44 results about "Rhythm analysis" patented technology

The invention discloses a guide bearing bush automatic grinding system and method based on multi-parameter cooperative control, and relates to the field of intelligent grinding of high-precision bearing parts. The system comprises a state sensing module, a rhythm analysis module, a stage identification module, a target weight adjustment module, a scheduling coordination module, a curved surface contact equalization module, a clamp thermal deformation compensation module, a regional energy integration module and an end point intelligent discrimination module. The self-adaptive frequency adjustment and priority scheduling of each control variable are realized by collecting pressure, temperature rise, displacement, vibration and microchip information in real time and calculating the change rate of the information; in combination with grinding stage identification and task target weight reconstruction, control strategy switching is optimized; and high-consistency morphology control is realized through pressure spectrum correction, thermal drift compensation and regional energy adjustment. The method has the advantages of being fast in dynamic response, high in control precision, intelligent in abnormal intervention and the like, and the grinding quality and production efficiency of the guide bearing bush are remarkably improved.

The invention discloses a muscle function rhythm analysis method and system based on unhealthy side cooperation and electronic equipment, and relates to the technical field of data processing. The method comprises the following steps: acquiring an uninjured side electromyographic signal of a patient, and a joint angle signal and a movement track signal of an affected side; based on the electromyographic signal, extracting an uninjured-side cooperative adjustment decline trajectory, and based on the joint angle signal and the motion trajectory signal, extracting an affected-side function take-over response trajectory; identifying a critical point of affected-side function takeover; calculating a first change curvature and a second change curvature, and taking a time point when the first change curvature is greater than the second change curvature for the first time as a motion stability starting point of the affected side; extreme point distribution is extracted, the motion rhythm period of the affected side is determined, and the time length change trend is calculated; and based on the time length change trend, determining a function autonomous maintenance score, and calculating a muscle function rhythm index of the upper limb of the affected side according to the function autonomous maintenance score. By implementing the technical scheme provided by the invention, the accuracy of analyzing the motion data of the limb on the affected side can be improved.

The invention relates to the technical field of intelligent manufacturing, in particular to a welding production line robot rhythm analysis method and a computer program product, and the method comprises the following steps: extracting production rhythm data of a station by integrating multi-source heterogeneous signals such as program operation, material in-place and equipment state; constructing production time sequence characteristics reflecting a system coupling relation by combining robot operation records and upstream and downstream station data; then positioning key influence factors by using a beat anomaly analysis model; and finally, generating a feasible production rhythm optimization scheme based on an analysis result and a production constraint condition. According to the method, the abnormal time period and the key root cause can be positioned from the complex time sequence data through multi-source signal fusion and time sequence feature construction, so that the automation level of abnormality diagnosis and the accuracy of root cause positioning are improved, coupling evaluation is performed on an optimization scheme and a preset constraint condition, the feasibility of the proposed scheme is ensured, and the accuracy of root cause positioning is improved. And the overall production efficiency and stability of a welding production line are effectively improved.

The invention provides a creative video understanding and analyzing system and a creative video understanding and analyzing method, which relate to the technical field of image video processing and adopt a collaborative architecture formed by sequentially connecting intelligent agents in five stages of video sub-mirror identification, video outline extraction, creative factor analysis, shooting logic induction and audio rhythm analysis in series. The full-process end-to-end automatic analysis and generation of the creative videos from original input to structured creative video scripts are realized, and through professional division and collaboration of multiple agents, deep mirror segmentation, plot logic carding, creative bright spot extraction, shooting technique induction and sound and picture rhythm matching of the videos can be automatically completed; according to the method, manual analysis work which needs multi-field experts to consume several hours and even several days originally is compressed to be completed in minutes, the creative video generation efficiency is improved, the professionality and consistency of output results in the aspects of mirror splitting, narration, vision and audio are guaranteed, and the manpower and time cost of advertisement creative analysis and script generation is reduced.

This invention discloses a method, regulation method, and analysis system for human rhythm analysis based on behavior recognition. The analysis method includes the following steps: acquiring activity images of the person to be analyzed to form an image sequence; recognizing the image sequence to obtain behavior recording data; processing the behavior recording data to obtain behavior curves; and inputting the behavior curves into a neural network model to calculate the activity-rest transition points and their time-series curves based on a neural network model that predicts activity-rest transition points. This invention acquires activity images using a vision system, performs behavior recognition on the activity images to form behavior recording data, and converts the behavior recording data into behavior curves suitable for deep learning. By optimizing the data processing algorithm and using a neural network model to predict the behavior curves, the human rhythm of the person to be analyzed is obtained, ensuring efficiency in processing large amounts of behavior recording data and calculating activity-rest transition points, while also exhibiting good accuracy.

The invention provides a user dining recording method, system and device based on image recognition, and aims to solve the problems that traditional dining records have privacy disclosure risks, cannot capture dynamic behaviors and are large in dining content inference error and the like. Comprising the steps of multi-modal data acquisition, data coupling alignment, feeding rhythm analysis, dining content inference and state feedback. Visual identification is replaced by physical field perception, the recording accuracy is improved while privacy is guaranteed, and the method is suitable for scenes of health management, special crowd monitoring and the like.

The invention discloses a real-time heart rhythm monitoring and early warning system and method based on intelligent recognition, and relates to the field of heart rhythm monitoring, and the system comprises a data collection module which is used for obtaining heart rhythm original data, body temperature data and motion data including real-time rotation, running and jumping actions of a user in real time; the heart rhythm analysis module is used for analyzing the heart rhythm data in the current monitoring period, identifying and extracting characteristic parameters of heart rhythm fluctuation and judging whether abnormal fluctuation exists or not; the attention management module is used for starting an attention period when the abnormal fluctuation is identified, and judging whether the accumulated number of times of the abnormal fluctuation triggers strong attention or not; according to the method, physiological cardiac rhythm acceleration and pathological arrhythmia caused by movement are effectively distinguished, the false alarm rate is greatly reduced, the overreaction of single accidental fluctuation is avoided, it is ensured that early warning aims at a continuous abnormal mode, an early warning signal output by the system has higher specificity and clinical reference value, and unnecessary psychological burden of a user is relieved.

The invention discloses a cardiac mechanical signal processing method and device based on wavelet reconstruction. The method comprises the following steps: performing trend removal and frequency band extraction on an original SCG signal, and reserving main mechanical energy components corresponding to a heart sound event; then wavelet decomposition and main scale reconstruction are carried out, and time domain features of key components such as S1 and S2 structures similar to PCG signals are strengthened, so that heart sound-like signals which are similar to PCG in form and clear in rhythm are generated. Compared with an original SCG signal, the heart sound-like signal obtained through reconstruction is remarkably improved in the aspects of rhythm definition, form consistency and peak stability. And further performing rhythm analysis on the reconstructed signal, introducing physiological constraints, and screening to obtain a cardiac trigger point sequence, thereby realizing high-precision cardiac recognition. The device can be integrated with medical image equipment and wearable equipment, and the functions of heart sound gating, synchronous triggering or auscultation auxiliary analysis and the like are achieved.

The invention relates to the technical field of data analysis, provides a disease risk prediction method and system based on multi-modal data fusion, and solves the problems of poor interpretability and insufficient prediction adaptability caused by dependence on labeled data and neglect of rhythm collaboration. The method comprises the following steps: collecting physiological signals and inflammatory factor concentration of a user in a daily state; extracting a time domain feature and a frequency domain feature from the physiological signal, and extracting a concentration fluctuation feature from the concentration of the inflammatory factor; respectively calculating correlation intensity values between the time domain feature and the concentration fluctuation feature and between the frequency domain feature and the concentration fluctuation feature, and constructing a causal correlation map in combination with medical priori knowledge; analyzing physiological rhythm characteristics in the physiological signals and biochemical rhythm characteristics in the inflammatory factor concentration by using a biological rhythm analysis model, and determining rhythm coupling characteristics; rhythm coupling characteristics and node association information in a causal association map are analyzed through a containerized model, a disease risk prediction result of the user is generated, and the interpretability and individual adaptability of disease risk prediction are improved.

The invention provides an eyeball tremor identification method and system, and belongs to the technical field of medical auxiliary diagnosis, and the method comprises the steps: obtaining pupil data which comprises time sequence information and corresponding pupil position coordinate information; preprocessing the pupil data; segmenting the preprocessed pupil data to form a plurality of interval data segments; detecting a fast phase mode and a slow phase mode according to the speed characteristics of each interval data segment; when it is detected that the fast phase and slow phase alternating mode continuously appears for at least a preset number of times and the rhythm characteristic meets the rhythm requirement, it is judged that an eyeball tremor event occurs; wherein the rhythm characteristic is a speed variation coefficient. The method has the advantages that autonomous eye movement and pathological nystagmus can be accurately distinguished by combining phase features and rhythm analysis, the misjudgment rate is reduced, the method has the advantages of being high in recognition precision, high in anti-interference capacity and high in automation degree, an objective quantitative basis is provided for clinical diagnosis of nystagmus, and the method can be widely applied to clinical diagnosis of the ophthalmology department.

This invention provides a method and system for monitoring the dynamic changes of objects based on UAV images, belonging to the field of image analysis technology. The method includes: acquiring an image dataset of a target area and performing target tracking processing to obtain multiple trajectory segments; identifying multiple scene structural components and performing rhythm analysis on the target area to construct rhythmic profiles of the multiple scene structural components; collecting real-time monitoring data of the target area and performing anomaly detection to generate structural behavior anomaly detection data for the target area; constructing an interaction graph and dynamic flow constraint model for the target area; extracting behavior density data and behavior blockage data of the target area and identifying multiple local abnormal flow areas in the target area; identifying the diffusion impact of the local abnormal flow areas to determine multiple flow anomaly areas; and fusing the structural behavior anomaly detection data to generate dynamic change monitoring results for the target area. This invention improves the real-time perception capability of the gradual accumulation of risks in the dynamic behavior of objects.

The application discloses a music rhythm analysis and lamp effect generation method under a low-speed bus, belongs to the technical field of automobile atmosphere lamps, and is used for solving the problems of high data issuing time delay and high bus load in the lamp effect generation process of a music rhythm atmosphere lamp. The technical scheme of the application is as follows: a frequency simplification module in a car machine obtains complete frequency spectrum data in a current time period from a player in real time, and converts the complete frequency spectrum data into pseudo frequencies, the pseudo frequencies containing m pseudo frequency points; the frequency simplification module sends the pseudo frequencies to each lamp head through a gateway; a music analysis module in the lamp head carries out data filtering, normalization processing, frequency selection and data fusion operations on the m pseudo frequency point data in sequence, obtains a set number of beat data, and transmits the beat data to a lamp effect generation module; and the lamp effect generation module generates corresponding lamp effects according to the beat data or the pseudo frequencies. Effects: the bus data issuing efficiency can be improved, the bus load can be reduced, and the number of lamp nodes can be flexibly increased or reduced.

The present application relates to a kind of pronghorn identification system, method, processing device and storage medium based on video tracking, the system includes: data input interface, for receiving the video or image data stream from one or more camera equipment;Data type judging module is used to judge the data type of video or image data stream based on the meta information of video or image data stream;Refinement individual analysis channel is used to accurately track the individual of pronghorn in video or image data stream, trajectory optimization and behavior analysis are carried out to near view data, and the refinement individual analysis result of pronghorn is obtained;Macroscopic group analysis channel is used to carry out population statistics and rhythm analysis to long-range or aerial data in video or image data stream, and the macroscopic group analysis result of pronghorn is obtained;Data output interface is used to output the refinement individual analysis result and macroscopic group analysis result of pronghorn, the present application can be widely applied in computer vision and intelligent monitoring technical field.

The invention relates to an accurate medication time recommendation method and system based on a multi-organization rhythm map. The method comprises the following steps: constructing a drug database and a rhythm expression database; acquiring a drug identifier input by a user, performing retrieval in a database, performing rhythm feature analysis based on a retrieval result, and generating a drug-target rhythm analysis report; based on the drug information queried by the two-stage serial query architecture, querying all biological pathways and related genes in which the drug participates, carrying out standardized conversion on gene identifiers, carrying out rhythm feature analysis, and generating a drug-pathway rhythm analysis report; and taking the generated analysis report as input, carrying out semantic integration and reasoning through a locally deployed large language model, and automatically generating an optimal medication time suggestion. Compared with the prior art, the method has the advantages that batch rhythm characteristic analysis of drug target genes and related pathway genes is realized, the analysis efficiency and repeatability are greatly improved, and the decision intelligence level is improved.

The invention provides an object dynamic change monitoring method and system based on an unmanned aerial vehicle image, and relates to the technical field of image analysis. The method comprises the steps of obtaining an image data set of a target area, performing target tracking processing to obtain a plurality of track fragments, determining a plurality of scene structure components, performing rhythm analysis on the target area, and constructing rhythm portraits of the plurality of scene structure components. The method comprises the following steps: acquiring real-time monitoring data of a target area, performing anomaly detection, generating structural behavior anomaly detection data of the target area, constructing an interaction graph and a dynamic flow constraint model of the target area, extracting behavior density data and behavior blocking data of the target area, identifying a plurality of local abnormal flow areas of the target area, and generating a dynamic flow constraint model of the target area; and performing diffusion influence identification on the local abnormal flow area to determine a plurality of flow abnormal areas, and fusing the structure behavior anomaly detection data to generate a dynamic change monitoring result of the target area. According to the method, the real-time sensing capability of progressive risk accumulation in the dynamic behavior of the object is improved.

This invention discloses a method, system, terminal, and storage medium for cardiopulmonary resuscitation (CPR) assisted monitoring and control. The method includes: simultaneously acquiring the target user's electrocardiogram (ECG) signal and mechanical compression signal; suppressing interference in the ECG signal based on the mechanical compression signal to obtain a processed ECG signal; generating an ECG rhythm interpretation result based on the processed ECG signal; calculating the signal-to-noise ratio (SNR) based on the processed ECG signal; determining the reliability level of the ECG rhythm interpretation result based on the SNR; generating an ECG rhythm analysis result based on the ECG rhythm interpretation result and the reliability level; acquiring the target user's ventilation parameters; generating a comprehensive CPR quality index based on the ECG rhythm analysis result, ventilation parameters, and compression parameters; and generating adjustment instructions for the CPR assisted monitoring and control device based on the comprehensive CPR quality index. This invention eliminates the need for compression pauses, maintaining continuous chest compressions and avoiding the problem of decreased coronary perfusion pressure due to interruption.

The invention relates to the field of body-in-white welding production lines, in particular to a PDPS-based body-in-white welding production line rhythm optimization method, which comprises the following steps of 1, production line modeling, 2, rhythm analysis, 3, rhythm optimization and 4, optimization scheme output. The debugging cost is effectively reduced; meanwhile, rapid problem positioning and scheme verification are achieved through digital simulation and data analysis; the debugging efficiency can be obviously improved, efficient on-site implementation is guided by forming an executable digital deliverable, and the time for on-site implementation can be shortened in an auxiliary manner; the technical effects of the three aspects complement each other to jointly form a complete rhythm optimization device used for solving the problem of rhythm optimization of the body-in-white welding production line.

The invention belongs to the technical field of meridian analysis, and provides a traditional Chinese medicine meridian data dynamic analysis method based on edge calculation. The method comprises the following steps: setting edge nodes, dynamically collecting acupoint electric signals in combination with a midnight-noon ebb-flow rule, calculating a splitting sensitive coefficient of adjacent nodes, and constructing a splitting sensitive group; determining a maximum connected domain through percolation critical flow analysis, and performing hour rhythm analysis to judge whether hour-rhythm splitting exists or not; if the dissection exists, analyzing the relevance between the topological characteristics of the topological weak nodes and the rhythm dissection characteristics, and judging whether the temporal qi and blood streamer is hindered by the topological weak nodes or not; and optimizing the layout of the monitoring nodes through stream-oriented symmetric configuration based on an analysis result. According to the method, edge calculation and the traditional Chinese medicine midnight-noon ebb-flow theory are combined, dynamic analysis of meridian data and optimization of monitoring layout are achieved, and pertinence and adaptability of meridian data monitoring are improved.

The invention discloses a music rhythm analysis and lamp effect generation method under a low-speed bus, belongs to the technical field of automobile atmosphere lamps, and is used for solving the problems of high data issuing time delay, high bus load and the like in the lamp effect generation process of a music rhythm atmosphere lamp. According to the technical scheme, a frequency simplification module in the vehicle machine obtains complete spectrum data in the current time period from a player in real time and converts the complete spectrum data into pseudo frequency, and the pseudo frequency comprises m pseudo frequency points; the frequency simplification module sends the pseudo frequency to each lamp holder through the gateway; a music analysis module in the lamp holder sequentially performs data filtering, normalization processing, frequency selection and data fusion operation on the m pseudo frequency point data to obtain beat data of a set number, and transmits the beat data to a lamp effect generation module; and the lamp effect generation module generates a corresponding lamp effect according to the beat data or the pseudo frequency. The method has the advantages that bus data issuing efficiency can be improved, bus loads are reduced, and the number of lamp nodes is flexibly increased and decreased.

This application relates to the field of piano teaching technology, and more particularly to a method for detecting the playing of an acoustic piano based on photoelectric information. It includes: installing sensors; sampling a reference playing process using the sensors to obtain a set of photoelectric reference signals; performing intensity and rhythm analysis on each photoelectric reference signal to obtain the photoelectric reference signal analysis results and establishing a playing detection model; sampling the actual playing process using the sensors to obtain a set of actual photoelectric signals; inputting the actual photoelectric signal set into the playing detection model, which uses the photoelectric reference signal set as the detection basis to perform intensity and rhythm detection on each actual photoelectric signal in the actual photoelectric signal set, and outputting the timing-based detection results of the piano keys during the playing process. The playing detection model of this application detects whether the piano keys were pressed accurately, and the intensity and rhythm of the corresponding actual photoelectric signals after the keys were pressed, thereby achieving comprehensive detection.

The invention provides a digital human video generation method and device, equipment, a medium and a program product, and relates to the technical field of digital human. The method comprises the following steps: acquiring an output text to be output by a digital human; performing emotion and rhythm analysis on the output text to generate emotion and rhythm analysis data; the emotion and rhythm analysis comprises analysis of level and oblique patterns and / or fight patterns of the output text; based on the emotion and rhythm analysis data, generating voice data and visual data matched with the emotion and rhythm of the output text; the visual data comprises facial action data and / or limb action data; and based on the voice data and the visual data, generating a digital human video matched with the emotion and rhythm of the output text. According to the method, the digital human video with fuller emotion expression and richer cultural connotation can be generated, so that the generation effect of the digital human video is improved, and finally the user interaction experience feeling is improved.

The invention relates to a rhythm analysis method and device based on sit-up process data and a medium, and belongs to the technical field of rhythm analys.The method comprises the steps that the time point, the action quality and the rising amplitude of each sit-up action in the sit-up process of one minute and the standard number for achieving excellent evaluation are obtained; determining a first half effective time score, determining a first half effective number and a second half effective number, determining a first half rhythm score, and determining a second half rhythm score; determining an overall rhythm score of the sit-up; determining a variation criterion score, and determining a rhythm variation score; determining a speed control score, determining an amplitude control score, and determining a quality control score; determining a rhythm control score according to the speed control score, the amplitude control score and the quality control score; determining a rhythm evaluation score according to the overall rhythm score, the rhythm variation score and the rhythm control score; and judging the rhythm condition of sit-up according to the rhythm evaluation score.

This invention discloses an artificial intelligence-based factory manufacturing execution system, relating to the fields of intelligent manufacturing and industrial information technology. It includes a batch integrity modeling module, a defect concentration reconstruction module, a defect propagation identification module, a splitting rhythm analysis module, and a splitting rhythm control module. The batch integrity modeling module collects original production sequence records and current batch splitting records under high-paced production conditions. It aligns the original production sequence records and current batch splitting records according to a unified time scale, establishing a correspondence between products from the same source before and after splitting, and generating batch integrity markers based on this correspondence. This invention constructs a source continuity statistical framework, reconstructs the defect rate before and after splitting, and identifies concentrated changes in defect concentration. Through rhythm correlation analysis and splitting frequency control, defects are concentrated within the statistical period, improving the timeliness of quality risk identification and process control capabilities.

The invention relates to the technical field of intelligent shooting range data processing, in particular to a shooting training intelligent shooting range data processing method and system.The shooting training intelligent shooting range data processing method comprises the steps that impact point data containing ballistic sequence numbers and shooting timestamps are collected, and impact point distribution analysis and shooting rhythm analysis are conducted respectively; and generating an evaluation index containing the dispersion characteristics and the quantized rhythm pattern. And integrating the two indexes to carry out shooting situation evaluation to obtain a multi-dimensional evaluation result including stability, precision and efficiency. And performing action correlation analysis based on the evaluation result, and generating a specific improvement strategy aiming at the gun shooting posture, the aiming control and the shooting opportunity. According to the method, the time rhythm characteristics of the shooting process are fused with the spatial dispersion result, accurate diagnosis and attribution from training performance to specific technical action defects are achieved, and data support is provided for personalized training guidance.

This invention relates to the field of educational management technology, and discloses a method and system for managing intelligent teaching and research activities that supports multimodal input. The method includes: collecting audio streams, video streams, and comment texts of teaching and research activities; writing the comment texts into pointer fields pointing to speech segments and behavior tag indices to obtain chained annotations; establishing and encapsulating mutual pointers between the audio stream, video stream, and chained annotations based on time identifiers to obtain a teaching and research dataset; constructing a composite teaching activity curve with the speech text time period as the horizontal axis and the composite value of behavior frequency and speech transition number as the vertical axis; using the peaks, troughs, and slope change points of the curve as rhythm feature points, and matching them with a behavioral semantic database to obtain a rhythm analysis graph; using the graph as the time axis skeleton, embedding the chained annotations into the target time interval according to the pointer direction to obtain a comprehensive analysis report; this invention can improve the efficiency of intelligent teaching and research activity management that supports multimodal input.

The embodiment of the invention provides a voice generation method and device, electronic equipment and a storage medium. The method comprises the steps of determining a reference dialect type adopted by a target text, and performing phonetic notation analysis, rhythm analysis and word segmentation analysis on the target text based on the reference dialect type to obtain target text description information corresponding to the target text; and performing dialect migration based on the target text description information, the reference dialect type and the reference timbre to obtain a target voice. According to the method, the target text description information is obtained by carrying out phonetic notation analysis, rhythm analysis and word segmentation analysis on the target text according to the reference dialect type, so that the target text description information is ensured to accord with text information required for carrying out dialect migration on the target text; furthermore, dialect migration is performed on the target text based on the target text description information, the reference dialect type and the reference tone to generate the target voice, so that the problem that pronunciation is not standard due to phoneme or intonation inter-string synthesis of the dialect and the mandarin is solved, and the dialect generation effect is improved.

The invention relates to the technical field of intelligent agricultural lighting, and discloses a plant growth lamp intelligent control method and system based on biological rhythm. The method comprises the following steps: collecting physiological data of leaves and roots and environmental temperature and humidity, and removing anomalies to obtain multi-organ and environmental original data; extracting a leaf and root rhythm curve through rhythm analysis to obtain time difference characteristics; calculating a rhythm peak offset to obtain an accurate phase difference, and generating a preliminary illumination scheme in combination with a plant growth stage if the phase difference exceeds a threshold value; and fusing an environment data optimization scheme, comparing with a preset circadian rhythm to correct parameters, and finally driving the growth lamp to output a control instruction. Dynamic adaptation of illumination and biological rhythm is achieved, and the light energy utilization rate and the plant growth quality stability are improved.

The invention provides a medical time sequence data lightweight compression transmission method and system of wearable equipment. The method belongs to the technical field of wearable medical equipment, biomedical signal processing, low-power-consumption communication and edge intelligent crossing. The method comprises the following steps: continuously collecting multi-dimensional physiological time sequence data of a user by utilizing multiple types of sensors equipped on the wearable equipment, and preprocessing the multi-dimensional physiological time sequence data; based on the preprocessed data, carrying out physiological rhythm analysis by using a deep learning algorithm, and identifying data feature modes in different physiological states; and constructing a sparse dictionary customized by the physiological rhythm according to the identified feature mode. Precise feature extraction and coding are carried out by using the physiological rhythm customized sparse dictionary, an extremely lightweight feature packet is generated, the data volume is greatly reduced, an ultrahigh compression ratio is realized, and the data transmission bandwidth demand is effectively reduced.

This invention relates to the field of target recognition technology, and more particularly to a method and system for UAV recognition based on the linkage of radar and wireless signals. The method includes the following steps: acquiring radar echo data and radio frequency communication data; performing rotor micro-Doppler analysis on the radar echo data to obtain rotor spectrum data; performing modulation rhythm analysis on the radio frequency communication data to obtain radio frequency rhythm data; performing cross-modal mapping on the rotor spectrum data and radio frequency rhythm data to obtain cross-modal mapping data; performing structural coupling analysis on the cross-modal mapping data to obtain structural coupling feature data; performing structural back-inference on the structural coupling feature data to obtain structural fingerprint data; and performing embedding matching recognition on the structural fingerprint data to obtain UAV identification data. This invention, by fusing radar micro-Doppler features and radio frequency modulation rhythm features, and through cross-modal analysis, achieves back-inference recognition from the signal layer to the structural layer, thereby improving the accuracy of UAV recognition.

The present application relates to the field of audio analysis, and discloses a kind of audio data's tone analysis and play method, equipment and storage medium.The method comprises: receiving audio data;According to preset phoneme recognition algorithm, the phoneme recognition processing is carried out to the audio data, and phoneme sequence is obtained;According to preset tone rhythm data, the phoneme sequence is divided and marked, and tone sequence is obtained;Using preset description library, the tone sequence is described and matched, and the description text corresponding to the audio data is obtained;When the audio data plays, based on the playing position of the audio data, the text field corresponding to the playing position in the description text is shown.In the embodiment of the present application, the technical problem that the current analysis technology lacks tone analysis of audio and cannot meet the demand of people for audio music appreciation is solved.