312 results about "Quantum sensor" patented technology

The present invention provides a flight attitude control method based on inertial navigation technology, which relates to the field of aircraft control technology and includes an attitude control system. The attitude control system includes a quantum inertial navigation fusion module, a distributed multi-source collaborative inertial navigation module, a real-time error compensation module based on deep learning, an energy collection and self-powered inertial system module, a distributed attitude data management module based on blockchain, a multimodal fusion and virtual twin collaborative control module, and a terahertz communication and inertial navigation fusion anti-interference module. The present invention uses a quantum annealing algorithm combined with a compressed sensing algorithm to optimize quantum sensor data, and then combines the D-S evidence theory and the particle swarm optimization algorithm in the distributed multi-source collaborative inertial navigation module to fuse multi-source data, which can deeply mine the deep connection and complementary information between different sensor data, break the simple data level superposition limitation, and greatly improve the accuracy of the attitude information after fusion.

The invention provides an interference self-adjusting carrier communication system based on a complex environment, and relates to the technical field of communication data adjustment, and the system architecture comprises a quantum-assisted interference detection and protection layer, a multi-domain fused dynamic anti-interference core layer, and an edge computing driven real-time anti-interference optimization layer. The quantum-assisted interference detection and protection layer can accurately capture quantum state information of interference signals and quickly determine key parameters of the interference signals through the quantum sensor array and the quantum signal processing unit, and the multi-domain fused dynamic anti-interference core layer integrates space-time-frequency-energy multi-domain resources. An interference rule is predicted in advance in a time domain and communication is reasonably scheduled, an interference source and a terminal position are accurately positioned in a space domain to optimize an antenna beam, a frequency spectrum is sensed in real time in a frequency domain and parameters are optimized, and energy consumption is intelligently regulated and controlled in an energy domain. The real-time anti-interference optimization layer driven by edge computing realizes quick analysis and processing of local interference by means of distributed edge computing nodes, and data transmission delay and cloud processing pressure are effectively reduced.

The technology relates to enhancing performance of quantum sensor operation in a noisy environment. Quantum neural networks are used to pre- and post-process analog signals to which qubits of a quantum sensor are exposed. Intra-processing using additional quantum neural networks may also be employed. This approach filters out noise from both the input analog signal and the system itself to achieve a very high signal to noise ratio. This permits the system to detect induced dynamics associated during exposure of the qubits to the analog signals. This enables the quantum sensor to sense a change in a state of a system under test, which can be beneficial for areas such as imaging, magnetometry, sensing electric fields, optomechanical sensors, quantum radar and other areas where enhanced signal to noise ratios are desired.

The invention relates to the technical field of geological disaster monitoring, in particular to a geological disaster monitoring method and system based on a quantum coupling effect. The method comprises the following steps: acquiring geological environment parameters of a target monitoring area; laying a quantum sensor network; initializing a quantum bit; the tunneling effect of quantum bits is excited by using microwave signals; obtaining quantum state data by using a quantum measurement technology; analyzing a coupling relationship among the geological environment parameters to realize geological disaster risk early warning; the causes and development tracks of geological disasters are traced, and monitoring and early warning strategies are optimized. Through a quantum sensor network and a multi-field coupling analysis model, ultrahigh-precision monitoring of stress, displacement, temperature and water level parameters is realized by using a quantum entanglement state, topology protection and time reversal technology, a disaster chain reaction path is revealed, cause and risk evolution are dynamically traced, the early warning reliability is remarkably improved, and the early warning effect is improved. And the monitoring mode is promoted to transition from passive response to active intervention.

The invention relates to the technical field of water quality pollution detection, in particular to a water quality pollution rapid detection method driven by a quantum sensing technology. A quantum sensor array is deployed in a water area to be detected, and quantum signal response data of the water area is collected; constructing a pollutant quantum recognition model, and inputting quantum signal response data into the model to obtain an initial predicted value of pollutant concentration; generating an initial detection parameter of the quantum detection instrument based on the initial predicted value, executing primary pollution detection by the instrument according to the parameter, and collecting primary deviation data of an actual detection value and an expected detection value; determining a detection error according to the deviation data, further correcting the initial detection parameter, and generating an optimized detection parameter; and finally, the instrument performs secondary pollution detection based on the optimized detection parameters. According to the method, complex water sample pretreatment is not needed, water quality pollution detection can be rapidly and accurately completed, detection requirements of different water areas are met, and the detection efficiency and accuracy are improved.

The invention relates to the technical field of power equipment abnormity monitoring, in particular to a power equipment fingerprint coding method. According to the method, quantum sensors are deployed at key parts of equipment to collect electric power parameters, and quantum-state electric power fingerprint data are generated, encrypted and stored. A block chain is utilized to construct a distributed account book to record equipment information, and dynamic calibration is realized through an intelligent contract. And feature extraction and modeling are carried out by means of quantum calculation, and an equipment fingerprint coding model is constructed. The model is combined with a quantum state matching algorithm to monitor the equipment state, and early warning and information broadcasting are carried out in time when abnormity occurs. And calling quantum computing resources through a block chain smart contract to position abnormity, judging types, generating processing measures, and automatically distributing the processing measures to execution nodes. The method realizes comprehensive monitoring and efficient fault diagnosis and processing of power equipment, guarantees data safety, improves the intelligent level of equipment management, reduces the operation and maintenance cost, and provides powerful support for stable and reliable operation of a power system.

The utility model discloses a transformer partial discharge detection device based on a quantum sensor. The transformer partial discharge detection device comprises a quantum detection module, a signal processing module, a control module, a power supply module, a communication module and a signal analysis module. The quantum detection module comprises a diamond NV color center sensor and a fluorescence detection unit; and the fluorescence detection unit outputs laser to the diamond NV color center sensor to obtain electron spin resonance information of the diamond NV color center sensor. According to the utility model, the diamond NV color center is used as the quantum sensor for partial discharge detection, and tiny partial discharge events in the transformer can be detected in real time in the early stage of partial discharge based on high sensitivity of the quantum sensor and simultaneous measurement of a plurality of physical quantities such as a magnetic field, an electric field, temperature and the like, so that the detection sensitivity is improved; abundant signal data is provided, and more time windows are provided for maintenance and fault prevention of power equipment; and the spatial resolution is high, so that the partial discharge generation position can be accurately positioned.

The invention discloses an intelligent peak regulation method with optimized combination of energy storage and conventional peak regulation means, and the method comprises the following steps: building a holographic situation awareness layer: capturing the voltage, current phase angle and frequency deviation of a power grid, and monitoring the pressure fluctuation in a diesel engine cylinder; data transmission and preprocessing: encrypting data of the miniature phasor measurement unit and the quantum sensor by using a quantum key distribution technology; the self-adaptive decision engine is used for performing Nash equilibrium calculation by utilizing a federal reinforcement learning architecture, through a local Agent based on a power generation / energy storage unit state autonomous optimization control strategy and in combination with a digital twin platform, solving multi-target conflicts of economy, reliability and carbon emission, and generating a global optimal scheduling instruction; the execution control layer is used for tracking resonance points and dispersing harmonic energy spectrums; dynamic topology reconstruction: a harmonic source is positioned by using a digital twin platform, and the topology of the energy storage system is automatically switched according to the harmonic frequency and position; continuously optimizing the digital twin platform; and full-process closed-loop feedback and self-learning are carried out.

The invention discloses an intelligent equipment management and monitoring method based on the Internet of Things. The method comprises the following steps: S1, collecting and preprocessing equipment state data through a quantum sensor; s2, constructing a quantum sensing network, and dynamically optimizing a network topology structure by using a quantum entanglement technology; s3, mapping the equipment state data into a quantum state, and optimizing time delay and spatial distribution in a data transmission process through quantum superposition and quantum interference technologies; s4, correcting error data in the transmission process by adopting a quantum error correction algorithm, and encrypting the corrected data through a quantum key distribution technology; s5, predicting the state of the equipment, and fusing a prediction result with the encrypted data to form a management instruction; s6, executing the management instruction and adjusting the equipment management strategy; and S7, monitoring the running state of the equipment in real time and updating the management instruction. The method has the advantages of high efficiency, accuracy, safety and high adaptability, and the equipment operation and maintenance efficiency is improved.

The invention provides a product production quality inspection management method and system based on quantum sensing, and relates to the technical field of industrial automation and quantum detection, and the method comprises the steps: collecting the quantum phase difference, spin relaxation time and energy density data of a product through a quantum sensing array; performing quantum state decoupling processing on the multi-dimensional field data, and extracting a quantum hue consistency coefficient and a structure anomaly index; constructing a multi-scale convolutional neural network to generate a three-dimensional quality feature tensor; dynamically optimizing a defect judgment threshold value based on a quantum annealing algorithm; and generating a visual thermodynamic diagram and triggering a process control instruction. The system comprises a quantum sensing module, an edge computing unit, a dynamic decision engine, a man-machine interaction terminal and a feedback control module, and closed-loop management is realized through multi-physics field synchronous acquisition and real-time control. According to the method, traditional detection resolution limitation is broken through by utilizing quantum sensing, micro defects are accurately identified, and complex working conditions are adapted through dynamic threshold optimization.

Described herein are systems and techniques for improving an accuracy of determinations made using data sensed in a wellbore or in a laboratory. Nuclear magnetic resonance (NMR) sensing devices may be used to collect data in a wellbore or lab. NMR sensing devices include a magnet (e.g., a permanent magnet or electromagnet) that provides a magnetic field that aligns the spins of protons / nuclei in substances near the NMR sensing device. The magnetic field strength provided by the magnet of the NMR sensing device affects the sensitivity of the NMR sensing device and affects frequencies that the NMR sensing device effectively uses when the NMR sensing device operates. Systems and techniques of the present disclosure may measure concentrations of lithium in brine deposits when identifying particular brine deposits that include sufficient lithium concentrations to justify extracting lithium from those particular brine deposits.

The embodiment of the invention provides a switch cabinet partial discharge quantum sensing monitoring device. The device is applied to the technical field of power equipment monitoring, and comprises a light path regulation and excitation module which is used for generating and beam-splitting detection laser of a quantum sensor coupled to each Rydberg atom; the quantum electromagnetic induction module acts on Rydberg atoms and a partial discharge electromagnetic field, and fluorescence or absorption spectrum characteristics of atomic energy level transition are changed; extracting a weak discharge signal, and converting the weak discharge signal into an analyzable electric signal; the signal processing and diagnosis module is combined with spatial information acquired by a quantum sensor of doydberg atoms in a distributed manner, and a time-frequency analysis and pattern recognition algorithm is adopted to extract discharge characteristic quantity; partial discharge positioning, type identification and insulation state evaluation are realized based on the parameters, and a real-time monitoring result and early warning information are output. In this way, through deep fusion of quantum sensing and advanced signal processing, a high-precision and high-reliability technical solution is provided for power equipment state monitoring.

The invention relates to a high-precision photonic crystal waveguide signal detection method and device based on a diamond quantum sensor. The method comprises the following steps: acquiring a vibration signal transmitted by a phononic crystal waveguide through a diamond quantum sensor; performing frequency domain transformation on single-frame signals in the vibration signals in sequence to obtain single-frame frequency domain features; inputting the frequency components into a trained detector model, acquiring a long-range dependency relationship between frequency characteristics corresponding to different frequency components and context information between the frequency characteristics through a self-attention module, and correcting the frequency characteristics corresponding to the related frequency components according to the long-range dependency relationship and the context information; identifying an aggregation feature containing the corrected frequency feature through a classification layer to obtain a predicted binary numerical value corresponding to the single-frame frequency domain feature; the long-range dependency relationship means that the amplitude information and / or the phase information between the two frequency components with the frequencies exceeding the preset threshold value have an association relationship. The method can improve the signal detection precision.

The invention belongs to the technical field of power equipment monitoring, and discloses a quantum sensing and MEMS sensing integrated partial discharge detection device and method. Partial discharge signals are collected through the quantum sensor and the electric field sensor; the data acquisition card transmits data to the microprocessor, the microprocessor judges the discharge type by using a wavelet transform method, extracts characteristic parameters, transmits the data to the computer, analyzes and determines calculation weights of different sensors according to the characteristic parameters to perform data fusion, and calculates and displays the partial discharge electric field intensity. According to the method, data fusion of the quantum sensor and the MEMS sensor is realized, more comprehensive and accurate information is provided, the source and characteristics of partial discharge can be better identified, the diagnosis accuracy and the reliability of a detection system are improved, false alarm and missing alarm are reduced, and reliable data are provided for the operation state, fault diagnosis and maintenance of power equipment.

The invention belongs to the technical field of crop growth monitoring, and provides a novel crop growth monitoring method, which comprises the following steps: S1, optical PPFD quantum sensors are placed at horizontal and vertical distance fixing positions among crop rows according to a space grid method, the transverse and longitudinal intervals of the plurality of optical PPFD quantum sensors are 20cm, and the distance between the optical PPFD quantum sensors is 10cm; collecting PAR data in the canopy at a specific time frequency; s2, before use, calibrating the sensor according to an in-situ calibration method; s3, an optical PPFD quantum sensor is adopted to measure the PAR level of the crop in the growth stage; s4, preprocessing the original FIPAR data, removing error entries, and calculating a missing value by using an inverse distance weighting method; s5, performing visual modeling on the FIPAR data by adopting a space-time Kriging (STK) model, a fixed rank Kriging (FRK) model and an integral difference equation (IDE) model; according to the invention, the optical PPFD quantum sensor can be used for monitoring the spatial and temporal changes of the canopy and PAR of the crop, and the growth condition of the crop can be reflected by monitoring the spatial and temporal variability of the PAR of the canopy.

In one form of the present disclosure, a quantum sensor comprises a quantum device. The quantum device comprises gallium nitride (GaN) with a color center with a zero-phonon line (ZPL) between about 900 nanometers (nm) and about 990 nm. The GaN can be doped with silicon (Si) and have low carbon (C) and oxygen (O) impurities. In one example, the quantum device is GaN doped with about 1016 atoms of Si per cm3, having less than about 8×1015 C atoms per cm3 and less than about 6×1015 O atoms per cm3, and a Ga vacancy density less than about 1016 vacancies per cm3.

A system includes a memory configured to store instances of a software application and a quantum processor operably coupled to the memory and configured to receive, from an instance of the software application, a user request to initiate an execution of multiregional interactions. The quantum processor is further configured to determine, based on the user request, structured data items configured to be completed by the user in order to satisfy the user request, identify, based one or more data fields within the structured data items, an input of first user identity verification data for satisfying the user request, extract, based on quantum sensor data obtained from quantum sensors, second user identity verification data, execute one or more quantum machine-learning (QML) models trained to identify whether the second user identity verification data matches to the first user identity verification data, and initiate the execution of the one or more multiregional interactions.

Systems, apparatuses, and methods provide for predicting a remaining useful life of semiconductors utilizing quantum sensors. A layer of 2-D material of the quantum sensor is excited via a microwave field source and a light source of a quantum sensor while also subject to a magnetic field, where the quantum sensor is located adjacent a semiconductor device. The excitation of the layer of 2-D material is sensed, via a photodetector of the quantum sensor. A magnetic field, a temperature, and / or a strain field effect of the semiconductor device are measured based on the sensed excitation of the layer of 2-D material. A remaining useful life of the semiconductor device is predicted based on one or more of the measured magnetic field, the measured temperature, or the measured strain field effect.

Provided is an interposer comprising: one or more photonic waveguide; one or more microwave circuit; one or more optical interconnect; and one or more electronic interconnect, further configured to support a quantum sensor, and methods of operating and fabricating thereof. Further provided is a the interposer containing one or more classical sensors. Further provided is a network of quantum sensors supported by said interposers.

The invention belongs to the field of quantum sensors, and discloses a diamond spin quantum sensor and a preparation method thereof. The preparation method comprises the following steps: cleaning and polishing a monocrystal diamond substrate; a microwave plasma chemical vapor deposition method is adopted for preparing a diamond film with the nitrogen-vacancy color center density larger than 10 < 16 > cm <-3 > on the single crystal diamond substrate; and preparing an anti-ferromagnetic NiO film on the diamond film by adopting a radio frequency magnetron sputtering method to obtain the diamond spin quantum sensor. The diamond spin quantum sensor disclosed by the invention contains a high-concentration nitrogen-vacancy color center diamond film, and nitrogen-vacancy color center measurement has extremely high spatial resolution, so that the change of a nano-scale magnetic field can be detected; the diamond spin quantum sensor is applied to precise measurement of the magnetic moment of an antiferromagnetic film and the magnetic coupling effect of an antiferromagnetic / ferromagnetic heterojunction interface. And the preparation method is simple, economical and applicable, and provides possibility for application of the diamond nitrogen-vacancy color center material in the field of quantum magnetic sensors.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for valuing and or authenticating property. An example system includes a sensor system and a computer system. The sensor system includes one or quantum sensors, and is configured to generate first sensor data representing one or more molecular properties of a first object at a first time. The computer system is configured, at least, to: receive the first sensor data from the sensor system; obtain model data representing one or more molecular properties of a model object; generate, based on the first sensor data and the model data, a comparison between the one or more molecular properties of the first object at the first time and the one or more molecular properties of the model object; and determine an authenticity of the first object based on the comparison.

The invention provides an installation and adjustment control system of a quantum sensing device, which belongs to the technical field of sensors and comprises a device installation and adjustment device arranged on a workbench. Each device assembling and adjusting device comprises a light intensity detection module and a multi-degree-of-freedom adjusting mechanism, the light intensity detection module is used for collecting light intensity signals of emergent light generated when incident light sequentially penetrates through the first assembly and the second assembly, and the multi-degree-of-freedom adjusting mechanism is used for adjusting the position of the first assembly from multiple degrees of freedom. Outputting a light intensity optimization control signal, or generating dispensing control data of the device assembling and adjusting device of the channel to be assembled and adjusted and storing the dispensing control data into a dispensing sequence, and taking out the dispensing control data from the dispensing sequence by the high-precision dispensing control units which run in parallel; and controlling the dispensing three-axis motion assembling module to assemble a target first assembly and a target second assembly of the target device assembling and adjusting device. According to the invention, a cross-domain coupling system of light intensity optimization and dispensing control is constructed, and multi-channel parallel installation and adjustment of the quantum sensor are realized.

The invention provides a material quality detection method and device based on quantum sensor detection, and the method comprises the steps: obtaining an original quantum sensing data sequence collected by a quantum sensor in a material detection scene, carrying out the multi-dimensional feature conversion of the original quantum sensing data sequence, generating a quantum feature set reflecting the internal structural features of a material, and carrying out the detection of the internal structural features of the material; and calling a pre-trained defect diagnosis model to perform defect mode analysis processing on the quantum feature set, outputting defect probability distribution information and defect type confidence information in the material, and determining defect positioning information and defect type classification information of the material based on the defect probability distribution information and the defect type confidence information. And according to the defect positioning information and the defect type classification information, generating a quality detection report containing a defect space distribution diagram and a type analysis table. According to the invention, the comprehensiveness, accuracy and processing efficiency of material internal defect detection can be improved.

The invention relates to a method for calibrating a quantum sensor, in particular a magnetic field sensor (1), which has a crystal (2) with color centers (2a), in particular a diamond crystal with NV centers. During calibration, the quantum sensor is operated in a calibration mode which comprises the following steps: a) automatically setting a plurality of values of at least one operating parameter (PA, PM, MD, fMW, …) which influences the sensitivity (ηB) of the quantum sensor, b) automatically determining a measure of the sensitivity (ηB) of the quantum sensor for the plurality of values of the at least one operating parameter (PA, PM, MD, fMW, …), and c) automatically selecting a value (PA,OPT, PM,OPT, …) of the at least one operating parameter (PA, PM, …) that is optimal for the sensitivity (ηB) of the quantum sensor. The invention also relates to a quantum sensor, in particular a magnetic field sensor (1), which has a calibration device (12) designed to carry out the method.

Examples relate to the field of radio frequency (RF) signal processing such as classifying RF signals with low latency. The method involves receiving portions of an RF signal, transforming these portions into a time-resolved frequency representation using a continuous wavelet transform, and processing this representation with a recurrent neural network. The neural network modifies a neural network state incrementally to generate a classification output, which may include modulation classification, signal-to-noise ratio (SNR) classification, or jamming detection. The system achieves sub-millisecond inference latency through techniques such as model quantization and batch size optimization. Principal uses include real-time RF signal analysis and jamming detection, with applications in communication systems and environmental monitoring. The RF signal may be received from a quantum RF sensor based on Rydberg atoms, enabling broad frequency range detection.

The invention relates to the technical field of power supply detection, in particular to a mobile power supply detection method, which comprises the steps of determining a corresponding target mobile power supply, detecting the target mobile power supply based on a quantum sensor, and obtaining atomic dynamic information of the target mobile power supply based on a detection result, generating a first-stage microscopic data set based on the atomic dynamic information; constructing a target topological structure corresponding to the first-stage microscopic data set in the target topological space, inputting the target topological structure into a topological recognition model for recognition, and generating a second-stage topological analysis result; calling a pre-designed encryption communication mechanism, carrying out encryption transmission on data in the second-stage topology analysis result, generating third-stage encryption security data, generating virtual data corresponding to the third-stage encryption security data based on the generative adversarial network, and sending the virtual data to a server; and generating a target detection report based on the fused virtual data and the third-stage encrypted security data. According to the invention, the detection accuracy of the mobile power supply can be improved.

The invention provides a subjective question intelligent reviewing and learning condition analysis system based on writing features, and relates to the technical field of education, the system architecture comprises a writing feature acquisition and analysis subsystem, an intelligent reviewing subsystem, and a learning condition analysis and prediction subsystem, and comprehensive innovation and improvement are realized by means of quantum technology. A model constructed by a quantum sensor and calculation enables microcosmic dynamic data to be accurate and observable, time sequence feature depth to be analyzed, a quantum algorithm on the macroscopic aspect has a remarkable effect on font aesthetics and multi-factor association model construction, quantum natural language processing and neural network cooperation, semantic style fusion innovation, knowledge graph reasoning by means of a quantum graph algorithm and the like, and the method has the advantages of being high in practicability and easy to popularize. Various question types can be accurately judged and scientifically guided, quantum hash and federated learning assistance multi-source data fusion is achieved, quantum random walk and an autoregressive moving average model achieve psychological association prediction, learning conditions are accurately informed, physical and psychological and academic co-proceeding of students is effectively intervened and assisted, and the efficiency and value of the system in the education field are greatly enhanced.

Disclosed is a diamond quantum sensor-based breast cancer detection apparatus. The apparatus comprises a fluorescence reading apparatus, a microwave generation control apparatus, a laser generation control apparatus, a calculation control system, and a medical diagnosis station. A diamond microwave sensing probe in the medical diagnosis station is configured for radiating detecting microwaves to a target to be tested, and a camera is configured for photographing an image of said target and sending the image to the calculation control system. The microwave generation control apparatus is configured for generating a control microwave input into the diamond microwave sensing probe. The laser generation control apparatus is configured for generating a laser input into the diamond microwave sensing probe. The calculation control system is configured for calculating the intensity of a microwave scattered by said target and solving for the distribution of dielectric properties in said target. In the present invention, the NV center in diamond is used as a probe to measure a microwave field, so that high-sensitivity and high-spatial-resolution microwave imaging of cancerous tissue in mammary tissue can be realized.

The invention discloses a deep learning switching-on safety risk assessment system and method fused with multi-source information, and relates to the technical field of switching-on safety risk assessment, the deep learning switching-on safety risk assessment system fused with the multi-source information and the method thereof realize accurate assessment of the switching-on safety risk of a circuit breaker through fusion of quantum and classical technologies, and improve the safety of the circuit breaker. Various beneficial effects are achieved; in the aspect of data acquisition, a quantum sensing array acquires microscopic quantum data in equipment, a classical module synchronizes SCADA system data, a multi-dimensional acquisition system is formed, and comprehensive information is provided; during data processing, a quantum-classical hybrid processor combines quantum convolution and a space-time attention mechanism to improve feature extraction efficiency and precision; in risk prevention and control, a risk decision engine scientifically and accurately evaluates the risk, an adaptive locking controller is quick in response, and the fault probability is reduced; meanwhile, the system guarantees stable and reliable operation through quantum noise compensation, high-fidelity quantum state transmission, data synchronization and other measures.

The invention relates to the technical field of earphone control, and discloses a multi-scene adaptive wireless earphone dynamic control method, which comprises the following steps: identifying environmental noise through phonon entangled state density and phase coherence length by adopting a quantum sensor array; physiological signals of a user are collected through the anti-interference electroencephalogram electrode, and the auditory state is analyzed; a millimeter wave radar is used to construct an environmental acoustic model, and quantum-classical hybrid calculation is combined to realize rapid sound field simulation; establishing a multi-objective optimization function to dynamically adjust noise reduction, equalization and spatial sound effect parameters; and realizing smooth transition control based on scene change prediction. According to the invention, the control accuracy of the wireless earphone during multi-scene adaptation can be improved.