73 results about "Sound analysis" patented technology

The invention provides an underwater plosive sound analysis method and device, and relates to the technical field of underwater noise analysis, and the method comprises the steps: obtaining a plurality of sound wave signals received by a monitoring point; respectively analyzing the actual propagation time and the actual signal intensity of each sound wave signal; based on a preset sound velocity profile model, calculating sound wave propagation velocities of different depths of a preset water area; performing prediction path analysis based on the sound wave propagation speed to obtain a plurality of prediction paths; according to the actual propagation time and the actual signal intensity, performing propagation time matching and signal intensity matching on the plurality of prediction paths, and determining a target prediction path; based on the target prediction path, performing blasting source position calculation to obtain a predicted blasting source position; and if it is judged that the predicted blasting source position is consistent with the preset blasting source position, determining that the target predicted path is a blasting sound propagation path. According to the method, the propagation path of the underwater plosive sound can be analyzed.

The invention discloses an elevator state monitoring method and device and a computer readable storage medium. The method comprises the steps that video data and audio data collected by image collection equipment in the elevator running process are obtained; performing vibration analysis on the video data to obtain time sequence vibration data, and performing abnormal sound analysis on the audio data to obtain time sequence abnormal sound data; performing weighted fusion on the time sequence vibration data and the time sequence abnormal sound data by using an attention mechanism to obtain time sequence fusion data; and the time sequence fusion data are input into a state monitoring model, the state monitoring model is used for conducting state evaluation on the time sequence fusion data, and a time sequence health score of the elevator in the running process is obtained. The technical problems that in the related technology, due to the fact that a single sensor is adopted, it is difficult to synchronously monitor possible faults of an elevator from multiple angles, the monitoring result is inaccurate, and extra hardware cost is likely to be increased are solved.

The invention relates to the technical field of equipment management, in particular to an industrial equipment on-line state and configuration state management system which comprises an emotion perception regulation and control module for collecting heart rate data and skin electricity data of a working area, analyzing physiological index fluctuation through heart rate variability measurement in combination with skin electricity response, recognizing a working pressure state and obtaining emotion characteristics. According to the invention, by comprehensively collecting and analyzing the physiological and environmental data of the working area, the dynamic adjustment ability of the production environment emotion is improved. By monitoring the heart rate variability and the electrodermal response, the pressure state of the employee is effectively recognized, and emotion data is further supplemented through sound analysis. The data comprehensive analysis not only optimizes the operation parameters of the equipment, such as adjusting speed and temperature, but also realizes the humanization of the production environment, reduces the pressure of employees, and improves the production efficiency.

The present invention discloses an earphone audio system and control method based on an array sensor module, and relates to the field of earphone audio processing technology, including a noise reduction demand entry module, an environmental audio monitoring unit, an environmental sound analysis unit, and an array audio sensor unit. The noise reduction demand entry module of the present invention provides a more specific noise reduction demand entry method, and the environmental noise data monitored interactively by the microprocessor and the environmental sound analysis unit are displayed on a touch screen in combination with the current direction data, providing users with more accurate noise reduction demand options; after the user selects the noise reduction demand of the corresponding direction by operating the touch screen or recording the voice through the microphone of the earphone, the array audio sensor module transmits the reference reflection signal after adaptive filtering and delay adjustment, and the reference reflection signal should have the same frequency and amplitude as the noise, but the opposite phase, so that the specified direction can be targeted and directional and accurate noise reduction can be performed, and the noise reduction effect is outstanding.

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.

[Problem] To improve the estimation accuracy of urine flow rate. [Solution] A urine flow rate estimation device (70) comprises: a camera (71) configured to acquire an image of discharged urine; an image analysis unit (72) configured to estimate a first urine flow rate on the basis of the image acquired by the camera (71); a microphone (73) configured to acquire sound associated with the discharge of urine; a sound analysis unit (74) configured to estimate a second urine flow rate on the basis of the sound acquired by the microphone (73); and a urine flow rate estimation unit (76) configured to estimate a third urine flow rate on the basis of the first urine flow rate and the second urine flow rate.

The invention provides a two-channel heart and lung sound intelligent analysis method based on time-frequency feature fusion. The method is used for solving the problem that in the prior art, the heart and lung sound signal analysis recognition capacity is insufficient. According to the method, the time-frequency features of the heart and lung sound signals of the patient are fused, and a plurality of feature extraction methods are combined, so that the accuracy of an analysis result is remarkably improved. The method is characterized by comprising the following steps of S1, performing data analysis on heart and lung sound signals through two feature extraction methods to obtain two feature images with time domain features and frequency domain features of heart and lung sound; s2, transmitting the two feature images with the time domain features and the frequency domain features of the heart and lung sounds to a dual-channel heart and lung sound intelligent analysis model; and S3, the two-channel cardiopulmonary sound intelligent analysis model performs dynamic feature fusion based on the two feature images with the cardiopulmonary sound time domain features and the cardiopulmonary sound frequency domain features, and obtains a cardiopulmonary sound analysis result based on a fusion result.

The invention relates to the technical field of infant sleep monitoring, in particular to an infant sleep state monitoring method and system based on sound analysis, and the method comprises the following steps: based on an intelligent infant bed, collecting sound signals sent by an infant in real time through a microphone sensor on the inner side of the bed, recognizing sound in a deep sleep period, sound in a light sleep period and sound in a rapid eye movement period, and transmitting the sound signals to the intelligent infant bed; and acquiring a sleep cycle sound category. According to the invention, the sound signals are collected in real time and are accurately classified according to the frequency range, so that the states of deep sleep, light sleep and rapid eye movement periods of the baby can be more accurately identified, and through careful comparison with reference modes in the audio database of the baby crib, the matching precision of data is improved, and the accuracy of the baby crib is improved. And the utilization efficiency of the sound data is optimized, so that the response capability of the whole monitoring system is improved, the monitoring sensitivity is dynamically adjusted, the sampling frequency is adjusted according to real-time data, the potential of misinformation is reduced, and the practicability of the monitoring system is improved.

The invention discloses a 3D printing platform leveling method and system based on multi-point sound analysis. The method comprises the steps that sound data corresponding to multiple platform positions of a 3D printing platform are obtained; according to the sound data, the overall inclination risk of the 3D printing platform is determined; when the overall inclination risk is greater than a preset risk threshold value, screening out a plurality of dangerous platform positions according to the sound data; according to the sound data of the dangerous platform position, based on a prediction algorithm, a leveling control instruction corresponding to a leveling mechanism of the 3D printing platform is determined; the leveling control instruction is used for controlling the leveling mechanism to level the 3D printing platform. Therefore, accurate inclination risk assessment and leveling control based on sound analysis can be realized, the stability and the printing precision of the 3D printing platform are improved, and the printing failure risk caused by inclination is reduced.

A sound analysis device 1 according to one embodiment of the present invention comprises: an acquisition unit 131 that acquires information related to sounds acquired by a plurality of sound collection devices disposed in a predetermined region; and an output unit 133 that outputs information corresponding to the frequency of sound production by a living being in the region on the basis of the information acquired by the acquisition unit. The acquisition unit 131 acquires, for example, information indicating the arrival direction of the sound for each of the plurality of sound collection devices estimated on the basis of the sound that has arrived at each of the plurality of sound collection devices. The output unit 133 outputs the information corresponding to the frequency of sound production, for example, on the basis of a sound production position that is a position where specified sound production has been performed using the relationship between a plurality of arrival directions corresponding to the same sound that has arrived at the plurality of sound collection devices.

The invention discloses an ensemble synchronous light guide system, belongs to the technical field of intelligent musical instruments, music education and stage performance, and is particularly suitable for realizing accurate synchronization and cooperative training during ensemble of various musical instruments through light guide. The system adopts a terminal (terminal and intelligent musical instrument hardware)-central control (central control layer and tablet App synchronization and cooperation)-cloud (cloud, data storage and adaptive algorithm model) architecture, combines a Bluetooth Mesh + local area network dual-protocol synchronization mechanism, realizes high-precision synchronization of less than or equal to 5ms, provides a sound analysis algorithm (the accuracy rate is greater than or equal to 99%), a global light prompt rule and a collaborative analysis module, and realizes high-precision synchronization of less than or equal to 5ms. The problems that traditional ensemble training lacks visual synchronous guidance, cooperative perception is weak, feedback is not timely and the like are solved, high-precision, high-reliability, intelligent and personalized ensemble synchronous light guidance is achieved, and therefore ensemble efficiency and teaching quality are improved.

The utility model discloses a refrigerator press room noise monitoring device which comprises a plurality of sound acquisition devices, a sound analysis module and a control module. The vibration sensors are a microphone installed in a press chamber, a first vibration sensor installed on the outer surface of a compressor, a second vibration sensor installed on a refrigerant transmission pipeline, a third vibration sensor installed on a fan shell and a fourth vibration sensor installed on the outer surface of a condenser. Each sound collection device is electrically connected with the sound analysis module, the sound analysis module is used for processing noise collected by each sound collection device, the sound analysis module is electrically connected with the control module, and a noise threshold value corresponding to each sound collection device is preset in the control module; and the control module is used for comparing the processed noises with the corresponding noise thresholds respectively, and if the noises exceed the noise thresholds, an alarm is given, so that a user can process the noises in time.

1. Name of the product of this design: Clock and watch corrector pickup (I). 2. Purpose of this design product: It is used to capture and record the sound of clocks and watches for the purpose of sound analysis and fault diagnosis. 3. The key point of the design of this product lies in its shape. 4. The picture or photo that best illustrates the design points: three-dimensional picture.

Provided is an abnormal sound analysis method with which it is possible to determine abnormal sound caused by deterioration of a support cushion rubber. This abnormal sound analysis method detects the frequency of an abnormal sound generated from a vehicle, and estimates the degree of deterioration of a support cushion rubber that supports a structure in the vehicle on the basis of the state of use of the vehicle. When the difference between the resonance frequency of the support cushion rubber and the frequency of the abnormal sound corresponding to the degree of deterioration is equal to or less than a threshold value, the support cushion rubber is determined as the main cause of the abnormal sound.

The invention relates to the technical field of intelligent sound boxes, and discloses an audio playing control method and system for an intelligent sound box and a storage medium, and the audio playing control method comprises the steps: obtaining environment information and user information; performing environment state recognition based on the environment information; performing emotional state analysis based on the user information; according to the environment state and the emotional state, generating an audio playing control parameter; according to the audio playing control method and device, the audio playing parameters are adaptively adjusted through real-time environment sound analysis, the space sound field control technology is adopted, directional sound release is achieved, smooth transition of the audio parameters is achieved when the environment changes, the user experience is improved, and therefore the problem of environment noise interference is solved.

The utility model relates to a multifunctional stethoscope, which belongs to the field of stethoscopes, and comprises a stethoscope head, one side of the stethoscope head is provided with a temperature adjusting mechanism, the temperature adjusting mechanism comprises a sound guide tube fixedly installed on one side of the stethoscope head, one side of the sound guide tube is fixedly provided with a main sound tube, the outer side of the main sound tube is fixedly provided with a mounting seat, and the mounting seat is fixedly provided with a handle. Mounting boxes are fixedly mounted on the left side and the right side of the mounting base correspondingly. According to the multifunctional stethoscope, the stethoscope head can be placed in the skin area of a patient for auscultation, the doctor-seeing comfort of the patient can be improved conveniently, the sound collector is used for capturing sound signals in the body of the patient, the amplifier is used for amplifying the sound signals, and the recording module is used for recording the amplified sound signals. The sound analyzing and processing module is used for analyzing and processing the recorded sound signals in real time, extracting key diagnosis data and displaying the key diagnosis data to a doctor through the display screen, and the display screen can display the heart rate and the respiratory rate and prompt conditions such as atrial fibrillation and valve noise, so that the doctor can listen to the conditions more clearly.

The invention relates to the field of noise elimination, in particular to a method, a medium and equipment for eliminating FSK noise in a cockpit voice record. Comprising the following steps: determining whether an FSK noise section and a reference audio section on a to-be-processed recorded audio are background noise or not; if the FSK noise section and the reference audio section are both non-background noise, the frequency domain similarity between the first discriminant audio and the first reference audio is greater than a first similarity threshold, and the time domain similarity between the first discriminant audio and the first reference audio is greater than a second similarity threshold, determining that the first discriminant audio and the first reference audio are not background noise; if so, the audio of the FSK noise segment is replaced with the audio in the reference audio segment. According to the method, the characteristics of CVR multi-channel recording are utilized, the audio similarity of two microphone channels is compared, noise is eliminated in an automatic mode, the method is suitable for rapidly processing single or multiple records, and the cabin sound analysis efficiency is improved.

To prevent missed shots without a user performing special operations on an imaging device.SOLUTION: Images repeatedly captured by an imaging apparatus are analyzed, and audio collected by sound collection means is also analyzed. On the basis of the obtained image analysis results and audio analysis results, it is determined whether to capture an image to be recorded. If it is determined that capturing should be performed, the imaging apparatus is instructed to capture the image for recording.SELECTED DRAWING: Figure 5A

The invention discloses a sound visualization analysis method for vocal music teaching, and particularly relates to the field of music education, comprising sensor setting, data acquisition, sound data analysis, multi-dimensional correlation analysis and visualization. Through accurate sound and physiological data collection and in combination with multi-dimensional sound data analysis and correlation analysis, the vocal music skill and the sounding state of a singer can be comprehensively and deeply evaluated, the analysis result is intuitive and easy to understand through the real-time data visualization function, the singer and a teacher can quickly understand and make adjustment conveniently, and in addition, the analysis efficiency is improved. The method can also predict the change trend of sound indexes, provides a scientific basis for personalized teaching and training, and is beneficial to improving the vocal music teaching effect and the performance level of singers.

The application discloses an arbitrary sampling rate sound analysis method based on a pre-training neural network and relates to the technical field of sound analysis. The method comprises the following steps: acquiring input audio, converting a spectrogram, and performing short-time Fourier transform on the input audio to obtain the spectrogram. The application solves the problem of difficulty in unified modeling of various sound signals (such as 8KHz-192KHz) with large sampling rate span differences. Different from a traditional resampling-based method, the application proposes sub-band segmentation of a fixed frequency band on a spectrogram in a time-frequency domain, models the sub-bands, can decompose the spectrogram of an arbitrary sampling rate into a combination of sub-band graphs, extracts high-dimensional representations of the sub-band graphs, performs vector splicing, and obtains a final signal representation. Vector distance calculation is performed at the high-dimensional representation level to determine the similarity between sound segments. The method is not only suitable for sound, but also suitable for digital signals such as high-frequency vibration.

Children with autism hear all the sounds surrounding them with the same sound at once. Autism headset will control the degree of voice entering the ear separately and different degrees and most importantly hear the teacher for example during the explanation without being affected by the backgrounds, which helps to focus and not to distract. The headset to enhance the auditory experience for children with Autism Spectrum Disorder (ASD) includes sound programming to reduce surrounding noise, programming for identifying human voices and separating them from background noise, programming to focus on targeted sounds, such as a teacher's or parent's voice, Al technology for dynamic sound analysis and processing according to the surrounding environment, use of special materials suitable for sensory sensitivity in autism, like soft and non-irritating materials for the skin, design of the headset to be compact and easily storable, a which is applicable for a medical product.

The invention relates to a sound analysis method and system based on a neural network, a terminal and a storage medium, and the method comprises the steps: obtaining a sound signal, converting the sound signal into a Mel spectrogram, processing the Mel spectrogram through a neural network, extracting a first feature of the spectrogram through a first convolution kernel, carrying out the down-sampling of the first feature through a pooling layer, and carrying out the processing of the Mel spectrogram through a second convolution kernel; the spatial dimension of the first feature map is reduced, features in the first features are extracted, and the calculation complexity is reduced; the first convolution kernel extracts a first feature of the spectrogram, the second convolution kernel extracts a second feature of the spectrogram, the pooling layer performs downsampling on the second feature and extracts features in the second feature, nonlinearity is introduced in the extraction process, gradient explosion is avoided, the post-full connection layer filters and screens the extracted features and then combines the features, and the processed spectrogram is obtained. The sound spectrogram and the parameters are combined to generate the final sound analysis result, the defect of single parameter or feature extraction is overcome, faster sound analysis can be realized, the analysis result can be quickly obtained, and the analysis result is more accurate and visual.

The invention discloses an arbitrary sampling rate sound analysis method based on a pre-trained neural network, and relates to the technical field of sound analysis. Comprising the following steps: acquiring an input audio, converting a spectrogram, and performing short-time Fourier transform on the input audio to obtain the spectrogram. According to the method, the problem that unified modeling of various sound signals (such as 8KHz-192KHz) with large sampling rate span difference is difficult is solved. Different from a traditional method based on resampling, the method provided by the invention carries out sub-band segmentation of a fixed frequency band on a spectrogram of a time-frequency domain, carries out modeling on sub-bands, can decompose the spectrogram of any sampling rate into a combination of sub-band graphs, carries out vector splicing after carrying out high-dimensional representation extraction on the sub-band graphs, and obtains final signal representation. And carrying out vector distance calculation on the high-dimensional representation level to judge the similarity between the sound segments. The method is not only suitable for sound, but also suitable for digital signals such as high-frequency vibration.

The invention discloses a vehicle anomaly detection method, a vehicle and a storage medium, and relates to the technical field of vehicle detection. The method comprises the following steps: acquiring original audio data, context awareness data and chassis state data of a target vehicle; performing data conversion processing on the original audio data, the context awareness data and the chassis state data to obtain a data conversion result; performing abnormal sound analysis processing on the data conversion result to obtain an abnormal sound analysis result, and performing noise evaluation processing on the data conversion result to obtain a noise evaluation result; the abnormal sound analysis result and the noise evaluation result are verified, an abnormal detection result is obtained, and the abnormal detection result is used for representing abnormal state information of the target vehicle; and displaying the anomaly detection result in a graphical user interface of the target vehicle. The technical problem that driving safety is affected due to the fact that vehicle noise and abnormal sound monitoring is insufficient in the prior art is solved.

The utility model relates to the technical field of electric power equipment, in particular to a distribution transformer rack wiring terminal protection device, which comprises a controller, an ultrasonic generator, a plurality of waterproof sound sensors distributed and mounted on a distribution transformer rack, and infrared sensors distributed and mounted on the distribution transformer rack and close to each wiring terminal, the detection range of each infrared sensor covers the position of the terminal closest to the infrared sensor; the controller comprises a power supply module, a processor and a spectrum analysis circuit module; the electronic components are connected in a matched mode. According to the distribution transformer rack wiring terminal protection device, whether birds approach or not and the types of the birds are analyzed and judged by collecting sounds of all wiring terminals close to a distribution transformer rack, then the ultrasonic generator is controlled to emit ultrasonic waves with different frequencies according to different birds so as to repel the birds, and the wiring terminals can be protected.

The utility model discloses a hydraulic pressure test device for intelligent pressure vessel equipment, which comprises a rack and a human-computer interface touch screen, automatic brake mechanisms are fixed on two sides of the bottom of the rack, each automatic brake mechanism comprises a hydraulic telescopic cylinder, a thread installation clamping column and an anti-skid rubber supporting leg, a water storage tank is fixed in the rack, and a water pump is fixed in the water storage tank. And a fixed seat is welded on the rack. According to the utility model, the sound insulation protective cover, the sound pickup and the like are arranged, so that when the device is used, the sound pickup arranged on the sound insulation protective cover can be used for automatically monitoring sound generated in a water pressure test and then sending the sound to the human-computer interface touch screen, and the result of the water pressure test can be intuitively displayed after the result is calculated based on water sound analysis; and the sound insulation protective cover can effectively solve the interference of external environment noise on the sound pick-up, so that the test precision is improved.

The application discloses a vehicle anomaly detection method, a vehicle and a storage medium, and relates to the technical field of vehicle detection. The method comprises the following steps: acquiring original audio data, scene perception data and chassis state data of a target vehicle; performing data conversion processing on the original audio data, the scene perception data and the chassis state data to obtain a data conversion result; performing abnormal sound analysis processing on the data conversion result to obtain an abnormal sound analysis result, and performing noise evaluation processing on the data conversion result to obtain a noise evaluation result; performing verification processing on the abnormal sound analysis result and the noise evaluation result to obtain an anomaly detection result, wherein the anomaly detection result is used to represent abnormal state information of the target vehicle; and displaying the anomaly detection result in a graphical user interface of the target vehicle. The application solves the technical problem that, in the related art, vehicle noise and abnormal sound monitoring is insufficient, thereby affecting driving safety.

The invention discloses a transformer substation cable insulation monitoring method for realizing early warning. The method comprises the steps of deployment of a sensor network, sound signal analysis, abnormal sound analysis and evaluation, insulation hidden danger positioning, early warning, emergency and the like. According to the invention, through combination of various sensors and signal processing technologies, comprehensive monitoring of the insulation state of the transformer substation cable is realized, the accuracy and reliability of monitoring are improved, early signs of cable insulation problems can be captured in real time, sufficient time is provided for operation and maintenance personnel to carry out intervention and maintenance, and the operation and maintenance efficiency is improved. Therefore, potential electric power accidents are effectively avoided, safe and stable operation of a power grid is ensured, abnormal sound signals in cable operation can be accurately recognized through the sound sensor in the aspects of sound signal collection and analysis, deep analysis is conducted on the abnormal sound signals, and the accuracy of insulation problem detection is further improved.

The application relates to a control method of a deep-well pump and the deep-well pump. The method comprises continuously acquiring sound data collected by a vibration sensor of the deep-well pump and dividing the sound data in a time dimension to obtain sound analysis data; performing filtering processing and noise reduction processing on the sound analysis data to obtain basic analysis data; converting the basic analysis data into image data; acquiring surrounding image data of a feature and determining a texture feature of the surrounding image data; analyzing the texture feature in a comparison mode and classifying the feature according to an analysis result; monitoring an occurrence time and / or an occurrence frequency of an abnormal feature and adjusting an operation state of the deep-well pump according to a monitoring result. The control method of the deep-well pump and the deep-well pump can judge the operation state of the deep-well pump during operation through a localized comparison processing mode and simultaneously adjust the operation state of the deep-well pump, so as to ensure safe operation of the deep-well pump.

The invention discloses a multi-mode interaction method of intelligent equipment, a storage medium and an electronic device, and relates to the technical field of intelligent home furnishing.The multi-mode interaction method of the intelligent equipment comprises the steps that knocking information sent by the intelligent equipment is received, the knock information is obtained by a voice module in the intelligent device to obtain interaction information generated when a user knocks the intelligent device, sound analysis is performed on the knock information, a first confidence coefficient of the knock information is determined, the first confidence coefficient represents the degree of the knock information used for triggering the control instruction, and when the first confidence coefficient is greater than a preset threshold value, the knock information is sent to the intelligent device. Whether the knocking function of the intelligent equipment is started or not is judged, if the knocking function of the intelligent equipment is started, and the intelligent equipment is in a standby state, a target control instruction corresponding to the knocking function is inquired, and the target control instruction is sent to the intelligent equipment; the method improves the control convenience of the intelligent device, ensures the operation accuracy, and improves the user experience.