fluctuation trend judgment of main sound point time index differences in a continuous period, dynamic perception and track identification of sound source feature changes are realized. The stability of path identification is enhanced by using direction consistency and time sequence alignment operation, accurate binding and real-time adaptive sound source tracking of multiple channels are completed, the identification accuracy and path continuity in a sound source dynamic change scene are effectively improved, meanwhile, redundant channel interference is avoided, and the accuracy of path identification is improved. And the processing efficiency and the adaptive capacity of the acoustic model are enhanced.

The invention discloses a digital equivalent source sound field reconstruction system based on an underwater complex sound field environment. The digital equivalent source sound field reconstruction system comprises a sound pressure acquisition module which acquires radiation sound pressure data on a measurement point through a hydrophone array; the intelligent analysis module is used for performing shallow sea sound pressure Green function derivation by utilizing a shallow sea Pekeris waveguide model based on the radiation sound pressure data, and constructing an underwater sound field equivalent source equation; the compressed sensing module is used for converting an underwater sound field equivalent source equation into a compressed sensing problem based on the underwater sound field equivalent source equation, and solving a norm for reducing L1 by adopting an algorithm under an accelerated near-end gradient to obtain compressed sensing equivalent source intensity; and the sound field reconstruction module is used for constructing a free field green function, obtaining underwater reconstruction sound pressure by combining the free field green function with the compressed sensing equivalent source intensity, realizing digital equivalent source sound field reconstruction of an underwater complex sound field environment, improving data processing efficiency and reducing requirements on computing resources.

The invention relates to the technical field of reducer vibration noise optimization, and discloses a planet row coaxial reducer vibration noise optimization method, which comprises the steps of obtaining initial assembly parameters of a reducer, collecting load measurement signals of planet wheels of the reducer under an order frequency sweeping working condition, converting the load measurement signals into equivalent meshing loads based on a calibration curve, and calculating the equivalent meshing loads according to the equivalent meshing loads. Calculating a load imbalance coefficient according to the equivalent meshing load, and taking a peak value of the load imbalance coefficient as a first evaluation index; shell radial acceleration and sound pressure signals are synchronously collected under the order frequency sweeping working condition, the side-band ratio is calculated, and the peak value of the side-band ratio is taken as a second evaluation index; and performing diagnosis shunting based on the first evaluation index and the second evaluation index, determining an assembly parameter which is adjusted preferentially, executing iterative adjustment, and outputting a final assembly parameter after iteration is completed. According to the method, uniform load unbalance caused by assembly errors and side band amplification caused by geometric eccentricity can be effectively separated and solved, and vibration and noise of the speed reducer are reduced fundamentally.

The invention relates to a main sound device and a sound device control method, the main sound device and at least one auxiliary sound device form a surround sound system, and the main sound device comprises a controller configured to send a volume acquisition request used for requesting volume information of the auxiliary sound device; receiving first volume information, wherein the first volume information is used for indicating an output sound pressure level supported by the target auxiliary sound equipment; determining a target sound pressure difference, wherein the target sound pressure difference is a sound pressure level corresponding to the difference between the distance from the main sound box to the user and the distance from the target auxiliary sound box to the user; based on a first audio signal corresponding to the main sound box, the current output sound pressure level of the main sound box, a second audio signal corresponding to the target auxiliary sound box, the first volume information and the target sound pressure difference, determining a third audio signal played by the main sound box based on the current output sound pressure level and a fourth audio signal played by the target auxiliary sound box based on the target output sound pressure level, the sound pressure level when the third audio signal reaches the user and the sound pressure level when the fourth audio signal reaches the user meet the consistency condition.

An oral function evaluation device includes: an obtainer that obtains voice data; an extractor that extracts a feature from the voice data; an S / N ratio calculator that calculates a signal-to-noise (S / N) ratio of a second average intensity of a sound collected in a period when a voice is uttered to a first average intensity of a sound collected in a period when no voice is uttered; a determiner that determines an estimating equation; and an evaluator that evaluates the deterioration state of oral function through assessment using an oral function evaluation indicator, based on the estimating equation determined and the feature extracted. As the estimating equation, the determiner determines: a first estimating equation that includes a sound-pressure-related feature when the S / N ratio is greater than a first threshold; and a second estimating equation that does not include the sound-pressure-related feature when the S / N ratio is the first threshold or less.

The invention relates to the technical field of heat supply pipe networks, in particular to a small sample learning pipeline leakage identification method based on multi-dimensional acoustic feature fusion, which comprises the following steps of: acquiring sound pressure data based on a main line of a heat supply pipe network, analyzing signal amplitude and frequency features by a sliding window, constructing a multi-dimensional acoustic feature set, screening and aggregating leakage and normal state samples, and identifying leakage and normal state samples. Comparing the difference between the new data and the prototype, quantifying the feature distance, and judging the leakage state according to the minimum attribution principle. According to the method, multi-angle behavior expression is established, a typical category prototype is generated through feature induction, multi-category feature center aggregation and dynamic measurement are combined, the high-reliability judgment capability of the leakage state is improved, compared with a traditional technology, leakage signals are comprehensively represented through multi-dimensional features, and the reliability of the leakage state is improved. The adaptability to environmental noise, sudden interference and a complex pipe network structure is effectively enhanced, misjudgment is reduced, the dependence on a large amount of labeled data is greatly reduced through the small sample learning technology, and the data collection and labeling cost is remarkably reduced.