309 results about "Sound intensity" patented technology

The invention discloses a tunnel fire air curtain smoke prevention control method and system, and relates to the technical field of intelligent fire fighting, and the method comprises the steps: building a digital twinborn prediction model, and generating a fire source position coordinate and a smoke diffusion trend prediction map through multi-physics field coupling simulation; analyzing the stability requirement of the air curtain jet flow through a Brapare-Prandtt boundary layer analysis algorithm, and generating a jet flow enhancement requirement parameter table in combination with temperature gradient correction; optimizing an acoustic vortex main frequency band by adopting a Slodhaar number, and generating an acoustic vortex control parameter set in combination with a matched sound pressure level and a configured resonator phase difference; and converting the acoustic vortex control parameter set into an execution instruction, monitoring the jet velocity, the vortex street stability and the smoke retardation effect in real time, and dynamically correcting the parameters of the digital twinborn prediction model. According to the method, physical quantity outline matching of the blocking intensity and the sound pressure level is achieved through the sound intensity-momentum equivalent method, and the optimal phase configuration is determined in combination with POD modal analysis.

The invention provides a sound standardization evaluation system for multi-dimensional acoustic parameter and emotional scene dynamic analysis, and aims to realize structured and objective evaluation of voice performance. The system comprises an audio acquisition module, an audio processing module, a standard evaluation module and an integration processing module. The audio processing module performs noise reduction, pre-emphasis, sampling rate adjustment, framing and slicing operation on the original voice data; the standard evaluation module executes character and pronunciation accuracy analysis, acoustic basic skill feature evaluation or emotion and scene adaptation degree analysis based on multi-modal fusion according to an evaluation type set by a user; parameters including fundamental frequency, formant, sound intensity, fundamental frequency perturbation, amplitude perturbation and the like are extracted in evaluation, and classification prediction is completed in combination with a machine learning model; and finally, the integration processing module generates an evaluation report including a scoring result, question prompts and personalized training suggestions, and provides closed-loop feedback to support sound training and expression optimization.

The invention belongs to the technical field of underwater small target object analysis and recognition methods, and particularly relates to a sound signal feature optimization method for underwater small target object analysis and recognition. Comprising the following steps: 1, acquiring and processing original data; 2, eliminating interference line spectrums, and intercepting and splicing by adopting a time window to obtain a time recombination sound signal; using range transformation to optimize signal amplitude characteristics; processing the sound signal by using an FIR digital high-pass filter; obtaining an optimized signal by using a homomorphic filter; 3, extracting structural features, energy features, frequency features and sound intensity features of the optimized digital signals; step 4, sound signal feature fusion: carrying out underwater target sound signal feature fusion processing based on a canonical correlation analysis method; the invention provides a method for extracting effective sound signal data of an underwater target under the background of optimizing a complex marine environment, enhancing signal effectiveness during long-distance detection, and constructing effective sound signal features capable of being used for classification and recognition of the underwater target at the same time.

The invention relates to the technical field of model construction, in particular to a construction method and system of an electrolysis energy consumption model and a storage medium. The method comprises the following steps: collecting electrolysis process parameters by using a multi-mode sensor system, wherein the electrolysis process parameters comprise a current value, a voltage value, an electrolyte temperature and electrolysis time; constructing an electrolysis energy consumption initial model based on the electrolysis process parameters, and inputting the electrolysis process parameters into the electrolysis energy consumption initial model to output a unit product energy consumption value and a current-voltage efficiency curve; electrolytic bubble acoustic monitoring is conducted on the side wall of the electrolytic cell to obtain bubble breakage acoustic wave signals; and analyzing the sound intensity and the rupture frequency of the bubble rupture sound wave signal. According to the method, through the multi-modal sensor, multi-dimensional signal analysis and dynamic parameter correction, the defects of single data and static state of a traditional electrolysis energy consumption model are broken through, and high-precision dynamic modeling and optimization of energy consumption in the electrolysis process are achieved.

The invention provides an acoustic coalescence elimination method for hydrogen bubbles in molten aluminum, and belongs to the technical field of molten aluminum bubble elimination. According to the method, sound field collaborative focusing is achieved by arranging a phase control array transducer set in a molten aluminum smelting furnace, primary gathered sound waves and efficient coalescence sound waves are applied in stages according to bubble size evolution in a double-frequency scanning mode, and the hydrogen bubbles in the molten aluminum are eliminated. A target frequency is dynamically adjusted in combination with a bubble resonance frequency optimization model to match the inherent frequency of a bubble, a sound-bubble coupling dynamic tracking system is used for monitoring bubble evolution triggering stage switching in real time, and a sound field focus point dynamically scans and covers a three-dimensional space area through phase delay control. A delay detection method is adopted to eliminate cavitation bubble interference and accurately measure the hydrogen content, sound intensity and frequency parameters are optimized according to a sound field parameter self-adaptive regulation and control model, and the technical problem that hydrogen bubbles in a molten aluminum deep area are difficult to be effectively driven by sound waves and cannot be fully coalesced and eliminated is solved.

The invention relates to the technical field of voice processing, in particular to a sound source direction-finding positioning method and system for a complex environment, and the method comprises the steps: serializing the sound intensity of each microphone, and calculating a maximum receiving interval according to the distance between adjacent microphones, the sound transmission speed and the sampling frequency; the method comprises the following steps: determining a short-time audio similarity through moving a sound source signal sequence, extracting a sound source synchronization sequence and a sound source same-frequency sequence, and further evaluating a tone quality deviation degree; optionally selecting a reference microphone, and comparing the reference microphone with a sound source synchronization sequence of other microphones to obtain a time delay data length and a sound source similar sequence; based on the arrangement values of the same position elements of the sound source similar sequence, a sound intensity distribution sequence is obtained, and the sound intensity interference degree of each microphone is obtained; and determining a fixed beam direction and calculating the distance between the reference microphone and the sound source. The invention aims to improve the accuracy of sound source positioning.

The invention discloses a GIS equipment defect three-dimensional visual positioning method based on acoustic imaging, and relates to the related technical field of GIS equipment, and the method comprises the steps: constructing a sound intensity detection dual system; sound source signals of the GIS equipment are synchronously acquired, and near-field acoustic signals and far-field acoustic signals are output; performing frequency band separation through a self-adaptive band-pass filter, and identifying near acoustic abnormal features and far acoustic abnormal features of the separated frequency band; carrying out spatial positioning fusion and outputting a positioning point; and importing a GIS equipment three-dimensional model according to the sound source fusion positioning point, and outputting a GIS equipment visual positioning result. The technical problems that in the prior art, the GIS equipment defect detection range is limited, the positioning precision is insufficient, the defect space position is difficult to visually present, the equipment defect positioning is not rapid and accurate enough, and the equipment operation and maintenance efficiency and reliability are affected are solved. The technical effects of quickly and accurately positioning the equipment defects and effectively improving the operation and maintenance efficiency and reliability of the equipment are achieved.

The invention discloses a vehicle door control method and device, electronic equipment and a vehicle, and belongs to the technical field of vehicles. The method comprises the steps that when the vehicle senses an external knocking action, the environment sound intensity is detected; the response feasibility of the knocking signal is determined according to the environment sound intensity to control the vehicle door to be opened. According to the method, a user can unlock and open the vehicle door only through simple knocking without traditional key or key operation, the method is particularly suitable for the situation that a heavy object is held by hand or the key cannot be easily taken out, whether the knocking signal is responded or not is determined according to the environment sound intensity, false triggering can be reduced, high accuracy of knocking to open the door in the complex environment is achieved, and the user experience is improved. And the trouble that the user can take effect and is invalid when knocking to open the vehicle door is reduced.

The invention discloses a woodworking machine tool noise sound power level measurement method based on a sound intensity method, and belongs to the technical field of machine tool noise measurement, and the method specifically comprises the steps: determining a housing surface covered by a tool rotation plane projection as a main sound radiation region, and determining a main bearing pedestal installation surface as an infrasound radiation region; sound pressure, vibration acceleration signals and dynamic air pressure signals of a main sound radiation area are collected; resampling a dynamic air pressure signal rotation angle domain, extracting a reference pneumatic pulsating waveform synchronous with tool tooth sweeping, and establishing an airflow induced sound pressure model according to the reference pneumatic pulsating waveform and a phase relation; calculating a surface normal vibration speed according to the vibration acceleration, and establishing a structure radiation sound pressure model in combination with a sound wave equation; decomposing the sound pressure signal to obtain two types of component estimation values, and performing parameter optimization to obtain net sound intensity of a main sound radiation area; extracting vibration frequency band energy of an infrasound radiation area, calculating equivalent sound intensity by combining a sound radiation efficiency model, and outputting a total sound power level by space integration; the invention provides an effective method for accurately measuring and controlling the noise of the woodworking machine tool.

The invention discloses a video editing method based on multi-modal large model collaboration, and belongs to the technical field of video processing. The method specifically comprises the following steps: S1, video preprocessing and intelligent blocking: preprocessing an original video, cutting the video into small blocks, ensuring that the end of each small block is a complete statement, outputting a timestamp and an audio text segment of each block, and storing the timestamp and the audio text segment in the form of structured data; and S2, multi-modal scene separation and verification: inputting each block, namely an audio text segment and a timestamp thereof into a large language model, initially dividing a scene according to a rule, then constructing a spurious chart, inputting a large visual model to verify whether a commodity is switched, and finally outputting scene time, a title and a brief introduction. Through a combination strategy of audio feature extraction, semantic integrity judgment and quantitative blocking rules, the problems of statement truncation and timestamp confusion which are easy to occur in traditional video blocking are solved. Specifically, sound wave intensity, voice pause features and a statement boundary identified by a language large model are combined.

The invention relates to a personalized timbre migration and synthesis method based on a virtual singer, and the method comprises the steps: obtaining a reference singing audio of a target virtual singer, and extracting a timbre identity benchmark feature used for representing the timbre identity stability through timbre coding; obtaining personalized timbre migration demand information for the virtual singer, wherein the demand information comprises a to-be-migrated timbre attribute and a corresponding target change amplitude or change direction; calculating a compatibility score according to the timbre identity reference feature and a migration demand, generating a timbre migration risk indication value, and comparing the risk indication value with a preset threshold value or a preset threshold value interval to determine that the migration is high-risk migration or low-risk migration or conservative-risk migration; according to the method, the tone identity benchmark features in the reference singing audio are extracted, and the tone identity invariant set with stable transpitch and sounding intensity is further constructed, so that the core tone identity of the virtual singer is accurately described.

The invention relates to a method for testing a participant's ability to accurately detect speech under background noise, comprising: (a) audibly presenting a series of 2-bit numbers, 3-bit numbers, 4-bit numbers and / or 5-bit numbers in a random or fixed order to a participant's first ear at a fixed or varying signal-to-noise ratio (SNR) in a quiet or noisy environment, (b) audibly presenting a series of 2-bit numbers, 3-bit numbers, 4-bit numbers and / or 5-bit numbers in a random or fixed order to the second ear of the participant at a fixed or random signal-to-noise ratio (SNR) in a quiet or noisy environment, where the numbers are presented in the native language of the participant or the fluent language of the participant, (c) recording the numbers or sequence of numbers correctly recognized by the participant, and (c) storing the recorded numbers or sequence of numbers at the second ear of the participant. And (d) calculating a score as a function of the percentage of the number or sequence of numbers correctly replicated by the subject, or as a function of the sound intensity difference between the speech and noise required to achieve the correct recognition of 50% sequence of numbers. The invention also relates to a device and a method for measuring the digital recognition capability related to hearing loss, and to a computer-implemented method for evaluating the speech recognition capability of a participant.

The invention relates to the technical field of intelligent voice, in particular to a pet emotion recognition method and system based on sound analysis, and the method comprises the following steps: extracting a dominant frequency value, a frequency spectrum gravity center and an energy concentration degree through audio collection equipment, and respectively mapping the dominant frequency value, the frequency spectrum gravity center and the energy concentration degree into three-dimensional coordinate axes to generate time sequence emotion state points; and calculating a sound intensity change rate by utilizing Gaussian kernel density estimation, judging an emotion activation source through a tension response function to generate a response graph, executing gradient calculation and non-maximum suppression to generate a label intensity graph, and generating a composite emotion expression result by combining a path turning angle and the graph. According to the method, emotional coordinates are mapped through a main frequency value, a frequency spectrum gravity center and an energy concentration degree, sound intensity changes are estimated through Gaussian kernel density, disturbance and space are correlated through a tension response function, a focused emotional interval is suppressed through a non-maximum value, path turning is analyzed through dynamic time warping, emotional evolution is described through a label map, and judgment continuity and consistency are improved through multi-dimensional feature fusion.

The invention relates to the technical field of volume adjustment, and particularly discloses an intelligent volume adjustment method and system based on an MEMS earphone and a storage medium, and the method comprises the following steps: obtaining the acoustic characteristics of a sound signal in a time window, and obtaining the actual sound intensity based on the acoustic characteristics; matching the actual sound intensity with historical volume preference data of the user, and determining a target output volume of the currently played content; acquiring a driving voltage amplitude, and realizing digital gain control on original PCM audio sampling data; and sending the audio data subjected to digital gain control into a high-speed digital-to-analog converter, outputting a corresponding analog voltage signal, and controlling an MEMS acoustic unit to carry out audio output according to the target output volume based on the analog voltage signal. According to the invention, the convenience of volume adjustment of the MEMS earphone is improved.

The invention discloses a method for detecting and analyzing the defect or damage condition of a full-water pipeline, and the method comprises the steps: presetting a sound wave reflection time threshold value of each medium interface when an underwater robot is located in the middle of the pipeline according to the size of the full-water pipeline, and carrying out the sound wave detection through the underwater robot, the collected reflection sound intensity and reflection time data are transmitted to the data processing module, the data processing module carries out pre-classification, whether the collected reflection time is compared with a sound wave reflection time threshold value or not is judged according to the classification condition, a medium algorithm is matched, and the medium algorithm obtains the distance of the reflection time and the reflection sound intensity; and judging whether the reflection interface accords with a medium interface corresponding to the medium algorithm, if so, uploading and adjusting the underwater robot to keep the middle position according to the distance data, if not, uploading and reporting an error, and finally, receiving data three-dimensional modeling by a modeling analysis module, and generating a three-dimensional detection diagram. The problem that the identification effect of the deformation or damage condition of the pipeline covered by the sediment is poor is solved.

The invention discloses an underwater structure low-frequency radiation sound power forecasting method based on blind source separation, and the method comprises the following steps: (1), setting a housing sound source in a shallow sea environment, and obtaining discrete sound pressure; (2) obtaining an estimation signal of the source signal through a blind source separation algorithm; (3) windowing the estimated signal space data of the source signal in the z direction to obtain the sound pressure propagating outwards after windowing; (4) the sound pressure propagating outwards is converted into a wave number domain through discrete space Fourier transform, and a holographic surface sound pressure cylindrical wave spectrum is obtained; (5) filtering evanescent waves in a wavenumber domain by using a wavenumber domain filter to obtain propagation waves on a holographic surface; (6) transmitting the filtered sound pressure to a far field in a spherical shape through a near-field acoustical holography technology by means of stable-phase estimation; (7) deducing the sound intensity by using the far-field sound pressure so as to obtain the radiation sound power; according to the invention, the measurement workload is reduced; measurement is carried out on a holographic surface close to a sound source, the influence of boundary reflection is small, and a calculation result is accurate.

The invention relates to the technical field of artificial intelligence, and discloses a reinforcement learning detrapping method and system for complex path planning of a swimming pool robot, and the method comprises the steps: extracting deep fusion features in an underwater holographic image, analyzing the multi-dimensional feature semantics of the deep fusion features, and determining an environment obstacle in an environment where the swimming pool robot is located; calculating an obstacle sensing distance corresponding to the environmental obstacle; based on the sound wave signal frequency, calculating a medium energy absorption coefficient corresponding to the sonar device in the underwater environment, calculating sound energy transmission loss of the sonar device in water, calculating a radiation sound intensity level corresponding to the sonar device, and calculating obstacle strength corresponding to an environmental obstacle; and the echo signal energy intensity corresponding to the environmental obstacle is calculated, a corresponding escape-cleaning planning path of the swimming pool robot about the environmental obstacle is formulated, motion control processing of the swimming pool robot is executed, and a control result is obtained. According to the invention, the planning accuracy of the swimming pool robot in a complex path can be improved.

The invention relates to the technical field of intelligent medical monitoring and health data analysis, and particularly discloses a digestive tract health data analysis method and system. Differential frequency and sound intensity data generated by intestinal tract movement are collected in real time through a multi-source sensor array deployed on the body surface of the abdomen; the method comprises the following steps: extracting an intestinal motion rhythm stability characteristic value by combining empirical mode decomposition and Hilbert transform, calculating a borborygmus intensity variation characteristic value by adopting a normalization and Haar wavelet decomposition method, constructing an intestinal function state characteristic vector, and inputting the intestinal function state characteristic vector into a health assessment model trained on the basis of a random forest algorithm to obtain a health assessment result. According to the system and the method, individual digestive tract health scores and health level indexes are output, multi-type abnormal early warning signals are triggered, a closed-loop management system from data acquisition, intelligent analysis to risk early warning is constructed, and the intelligent level of early recognition and health management of digestive tract diseases is improved.

The invention provides an ultrasonic parameter adaptive adjustment and cleaning evaluation method in a wafer cleaning process, and relates to the technical field of semiconductor manufacturing, and the method comprises the steps: calculating sound field energy distribution through collecting wafer surface temperature distribution and cavity vibration response data; based on the temperature gradient and the sound intensity gradient, calculating the micro-flow field distribution of the cleaning fluid, and establishing a cavitation bubble collapse characteristic matrix; recognizing and cleaning a dead zone through singular value decomposition of the feature matrix, and controlling a piezoelectric transducer to generate focused ultrasonic waves; meanwhile, the plasma resonance sensor is used for monitoring the surface adsorption characteristic change and evaluating the cleanliness. According to the invention, real-time self-adaptive adjustment of ultrasonic cleaning parameters is realized, and the cleaning uniformity and efficiency are improved.

The invention relates to the technical field of ultrasonic medical instruments, and discloses a wide-area closed-loop control transcranial ultrasonic stimulation system, which comprises an ultrasonic circuit and an ultrasonic transducer, and is characterized in that the ultrasonic circuit is composed of a power supply, a main control circuit, an ultrasonic driving circuit, a matching circuit and a sampling circuit; the power supply is used for adjusting a direct-current input voltage value of the ultrasonic driving circuit according to a control signal of the main control circuit; the matching circuit is used for adjusting a matching inductance value connected in series into the circuit; the sampling circuit is used for sampling and measuring the direct-current input voltage value of the ultrasonic driving circuit and the output voltage applied to the two ends of the ultrasonic transducer. According to the transcranial ultrasonic stimulation system, the output of the ultrasonic transducer can be adjusted in a wide sound intensity range, so that the system can adapt to more application scenes; and meanwhile, the required sound intensity is automatically adjusted by adopting a closed-loop algorithm, so that preset parameters are reduced, the adaptability of an ultrasonic circuit and an ultrasonic transducer is wider, and the use cost is lower.

The utility model relates to a phase change thermo-acoustic engine experimental device which comprises a thermo-acoustic conversion system and an acoustic-electric conversion system. The thermo-acoustic conversion system comprises a sound production module and a Helmholtz resonant cavity, a ceramic plate stack soaked with water exists in the sound production module, and the stable temperature difference needed for generating the thermo-acoustic effect at the two ends of the ceramic plate stack is reduced. Sound waves generated by the thermoacoustic effect form standing waves in the Helmholtz resonant cavity, and the sound intensity is amplified; the acoustic-electric conversion system comprises piezoelectric ceramics and a triode common-emitter amplification circuit, the piezoelectric ceramics are arranged at the tail end of the resonant cavity and convert acoustic energy into electric energy, and the electric energy is amplified by the triode common-emitter amplification circuit and then drives a nixie tube to display. The experimental device integrates thermodynamics, fluid mechanics, acoustics, material science and electronic technology, has the characteristics of simple structure, low cost, rich physical process and strong exploration, is suitable for experimental teaching, particularly suitable for new engineering teaching requirements, and is beneficial to improving the multidisciplinary cross practice ability of students.

The invention discloses a rhythm mode intelligent identification and sightsinging rhythm training system and a method thereof, and relates to the technical field of music rhythm data processing, and the method comprises the steps: collecting multi-dimensional audio data played by a user, generating physical deviation data through time sequence comparison, judging a rhythm position and a timbre attribute in combination with sound intensity and frequency spectrum data, and carrying out the intelligent identification of the rhythm mode and the sightsinging rhythm training. Calculating deviation data by using the sensing weight coefficient; identifying a core rhythm problem based on the deviation data, and generating a personalized prescription exercise song in combination with the music style preference of the user; determining whether to add interference scene data or not according to a threshold value, generating interference music segments through an algorithm composition engine, and mixing and outputting the interference music segments; the interference intensity and the rhythm density are dynamically adjusted by comparing the change of deviation data before and after the change of the simulated exercise curve. According to the invention, personalized dynamic adjustment and closed-loop optimization of rhythm training are realized, and rhythm evaluation accuracy and training effect are effectively improved.

The application discloses a wireless microphone based on intelligent terminal control, which comprises a disc base, an outer cover and a holding handle, the holding handle is threadedly connected with the disc base, a battery is arranged in the holding handle, a mounting column is connected with the disc base through bolts, three embedded grooves are arranged on the outer wall of the mounting column, sound emitting pieces are arranged in the embedded grooves, a mounting hole is arranged in the center of the mounting column, and a sound receiving piece is arranged in the mounting hole, the sound emitting pieces, the sound receiving piece and a control panel are arranged in the microphone, the control panel is connected with an external audio device through a Bluetooth module, the sound receiving piece converts the received sound into an electric signal, and then the electric signal is transmitted to the sound emitting pieces for external playing, so that the sound conduction can be enlarged without external playing sound, and the relative position of the sound guide area and the sound emitting pieces is changed by rotating the second cover body, so that the sound intensity of the sound external playing and the sound conduction direction are changed.

The application discloses a steel-concrete composite beam crack discrimination method based on bending wave structural sound intensity aggregation degree testing, which comprises the following steps: dividing a to-be-tested plate into a series of scanning areas, setting a scanning path, and calculating the bending wave structural sound intensity aggregation degree; traversing the plate according to a scanning algorithm and calculating the bending wave structural sound intensity aggregation degrees of all areas; calculating the bending wave structural sound intensity aggregation degrees of all areas of the steel-concrete composite beam plate in a service period; comparing the bending wave structural sound intensity aggregation degree spectrum peak values, and if the difference between the bending wave structural sound intensity aggregation degree spectrum peak values of a scanning area of the two exceeds a preset threshold value, it is determined that the scanning area of the steel-concrete composite beam plate in the service period has cracks. The application combines the characteristics that the bending wave signal is easy to test, adopts the bending wave structural sound intensity testing technology and the structural sound intensity aggregation degree scanning algorithm, and can realize efficient discrimination and positioning of the steel-concrete composite beam cracks, and has great theoretical significance and engineering value for damage identification of the bridge.

The utility model provides a high sound intensity reverberation room ventilation noise elimination channel, which is applied to the noise elimination channel technology field, and comprises a resistive noise elimination section and a reactive noise elimination section to form a composite noise elimination channel, the resistive noise elimination section comprises a sheet type silencer and a maze silencer, one end of the sheet type silencer is provided with a static pressure box group, and the other end of the sheet type silencer is provided with a static pressure box group. The other end of the labyrinth silencer is connected with a resistance silencing section, the other end of the resistance silencing section is connected with a static pressure box connecting piece, the other end of the static pressure box connecting piece is connected with a ventilation pipeline through a soft connecting piece, and the other end of the ventilation pipeline is connected with an outlet pipeline. And an anti-bird net is arranged in the outlet pipeline. According to the ventilation noise elimination channel of the high-sound-intensity reverberation chamber, the static pressure boxes are arranged at the inlet and the outlet of the composite noise elimination channel, dynamic pressure in the channel is reduced through the characteristics of the static pressure boxes, and secondary noise pollution of airflow can be reduced.

The invention discloses a deep sea multi-beam sound intensity data reconstruction method and device fusing an attention mechanism. The method comprises the following steps: respectively designing damages of different sizes, including rectangular damages and irregular damages, for multi-beam backscattering intensity images of a shallow sea area and a deep sea area, taking the intensity images of the shallow sea area as a training set and a test set, and taking the images of the deep sea area as a verification set; a UNet structure is used as a trunk, and a residual module and a multi-scale channel space attention mechanism are fused to construct a UNet-MCSA intensity image restoration model; and repairing the damage intensity image by using a nearest neighbor interpolation method to obtain an NNI repaired image, and constructing a UNet-MCSA-NNI model through a histogram registration method by taking the UNet-MCSA repaired image as a basis and the NNI repaired image as a reference to obtain a deep sea multi-beam backscattering intensity repaired image with both high precision and visual fidelity. The depth and depth are combined, advantages are complementary, and a new normal form is provided for deep sea multi-beam backscattering intensity image restoration.

The invention relates to a method and a system for measuring a sound source by measuring sound at a plurality of discrete measurement locations. AUGMENTED REALITY is used in that a camera scans a physical reference mark arranged in space relative to a source; the processing software generates a surface grid forming the measurement surface in the coordinate system and determines a measurement position to be occupied in a real three-dimensional space with reference to the reference mark such that the measurement position lies on the surface grid, the processing software also generates a virtual mark, and the virtual mark is located on the reference mark. And displaying the virtual indicia on a transparent display of a glasses-type presentation device such that the geometric position of the indicia in real space is fixed with reference to a reference mark and is independent of the orientation of the display. Subsequently, during the display of the indicia, sound measurement probes, which are visible through the display, are sequentially manually guided to the location of each virtual indicia, and sound intensity measurements are then performed there, respectively.

The invention provides an acoustic imaging processing method and acoustic imaging equipment. The method comprises the following steps: acquiring audio data of each microphone in a microphone array of an acoustic imager when the acoustic imager is located in a current space; based on the audio data of each microphone, determining a current maximum sound intensity point coordinate corresponding to the current space, the current maximum sound intensity point coordinate being used for representing the position of a sound source; determining a reference microphone according to the current maximum sound intensity point coordinate and a mapping relation between each maximum sound intensity point coordinate obtained in a calibration process and each microphone priority list; and displaying a sound source imaging result based on the audio data of the reference microphone. According to the invention, the reference microphone can be rapidly and accurately selected, and the determined reference microphone can optimally reflect the actual characteristics of the sound source in the current space.

The present invention relates to a method for deploying fish-driving sound sources to maintain fish migration pathways within reservoirs. First, hydrodynamic simulations are used to determine the interruption areas and required channel widths of the migration pathways. Then, the required sound intensity of the fish-driving sound sources is determined based on the specific effects of sound on fish. Finally, the number and location of the sound sources are determined by combining acoustic methods and the physiological needs of fish. This method can maintain fish migration pathways within reservoirs and promote successful fish migration, which is of great significance to the utilization of reservoir water resources and the protection of river ecosystems.

The invention discloses a robust sound source localization method fusing sound intensity amplitude inter-frame correlation, and the method comprises the steps: receiving a time domain voice signal through a regular triangle array, and carrying out the short-time Fourier transform of the time domain signal, and obtaining a time-frequency domain signal; calculating a sound intensity component by using a sound intensity estimation method of sound pressure Taylor series expansion; calculating a comprehensive weight of each time frequency point by using a sound intensity estimation consistency algorithm, and calculating a sound intensity amplitude at the same time; weighting the sound intensity amplitude by using the comprehensive weight; constructing a reliable time-frequency point screening factor fusing the inter-frame correlation of the sound intensity amplitudes by utilizing the strong correlation between the weighted sound intensity amplitudes and the unweighted sound intensity amplitudes; screening out time-frequency points which are less influenced by reverberation and noise by using the screening factor, and superposing the sound intensity corresponding to the screened time-frequency points to obtain an azimuth angle estimated value; the method provided by the invention has better anti-reverberation and anti-noise capabilities in indoor sound source localization.