58 results about "Sound analysis" patented technology

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 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 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 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.

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 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.

A head-up display device (HUD) includes a sound analysis portion that determines whether a specific alarm is involved in sound signals from microphones 40a to 40d to collect ambient sound around a vehicle. When a specific alarm has been detected as determined by the sound analysis portion, an image display unit displays icons, representing the specific alarm. The specific alarm includes a siren sound given from an emergency vehicle and a horn sound given from a general vehicle and the sound analysis portion analyzes frequency of input sound signals and thereby determines whether the sound is the specific alarm.

The invention belongs to the technical field of compressors, and particularly relates to a reciprocating compressor air valve fault recognition method. The air valve serves as an important component of the reciprocating compressor, the fault occurrence rate of the air valve is relatively high, and the fault problem of the air valve is more prominent especially in the ultrahigh-pressure reciprocating compressor. Existing fault judgment is mostly limited to process parameter and sound analysis, the analysis method is complex, the requirement for professional experience of detection personnel is high, and engineering practice is not widely applied. The invention provides a reciprocating compressor air valve fault detection method, and the method comprises the steps: obtaining the temperature of an air valve cover at the same side of a cylinder according to the temperature data distribution and trend characteristics; according to the method, data are processed, evaluation indexes are constructed according to the similarity of the temperatures of valve covers of the air valves, valve faults are recognized according to the characteristic distribution rule of normal air valve temperature data, and a reference method easy for engineering practice is provided for early-stage rapid recognition of the faults of the air valves of the reciprocating compressor.

A management system (1090) includes an air conditioner (1062), a sound input unit (1064), an operation sound analyzing unit (1016), a first preprocessing unit (1011), a command extracting unit (1014), and a control unit (1017). The sound input unit (1064) is provided in a room where the air conditioner is provided and obtains sound data (SD). The operation sound analyzing unit (1016) analyzes the sound data by a predetermined analysis method so as to obtain a determination result (RE) regarding whether an abnormality exists in the air conditioner or details of the abnormality. The first preprocessing unit (1011) performs first preprocessing on the sound data. The command extracting unit (1014) extracts a command (CM) of a user from the sound data that has been subjected to the first preprocessing. The control unit (1017) controls the air conditioner on the basis of the command.

Provided are a washing machine abnormal sound detection method and apparatus, an electronic device, and a storage medium. The method includes acquiring target sound data and target vibration data of a to-be-detected washing machine; selecting a matching sound analysis algorithm and a matching vibration analysis algorithm to analyze the target sound data and the target vibration data according to device identification information of the to-be-detected washing machine; determining the position at which an abnormal sound is generated in the to-be-detected washing machine and the cause of the abnormal sound according to the sound data analysis result and the vibration data analysis result.

The invention discloses a tuberculosis auxiliary diagnosis system fusing chest radiography and breath sound characteristics. The tuberculosis auxiliary diagnosis system comprises a breath sound acquisition module, a breath sound dynamic analysis module, a chest radiography acquisition module, a chest radiography detection module, an activity discrimination fusion module and a result output module. Breathing sound signals are collected at a plurality of standard point positions on the body surface of a patient, dynamic abnormal indexes are extracted, meanwhile, chest radiography images are obtained, focus attribute information is recognized, an activity judgment fusion module conducts consistency analysis on the chest radiography images and the dynamic abnormal indexes, standardized risk scores are generated, and high-risk, low-risk or uncertain grading results are output. According to the method, the misdiagnosis and missed diagnosis risks can be effectively reduced under the complex conditions of old focus combined activities, early hidden cases, combined chronic obstructive pulmonary disease and the like, and a visual diagnosis report containing a chest radiograph thermodynamic diagram and a breath sound frequency spectrum is provided. Compared with single chest radiography or single breath sound analysis, the sensitivity and specificity of active tuberculosis diagnosis are improved, and the method has high clinical application value.

The invention relates to the technical field of man-machine conversation, sound analysis and the like, and provides a volume test method and system based on a sound mixing algorithm in a complex audio conference scene, and the method comprises the steps: configuring a conference room audio system, arranging at least three loudspeakers and microphones to form an audio input / output pair, and enabling the position distribution to be matched with the acoustic characteristics; any loudspeaker is selected as a test sound source, and predefined stable test sound signals are sent to all microphones; each microphone receives the signal and calculates the signal intensity, and generates a test volume value of the position; and after receiving all the volume values, the DSP processor operates a sound mixing algorithm, and calculates volume data sent to the corresponding horns by the microphones in combination with an acoustic model. According to the invention, automatic and systematic volume calibration can be realized, the problems of poor test consistency, low repeatability, low efficiency, large deviation from the actual effect and the like in the traditional technology are effectively solved, and an efficient, objective and accurate conference room audio system optimization effect is achieved.

This application belongs to the field of compressor technology, specifically relating to a method for identifying valve faults in reciprocating compressors. As a crucial component of reciprocating compressors, valves have a relatively high failure rate, especially in ultra-high pressure reciprocating compressors, where valve failures are even more prominent. Existing fault diagnosis methods are mostly limited to process parameters and sound analysis, which are complex and require a high level of professional experience from testing personnel, thus limiting their widespread application in engineering practice. This application provides a method for detecting valve faults in reciprocating compressors. It obtains the temperature of the valve cover on the same side of the cylinder and processes the data based on its distribution and trend characteristics. Evaluation indicators are constructed using the similarity of the temperatures of each valve cover, and valve faults are identified using the characteristic distribution patterns of normal valve temperature data. This provides an easily applicable reference method for early and rapid identification of valve faults in reciprocating compressors.

The invention relates to a deep-well pump control method and a deep-well pump, and the method comprises the steps: continuously obtaining sound data collected by a vibration sensor of a deep-well pump body, and segmenting 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 the features and determining texture features of the surrounding image data; analyzing the texture features by using a comparison mode, and classifying the features by using an analysis result; and monitoring the occurrence time and / or occurrence frequency of the abnormal characteristics and adjusting the running state of the deep-well pump according to the monitoring result. According to the control method of the deep-well pump and the deep-well pump, the operation state of the deep-well pump in the operation process can be judged and the operation state of the deep-well pump can be adjusted at the same time in a localized comparison processing mode, so that safe operation of the deep-well pump is guaranteed.

The invention discloses a vehicle dynamic abnormal sound detection method and device, and relates to the technical field of abnormal sound detection, and the method comprises the following steps: constructing a data structure of an abnormal sound problem database; obtaining road surface amplitude spectrums and background noise amplitude spectrums corresponding to different preset road surfaces; abnormal sound problem numbers, abnormal sound problem descriptions and abnormal sound problem amplitude spectrums corresponding to different preset pavements and different single known abnormal sound problems are obtained; the to-be-detected vehicle is controlled to run on the target road surface according to the vehicle speed set by the driver in real time, and an abnormal sound detection amplitude spectrum is obtained; and road surface type identification is carried out on the target road surface, and abnormal sound analysis is carried out based on the abnormal sound detection amplitude spectrum and the abnormal sound problem database. The abnormal sound problem data structure is constructed based on the whole vehicle dynamic abnormal sound detection correlation factors, the detection principle is simple, operation is convenient, and the abnormal sound detection efficiency and reliability are effectively improved.

The invention belongs to the technical field of servo transmission, and discloses an equipment abnormal sound diagnosis method. The method comprises the following steps: collecting audio data or video data when equipment has abnormal sound, and extracting abnormal sound characteristic frequency from the audio data or video data; the rotating frequency of each stage of transmission component is obtained by collecting motor rotating speed information; and comparing and analyzing the abnormal sound characteristic frequency and the rotation frequency of each stage of transmission part, and positioning the position of an abnormal sound source. Compared with a traditional method, the method has the advantages that the troubleshooting time is shortened, the equipment maintenance efficiency is improved, the problems of low efficiency, high cost and difficulty in positioning of a traditional abnormal sound troubleshooting method are effectively solved, and reliable support is provided for equipment operation and maintenance. And the application of the abnormal sound analysis technology reduces the precision requirement on data acquisition equipment, does not need to depend on professional microphone equipment, and improves the convenience of field application. On the basis of accurate abnormal sound source positioning, fault parts can be maintained or replaced in a targeted mode, blind overhaul is avoided, and manpower and material resources are further saved.