259results about How to "Maintain continuity" patented technology

The invention provides an RFID-based power supply management method for a tilt angle sensor of a power tower, and the method comprises the steps: employing a support vector machine and a decision tree, analyzing the historical operation data of the tower, building a tower fault prediction model, predicting the state of the tower through the tower fault prediction model, and obtaining the fault probability and time of the tower; according to a tower fault prediction result, a preventive maintenance plan is made, priority maintenance is arranged for the tower with the fault probability larger than a preset threshold value, and a power supply strategy is adjusted in advance for the tower predicted to have a fault, and load pressure is reduced; a tower group intelligent power supply management system is adopted, state information and a power supply strategy of a single tower are integrated into a whole power grid, the power supply load of each tower is dynamically adjusted through a load balancing algorithm, and for a tower in a dangerous state, the power supply load of the tower is reduced, and the load is transferred to a tower in a good state.

The invention relates to the technical field of information security, in particular to a cloud-based EMM encryption method and system, and the method comprises the following steps: collecting user login data and equipment use data based on mobile equipment operation information, recognizing the time and position information of user login and equipment use, calculating the risk scores of various behavior modes, and storing the risk scores of various behavior modes. And obtaining user behavior identification data. According to the method, the comprehensiveness and the dynamism of data security management are improved by collecting and analyzing the user login data and the equipment use data in real time, identifying unauthorized access and performing risk scoring on the mobile equipment, and encryption parameters are optimized by combining real-time monitoring on the user behavior pattern and the equipment performance and utilizing data sensitivity scoring; the data encryption efficiency and security are improved, the risk of data leakage is reduced by adjusting the updating frequency and parameters of the encryption key, the response speed to security threats is improved, the flexibility of enterprise data protection is enhanced, and the service continuity is maintained.

The invention relates to the technical field of audio processing, and discloses an audio processing method and system for speech spectrum reconstruction, and the method comprises the steps: carrying out the preprocessing of an original speech signal collected by a vehicle-mounted microphone, and obtaining a speech signal time-frequency matrix; performing singular value decomposition on the voice signal time-frequency matrix to obtain a sparse matrix representing voice components and a low-rank matrix representing noise components, and establishing a frequency band characteristic incidence matrix through a mutual information entropy calculation method; inputting the sparse matrix into a selection forgetting extreme learning machine for voice feature prediction to obtain predicted voice feature data; and based on the predicted voice feature data and the frequency band feature incidence matrix, performing voice probability calculation and feature interpolation on each time frequency point by adopting a logarithmic frequency spectrum amplitude calculation method to obtain reconstructed frequency spectrum data, thereby improving the accuracy of voice recognition and meeting the requirement of real-time processing in a vehicle-mounted environment at the same time.

The invention relates to the technical field of image annotation, in particular to a medical image auxiliary annotation method and system based on image processing, and the method comprises the following steps: obtaining medical image data, and carrying out the edge enhancement processing of the image data; performing preliminary labeling on the central necrosis layer, the edge active layer and the peripheral normal tissue layer to generate preliminary labeling areas of different focus levels; extracting textural features, morphological features and density features of each level, and converting the textural features, morphological features and density features into feature vectors for storage; forming a multi-level lesion association model; adjusting the boundary positions of the layers, and ensuring that the relative position relation between the layers is reasonable; dynamically updating the level annotation according to the change characteristics; and outputting a labeling layer containing the multi-level focus characteristics of the central necrosis area and the edge active area. Compared with an existing single-level or coarse-grained marking method, the method has the advantages that the hierarchical expression effect of the focus area is improved, and the detail level of the focus in the complex form is clearly presented.

The invention relates to a collaborative autonomous perception and navigation method in a denial environment, which comprises the following steps: constructing a self-organizing robust communication system to realize dynamic networking and data sharing among multiple unmanned aerial vehicles in the denial environment, and adopting a self-adaptive network protocol to realize automatic configuration of a communication network under network topology change or communication interference; based on a multi-sensor fusion sensing system, environment information and motion information of the unmanned aerial vehicle are processed through a data fusion algorithm; a single unmanned aerial vehicle constructs a reward function based on unmanned aerial vehicle energy consumption, an exploration area, a path overlapping degree and a path danger degree, executes autonomous perception and exploration in an unknown environment and completes mapping; the distributed multiple unmanned aerial vehicles carry out individual communication and game playing in the unmanned aerial vehicle cluster according to map information, respective positions and working states, task distribution is achieved, and path planning and action decision making are completed. According to the invention, autonomy and collaboration of the unmanned aerial vehicle in a denial environment are improved, and an effective solution is provided for navigation in a complex environment.

The invention relates to a satellite internet resource scheduling method based on deep reinforcement learning, and aims to solve the problem that in an SGIN environment, an unstable link easily causes increase of a VNF backup AoI and thus it is difficult to ensure that the VNF can be quickly recovered when a fault occurs. A VNF state transition and failure recovery model is established for the problem that the AoI of VNF backup is increased due to link instability, and a VNF backup model perceived by the AoI is established to adjust bandwidth resources to optimize the AoI. In order to solve the problem that the VNF backup is far away from the original VNF due to relative movement between network nodes, a VNF backup migration mechanism is introduced. In order to make an adaptive optimization strategy for services with different time delay sensitivities, a time delay sensitive factor is introduced as a weight, an optimization problem is established by taking maximization of VNF backup income as an optimization target, and the optimization problem is solved. A simulation result shows that the scheme can reduce the interruption time delay of the VNF with a serious fault under the condition of reasonably utilizing network resources.

The invention provides an unknown environment adaptive navigation control system based on deep learning, and aims to improve the autonomous navigation capability of a machine in a complex and unknown environment. According to the system, an advanced sensing module is adopted, multi-sensor data are combined, and a dynamic environment is quickly and accurately sensed through a deep learning algorithm. The online environment modeling mechanism can update the environment information in real time without depending on a pre-constructed map. And by utilizing a reinforcement learning algorithm, the system can autonomously learn and optimize path planning, and meanwhile, energy consumption, time efficiency and safety are considered. An innovative multi-mode obstacle avoidance strategy is adopted, and obstacle avoidance behaviors are dynamically adjusted according to environment complexity and machine states. The intelligent decision support system combines a decision tree and fuzzy logic, and provides fast and accurate decision ability. The adaptive motion control algorithm optimizes path tracking performance and adapts to dynamic characteristics and environmental conditions of a machine. In addition, the collaborative job mechanism supports efficient communication and task collaboration in a multi-machine system.

The invention, which relates to the technical field of artificial intelligence, discloses a warehouse-in and warehouse-out path planning method and system for intelligent warehousing, and the method comprises the steps: generating an optimal operation path of a to-be-operated carrier through a path planning model; the method comprises the following steps: predicting whether a current carrier has a collision risk with all carriers in a warehouse in a time dimension or not through a time block, predicting whether the current carrier has a collision risk with all carriers in a warehouse in a space dimension or not through a space block, and when the time block and the space block simultaneously detect that the current carrier has the collision risk at a certain moment, judging whether the current carrier has the collision risk; the decision block judges that the current carrier has a collision conflict, and determines an optimal avoidance strategy through an action value function; according to the optimal avoidance strategy, the avoidance waiting carrier is determined, the total waiting time and the waiting space position of the avoidance waiting carrier are calculated, and the avoidance strategy is executed. According to the technical scheme, the problem that in-out garage path planning and collision processing cannot be intelligently and accurately carried out in the prior art can be solved.

The invention provides a self-discovery ad-hoc network control method based on a swan-gap operating system, and relates to the technical field of data processing, and the method comprises the steps: based on the swan-gap operating system, extracting the identification information and communication parameters of equipment from all to-be-networked equipment; carrying out compatibility judgment on the communication protocol version and the maximum support bandwidth between the devices; determining a control relationship between the master device and the slave device; dynamically allocating communication resources to each device by adopting a distributed channel allocation algorithm in combination with task requirements of the devices and network bandwidth information; periodically synchronizing the resource state of each device; when the slave device sends a networking quitting request, the master device updates the networking candidate data and re-determines the networking control relationship after releasing the corresponding communication resources; when the master device exits, the device with the highest priority is selected from the slave devices to automatically take over the control role and complete the reconstruction of the networking control relation; according to the invention, the autonomy and accuracy of networking are improved.

The invention relates to the technical field of data processing, in particular to a hoisting state intelligent sensing and early warning system, method and equipment, and the system comprises an environment interference early warning module, a hoisting equipment abnormity early warning module, a hoisting operation abnormity early warning module and a hoisting system database, according to the intelligent sensing and early warning system, method and equipment for the hoisting state, the influence of environment interference, hoisting equipment abnormity and hoisting state abnormity on hoisting operation is comprehensively analyzed, and a comprehensive hoisting operation abnormity evaluation system is formed; the evaluation system not only can monitor the environmental interference degree of a hoisting operation site in real time, but also can perform analysis and early warning on hoisting equipment abnormity and hoisting state abnormity, and through comprehensive evaluation and early warning on hoisting operation, the emergency response capability of hoisting operation can be improved, and the safety of hoisting operation is improved. And therefore, the hoisting operation can still be kept stable and safe under the emergency condition.

The invention provides an NPU instruction level context switching method and device, and relates to the technical field of data processing.The method comprises the steps that when a context switching instruction is received, a non-refresh instruction is forbidden, it is waited for completion of an instruction being executed, and context data is stored in a main storage module; after completion, recovering the context switching related instruction of the NPU module, and executing the target task; and after the target task is executed, recovering the context data to the NPU module, and recovering the execution of the non-refresh instruction. According to the method, optimization is carried out aiming at the problem that an existing NPU architecture generally can only support limited preemption at an algorithm boundary or a specific context switching point and even cannot preemption, so that a high-priority task must wait for a low-priority task to be completed, and remarkable priority inversion and / or key inversion are / is caused. A full-stack solution from a system on chip to an instruction set architecture and then to an operating system kernel is provided, and preemption of an NPU instruction level is achieved.

The invention discloses a grinding workpiece edge shape detection method and system based on machine learning, and the method comprises the steps: obtaining an original image of a grinding workpiece, and carrying out the preliminary image preprocessing; denoising the image and enhancing edge information by combining image filtering and mathematical morphology image processing; based on a second-order differential operator, edge detection is carried out in combination with the morphological gradient, and a workpiece edge contour is obtained; performing feature extraction on the image by using a convolutional neural network, automatically learning workpiece edge features, and constructing and training an edge detection model; acquiring a workpiece image in real time, inputting the workpiece image into the edge detection model for detection, and dynamically correcting the model; and S6, outputting a final edge detection result. According to the invention, by combining image preprocessing, composite image filtering, second-order differential operator and morphological gradient edge detection and feature extraction and model construction of the convolutional neural network, high-precision and robust detection of the edge of the grinding workpiece is realized.

The invention discloses an intelligent electric vehicle driving state safety estimation method under network attacks, and relates to automobile intelligent safety and automatic driving. Firstly, a three-degree-of-freedom dynamic model of the intelligent electric vehicle is established, the model comprehensively considers transverse, longitudinal and yaw dynamic characteristics of the vehicle, and accurate description is provided for subsequent state estimation. And designing an attack signal and state security estimation method based on an adaptive tolerance extended Kalman filtering algorithm. According to the method, the real-time and accurate estimation of the vehicle state is realized by fusing the information of various sensors such as GPS, LiDAR, IMU and the like, and malicious data introduced due to network attack can be effectively eliminated. Meanwhile, the method also has the capability of tolerating non-ideal network environments such as sensor data packet loss and the like, and the safety and reliability of the self-driving automobile are further enhanced. The intelligent electric vehicle can still maintain accurate driving state estimation when subjected to network attack, and safe driving of the vehicle is ensured.

The invention provides a motor fault-tolerant control method for a high-altitude operation unmanned aerial vehicle, and the method comprises the steps: determining a motor fault type through collecting the operation state data of a target motor, including a vibration signal, a temperature signal, a current signal, a rotating speed signal, attitude information, environment air pressure and environment wind speed; the fault types comprise rotor unbalance, current overload, thermal runaway, bearing fault and open-phase fault. And executing corresponding adjustment operation according to the fault type and the current flight state of the unmanned aerial vehicle, including: when the rotor is unbalanced, adjusting the PWM duty ratio by calculating the transverse component of the target rotating speed so as to offset the offset torque and the like. And after the adjustment operation is completed, adjusting a task execution mode according to the motor operation state, including reducing a task load or starting a landing mode, and ensuring task completion and flight safety of the unmanned aerial vehicle. According to the method, the reliability and the fault-tolerant capability of the unmanned aerial vehicle in a complex high-altitude operation environment are improved.

The invention relates to the field of computer vision and artificial intelligence, in particular to a real-time multi-person motion analysis system based on motion perception and semantic understanding, which comprises a motion perception module, a motion tracking module, a motion semantic understanding module and a motion performance analysis module. The motion area segmentation unit adopts a background modeling or inter-frame difference method to identify a motion area and generate a motion mask; the target detection unit is connected with the central processing unit through a data bus and used for processing video frame data and detecting the position and the bounding box of a moving target. The motion area segmentation unit is connected with the target detection unit and is used for generating a motion mask. By integrating a plurality of modules, the motion data can be comprehensively captured and analyzed, and the accuracy and real-time performance of motion analysis are improved. Through combination of the target detection unit and the motion area segmentation unit, the system can accurately identify a motion target and a motion area, and a solid foundation is laid for subsequent tracking and analysis.

The invention discloses a user track privacy protection method and system fusing a generative model and three-stage personalized differential privacy, and relates to the technical field of data security, and the method comprises the steps: obtaining real user track data, and carrying out the preprocessing of the real user track data to form standardized track representation; training a depth generation model to generate synthetic trajectory data; performing density clustering on the synthetic trajectory to obtain a feature region and calculating a region centroid; point-level privacy budgets are distributed according to three stages of the area proportion, the centroid distance and the global density; constructing an adaptive elliptical disturbance domain based on the regional covariance, sampling candidate confusion points in the disturbance domain and applying road feasibility screening; and calculating a score based on the privacy budget and the utility function, and sampling replacement points by adopting an index mechanism to output a privacy protection trajectory. According to the technical scheme, the track structure continuity and the road semantic consistency are remarkably improved under the condition that the differential privacy constraint is met, and the privacy intensity and the data availability are both considered.

The invention relates to the field of cigar cabinet electronic control, in particular to a constant-temperature and constant-humidity cigar cabinet and a temperature and humidity control method thereof.The constant-temperature and constant-humidity cigar cabinet comprises a base, a cabinet box, a constant-temperature and constant-humidity module, an alarm control panel, a machine top shell and sliding plates; the system further comprises a constant-temperature and constant-humidity module, an alarm, a first overall temperature and humidity sensor, a second independent temperature and humidity sensor, a third external environment temperature and humidity sensor and a fourth internal environment temperature and humidity gradient sensing linear array, and a temperature and humidity control strategy is determined in a constant-temperature and constant-humidity module controller based on data of the temperature and humidity sensors. And the temperature control accuracy is improved. In addition, a user can be informed of detection and maintenance at the first time through an alarm, and the storage safety of high-grade cigars can be ensured through an uninterrupted power supply.

The present invention discloses a transcranial magnetic stimulator, which belongs to the technical field of medical devices. It includes: a circular hole is provided on a substrate; a first rotating ring is rotatably installed in the circular hole of the substrate; a circular hole arranged eccentrically relative to the axis of the first rotating ring is provided on the first rotating ring; a first driving mechanism is installed on the substrate, which is used to control the first rotating ring to rotate around the circular hole of the substrate; a second rotating ring is rotatably installed in the circular hole of the first rotating ring; a circular hole arranged eccentrically relative to the axis of the second rotating ring is provided on the second rotating ring; a second driving mechanism is installed on the first rotating ring, which is used to control the second rotating ring to rotate around the circular hole of the first rotating ring; a shaft cylinder is rotatably installed in the circular hole of the second rotating ring; a magnetic head is installed at the lower end of the shaft cylinder. The present invention realizes the flexible movement of the magnetic head on a two-dimensional plane through a two-stage rotating ring, which greatly increases the flexibility and accuracy during treatment, helps to achieve more accurate and personalized treatment, and improves the treatment effect.

The invention relates to the technical field of smart mines, unmanned driving technologies and maps, and discloses a topographic data updating method, device and system. The method comprises the following steps: acquiring and storing initial topographic data of a target area, receiving and processing position data uploaded by at least one operation device, and preprocessing the position data to generate topographic change area data; generating a topographic data acquisition task based on the topographic change area data, issuing a task instruction corresponding to the topographic data acquisition task to topographic data acquisition equipment, and enabling the topographic data acquisition equipment to execute the task instruction according to the target acquisition path so as to perform topographic data acquisition; and receiving and processing the topographic data acquired by the topographic data acquisition equipment, and performing data updating on the initial topographic data through the topographic data acquired by the topographic data acquisition equipment to obtain updated topographic data. According to the invention, the updating efficiency and accuracy of the topographic data can be improved.

The invention provides a method and a system for constructing and optimizing an environment map based on an ultra wide band (UWB). The method and the system are suitable for an extreme environment. The method comprises the following steps: firstly, initializing a two-dimensional grid map by a system, and collecting signal data through UWB equipment; when the LOS path is determined, the corresponding grid is defined to be in a free state, and otherwise, the corresponding grid is marked to be in an occupied state. For NLOS features, obstacle locations are mapped onto a map. Then, the map is refined through a mean filter, a morphological filter and a region growing algorithm, and the accuracy of obstacle representation is improved; and finally, the optimized map information is utilized, and the weight of a positioning algorithm is adjusted through a weighted least square (WLS) method, so that the positioning precision is improved. The method has the advantages that environment obstacle information can be effectively constructed, the environment obstacle information is suitable for navigation after being refined, and a map can be normally constructed in dark light and smog environments. The system only depends on a UWB sensor, and accurate positioning is achieved in an obstacle environment.

The utility model provides a skid-mounted mixing system and belongs to the technical field of skid-mounted mixing. Comprising a box body; the stock bin is arranged in the box body; the grading part is arranged on the stock bin, and the grading part comprises a high-level material level sensor which is arranged at the top of the stock bin and used for preventing excessive filling of materials. According to the utility model, the grading part is arranged, and high, middle and low three-level material level monitoring points are arranged in the stock bin, so that the real-time monitoring of the material level in the stock bin is realized, the overflow caused by excessive filling of the material can be effectively prevented, the continuity of material supply is ensured, the interruption of production due to material shortage is avoided, and when the material level drops to an early warning point, the production efficiency is improved. The system can trigger a material supplementing mechanism in time to prevent a production line from being shut down due to material exhaustion, so that the continuity and the stability of a production process are maintained.

The invention discloses a remote control anti-delay video transmission method based on a future scene generation network. The remote control anti-delay video transmission method comprises the following steps: synchronizing time references of a remote control vehicle and a remote cockpit; original video stream data of the environment where the remote control vehicle is located is collected; adding a camera number and timestamp information into the original video stream data; preprocessing the decoded video stream data to generate a plurality of paths of future scenes; generating multiple paths of future scene video stream data; camera numbers and timestamp information are added to the multiple paths of future scene video streams; decrypting, decoding and distributing the data; performing packet loss and time delay detection on the original video stream data, and performing visual quality optimization on the future scene video stream data; and a complete and continuous video stream is formed. According to the method, the delay in video transmission is greatly reduced, and the video content at the future moment can be predicted and generated in advance in future scene generation, so that the video blank possibly occurring due to transmission delay or data packet loss is effectively filled.

The invention discloses a 3D medical image registration method and device for contrast learning enhancement of double attention converters. The registration method comprises the steps that a 3D medical image data set is acquired and preprocessed; then down-sampling the fixed image and the floating image to create an image pyramid; then, a registration network based on a converter is established, finally, a loss function value between a fixed image and a registered image is calculated by using a loss function, and a network model is optimized through back propagation, so that a trained neural network model is obtained. According to the invention, by combining a self-attention mechanism and a cross attention mechanism, local and global context information can be comprehensively captured, and the modeling capability of image details and an overall structure is improved. And measuring the distance of the corresponding feature points between the images by using a contrast loss function. Meanwhile, the similarity between the images is further calculated by adopting a normalized total gradient and a modal independent neighborhood descriptor loss function, so that the accuracy and precision of medical image registration are improved.

The invention relates to a power-down protection method, device and equipment for an intelligent storage high-computing-power industrial control chip, and the method comprises the steps: monitoring the power supply voltage of the industrial control chip in real time, generating a power-down signal when the power supply voltage is lower than a preset voltage threshold range, reading the task processing data of a current computing task, and pausing the current computing task; starting a ping-pong power failure protection mechanism according to the power failure signal, storing task processing data in a preset main and standby data storage area in a segmented manner, and generating a data check code; performing data synchronization on the main and standby data storage areas and a preset nonvolatile memory based on the data check code to obtain backup data, and generating a synchronous check code; when the power supply voltage recovers to accord with the voltage threshold range, performing data reading on the nonvolatile memory according to the synchronous check code to obtain backup data; and performing data recovery on the backup data according to the data check code, and restarting the current calculation task. According to the invention, chip data loss caused by sudden power failure can be avoided.

The invention relates to the technical field of metal processing, in particular to a phosphor bronze wire rolling mill device which comprises a bottom plate, machine bodies are arranged on the bottom plate, an upper roller and a lower roller which are vertically arranged in parallel are arranged between the machine bodies, and the upper roller is slidably arranged between the machine bodies through sliding plates on the two sides; the outer walls of the two studs are both sleeved with rotating wheels, and a belt is arranged between the two rotating wheels. The stand column is provided with a set of transmission adjusting assemblies arranged in a triangular mode. The air cooling mechanism is arranged on the bottom plate and corresponds to the discharging direction of the machine body; two traction rollers are arranged between the two supporting frames; and a speed change mechanism is arranged on the vertical plate. The rotating wheel rotates to drive the stud to move up and down, the position of the upper roller can be adjusted, the rolling machine can be suitable for producing wires of different diameters, the adaptability and flexibility of a production line are improved, the upper roller and the lower roller are each provided with a groove, and the precision of wire rolling and the product quality are ensured.

The invention provides a multivariable control method for the carbon content of a ferrosilicon furnace, and is applied to the technical field of ferrosilicon-manganese alloy smelting. The method comprises the following steps: acquiring multivariable parameters for the carbon addition amount of the silicon iron furnace; the multiple parameters comprise an electrode current, a power factor, an artificial iron control parameter, an electrode pressure release amount, an electrode position, a furnace gas size, a weight of fly ash, hole opening time, a molten iron temperature and a hole opening flow rate; setting a judgment quantity, wherein the judgment quantity has an initial value; for each parameter in the multivariable parameters, adding different numerical values to the judgment quantity according to different conditions of parameter values to obtain a final accumulated value of the judgment quantity; when the accumulated value of the final judgment quantity is larger than a first threshold value, the silicon iron furnace is judged to be high in carbon intensity, and the carbon adding quantity is reduced by a first preset quantity; and when the accumulated value of the final judgment quantity is smaller than a second threshold value, the silicon iron furnace is judged to be carbon-deficient, and the carbon addition quantity is increased by a first preset quantity. According to the method, the carbon addition amount can be adjusted in time, and the purposes of stabilizing the furnace condition, reducing the unit consumption and improving the yield are achieved.

The invention provides a receiving waveform position judging method of an ultrasonic flow metering device, and aims to improve the reliability of flight time measurement and reduce flow metering errors. According to the method, head wave and tail wave detection is achieved through the variable threshold comparator, the threshold is dynamically adjusted to adapt to different detection stages, and it is ensured that echo signals are accurately recognized. Through combination of zero crossing point flight time measurement and pulse width difference comparison, the method can determine the position of a tail wave, forwards presumes the position of an echo waveform, and judges the accuracy of a zero crossing point. In addition, the measurement accuracy is further improved by adjusting the phase of the transmitted ultrasonic signal to enhance the tail wave characteristic. The method is suitable for the field of flow measurement of water meters, heat meters, gas meters and the like, and metering errors caused by signal fluctuation or interference are effectively reduced.

The invention is suitable for the technical field of communication fusion, and particularly relates to a wireless and wired fusion data center interconnection structure, device and method. The cellular network clusters are connected through optical fiber links, each cellular network cluster is composed of a plurality of cellular units, and the cellular units in the same cellular network cluster are interconnected in a wireless link mode. By building a wireless free space optical communication link, direct interconnection between cellular units in the same cellular network cluster is realized, the routing hop count is reduced, the communication time delay is reduced, the flexibility and efficiency of network interconnection are greatly improved, and by combining the optical fiber, the communication efficiency is improved. The high stability and the anti-electromagnetic interference capability of the optical fiber can be fully utilized, a flexible redundant path can be provided for a wireless free space optical communication link, and the continuity and the reliability of communication can still be kept when a wired link is blocked.

The invention provides a display device and a sound synthesis method, and the method comprises the steps: receiving sound data collected by a sound collector in response to an access instruction of the sound collector, and storing the sound data and corresponding collection time at a preset position; according to an input playing instruction, accompaniment audio data and original sound audio data of a target song are decoded, a start time identifier contained in the accompaniment audio data is detected, and after the start time identifier is detected, sound data are periodically read according to time corresponding to the start time identifier and collection time; when the sound data is read, generating target audio data according to the accompaniment audio data and the read sound data; and when the sound data is not read, generating target audio data according to the accompaniment audio data and the replacement audio data. According to the method, the missing sound data of the user can be filled in a mode of replacing the audio data, the integrity of the target audio is ensured, and the problem that the audio is incomplete in the audio recording process is solved.

The invention discloses an AB backup method for realizing OTA upgrade by a single Flash Bank, which ensures that a system can automatically recover to a previous stable version without staying in a BOOT boot area under the condition that the OTA upgrade fails. The problem that the ECU can only execute a firmware upgrading function and cannot work normally after the traditional OTA upgrading fails is avoided, so that continuous operation of core functions of the ECU is guaranteed, the driving experience of a user and the stability of a system are improved, and in addition, the method has the advantages that fault tolerance and recovery capacity of double Flash Banks similar to that of a high-end MCU are achieved on a single Flash Bank of a common MCU. Thus, an automobile manufacturer (OEM) does not need to use a more expensive special MCU for supporting an AB backup function, hardware cost is greatly reduced, and feasibility and economical efficiency of the method are improved.