50 results about "Environmental acoustics" patented technology

The invention relates to the technical field of audio signal processing, and discloses a sound box and sound effect intelligent adjusting method and system based on data analysis and a storage medium, and the sound box and sound effect intelligent adjusting method based on data analysis comprises the steps: constructing a user feature modeling engine, and extracting user auditory characteristic data; constructing an environment characteristic analysis engine, and collecting environment acoustic characteristic data; constructing a content feature extraction engine, and analyzing audio content semantic data; constructing a three-dimensional fusion optimizer, inputting the three feature vectors into an auditory scene fusion model, calculating an auditory experience score through tensor fusion operation, and solving an optimal sound effect parameter by applying a multi-objective optimization algorithm; constructing a parameter generation controller, and converting the optimal sound effect parameter into a specific audio processing parameter; according to the invention, the problem of mutual interference caused by traditional separated processing is solved, and the accuracy of sound effect adjustment and the user satisfaction are improved.

The present application relates to the technical field of speech processing, and particularly relates to a mixed speech processing method, an electronic device and a computer readable medium. The method comprises the following steps: collecting mixed speech and environmental influence parameters; performing bionics frequency domain analysis on the mixed speech to obtain low-frequency attenuation compensation feature data; performing multipath effect propagation analysis on the low-frequency attenuation compensation feature data through the environmental influence parameters to generate channel distortion data; performing time domain-frequency domain joint deconvolution processing on the mixed speech by using the channel distortion data to generate direct sound components and reflected sound components; performing adversarial training based on the direct sound components and the reflected sound components to generate anti-multipath speech enhancement data; and constructing a dynamic frequency compensation filter based on preset environmental acoustic characteristics. The present application improves the output quality of mixed speech through multi-stage signal processing, frequency compensation and real-time optimization technology.

The invention relates to the field of photovoltaic equipment abnormity early warning, and provides a photovoltaic equipment temperature abnormity prediction method and device based on a digital twinborn model, and the method comprises the steps: obtaining an environment acoustic signal, meteorological data, and the actually measured temperature data of photovoltaic equipment; performing acoustic spectrum feature extraction according to the environmental acoustic signal to obtain a virtual environmental parameter set; sending the meteorological data and the virtual environment parameter set to a preset digital twinborn model for processing to obtain an initial temperature predicted value set; determining a temperature prediction value distribution diagram according to the initial temperature prediction value set and actually measured temperature data of the photovoltaic equipment, and comparing a temperature prediction result with an abnormal temperature threshold value to obtain a temperature abnormal risk point; and processing according to the temperature prediction value distribution diagram, the temperature anomaly risk points and the meteorological data to obtain temperature anomaly early warning information of the photovoltaic equipment, and improving the accuracy and foresight of temperature anomaly prediction of the photovoltaic equipment.

The invention relates to the field of digital information transmission, and discloses a safe box encryption method based on voice and voiceprint recognition, which comprises the following steps of: synchronously acquiring environmental acoustic fingerprints of a user terminal and a safe box, and combining a voiceprint transient entropy characteristic extracted by a voice signal and a physical layer modulation characteristic of a wireless channel during sound production; and constructing a triple physical layer verification mechanism to cooperatively generate a one-time session key. According to the method, the voiceprint biological characteristics and the channel environment characteristics are deeply coupled, qualitative change from pure data protection to interaction process authenticity verification is realized, meanwhile, the context constraint of key negotiation is enhanced by using the space-time anchoring effect of the environmental acoustic fingerprints, and the transmission security in a near-field voice interaction scene is remarkably improved.

The invention relates to the technical field of engineering machinery control, and discloses a hydraulic control system under a variable load piling working condition, which comprises a multi-dimensional state acquisition module, a fluid parameter observation module, a signal reconstruction decoupling module, a virtual impedance mapping module and a fluid phase locking control module. The acquisition module acquires a basic physical state; the observation module solves the effective volume elastic modulus of the hydraulic oil based on a fluid continuity equation; the reconstruction module utilizes the modulus to correct signal lag, reconstructs external load force through an inverse dynamic model and decouples environmental acoustic impedance; the mapping module dynamically generates a target mechanical impedance parameter according to the environment impedance; and the control module calculates an ideal instruction based on the target parameter, corrects the gain by utilizing the fluid modulus and locks the rebound peak phase to adjust the action time sequence of the valve core. Control distortion caused by fluid parameter drift is solved, active flexible adaptation to variable load geology is achieved, energy hedging is avoided, and operation efficiency is improved.

This application discloses a planar scanning-based immersion battery thermal runaway identification device and method, relating to the field of battery energy storage safety monitoring technology. The device consists of a fully enclosed immersion tank, immersion liquid, ultrasonic phased array sensors located at the corners of the inner wall of the tank, and a signal processing module. The sensors are installed below the liquid surface and above the individual battery cells, emitting fan-shaped ultrasonic beams to form a horizontal logical scanning plane covering the entire diagonal length of the bottom surface of the module. This identification method employs active scanning and physical feature extraction logic: first, an environmental acoustic impedance reference spectrum is established using phased array beams; then, echo changes within the scanning plane are monitored in real time. This invention effectively eliminates the interference of battery bulging and mechanical vibration on traditional monitoring methods, achieving refined characterization and centimeter-level precise positioning of the gas-generating physical characteristics during the thermal runaway evolution process, significantly improving the intelligent safety level of immersion energy storage systems.

The present application relates to the technical field of speech processing, which can be applied to business scenarios such as financial technology and medical health, and discloses an environmental acoustic simulation speech generation method, device, equipment and medium, comprising: obtaining and separating mixed speech data to generate original speech content and original environmental acoustic information; converting the original speech content into first text information; determining a target environmental acoustic label in combination with the original environmental acoustic label, the first text information and target geographic location information; obtaining target environmental acoustic information from a preset sound data set based on the label and adjusting its amplitude characteristics to match the original environmental acoustic information; and combining the adjusted target environmental acoustic information with the original speech content to form simulation speech data. The present application introduces target geographic location information to participate in acoustic feature determination and amplitude adjustment, so that the generated simulation speech data is more consistent in geographic semantics and acoustic performance, effectively improving the authenticity and concealment of speech environment camouflage.

The invention relates to the technical field of voice recognition, and particularly discloses a building indoor acoustic noise reduction and sound absorption optimization system based on deep learning. The system comprises a sound field perception and data acquisition module, a cross-environment acoustic feature extraction module, a meta-learning driving model rapid adaptation module, a multi-target acoustic optimization decision module and a distributed sound absorption actuator control module, rapid model adaptation is realized through meta-learning, parameters are finely adjusted by using a small amount of field data, and the sound absorption performance is improved. And in combination with a multi-objective optimization algorithm, acoustic indexes such as voice definition, noise suppression and space sense maintenance are balanced, and finally, the sound absorption unit is dynamically regulated and controlled through the distributed actuator, so that efficient and accurate indoor acoustic environment optimization is achieved.

The invention relates to the technical field of environmental acoustics, discloses a road totally-enclosed sound barrier sound field prediction method and system, belongs to the field of environmental acoustics, and has very high practicability in sound field prediction and noise pollution evaluation of public road traffic noise after a totally-enclosed sound barrier is implemented. On the basis of the acoustic propagation principle, a new prediction method is provided for a road traffic noise source and a totally-closed sound barrier, a sound field is divided into two subsystems including a barrier internal space and an external space, and equivalent acoustic models of the two subsystems and a calculation method and recommendation parameters of the noise source sound power level are given respectively. According to the method, the sound environment of the high-rise building close to the urban road can be accurately predicted and calculated, and a basis is provided for noise pollution evaluation and control. And meanwhile, the method can be matched with a national standard method or commercial acoustic software for use, and has relatively high applicability.

The invention provides a multi-modal and multi-task-based conjoint analysis system and method, and belongs to the technical field of environmental acoustic perception, a bimodal feature decoupling architecture is adopted, dynamic separation of modal invariant features and modal specific features is realized in text-audio cross-modal fusion, and a scene adapter automatically adjusts bimodal interaction strength; for time sequence positioning characteristics of text-to-audio positioning and semantic understanding characteristics of sound scene classification, an expert network structure is adopted to ensure that scene classification utilizes fused characteristics for reasoning, and meanwhile, a time sequence structure of original audio is reserved for a text-to-audio positioning task. A multi-task learning scheme is adopted for text-to-audio positioning and sound scene classification tasks. According to the invention, key challenges in intelligent city acoustic perception are effectively solved. Dynamic decoupling and recombination of audio-text features are realized; and the problem of negative migration in multi-task learning is solved.

The application discloses an adaptive sound effect management method and system with a scene analysis module, relates to the field of adaptive sound effect management, and comprises the following steps: S1, collecting environmental acoustic characteristics and user behavior data in real time through a scene analysis module; S2, dynamically extracting user hearing preference parameters and scene classification labels; S3, constructing a virtual listening sweet spot matched with a physical space; and S4, dynamically adjusting the phase delay and energy distribution ratio of each frequency band to generate an optimal loudness equalization curve meeting multi-scene constraints. Through a multi-level perception-optimization closed-loop architecture, the application realizes adaptive matching of sound field characteristics in a complex dynamic scene, deeply integrates acoustic characteristic extraction and physical space modeling, breaks through the technical boundary of traditional pure signal processing, and solves the multi-objective conflict problem based on cross-modal collaborative learning and a global optimization algorithm.

The invention discloses an active sound production system and method for optimizing door closing sound quality, and relates to the field of simulation testing, a multi-dimensional sensing array module comprises a distance sensor, a three-axis acceleration sensor, a distributed microphone array and a temperature and humidity sensor, the sensors synchronously collect data, the data are transmitted through a CAN bus, and the timeliness and consistency of the data are ensured; the environmental acoustic modeling module is used for carrying out noise spectrum analysis on microphone signals, evaluating a vehicle door motion state, processing distance and acceleration data, calculating a temperature correction coefficient, dynamically adjusting sound pressure parameters, periodically updating an environmental parameter matrix and reflecting acoustic characteristics under different working conditions; and the PID-fuzzy hybrid algorithm module adopts a PID and fuzzy logic fusion framework, presets a target frequency, a maximum sound pressure level and a door closing speed threshold value, and calculates frequency, sound pressure and speed deviation, and the fuzzy logic module dynamically adjusts PID parameters according to the noise level, weights and superposes a proportional term, an integral term and a differential term, and is used for regulating and controlling the door closing sound quality.

The invention provides a far-field speech recognition method and system. The method comprises the following steps: constructing a three-dimensional visual robot indoor scene semantic map; marking the material acoustic attribute of each material on the three-dimensional visual robot indoor scene semantic map to construct a spatial acoustic fingerprint; voice signals are collected in different directions, and sound source information is determined; fusing the spatial acoustic fingerprint and the sound source information to obtain environmental acoustic data; adjusting voice recognition parameters according to the environmental acoustic data state; and analyzing a voice instruction in the voice signal according to the adjusted voice recognition parameter.

The invention provides an underwater near-field sensing method and system based on a mechanical scanning sonar and an optical camera, and the method comprises the steps: obtaining echo data of the mechanical scanning sonar, and carrying out the preprocessing of the echo data, and obtaining sonar image data; after sonar image data is processed, a near-field acoustic boundary is obtained by combining near-field environment acoustic reflection propagation characteristics, and a real near-field boundary is further obtained; acquiring an optical image, and acquiring a near-field optical enhancement image based on an underwater light propagation model compensation and weight fusion image enhancement method; and synchronizing and outputting the near-field acoustic boundary and the near-field optical enhancement image by using a timestamp. Different sensing modes of acoustics and optics are combined, sonar focuses on geometric boundary and scale measurement, optics provides visual details and textures through double-branch multi-scale fusion of underwater light propagation compensation and non-blind sharpening, two paths of information are clear in positioning and do not interfere with each other, the system can obtain the sensing ability of structure contours and texture details at the same time, and the accuracy of the system is improved. Therefore, the identifiability and integrity of the near-field environmental elements are improved.

The invention relates to the technical field of man-machine interaction, and discloses an audio-visual linkage system based on AI sound scene regulation and control, and the system comprises a composite sensing assembly which collects environmental acoustics and audience biological characteristics; the emotional state evaluation engine is used for updating the emotional belief state of the audience based on the collected features, and actively calibrating the state by releasing an emotional probe and monitoring biological feature changes when the belief state is high in uncertainty; the hierarchical strategy engine is used for generating a director intention and a collaborative rendering action according to the belief state; and an audiovisual rendering component for executing a rendering action to regulate and control the audiovisual scene in a linkage manner. The method comprises the steps of collecting multi-modal data, evaluating and updating an emotional belief state, judging uncertainty and executing active calibration, performing hierarchical decision to generate a rendering instruction, and finally executing the instruction to realize audio-visual linkage and form closed-loop control. According to the invention, deep, real-time and adaptive coupling of the audio-visual content and the inherent emotion of the audience can be realized.

The invention relates to a mine dynamic risk assessment method and system based on acoustic signal analysis, and the method comprises the steps: collecting environmental acoustic signals through an acoustic sensor array disposed in a mine monitoring region, and carrying out the preprocessing of the environmental acoustic signals; performing feature extraction on the preprocessed environmental acoustic signals to obtain multi-dimensional acoustic features; inputting the multi-dimensional acoustic features into a pre-trained SISSO algorithm risk quantification model, and outputting a risk quantification value; the environmental acoustic signals are processed based on a TDOA positioning algorithm, and sound source space coordinates are obtained through calculation; and fusing the risk quantized value and the sound source space coordinate to generate a risk field of the mine monitoring area so as to realize continuous quantitative evaluation and spatial distribution visual representation of the mine risk. The problem that mine risk monitoring in the prior art cannot realize accurate quantification and spatialization representation is solved.

The invention belongs to the field of building talkback noise reduction, and particularly relates to a self-adaptive building talkback audio noise reduction method based on environmental perception, which comprises the following steps: S1, an environmental perception layer acquires acoustic and visual information of an environment where building talkback equipment is located in real time, and extracts key characteristic quantities; according to the invention, environmental acoustic and visual features around the building intercom device are sensed in real time in a multi-mode manner, optimal noise reduction algorithm parameters are dynamically generated by using a fuzzy logic engine, and the working mode and parameters of the noise reduction core module are adaptively adjusted according to the optimal noise reduction algorithm parameters. Therefore, the voice definition and intelligibility are remarkably improved under various complex environment noise backgrounds, and meanwhile, the transient characteristics of human voice are protected.

The invention belongs to the technical field of acoustic feature recognition and environmental acoustic regulation and control, and discloses a voiceprint feature intelligent recognition and acoustic environment dynamic regulation and control system and method. Aiming at the problems of poor voiceprint recognition robustness, acoustic event early warning response lag and insufficient acoustic environment regulation and control adaptability under complex noise in the prior art, four invention points of a multi-dimensional voiceprint fusion recognition algorithm, an acoustic event evolution early warning model, an acoustic environment dynamic adaptation regulation and control mechanism and a global cooperative processing framework are provided. The method comprises two innovative algorithm formulas of voiceprint feature fusion weight calculation and sound environment regulation and control parameter dynamic correction. By constructing a recognition-early warning-regulation global collaborative closed loop, the voiceprint recognition accuracy under complex noise is remarkably improved, the acoustic event early warning response timeliness is greatly enhanced, the acoustic environment regulation adaptability is remarkably improved, and the method is suitable for various acoustic application scenes such as public safety, smart home and industrial acoustic monitoring. And the intelligent level of acoustic feature utilization and environment regulation and control is comprehensively improved.

This application discloses an AI-based method and system for intelligent control of digital speaker sound field parameters, relating to the field of digital professional audio equipment technology. The method includes: acquiring environmental acoustic parameters and user-played content, and identifying the playback scene to obtain the playback scene; performing auditory demand analysis to obtain an auditory demand solution; obtaining an initial sound field control target, and conducting an environmental impact assessment based on the environmental acoustic parameters to obtain an optimized sound field control target; iteratively optimizing the control parameters of the digital speaker in conjunction with the playback scene to obtain an optimized control scheme, and intelligently controlling the digital speaker. This solves the technical problem that existing digital speaker sound field parameter control methods cannot dynamically adapt to complex environmental changes and personalized auditory needs, resulting in poor sound quality and a poor user experience.

This invention discloses a method for a bird acoustic diversity index with low sensitivity to noise. The method first obtains the time-frequency power spectrum of field bird call monitoring data during the analysis period using short-time Fourier transform. Then, based on narrowband noise level estimation, it calculates candidate floating detection thresholds for each frequency point that meet local signal-to-noise ratio requirements. The full-scale relative level threshold is used as the lower limit to obtain the frequency-varying detection threshold after binarization of the time-spectrum. Finally, the Shannon index is calculated by counting the number of time-frequency points in each sub-band where the power is higher than the detection threshold, resulting in the acoustic diversity index based on frequency-varying threshold detection. This invention effectively addresses the fundamental limitation of ADI (Ambient Audio Diversity Index) being highly sensitive to noise, while remaining fully compatible with the ecological interpretations and findings of existing ADI studies. It provides a new tool for achieving stable and reliable rapid assessment of bird species diversity, and is of great significance for ecological and environmental acoustic monitoring.

The invention discloses an intelligent hearing-aid earphone semantic interaction method and system based on multi-mode perception. The method comprises the following steps: acquiring a user voice signal and an environmental acoustic signal through a multi-mode signal acquisition unit integrated on an intelligent hearing-aid earphone body; collaborative noise reduction processing is carried out to generate an enhanced voice stream; obtaining a semantic understanding result based on the enhanced voice stream, and generating a first response set; obtaining a user interaction signal and an interaction state, and generating a second response set in cooperation with the first response set; the semantic database is modified based on the first set of responses and the second set of responses. The method has the following advantages and effects: a closed-loop system capable of deeply fusing acoustic noise reduction, context-aware semantic analysis, real-time interaction optimization based on user feedback and dynamic evolution capability of a knowledge base is provided, so that accurate, smooth and continuously evolved semantic interaction experience is realized in a complex and changeable real environment; and the user communication efficiency and life quality are effectively improved.

The invention relates to the technical field of voice generation, in particular to a personification voice generation method and system for a carry-on AI partner, and the method comprises the following steps: collecting an external environment sound simulation signal through a carry-on equipment microphone array, obtaining an environment acoustic harmonic feature set, storing the environment acoustic harmonic feature set, and obtaining a voice simulation signal; and obtaining environment frequency spectrum characteristic data. According to the method, after a sound channel regular curled spectrum sequence is subjected to time domain smoothing to form frequency domain curled modulation data, a high-frequency-band spectrum envelope interval is extracted, amplitude gain improvement is executed according to a lip radiation impedance coefficient, then the frequency domain curled modulation data is superposed, and anthropomorphic interaction voice signals are generated. And high-frequency friction and gingival blasting details are enhanced without damaging the overall spectrum continuity, the environmental suitability, the anti-interference stability, the formant controllability and the high-frequency detail intelligibility, so that a chain gain is formed.

An injection device comprising an acoustic sensor configured to detect an ambient acoustic signal; an acoustic signal generator operable to generate an acoustic signal; and a controller configured to control the acoustic signal generator to generate an alert having acoustic properties selected based on the detected ambient acoustic signal. A feedback system comprising a first device comprising an acoustic signal generator operable to generate an acoustic signal; and a second device comprising an acoustic sensor configured to detect an ambient acoustic signal, and a controller configured to control the acoustic signal generator of the first device to generate an alert having acoustic properties selected based on the detected ambient acoustic signal; one of the first device and the second device being an injection device, and the other of the first device and the second device being a mobile device or a controller device.

The application relates to an earphone call and translation method and system adaptive to a scene, wherein the method comprises collecting an original audio signal comprising human voice and environmental noise through an earphone, and wirelessly transmitting the original audio signal to a paired mobile terminal; the mobile terminal extracts environmental acoustic characteristics according to the received original audio signal; the environmental acoustic characteristics are compared with a plurality of pre-stored environmental scene templates, and a corresponding environmental scene template of a current environmental scene is determined according to a comparison result; based on the determined environmental scene template, a corresponding noise reduction model is loaded and run on the mobile terminal, and a target human voice signal after noise reduction is obtained; real-time call transmission and real-time subtitle translation operations are synchronously performed according to the target human voice signal, and a translation result is rendered and displayed in real time on a display interface of the mobile terminal. The method solves the problem of how to adapt to different environmental scenes while realizing call enhancement and reducing translation delay in the related art.

This invention discloses an environmental acoustic adaptive sound effect control method, relating to the field of sound effect control. By integrating three modes—manual calibration, intelligent inspection, and event triggering—it can not only respond to user commands but also automatically trigger calibration when the speaker moves, there are sudden changes in environmental noise, playback mode switches, or a preset cycle is reached. This ensures that the speaker can proactively optimize the sound effect in a timely manner after changes in the usage environment, maintaining the speaker's sound effect at a suitable listening level. By quickly judging the suitability of the environment, it first assesses the background noise level, and only performs subsequent acoustic feature analysis when the environment is suitable for measurement. This avoids ineffective or even harmful calibration in high-noise environments, improving the reliability of system decisions and the accuracy of the final sound effect adjustment.

The utility model discloses an acoustic vibration analysis device, which relates to the technical field of environmental acoustic detection and comprises a top cover box, a bottom cover box and a decibel head, a control panel is fixedly arranged in an inner cavity of the bottom cover box, and an input panel is arranged at the top of the top cover box. The main body structure of the decibel meter comprises the top cover box, the bottom cover box and the decibel head, the decibel head is rotationally arranged on the top cover box, the top of the top cover box is provided with the containing assembly, the containing assembly can control the decibel head to stretch out of or retract into the inner cavity of the top cover box, and when the whole decibel meter is in a standby state, the decibel head can be effectively protected; in the prior art, the decibel head of the decibel meter is directly and fixedly arranged at the head part of the decibel meter shell, the decibel head containing a large number of precision sensors is easily damaged by external collision, the measurement precision is influenced or equipment failure is caused, the decibel head cannot be flexibly stored, and a user needs to carefully store and carry the decibel head. The equipment protection difficulty is increased; and the use is inconvenient.

The invention discloses an adaptive sound field adjustment system and method for smart home sound equipment with environmental acoustics perception, and relates to the technical field of sound field adjustment of smart home sound equipment, and the system comprises an environmental acoustics collection module which comprises omnidirectional and directional microphones, carries out the filtering, gain adjustment and 24-32-bit ADC processing, and packages data according to a standard format; the sound field analysis module is used for constructing a sound field model in combination with the room size and the furniture sound absorption coefficient; the adaptive adjustment decision module identifies 4-6 scenes and calculates frequency compensation, volume and pointing angle parameters; the sound execution module comprises a power amplifier, a unit loudspeaker array and an adjustable steering mechanism; the user interaction module supports far-field voice and touch operation; and the intelligent learning module is used for storing user data and optimizing and adjusting the model. According to the method, room acoustic characteristics are dynamically adapted, different use scenes are accurately matched, multi-region sound field collaboration is realized, the user preference is more and more fit when the method is used, and the auditory experience and use convenience are improved.

The application relates to the technical field of electroacoustic processing, and discloses a microphone anti-howling system. The system continuously collects an audio input stream containing time-domain waveform data and background acoustic parameters through an audio capture module; a dynamic range compression module processes the audio stream to generate a standardized audio frame sequence; a feature extraction module extracts sound pressure space-time variation features including a sound pressure gradient field, a sound energy density distribution and a phase coherence atlas from the sequence; a howling identification network in a howling identification module outputs a howling occurrence probability and hotspot area coordinates based on the features; a probability correction module performs real-time correction on the probability according to environmental acoustic parameters; and an intervention scheme construction module generates a targeted acoustic intervention scheme according to the corrected probability and the hotspot area coordinates. The application realizes accurate identification and effective suppression of the howling phenomenon, and significantly improves the stability and sound quality performance of an audio system.

This invention discloses a noise-reducing asphalt pavement maintenance decision-making method based on acoustic characteristic attenuation prediction, comprising: acquiring non-destructive testing signals of the porous asphalt pavement under test, including ultrasonic reflection signals; extracting acoustic feature indices for hierarchical screening, and performing inversion using a pre-constructed equivalent fluid physics model to obtain current microscopic acoustic parameters; calculating the acoustic safety margin of the pavement under test using an environmental acoustic model; acquiring historical microscopic acoustic parameter sequences, and performing feature direction decomposition with current parameters to deduce multi-dimensional independent evolution trends; and obtaining pavement maintenance decisions based on independent evolution trends and acoustic safety margins. This invention, through the combination of non-destructive testing and physical model inversion, can distinguish between the attenuation mechanisms of blockage and aging, supporting the shift from periodic maintenance to maintenance decisions oriented towards achieving acoustic environmental standards.

The application relates to the field of photovoltaic equipment anomaly early warning, and provides a photovoltaic equipment temperature anomaly prediction method and device based on a digital twin model, the method comprises the following steps: acquiring environmental acoustic signals, meteorological data and measured temperature data of a photovoltaic equipment; performing acoustic spectrum feature extraction according to the environmental acoustic signals to obtain a virtual environmental parameter set; sending the meteorological data and the virtual environmental parameter set to a preset digital twin model for processing to obtain an initial temperature prediction value set; determining a temperature prediction value distribution map according to the initial temperature prediction value set and the measured temperature data of the photovoltaic equipment, comparing a temperature prediction result with an abnormal temperature threshold, and obtaining a temperature anomaly risk point; and processing the temperature prediction value distribution map, the temperature anomaly risk point and the meteorological data to obtain photovoltaic equipment temperature anomaly early warning information, so that the accuracy and foresight of photovoltaic equipment temperature anomaly prediction are improved.